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An Evaluation of Vegetation and Wildlife Communities in Mitigation and Natural Wetlands of West Virginia

Collins K. Balcombe

Thesis submitted to the Davis College of Agriculture, Forestry, and Consumer Sciences

at West Virginia University in partial fulfillment of the requirements

for the degree of

Master of Science in

Wildlife and Fisheries Resource Management

James T. Anderson, Ph.D, Chair Ronald H. Fortney, Ph.D.

William N. Grafton Walter S. Kordek

James S. Rentch, Ph.D.

Morgantown, West Virginia 2003

Key Words: Wetland mitigation, wetland restoration, wetland management, mitigation wetland, constructed wetland, reference

wetland

ABSTRACT

An Evaluation of Vegetation and Wildlife Communities in Mitigation and Natural Wetlands of West Virginia

Collins K. Balcombe

The goal of this study was to evaluate the relative success of mitigation wetlands in West Virginia in supporting vegetation, invertebrate, and wildlife communities. Eleven mitigation wetlands were compared to 4 naturally occurring reference wetlands. For all vegetation species sampled, species richness (no. species/quadrat; P = 0.035), evenness (P = 0.033), and diversity (P = 0.025) were higher in mitigation than reference wetlands. Mean weighted averages per quadrat were similar between mitigation and reference wetlands (P = 0.242). Differences in vegetation composition between wetland types were reflected through ordination using Detrended Correspondence Analysis (DCA). Both mitigation and natural wetlands met criteria for hydrophytic vegetation according to the 1987 U.S. Army Corp of Engineers Wetland Delineation Manual. Overall invertebrate familial richness, diversity, density, and biomass were similar between mitigation and reference wetlands (P > 0.05). Within open water habitats, benthic density was higher in reference wetlands, but nektonic biomass was higher in mitigation wetlands (P < 0.05). Mitigation wetlands generally contained more abundant individual taxa than reference wetlands. Bird species richness (P = 0.711), diversity (P = 0.314), and abundance (P = 0.856) were similar between mitigation and reference wetlands. Waterbird (P = 0.013) and waterfowl (P = 0.013) abundance were higher in mitigation than reference wetlands. Frog species richness (P = 0.023), Wisconsin index value (P < 0.001), and abundance (P < 0.001) were higher in mitigation than reference wetlands. American bullfrog (Rana catesbeiana; WI: P = 0.033; A: P = 0.038), green frog (R. clamitans; WI: P = 0.012; A: P = 0.018), and pickerel frog (R. palustris; WI: P = 0.003; A: P = 0.005) were higher in mitigation wetlands. Habitat Suitability Index (HSI) scores for all 8 species combined were similar (P = 0.489) between wetland types. Red-winged blackbird (Agelaius phoeniceus; P = 0.001) and beaver (Castor canadensis; P = 0.037) HSI values were higher in natural than mitigation wetlands. All other species� SI values were similar between wetland types. Differences in vegetation and invertebrate community composition and structure likely contribute to differences in wildlife communities between wetland types, although Canonical Correspondence Analysis revealed no correlation between environmental variables and wildlife abundance. These data indicate that mitigation wetlands in West Virginia currently meet and exceed reference standards, although more time is needed for wetland stabilization. Numerous management strategies should be incorporated to facilitate colonization and proliferation of diverse wildlife taxa among current or future mitigation wetland.

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ACKNOWLEDGMENTS

I thank the following individuals for their assistance with the field sampling

conducted for this project: Sheri L. Helon, Seth R. Lemley, Joseph D. Osbourne,

Todd J. Polesiak, and Andrew K. Zadnik.

A special thanks is extended to George E. Seidel for assistance with statistical

analysis. A special thanks also is extended to my graduate committee, in particular

my advisor James T. Anderson, whose advice and genuine support afforded me the

opportunity to conduct this exciting research. I thank the West Virginia University

Davis College of Agriculture, Forestry, and Consumer Sciences (McIntire-Stennis

Program) for providing the majority of funds for my project. I also thank the West

Virginia Division of Natural Resources for funding and resources, as well as the West

Virginia Division of Highways, West Virginia Department of Environmental

Protection, and Trus Joist MacMillan for permission to conduct my research on

respective properties.

Finally, I thank my family, especially my mother, for supporting me in my

endeavors to become a wildlife biologist. A special dedication is extended to my

father, Douglas H. Balcombe, whose memory continues to inspire me to accomplish

high levels of achievement.

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CHAPTER I............................................................................................................... 1 A LITERATURE REVIEW OF WETLAND VALUE, FUNCTION, AND MITIGATION SUCCESS: PROJECT OVERVIEW ........................ 1 ABSTRACT.................................................................................................................. 2

Wetland value ........................................................................................................... 3 Vegetation and wildlife use ...................................................................................... 5 Wetland protection.................................................................................................... 7 Mitigation success..................................................................................................... 8

JUSTIFICATION ....................................................................................................... 10 OBJECTIVES............................................................................................................. 11 STUDY SITES............................................................................................................ 13

Overview of West Virginia..................................................................................... 13 AREA 1................................................................................................................... 14 AREA 2................................................................................................................... 16 AREA 3................................................................................................................... 18 AREA 4................................................................................................................... 22

QUALITY CONTROL............................................................................................... 24 LITERATURE CITED ............................................................................................... 25 TABLES ..................................................................................................................... 32 FIGURES.................................................................................................................... 36 CHAPTER II ........................................................................................................... 57 A COMPARISON OF VEGETATION COMMUNITITES IN MITIGATION AND NATURAL WETLANDS IN THE MID-APPALACHIANS................................................................................................. 57 ABSTRACT................................................................................................................ 58 INTRODUCTION ...................................................................................................... 59 METHODS ................................................................................................................. 62

Study sites ............................................................................................................... 62 Vegetation community sampling ............................................................................ 63 Data analyses .......................................................................................................... 64

RESULTS ................................................................................................................... 66 DISCUSSION............................................................................................................. 69 MANAGEMENT IMPLICATIONS .......................................................................... 74 LITERATURE CITED ............................................................................................... 78 TABLES ..................................................................................................................... 89 FIGURES.................................................................................................................... 91 CHAPTER III ......................................................................................................... 96 AQUATIC MACROINVERTEBRATE COMMUNITY STRUCTURE IN MITIGATION WETLANDS OF WEST VIRGINIA ............................ 96 ABSTRACT................................................................................................................ 97 INTRODUCTION ...................................................................................................... 98 METHODS ............................................................................................................... 102

Study sites ............................................................................................................. 102 Invertebrate sampling............................................................................................ 103

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Statistical analyses ................................................................................................ 104 RESULTS ................................................................................................................. 105

Taxa occurrence .................................................................................................... 105 Mitigation versus reference wetlands ................................................................... 105 Emergent versus open water habitats.................................................................... 108

DISCUSSION........................................................................................................... 108 Mitigation versus reference wetlands ........................................................................ 108 Emergent versus open water habitats.................................................................... 117 Future considerations ............................................................................................ 119 Management options............................................................................................. 121

LITERATURE CITED ............................................................................................. 125 TABLES ................................................................................................................... 137 CHAPTER IV ....................................................................................................... 144 WILDLIFE HABITAT USE IN MITIGATION AND NATURAL WETLANDS OF WEST VIRGINIA ............................................................. 144 ABSTRACT.............................................................................................................. 145 STUDY AREA ......................................................................................................... 151 METHODS ............................................................................................................... 152

Avian Communities .............................................................................................. 152 Anuran Communities ............................................................................................ 153 Habitat Quality...................................................................................................... 154 Statistical Analyses ............................................................................................... 157

RESULTS ................................................................................................................. 159 Avian Communities .............................................................................................. 159 Anuran Communities ............................................................................................ 160 Habitat Quality...................................................................................................... 161

Red-winged Blackbird.-- ................................................................................... 161 Beaver.--............................................................................................................ 162 Muskrat.--.......................................................................................................... 162 Mink.--............................................................................................................... 162 Great Blue Heron.-- .......................................................................................... 163 Wood Duck.-- .................................................................................................... 163 Red-spotted Newt.--........................................................................................... 164 Snapping Turtle.-- ............................................................................................. 165

DISCUSSION........................................................................................................... 165 Avian Communities .............................................................................................. 165 Anuran Communities ............................................................................................ 170 Habitat Quality...................................................................................................... 177

Red-winged Blackbird.-- ................................................................................... 177 Beaver.--............................................................................................................ 178 Muskrat.--.......................................................................................................... 179 Mink.--............................................................................................................... 180 Great Blue Heron.-- .......................................................................................... 181 Wood Duck.-- .................................................................................................... 184 Red-spotted Newt.--........................................................................................... 187 Snapping Turtle.-- ............................................................................................. 188

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Conclusions.-- ................................................................................................... 190 CONCLUSIONS....................................................................................................... 194 MANAGEMENT IMPLICATIONS ........................................................................ 196 LITERATURE CITED ............................................................................................. 206 TABLES ................................................................................................................... 228 CHAPTER V......................................................................................................... 234 VEGETATION, INVERTEBRATE, AND WILDLIFE COMMUNITY RANKINGS AND HABITAT ANALYSIS OF MITIGATION WETLANDS IN WEST VIRGINIA .............................................................. 234 ABSTRACT.............................................................................................................. 235 INTRODUCTION .................................................................................................... 236 METHODS ............................................................................................................... 240

Study sites ............................................................................................................. 240 Vegetation community sampling .............................................................................. 242 Wetland delineation .............................................................................................. 242 Invertebrate sampling............................................................................................ 243 Avian and anuran communities ............................................................................ 244 Habitat quality....................................................................................................... 244 Statistical analyses ................................................................................................ 245

RESULTS ................................................................................................................. 249 Wetland rankings .................................................................................................. 249 Canonical Correspondence Analysis .................................................................... 251 Wetland delineation .............................................................................................. 252

DISCUSSION........................................................................................................... 253 Wetland rankings .................................................................................................. 253 Environmental data ............................................................................................... 256 Mitigation success................................................................................................. 258 Conclusions........................................................................................................... 259

LITERATURE CITED ............................................................................................. 262 TABLES ................................................................................................................... 274 FIGURES.................................................................................................................. 297 APPENDICES ...................................................................................................... 307

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CHAPTER I. LIST OF TABLES Table 1. List of 11 mitigation and 4 reference wetland study sites in West Virginia, including site name, year constructed, size (ha), source builder, Universal Transverse Mercator (UTM) coordinates, 7.5 minute quadrangle, basin, and watershed, 2001-2002��..33 Table 2. Universal Transverse Mercator (UTM) coordinates of frog, bird, and vegetation sampling locations for 11 reference and 4 mitigation wetlands of West Virginia, 2001-2002��..34 CHAPTER I. LIST OF FIGURES Figure 1. Study site locations for mitigation and reference wetlands in West Virginia, 2001-2002��..37 Figure 2. Location of the Altona Marsh reference wetland on the Middleway 7.5 minute quadrangle, West Virginia, 2001-2002��38 Figure 3. Location of the Walnut Bottom mitigation wetland on the Old Fields 7.5 minute quadrangle, West Virginia, 2001-2002��..��..39 Figure 4. Location of the Elder Swamp reference wetland and the VEPCO mitigation wetland on the Mt. Storm 7.5 minute quadrangle, West Virginia, 2001-2002��40 Figure 5. Location of the Buffalo Coal mitigation wetland on the Davis 7.5 minute quadrangle, West Virginia, 2001-2002��41 Figure 6. Location of the Elk Run mitigation wetland on the Davis 7.5 minute quadrangle, West Virginia, 2001-2002��42 Figure 7. Location of the Meadowville reference wetland and the Sugar Creek mitigation wetland on the Nestorville 7.5 minute quadrangle, West Virginia, 2001-2002��..43 Figure 8. Location of the Leading Creek mitigation wetland on the Montrose 7.5 minute quadrangle, West Virginia, 2001-2002��44 Figure 9. Location of the Sand Run mitigation wetland on the Buckhannon 7.5 minute quadrangle, West Virginia, 2001-2002��45 Figure 10. Location of the Triangle and Trus Joist MacMillan mitigation wetlands on the Century 7.5 minute quadrangle, West Virginia, 2001-2002��..46

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Figure 11. Location of the Muddlety reference wetland and the Enoch Branch mitigation wetland on the Widen 7.5 minute quadrangle, West Virginia, 2001-2002��..47 Figure 12. Location of the Bear Run mitigation wetland on the Glenville 7.5 minute quadrangle, West Virginia, 2001-2002��48 Figure 13. Photograph of the Altona Marsh reference wetland, West Virginia, summer, 2001��...49 Figure 14. Photograph of the Walnut Bottom mitigation wetland, West Virginia, summer, 2001��...49 Figure 15. Photograph of the Elder Swamp reference wetland, West Virginia, summer, 2001��...50 Figure 16. Photograph of the VEPCO mitigation wetland, West Virginia, summer, 2001��..50 Figure 17. Photograph of the Buffalo Coal mitigation wetland, West Virginia, summer, 2001��...51 Figure 18. Photograph of the Elk Run mitigation wetland, West Virginia, spring, 2001��..51 Figure 19. Photograph of the Meadowville reference wetland, West Virginia, summer, 2001��...52 Figure 20. Photograph of the Leading Creek mitigation wetland, West Virginia, winter, 2001��.52 Figure 21. Photograph of the Sugar Creek mitigation wetland, West Virginia, summer, 2001��...53 Figure 22. Photograph of the Sand Run mitigation wetland, West Virginia, summer, 2001��..53 Figure 23. Photograph of the Triangle mitigation wetland, West Virginia, summer, 2001��..54 Figure 24. Photograph of the Trus Joist MacMillan mitigation wetland, West Virginia, summer, 2001��...54 Figure 25. Photograph of the Muddlety reference wetland, West Virginia, summer, 2001��..55

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Figure 26. Photograph of the Enoch Branch mitigation wetland, West Virginia, summer, 2001��...55 Figure 27. Aerial photograph of the Bear Run mitigation wetland, West Virginia, fall, 2001��..56 CHAPTER II. LIST OF TABLES Table 1. Total cover, richness, evenness, and diversity per 0.05 ha quadrat of native and nonnative species, as well as weighted averages and Wetland Indicator Statuses for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..90 CHAPTER II. LIST OF FIGURES Figure 1. Detrended Correspondence Analysis of vegetation quadrats for all species within 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West Virginia, 2001-2002. Two letter abbreviations with numbers represent individual quadrats at each wetland��.92 Figure 2. Detrended Correspondence Analysis of vegetation quadrats for native species only within 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West Virginia, 2001-2002. Two letter abbreviations with numbers represent individual quadrats at each wetland.��.93 Figure 3. Detrended Correspondence Analysis of vegetation quadrats for all species within 11 mitigation (n = 45) sites in West Virginia, 2001-2002. Quadrats were ordinated using age as a categorical variable. Two letter abbreviations with numbers represent individual quadrats at each wetland.��94 Figure 4. Detrended Correspondence Analysis of vegetation quadrats for all species within 11 mitigation (n = 45) sites in West Virginia, 2001-2002. Quadrats were ordinated using actual age as a quantitative variable. Two letter abbreviations with numbers represent individual quadrats at each wetland.��.95 CHAPTER III. LIST OF TABLES Table 1. Benthic invertebrate richness (no. families/wetland), diversity, density (no./m2) and biomass (g/m2) between mitigation (n =11) and reference (n = 4) wetlands across emergent areas, open water areas, and entire wetland complexes, 2001-2002 with comparisons of all invertebrate taxa and the 9 most common taxa (i.e., >100 individuals)��...��138 Table 2. Nektonic invertebrate richness (no. families/wetland), diversity, density (no./L) and biomass (g/L) between mitigation (n = 11) and reference (n = 4) wetlands

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across emergent areas, open water areas, and entire wetland complexes, West Virginia, 2001-2002 with comparisons of all invertebrate taxa and the 13 most common taxa (i.e., >100 individuals)��140 Table 3. Benthic and nektonic invertebrate familial richness (no. families/wetland), diversity, density (benthic: no./m2; nektonic: no./L) and biomass (benthic g/m2; nektonic: g/L) between emergent and open water areas of mitigation wetlands (n = 11) in West Virginia, 2001-2002 with comparisons of all taxa and for the 9 most common (abundant) benthic and 13 most common nektonic taxa (i.e., >100 individuals)��142 Table 4. Benthic and nektonic invertebrate familial richness (no. families/wetland), diversity, density (no./L), and biomass (g/L) among emergent, open water, and scrub-shrub areas of the Elder Swamp reference wetland (n = 1), West Virginia, 2001-2002 with density and mass comparisons of all taxa and for the 9 most common (abundant) benthic taxa and 13 most common nektonic taxa (i.e., >100 individuals)��143 CHAPTER IV. LIST OF TABLES Table 1. Optimal Suitability Index (SI) scores of 38 habitat variables evaluated for Habitat Suitability Index models on 8 wildlife species in mitigation (n = 11) and natural (n = 4) wetlands in West Virginia, 2001-2002��..229 Table 2. Richness (no. species/0.78 ha), diversity (per 0.78 ha), and abundance (no.birds/0.78 ha) comparisons for avian communities between mitigation (n = 11) and natural (n = 4) wetlands in West Virginia, 2001-2002��...231 Table 3. Wisconsin Index value and abundance per wetland for all anuran species combined and for each of 7 species heard at mitigation (n = 11) and natural (n = 4) wetlands, West Virginia, 2001-2002��.232 Table 4. Mean Suitability Index (SI) values between mitigation (n = 11) and natural (n = 4) wetlands of Habitat Suitability Index models for 8 wildlife species, West Virginia, 2001-2002��...233 CHAPTER V. LIST OF TABLES Table 1. List of 11 mitigation and 4 reference wetland study sites in West Virginia, including site name, year constructed, size (ha), source builder, Universal Transverse Mercator (UTM) coordinates, 7.5 minute quadrangle, basin, and watershed, 2001-2002��275 Table 2. Actual means and ranks of vegetation richness (no.species/plot), evenness, evenness (native species only), diversity, diversity (native species only), and

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weighted average, as well as total mean and scaled ranks for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..276 Table 3. Actual mean and ranks of benthic and nektonic invertebrate richness (no.families/wetland), diversity, density, and mass, as well as total mean and scaled ranks for 11 mitigation and 11 reference wetlands in West Virginia, 2001-2002�.278 Table 4. Actual means and ranks of avian richness (no. birds/0.78 ha plot) and diversity, and abundance (no.indiv./0.78 ha plot) for all birds, waterbirds, waterfowl, and passerines, as well as total mean and scaled ranks of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..280 Table 5. Actual means and ranks of anuran richness (no.species/wetland), Wisconsin Index (WI), and abundance for all species and for 7 individual species, as well as total mean and scaled ranks of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..282 Table 6. Actual Habitat Suitability Index (HSI) values and ranks of 8 species, as well as total and scaled ranks of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..284 Table 7. Vegetation, invertebrate, avian, anuran, and Habitat Suitability Index (HSI) ranks, as well as total mean and scaled ranks for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..286 Table 8. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of all avian species abundance within all wetlands (n = 15) and for mitigation wetlands only (n = 11) in West Virginia, 2001-2002��288 Table 9. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of waterbird species abundance within 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..289 Table 10. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of anuran species abundance within all wetlands (n = 15) and for mitigation wetlands only (n = 11) in West Virginia, 2001-2002��...290 Table 11. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of benthic invertebrate familial abundance within all wetlands (n = 15) and for mitigation wetlands only (n = 11) in West Virginia, 2001-2002��...291

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Table 12. Summary of parameters including general structure and intraset correlation coefficients for all environmental variables in the canonical correspondence analysis of nektonic invertebrate familial abundance within all wetlands (n = 15) and for mitigation wetlands only (n = 11) in West Virginia, 2001-2002��...292 Table 13. Species codes and common names of all avian and waterbird species included in canonical correspondence analysis of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..293 Table 14. Species codes and common names of 7 anuran species included in canonical correspondence analysis of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��...294 Table 15. Species codes and common names of benthic and nektonic invertebrates included in canonical correspondence analysis of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002��..295 CHAPTER V. LIST OF FIGURES Figure 1. Canonical correspondence analysis ordination of all avian species on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 5 environmental variables: open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity.��..�298 Figure 2. Canonical correspondence analysis ordination of all avian species on 11 mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity��..299 Figure 3. Canonical correspondence analysis ordination of all waterbird species on 11 mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity��..300 Figure 4. Canonical correspondence analysis ordination of all anuran species on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 5 environmental variables: open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity��...301

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Figure 5. Canonical correspondence analysis ordination of all anuran species on 11 mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate nektonic diversity��302 Figure 6. Canonical correspondence analysis ordination of benthic invertebrate families on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 4 environmental variables: open = % open water; emveg = % emergent vegetation; subm = % submergent vegetation; vegh = vegetation diversity��303 Figure 7. Canonical correspondence analysis ordination of benthic invertebrate families on 11 mitigation wetlands in West Virginia, 2001-2002, based on 6 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; subm = % submergent vegetation; vegh = vegetation diversity��304 Figure 8. Canonical correspondence analysis ordination of nektonic invertebrate families on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 4 environmental variables: open = % open water; emveg = % emergent vegetation; subm = % submergent vegetation; vegh = vegetation diversity��305 Figure 9. Canonical correspondence analysis ordination of nektonic invertebrate families on 11 mitigation wetlands in West Virginia, 2001-2002, based on 6 environmental variables: age, size, open = % open water; emveg = % emergent vegetation; subm = % submergent vegetation; vegh = vegetation diversity��306 LIST OF APPENDICES Appendix 1. Average percent cover/1.0 m2 quadrat of all herbaceous vegetation species sampled in 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West Virginia, 2001-2002��308 Appendix 2. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Walnut Bottom mitigation wetland, 2001-2002��313 Appendix 3. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the VEPCO mitigation wetland, 2001-2002��...314 Appendix 4. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Buffalo Coal mitigation wetland, 2001-2002��316

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Appendix 5. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Elk Run mitigation wetland, 2001-2002��...317 Appendix 6. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Leading Creek mitigation wetland, 2001-2002��.318 Appendix 7. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Sugar Creek mitigation wetland, 2001-2002��323 Appendix 8. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Sand Run mitigation wetland, 2001-2002��.325 Appendix 9. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Triangle mitigation wetland, 2001-2002��...327 Appendix 10. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Trus Joist MacMillan mitigation wetland, 2001-2002��..329 Appendix 11. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Enoch Branch mitigation wetland, 2001-2002��..331 Appendix 12. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Bear Run mitigation wetland, 2001-2002��.332 Appendix 13. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Altona Marsh reference wetland, 2001-2002��333 Appendix 14. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Elder Swamp reference wetland, 2001-2002��334 Appendix 15. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Meadowville reference wetland, 2001-2002��.335

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Appendix 16. Species list, origin (O), and average cover (AC) of all herbaceous vegetation species sampled, and vegetation species that were seen but not sampled (SBNS) per plot at the Muddlety reference wetland, 2001-2002��..336 Appendix 17. Woody and herbaceous vegetation species that were planted at 3 mitigation wetland sites, West Virginia, 2001-2002��.337 Appendix 18-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Altona Marsh reference wetland, West Virginia, 2001-2002��.338 Appendix 18-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PF = palustrine forested, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom, of the Altona Marsh reference wetland, West Virginia, 2001-2002��...339 Appendix 19-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Walnut Bottom mitigation wetland, West Virginia, 2001-2002�340 Appendix 19-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom, of the Walnut Bottom mitigation wetland, West Virginia, 2001-2002��..340 Appendix 20-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Elder Swamp reference wetland, West Virginia, 2001-2002��.341 Appendix 20-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PF = palustrine forested, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Elder Swamp reference wetland, West Virginia, 2001-2002��...342 Appendix 21-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the VEPCO mitigation wetland, West Virginia, 2001-2002��343 Appendix 21-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the VEPCO mitigation wetland, West Virginia, 2001-2002��...344 Appendix 22-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Buffalo Coal mitigation wetland, West Virginia, 2001-2002��345 Appendix 22-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Buffalo Coal mitigation wetland, West Virginia, 2001-2002��..346

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Appendix 23-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Elk Run mitigation wetland, West Virginia, 2001-2002��347 Appendix 23-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Elk Run mitigation wetland, West Virginia, 2001-2002��...348 Appendix 24-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Meadowville reference wetland, West Virginia, 2001-2002��..349 Appendix 24-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, and PSS = palustrine scrub-shrub, of the Meadowville reference wetland, West Virginia, 2001-2002��350 Appendix 25-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Leading Creek mitigation wetland, West Virginia, 2001-2002�.351 Appendix 25-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Leading Creek mitigation wetland, West Virginia, 2001-2002��...352 Appendix 26-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Sugar Creek mitigation wetland, West Virginia, 2001-2002��.353 Appendix 26-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Sugar Creek mitigation wetland, West Virginia, 2001-2002��..354 Appendix 27-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Sand Run mitigation wetland, West Virginia, 2001-2002��.355 Appendix 27-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Sand Run mitigation wetland, West Virginia, 2001-2002��..356 Appendix 28-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Triangle mitigation wetland, West Virginia, 2001-2002��357 Appendix 28-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,

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and PUB = palustrine unconsolidated bottom of the Triangle mitigation wetland, West Virginia, 2001-2002��..358 Appendix 29-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Trus Joist MacMillan mitigation wetland, West Virginia, 2001-2002��359 Appendix 29-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PSS = palustrine scrub-shrub, PUB = palustrine unconsolidated bottom, and PUS = palustrine unconsolidated shore, of the Trus Joist MacMillan mitigation wetland, West Virginia, 2001-2002��..360 Appendix 30-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Muddlety reference wetland, West Virginia, 2001-2002��...361 Appendix 30-2. Wetland classification (Cowardin et al. 1979) where PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Muddlety reference wetland, West Virginia, 2001-2002��362 Appendix 31-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Enoch Branch mitigation wetland, West Virginia, 2001-2002�..363 Appendix 31-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine unconsolidated bottom of the Enoch Branch mitigation wetland, West Virginia, 2001-2002��...364 Appendix 32-1. Bird, frog, and vegetation sampling points as well as dominant vegetation at the Bear Run mitigation wetland, West Virginia, 2001-2002��..365 Appendix 32-2. Wetland classification (Cowardin et al. 1979) where N/A = no applicable classification, PEM = palustrine emergent, and PUB = palustrine unconsolidated bottom of the Bear Run mitigation wetland, West Virginia, 2001-2002��366 Appendix 33. Number of benthic individuals collected by family and wetland from emergent (E) and open water (O) areas, as well as for the entire complex (total) for 11 mitigation wetlands in West Virginia, 2001-2002��.367 Appendix 34. Number of nektonic individuals collected by family and wetland from emergent (E), open water (O), and scrub-shrub (SS) areas, as well as for the entire complex (total) for 4 reference wetlands in West Virginia, 2001-2002��369

xviii

Appendix 35. Number of nektonic individuals collected by family and wetland from emergent (E) and open water (O) areas, as well as for the entire complex (total) for 11 mitigation wetlands in West Virginia, 2001-2002��.371 Appendix 36. Number of individuals collected by family and wetland from emergent (E), open water (O), and scrub-shrub (SS) areas, as well as for the entire complex (total) for 4 reference wetlands in West Virginia, 2001-2002��...374 Appendix 37. Species list of all birds sampled inside and outside 50 m radius plots (number of birds per point count) in 11 mitigation and 4 natural wetlands in West Virginia, 2001-2002��...377 Appendix 38. Number of birds sampled inside 50 m radius plots (I), outside plots (O) and totals for 11 mitigation wetlands in West Virginia, 2001-2002��..380 Appendix 39. Species list of all birds sampled inside 50 m radius plots (I), outside plots (O) and totals for 4 natural wetlands in West Virginia, 2001-2002��..383 Appendix 40. Species lista of all frogs sampled by survey period in 11 mitigation wetlands in West Virginia (WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run), 2001-2002��.��.387 Appendix 41. Species lista of all frogs sampled by survey period in 4 natural wetlands in West Virginia (AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��...388 Appendix 42. A comparison of actual mean values of all variables measured within the beaver, muskrat, mink, great blue heron, red-winged blackbird, wood duck, snapping turtle, and red-spotted newt Habitat Suitability Index models between mitigation (n = 11) and natural (n = 4) wetlands in West Virginia, 2001-2002��389 Appendix 43. Actual and Suitability index (SI) mean values for variables measured within the beaver, muskrat, mink, great blue heron, red-winged blackbird, wood duck, snapping turtle, and red-spotted newt Habitat Suitability Index models between mitigation (n = 11) and natural (n = 4) wetlands in West Virginia, 2001-2002��392 Appendix 44. Variable measurements and Suitability Index (SI) values for the red-winged blackbird Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��...396

xix

Appendix 45. Variable measurements and Suitability Index (SI) values for the beaver Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��398 Appendix 46. Variable measurements and Suitability Index (SI) values for the muskrat Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��400 Appendix 47. Variable measurements and Suitability Index (SI) values for the mink Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��403 Appendix 48. Variable measurements and Suitability Index (SI) values for the great-blue heron Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��.405 Appendix 49. Variable measurements and Suitability Index (SI) values for the wood duck Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��.408 Appendix 50. Variable measurements and Suitability Index (SI) values for the snapping turtle Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR =

xx

Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��...410 Appendix 51. Variable measurements and Suitability Index (SI) values for the red-spotted newt Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002��413 Appendix 52. Common and scientific names of all birds included in Analysis of Variance models used to calculate metrics for wetland rankings and in Canonical Correspondence Analyses (CCA) on 11 mitigation and 4 reference wetlands, West Virginia, 2001-2002��...415

1

CHAPTER I

A LITERATURE REVIEW OF WETLAND VALUE, FUNCTION,

AND MITIGATION SUCCESS: PROJECT OVERVIEW

COLLINS K. BALCOMBE [email protected]

West Virginia University Division of Forestry

PO Box 6125 Morgantown, WV 26505-6125

2

ABSTRACT

Wetlands are extremely valuable to both people and wildlife, but

unfortunately, wetlands have continually been destroyed for decades with little or no

compensation. Section 404 of the Clean Water Act authorized the U.S. Army Corps

of Engineers to issue permits for dredging and filling practices affecting wetlands.

The �no net loss� policy of 1987 introduced mitigation as the leading tool in

combating wetland loss in the U.S. Damages to wetland functions have begun to be

mitigation by creating compensatory wetlands that must equal or exceed the functions

of destroyed sites. Although no general definition of mitigation success is accepted,

most researchers focus on evaluating wetland functions as a measure of the success of

mitigation. By comparing mitigation sites to naturally occurring reference wetlands,

which are assumed to represent optimal standards of comparison, researchers can

gauge the success of wetland mitigation. Only 2 studies of limited scope have been

conducted in West Virginia on mitigation success, so there was a need for a

comprehensive evaluation on the success of mitigation wetlands in the state. This

study compared vegetation and wildlife communities in 11 mitigation wetlands to

communities existing in 4 reference wetlands. The objectives of this study were to

compare vascular plant community composition and structure, breeding bird

diversity, richness, and abundance, frog richness and abundance, macroinvertebrate

richness, diversity, density, and biomass, and wildlife habitat quality using Habitat

Suitability Index models for 8 wetland-dependent wildlife species. The results of this

study should further our knowledge of wetland ecosystems by providing data that are

regionally applicable to wetland protection and management.

This chapter is written in the style of The Journal of Wildlife Management

3

Wetland value

Wetland habitat in the U.S. is a precious resource that holds many values to

society and wildlife alike. Wetlands provide economic support and recreation for

many people, maintain water quality and quantity, and support numerous plant and

animal species (Wharton et al. 1982, Feierabend and Zelazny 1987, Ernst and Brown

1989). Wetlands hold an aesthetic value to millions of people, and provide various

recreational opportunities including hunting, fishing, and bird watching. Wetlands

also assist in the production of timber and the commercial harvesting of fish and

shellfish species (Johnson 1979, Feierabend and Zelazny 1987, Browder et al. 1989,

National Cooperative Highway Research Program 1996). Wetlands are valuable

ecosystems because they can reduce flood potential by storing rainwater, act as

buffers against storms, or recharge groundwater. They also can improve water

quality by removing organic and inorganic nutrients and toxins from water supplies

(Verry and Boelter 1979, Heimburg 1984, Sather and Smith 1984). This not only

benefits society, but wildlife and plant communities as well.

Wetlands are extremely important to wildlife. More than 50% of the 800

species of protected migratory birds rely on wetlands in some way (Wharton et al.

1982). Although wetlands comprise only about 5% of land in the U.S., about 50% of

all rare and endangered wildlife species are either located in wetlands or depend on

them in some way (Williams and Dodd 1979, Ernst and Brown 1989, Mitsch and

Gosselink 2000). Ernst and Brown (1989) listed 63 plant and 34 animal species as

endangered, threatened, or candidates for listing in forested wetlands throughout the

U.S. In West Virginia, Evans and Wilson (1982) reported 35 species of mammals, 71

4

species of birds, and 41 species of reptiles and amphibians in and around wetlands.

Numerous fish and shellfish species also rely on wetlands, with over 95% of the

nation�s harvest coming from wetlands (Feierabend and Zelazny 1987).

Because so many wildlife species have adapted to the unique habitat features

of wetlands, it is obvious that the destruction and degradation of wetlands negatively

affects biodiversity. Hudson (1991) concluded that wetland destruction in California

has the potential to negatively affect about 220 animal and 600 plant species.

Similarly, Gibbs (1993) used a model that predicted significant losses in turtles, small

birds, and small mammals due to losses of small wetlands. Harris (1988) reported

steady declines in certain waterfowl species due to losses in wetland habitat including

a 35% decline in mallard (Anas platyrhynchos) and a 50% decline in northern pintail

(A. acuta) from 1955 to 1985. While mallard populations have stabilized in recent

years, northern pintail populations currently remain well below population objectives

by the North American Waterfowl Management Plan (Williams et al. 1999). This is

probably attributable to the loss of 38% of the prairie pothole wetlands in the U.S.

(Dahl 1990). Other studies have shown that wetland losses negatively affect

amphibian assemblages (Kolozsvary and Swihart 1999, Lehtinen et al. 1999,

Semlitsch 2002). Conversely, Hickman (1994) revealed increases in biodiversity at

locations where wetlands have been created or restored in a disturbed landscape.

Recognizing the significant values wetlands possess, federal, state, and local

agencies have embraced a �no net loss� policy (National Wetland Policy Forum

1988). This policy seeks to replace lost wetland habitat with new habitat by restoring

and/or constructing wetlands. The federal government defines mitigation activities to

5

include avoidance of impacts, minimization of impacts, site restoration, or

replacement of unavoidable losses (40 CFR Part 1508.20). Wetland mitigation may

compensate for losses caused by (1) agricultural practices that cause sedimentation,

soil subsidence, and herbicide and pesticide accumulations, (2) irrigation and urban

water developments, (3) construction of roads, levees, or canals, (4) wetland and

wildlife management practices including flooding, draw-downs, and farming, and (5)

industrial and military developments. The �no net loss� policy has helped maintain

the numerous benefits of wetlands and their surrounding ecosystems while

accommodating the need for human development.

Vegetation and wildlife use

The term indicator species is often used to describe a species whose presence

represents the health of a community (Robinson and Bolen 1989). Because no single

species can be used to assess the health of an entire community, it is important to

evaluate species-groups or representative taxa that have narrow environmental

tolerances (Graul and Miller 1984), and unique dietary needs that place them at

integral positions within trophic levels.

It is difficult, however, to identify, measure, interpret, or monitor indicators of

biodiversity. Lindenmayer et al. (2000) pointed out some problems associated with

taxon-based indicator species. First, certain taxa can have different responses to

disturbance (Davies and Margules 1998). Some indicators can have high threshold

responses to some environmental conditions, while others may have low thresholds.

In addition, they argue that marked changes in the abundance of some taxa are rarely

synchronous across all taxa. Weaver (1994) mentions that it is difficult to choose an

6

appropriate scale over which one taxa can indicate status of an associated taxa.

Indeed, studies show that caution should be used in determining which indicator

species to use in assessing biodiversity. However, the use of indicator species is

project-specific, whether being used to indicate presence of other species, to assess

human abiotic conditions such as pollution, to serve as early warning indicators of

environmental changes, or as in this study, to assess the the efficacy of efforts to

mitigate disturbance effects. Thus, although the arguments presented above are

legitimate with respect to some projects, general statements about the invalidity of

taxon-based indicator species should be avoided. Numerous studies have

successfully used taxon-based indicators to assess functions of created or restored

wetlands, many of which are discussed below.

My study includes all species within representative taxa (i.e., birds, anurans,

invertebrates) in its assessment of function and does not weigh the abundance of any

species or taxa more heavily than another; nor does it seek to use one species as a

representative or surrogate of another. This study compares diversity, richness, and

abundance of all species and/or taxa to assess the level at which created wetlands are

functioning. As mentioned, wetlands have numerous functions that relate to

hydrological, biogeochemical, and ecological processes. Vegetation, birds,

amphibians and macroinvertebrates are of particular importance when assessing

wetland health because they likely are intricately involved in the complex interactions

that contribute to these functions. They are relatively easy to sample, are conspicuous

by sight and sound, and simple to recognize in the field (Ralph et al. 1993, Casey and

Record, unpublished data, Dodson 2001). Hence, these species supply consistent and

7

reliable data sets that are compatible with field research. Mammals and reptiles were

excluded because of difficulty in adequate sampling. Instead, I used Habitat

Suitability Index models to evaluate habitat for select mammal and reptile species.

Wetland protection

Wetland destruction and degradation has plagued the United States for

decades. The wetland resource base in the 1980s was only 47% of what was present

in the 1780s (Dahl 1990), with a total loss of 47.3 million ha. This destruction is

largely due to the draining or filling of wetlands for agricultural purposes, which for

many years, was subsidized by policies of the federal government (National Research

Council 1995). A concern for the comprehensive protection of wetlands has been

embraced only within the past 2 decades, and the influx of political support for such

protection has resulted in landmark legislation aimed at preserving these valuable

ecosystems.

The Federal Water Pollution Control Act was passed in 1972 in an effort to

restore and maintain the chemical, physical, and biological integrity of the nation�s

navigable waterways. The Act was amended in 1977 as the Clean Water Act, which

included all waters in the U.S., from oceans to inland freshwater wetlands (33 CFR

320). Specifically, Section 404 of the Clean Water Act (40 CFR Part 230.1)

authorizes the Army Corps of Engineers to issue permits for dredging and filling

practices affecting wetlands. Permits issued by the government has promulgated the

construction of thousands of ha of wetlands in the U.S. as a requirement for

mitigation of wetland losses. The �no-net-loss� policy for wetlands endorsed in the

late 1980s, introduced wetland mitigation as the leading tool in combating wetland

8

loss in the U.S. (Jones and Boyd 2000, Mitsch and Gosselink 2000). Damages to

wetland functions have begun to be mitigation by creating compensatory wetlands

that must equal or exceed the functions of the damaged site (Zedler 1996).

Mitigation success

On paper, the �no net loss� policy appears to be working with a gain of about

50,000 ha of wetland and associated uplands in the U.S. from October 1993 to

September 1999 (Mitsch and Gosselink 2000). Caution must be taken, however,

because a net gain in wetland area yields little insight into the actual success of

wetland mitigation in terms of wetland function. Although no generally accepted

definition of mitigation success has been approved, the major focus of researchers has

been on the evaluation of wetland function as a measure of the success of mitigation

wetlands (Wentworth et al. 1988, Atkinson et al. 1993, Reinartz and Warne 1993,

Niswander and Mitsch 1995, Wilson and Mitsch 1996, Campbell et al. 2002).

Wetland functions are, indeed, useful in compensatory mitigation because they allow

expression of the multifaceted nature of ecosystems and provide perspectives around

which performance standards can be designed (Brinson and Rheindhardt 1996).

These standards often come in the form of wetland �templates�, called reference

wetlands, that can guide the design and monitoring of mitigation wetlands. Many

studies have incorporated reference wetlands into monitoring mitigation wetland

function (Confer and Niering 1992, Havens et al. 1995, Moore et al. 1999, Stolt et al.

2000, Campbell et al. 2002).

Several approaches to assessing wetland function have been used by

researchers. The first functional assessment technique for regulatory purposes

9

emerged from the U.S. Army Corps of Engineers in 1975. Functions incorporated by

the U.S. Army Corps of Engineers were public interest, support of food chains and

wildlife habitat, education and recreation, erosion prevention, reduction of storm or

flood damage, ground water discharge and recharge, water purification, and

maintenance of biodiversity (33 CFR 320.4). The Method for Wetland Functional

Assessment, also called FHWA (Federal Highway Wetland Assessment), was

developed by the Federal Highway Administration (Adamus 1983, Adamus and

Stockwell 1983) and directly ranks effectiveness, opportunity, and significance values

of wetlands. The Wetland Evaluation Technique (WET), a modification of FHWA,

ranks functional probabilities and considers physical, chemical, and biological

functions of wetlands including ground-water flow, flood flow alteration, sediment

stabilization, sediment/toxicant retention, nutrient removal/transformation, production

export, wildlife diversity/abundance, aquatic diversity/abundance, recreation, and

uniqueness/heritage (Adamus 1983, Adamus and Stockwell 1983). The

Environmental Monitoring Assessment Program (EMAP) of 1988 focuses on

determining the ecological function of a group of wetlands in a region by comparing

the function of a statistical sample of wetlands to reference wetlands (Novitzki et al.

1994). The Hydrogeomorphic (HGM) approach, developed by Brinson (1993)

incorporates features of the other 2 methods and includes the comparison of regional

wetland data sets based on geomorphic setting, water source, and hydrodynamics

health.

As mentioned, most researchers today embrace the use of reference wetlands

in assessing mitigation success. This technique assumes that reference wetland�s

10

structural components and physical, chemical, and biological processes have reached

a dynamic equilibrium that has enabled them to represent the highest, sustainable

functional capacity of a wetland (Smith et al. 1995). Researchers, therefore, can

define mitigation success in terms of whether constructed wetlands have developed

sustainable functional attributes similar to those that have been reached by reference

wetlands.

JUSTIFICATION

Wetland degradation and destruction has occurred in the U.S. for many

decades, but the need to compensate for these losses has only been realized within the

past 20 years. West Virginia has played an active role in wetland mitigation, but only

2 studies have been conducted in the state that have evaluated the functional attributes

of these wetlands (R.H. Fortney, West Virginia University unpublished report,

Johnson et al. 2000). A major aspect of this unpublished report included the

evaluation of wildlife and vascular plant communities as an indicator of the

development of biological and ecological attributes in mitigation wetlands towards

reference standards. This study was extremely valuable in evaluating wetland

function and success and set the stage for the development of future projects of

similar design. However, the study was relatively limited in scope and addressed

only 6 wetlands within a limited area.

The mitigation wetlands evaluated in this study, coupled with their respective

reference wetlands, provide an opportunity for the study of wetland function and

mitigation success across West Virginia. This study was a comprehensive evaluation

11

of 15 wetlands, and included an assessment of wildlife and plant communities and

wildlife habitat suitability. The results should further our knowledge of wetland

ecosystems by providing data that are regionally applicable to wetland protection and

management. These data also could be used to establish protocols for the continued

monitoring of these and other mitigation wetlands in West Virginia. Finally, this

study should be valuable in the selection of future mitigation projects that will have

the highest probability of success.

OBJECTIVES

The purpose of this study was to determine if the mitigation wetland sites in

West Virginia have developed ecological functions similar to naturally functioning

reference wetlands. The objectives were to:

1) compare vascular plant community composition and structure;

2) compare vascular plant species diversity and richness;

3) compare breeding bird diversity, richness, and abundance;

4) compare anuran species richness and abundance;

5) compare macroinvertebrate familial richness, diversity, density, and biomass;

and

6) evaluate habitat suitability for a variety of wildlife species using standardized

models.

It was hypothesized that natural wetlands would support more vegetation

species adapted to wet environments (i.e., more facultative and obligate wetland plant

species; see Chapter II for definitions). Thus, I anticipated that weighted averages

12

(Chapter II) would be lower in natural wetlands. Because it is likely that reference

wetlands are wetter relative to mitigation sites, and because mitigation sites tend to

provide more disturbed habitat, I expected natural wetlands to support less nonnative

plant species than mitigation wetlands. Hence, I predicted reference wetlands to have

a lower vascular plant species richness and diversity than mitigation wetlands.

Because the mitigation sites are ≥ 5 years old, with some ≥ 10 years, I

anticipated finding high species richness, diversity, and abundance of vascular plants

and wildlife in mitigation wetlands. Hence, I expected to find evidence that showed

mitigation wetlands are developing toward reference standards. However, due to the

proximity of mitigation sites to human disturbances (i.e., roads), and the relatively

limited development time of these sites towards natural conditions, I expected

wildlife indices to be higher in reference wetlands than in mitigation wetlands. I

predicted that habitat suitability would vary among each evaluated species between

mitigation and reference wetlands, but that overall, reference wetlands would score

higher habitat suitability indices for all evaluated species combined.

As such, the following null hypotheses were tested.

1. Vascular plant community composition and structure were similar between

mitigation and reference wetlands.

2. Vascular plant species diversity and richness were similar between mitigation

and reference wetlands.

3. Breeding bird diversity, richness, and abundance were similar between


13

4. Anuran species richness, and abundance were similar between mitigation and

reference wetlands.

5. Macroinvertebrate familial richness, diversity, density, and biomass were

similar between mitigation and reference wetlands.

6. Habitat suitability indices for all evaluated species were similar between


STUDY SITES

Overview of West Virginia

West Virginia can be classified into 3 regions (Fenneman 1938; Figure 1).

The unglaciated Western Hill section is the largest province in West Virginia, and

includes the Appalachian Plateau between the Ohio River and the mountainous area

to the east. It is a mature plateau with moderate to strong relief in the south

consisting of numerous rolling hills. Most of the hills in the northern and western

portions of the state are ≤ 450 m in elevation. Southern sections of this region,

however, reach elevations ≥ 900 m and can exceed 1,000 m.

The Allegheny Mountain section includes the high mountains that lie in the

Cheat River system and in the headwaters of the North Branch of the Potomac River.

This section contains the highest elevations in West Virginia with many ridges

reaching between 1,200 m and 1,375 m in elevation. The highest point in the state,

Spruce Knob on Spruce Mountain in Pendleton County, is located in this region and

peaks at 1,482 m. This section contains the Allegheny Mountains that extend

northward from West Virginia into western Maryland and central Pennsylvania.

14

These mountain ranges are oriented in a northeast-southwest direction with deep,

narrow valleys in between.

The Ridge and Valley province is located east of the Allegheny Front, and is

drained primarily by the Potomac River. This region is a lowland area that, as its

name implies, contains numerous interspersed ridges that form a narrow belt along

the eastern margin of the state. The elevation of valley floors ranges from 300 to 400

m with ridges reaching ≥ 1,219 m in elevation.

Fifteen wetlands were evaluated including 11 mitigation wetlands and 4

reference wetlands (Figure 1). The study sites were condensed into 4 areas for

comparison with each area containing 1 reference wetland, although for statistical

purposes, all mitigation sites were compared to all reference sites. Reference sites

were chosen for each area based on their similarity in geographic location, elevation,

size, vegetative structure, and hydrology to mitigation sites. Since the reference

wetlands are relatively larger than mitigation sites, only portions of reference sites

resembling conditions to mitigation wetlands were selected for study. Monthly

average temperature for 2001-2002 ranged from 3.3 to 21.4°C ( x = 10.3, SE = 0.6)

and monthly precipitation ranged from 2.9 to 22.3 cm ( x = 10.0, SE = 0.7; National

Weather Service 2003). A summary of mitigation and reference sites are provided in

Table 1. I also provided a list of Universal Transverse Mercator (UTM) coordinates

for vegetation, avian, and anuran sampling points for all wetlands in Table 2.

AREA 1

The 2 study sites in this area are located within the South Branch of the

Potomac River drainage basin. They are located within the Ridge and Valley

15

physiographic region, which is typified by lowland areas containing interspersed

ridges, and a parallel drainage pattern (Fenneman 1938). Average elevation is about

252 m. Both wetlands in this area were classified as palustrine emergent persistent

wetlands (Cowardin et al. 1979).

Altona Marsh reference wetland

This reference site was chosen to represent the Walnut Bottom mitigation

wetland. It is located in Jefferson County (4353000 N 768600 E, Middleway 7.5

minute quad) on the eastern panhandle of the state 2.5 km west of Charles Town off

State Route 51 (Figures 2 & 13). It is located within the Shenandoah River floodplain

at an elevation of 170 m. The size of the area chosen for study was 15.2 ha. This

wetland contains a marl substrate (mixture of clay, calcium, and magnesium

carbonate) overlaid on a bed of limestone. It is typified by open water areas (0.7 ha)

surrounded by seasonally flooded meadows dominated by herbaceous communities

(10.2 ha) of broad-leaved cattail (Typha latifolia), Baltic rush (Juncus balticus), and

marsh fern (Thelypterus palustris). Shrub thickets (2.8 ha) of glaucous willow (Salix

discolor) and silky cornel (Cornus amomum) are prevalent on the western portion of

the wetland, as well as forested communities (1.6 ha) consisting of sycamore

(Platanus occidentalis),, and white ash (Fraxinus. americana).

Walnut Bottom

This wetland was built by the Division of Highways (DOH) in 1997 as

mitigation for the construction of a major highway named Appalachian Corridor H. It

is located in Hardy County (4334210 N 673914 E, Old Fields 7.5 minute quad), 2.0

km north of Moorefield off U.S. Route 220 (Figures 3 & 14). Located on the South

16

Branch of the Potomac watershed, it is at an elevation of 335 m. Walnut Bottom is

9.5 ha in size and consists of 3 main cells separated by 2 dikes. The upper, middle,

and lower cells are about 2.5, 3.0, and 4.0 ha, respectively. Permanently flooded

open water ponds are surrounded by wet meadows consisting of emergent vegetation

dominated by cattail, spikerush (Eleocharis tenuis), and reed canarygrass (Phalaris

arundinacea).

AREA 2

Study sites in this area are located north of Canaan Valley within the Cheat

and Potomac River drainage basins. They also are located within the Appalachian

Plateaus physiographic region that is typified by high elevations within the Allegheny

mountains, and a dendritic drainage pattern (Fenneman 1938). The wetlands in this

area average 954 m in elevation, making them the highest elevation wetlands in the

study. All were classified as palustrine systems dominated by persistent emergents

(Elder Swamp, VEPCO [Virginia Electric Power Company], and Buffalo Coal) or

open water (Elk Run; Cowardin et al. 1979).

Elder Swamp reference wetland

This reference wetland was chosen to represent the VEPCO, Buffalo Coal,

and Elk Run mitigation wetlands. Elder Swamp is located in Tucker County

(4340000 N 642200 E, Mt. Storm Lake 7.5 minute quad) within the Blackwater River

watershed. It is located off State Route 93, about 8.0 km east of Thomas, at an

elevation of 1,000 m (Figures 4 & 15). Within Elder Swamp, the area chosen for

study was 28.0 ha in size (10.1 ha emergent, 6.5 ha open water, 9.9 ha scrub-shrub,

and 1.5 ha forest). This wetland has diverse habitats with extensive shrub thickets

17

consisting of speckled alder (Alnus incana) and red chokeberry (Pyrus arbutifolia) as

well as forested areas consisting of red spruce (Picea rubens). Emergent vegetation is

dominated by swamp dewberry (Rubus hispidis) and broad-leaved cattail.

VEPCO

Located in Tucker County (4337900 N 641300 E, Mt. Storm Lake 7.5 minute

quad) within the Blackwater River watershed at an elevation of 1,036 m, this site was

built in 1995 as mitigation for the creation of the Phase A Flue Gas Desulfurization

By-Product Facility by Virginia Power Electric Company at the Mount Storm Power

Station. The A-Frame Road mitigation site (referred to as VEPCO) is located about

0.8 km from the impact site off State Route 93 (Figures 4 & 16). It is only 3.0 km

from Elder Swamp. The total mitigation area is 7.0 ha in size, consisting of 5.9 ha

emergents, 0.9 ha open water, and 0.2 ha scrub-shrub areas. This site consists of 4

cells. The 3 cells east of the A-frame road are separated by a series of dikes and each

consists of 1 or 2 open water areas separated by temporarily flooded emergent

vegetation dominated by common rush (Juncus effusus). The cell to the west, also

dominated by common rush, contains 1 speckled alder community near the road. A

list of vegetation species planted at this site during construction is provided in Table

3.

Buffalo Coal

This wetland also is located in Tucker County (4332100 N 630900 E, Davis

7.5 minute quad) at an elevation of 940 m within the Cheat River basin in the

Blackwater River watershed. It was constructed in 1981 as mitigation for the

destruction of 12.1 ha of wetlands resulting from mining activities committed by

18

Davis Trucking Company. It is situated near the State Route 32 and 93 interchange

about 2.0 km from Thomas (Figure 5 & 17). It is 9.0 ha in size, consisting of 6.2 ha

emergents, 2.3 ha open water, and 0.5 ha scrub-shrub areas. This site consists of 4

open water ponds separated by semi-permanently flooded emergent areas dominated

by common rush and cattail. This site contains glade St. Johns Wort (Hypericum

densiflorum) and spiraea (Spiraea alba) shrub thickets.

Elk Run

This site is located within Grant County (4342000N 636250 E, Davis 7.5

minute quad) in the north branch of the Potomac River basin within the Elk Run

watershed (Figure 6 & 18). It was constructed in 1981 as mitigation for the Island

Creek Coal Company�s creation of the Alpine Mine Complex Treated Water

Impoundment. Elk Run is 3.8 ha in size consisting of 0.4 ha emergents, 3.3 ha open

water, and 0.1 ha scrub-shrub areas. It is located at an elevation of 840 m. This site

represents the enhancement and expansion of existing wetlands through the creation

of water control structures. Currently, it consists of 2 cells connected by a large dike.

The first cell is a large permanently flooded open water pond while the second cell is

temporarily flooded and dominated by rough arrowwood (Viburnum dentatum) and

cattail.

AREA 3

All 5 wetland study sites in this area are located within the Tygart Valley

River drainage basin within the towns of Buckhannon, Elkins, and Belington. They

also are located in the Appalachian Plateaus region as well as the extreme western

portion of the Allegheny Mountain physiographic region that is generally typified by

19

low hills and narrow valleys and a dendritic drainage pattern, similar to the Western

Hill section (Fenneman 1938). Mitigation wetlands in this area average 496 m in

elevation. All can be classified as palustrine emergent persistent wetlands, except for

Meadowville, which is scrub-shrub (Cowardin et al. 1979).

Meadowville reference wetland

This natural wetland was used as a reference site to represent the Leading

Creek, Sugar Creek, Sand Run, Triangle, and Trus Joist MacMillan mitigation

wetlands. This wetland is located in the Laurel Creek watershed in Barbour County

(4330920 N 593940 E, Nestorville 7.5 minute quad) just north of Meadowville off of

State Route 92 (Figure 7 & 19). It is part of a bottomland wetland complex along

Glady Fork, that is a tributary of Sugar Creek. At an elevation of 570 m, it is 6.6 ha

in size, consisting of 2.0 ha emergents and 4.6 ha scrub-shrub areas. This wetland has

a semi-permanently flooded to saturated hydrologic regime with diverse vegetative

cover composed of scrub-shrub and emergent vegetation. It is dominated by

graminoid and forb emergent (persistent) vegetation including sedges (Carex spp.),

rice cutgrass (Leersia oryzoides), and cattail. The wetland also contains well

developed shrub thickets containing spiraea, swamp rose (Rosa palustris), brookside

alder (Alnus serrulata), and silky cornel.

Leading Creek

This wetland is Located in Randoph County (4321563 N 602550 E, Montrose

7.5 minute quad), 1.0 km south of Montrose off of U.S. Route 219 (Figure 8). It is

located within the Leading Creek watershed at an elevation of 600 m. This wetland is

8.6 ha in size, consisting of 6.5 ha emergents, 1.9 ha open water, and 0.2 ha scrub-

20

shrub areas. This wetland was built in 1995 by DOH as mitigation for Corridor H.

This complex wetland consists of cells located on both sides of Leading Creek. The

first cell, located north of Leading Creek, contains diverse graminoid and forb

persistent emergent vegetation communities dominated by common rush and wool

grass (Scirpus cyperinus). The second major area, located south of Leading Creek,

can be further divided into 3 cells, all of which are open water ponds surrounded by

stands of common rush and cattail. A wet meadow dominated by common rush exists

west of the southern-most open water cell east of Leading Creek.

Sugar Creek Like Leading Creek, Sugar Creek was constructed in 1995 by the DOH as

mitigation for Corridor H. It is situated within the Laurel Creek watershed in Barbour

County (4328850 N 591470 E, Belington 7.5 minute quad; Figure 7). At an elevation

of 478 m, it is 6.8 ha in size, consisting of 5.1 ha emergents, 1.2 ha open water, and

0.5 ha scrub-shrub areas. This wetland contains an upstream section and a

downstream section. The upstream portion is a combination of small, excavated

depressions with open water or saturated soils and emergent herbaceous vegetation

dominated by reed canarygrass. Another 0.5 ha of area exists at the extreme upstream

portion of the wetland and is composed of patches of scrub-shrub and young forested

stands. Common species include laurel oak (Quercus laurifolia), crab apple (Pyrus

coronaria), hazelnut (Corylus americana), and hawthorn (Crataegus spp.) The

downstream section of the wetland included a large contiguous area containing both

vegetated and unvegetated ponds, as well as temporarily flooded areas dominated by

various sedges.

21

Sand Run This wetland was constructed by DOH in 1992 to mitigate for the construction

of Corridor H. Located in the Sand Run watershed, this site is 3.0 ha in size (2.0 ha

open water and 1.0 ha emergents), with about 0.4 ha of wetland existing before

construction. At an elevation of about 472 m, Sand Run is located in Upshur County

(4315060 N 573140 E, Buckhannon 7.5 minute quad) 6.8 km east of Buckhannon off

U.S. Route 33 between Sand Run River and an embankment on the north side of U.S.

Route 33 (Figure 9). It is about 8.0 km from the confluence of the Sand Run and

Buckhannon Rivers. The hydrologic regime varies dramatically during the growing

season. Sand Run does not have a persistent water source during summer months,

with about three quarters of the site having standing water during spring and summer,

and only one-sixth to one-fourth of the site having standing water in August.

Nonetheless, Sand Run can be described as a large open water pond that supports

common rush and cattail communities in its western section, along with a few

buttonbush (Cephalanthus occidentalis) shrubs.

Triangle

This wetland also was constructed in 1992 by DOH as mitigation for Corridor

H. It is 3.1 ha in size, 0.3 ha of which existed as a wetland prior to its construction.

This site consists of 2.5 ha emergents, 0.4 ha open water, 0.2 ha scrub-shrub areas and

a few patches of forested areas. It is located in Upshur County (4316950 N 568500

E, Century 7.5 minute quad) less than 1,000 m downstream of the Buckhannon city

limits on the floodplain of the Buckhannon River (Figure 10). It features 2 separate

sections: an upper section on the north side with an elevation of about 429 m, and a

22

lower section on the south end with an elevation of about 428 m. Three basic habitat

or vegetation types exist in both areas. These include marsh habitats dominated by

rice cutgrass and purple loosestrife (Lythrum salicaria) that are contiguous with open

water areas, scattered wet meadows dominated by cattail, and bottomland overflow

habitats that were located along the margins of the wetland.

Trus Joist MacMillan

This wetland was created in 1994 as mitigation for the construction of the

Trus Joist MacMillan engineered wood plant. Like Triangle, this site is located

within the Buckhannon River watershed in Upshur County (4318340 N 569560 E,

Century 7.5 minute quad) at an elevation of 430 m (Figure 10). It is 3.2 ha in size,

consisting of 1.9 ha emergents, 0.8 ha open water, and 0.5 ha scrub-shrub areas. This

site consists of 2 major sections. The eastern section is dominated by a moderately

fished open water pond with a few seasonally flooded emergent areas dominated by

common rush and cattail along the perimeter. The western section is dominated by

brookside alder (Alnus serrulata) and possesses small patches of marsh habitat

dominated by cattail and rice cutgrass.

AREA 4

Study sites in this area are located within the Western Hills physiographic

region that is typified by low hills and narrow valleys, and a dendritic drainage

pattern (Fenneman 1938). Located within the Little Kanawha and Gauley River

drainage basins, these sites average 500 m in elevation. Both constructed sites are

classified as palustrine unconsolidated bottom, while the reference site is palustrine

scrub-shrub (Cowardin et al. 1979).

23

Muddlety reference wetland This site is situated within the Muddlety Creek watershed at an elevation of

590 m. Located in Nicholas County (4248480 N 516790 E, Widen 7.5 minute quad),

this natural wetland was used as the reference site to represent the Enoch Branch and

Bear Run mitigation wetlands. Muddlety is located off U.S. Route 19 about 4.0 km

north of Summersville (Figure 11). It is a semipermanently flooded to permanently

flooded bottomland complex dominated by shrub thickets consisting of swamp rose

and silky cornel, as well as emergent marshes of burreed (Sparganium americanum)

and cattail. These areas are contiguous with 2 open water ponds surrounded by

smartweed (Polygonum hydropiperoides).

Enoch Branch This site was created by DOH in 1997 as compensatory mitigation for the

construction of U.S. Route 19 (Corridor L). It is located in Nicholas County

(4247300 N 514550 E, Widen 7.5 minute quad) off U.S. Route 19 (Figure 11). It is

about 1.5 km from the Muddlety reference wetland. Enoch Branch is situated in the

Muddlety Creek watershed at an elevation of 620 m. It contains 2 main cells totaling

3.4 ha in size, consisting of 1.0 ha emergents, 2.0 ha open water, and 0.4 ha scrub-

shrub areas. Both cells are semipermanently to permanently flooded open water

ponds with patches of common rush. The western cell contains brookside alder along

its perimeter.

Bear Run

This site was constructed as a mine reclamation project mitigating for the

Abandoned Mine Land Program in 1993. At an elevation of 265 m, the site is located

within the Little Kanawha River watershed about 4.0 km north of Sand Fork in

24

Gilmer County (4305780 N 519750 E, Glenville 7.5 minute quad; Figure 12). It is

6.2 ha in size, consisting of 1.4 ha emergents and 4.8 ha open water areas. This site

consists of a series of dikes and channels that connect 12 semi-permanent to

permanently flooded open water ponds, some of which are moderately used by

fisherman. Persistent emergent communities of spikerush (Eleocharis

quadrangulata) and cattail have been established at the 3 upper-most cells

(southeast).

QUALITY CONTROL

Plant identification was performed by experts in field botany: Dr. Ronald H.

Fortney, William N. Grafton, and Dr. James S. Rentch. Aquatic macroinvertebrate

familial taxonomy was performed by myself and confirmed by Dr. James T.

Anderson. Avian and anuran species calls were learned using various audiotapes and

confirmed by field technicians knowledgeable in respective taxa. If an avian species�

call could not be identified, it was recorded using a handheld tape recorder and

presented to Greg Forcey, an ornithologist at West Virginia University, for

identification. Dr. James T. Anderson reviewed all methodologies and techniques

incorporated into data collection for this project. Dr. George Seidel and James T.

Anderson assisted in all statistical analyses.

25

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31

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32

CHAPTER I

TABLES

33

Table 1. List of 11 mitigation and 4 reference wetland study sites in West Virginia, including site name, year constructed, size

(ha), source builder, Universal Transverse Mercator (UTM) coordinates, 7.5 minute quadrangle, basin, and watershed, 2001-

2002.

Site name Year Size (ha) Source UTM Y UTM X Quad Basin Watershed

Altona Marsha N/A 15.2 N/A 4353000 768600 Middleway Shenandoah River Shenandoah River Walnut Bottom 1997 9.5 Division of Hwys 4334210 673914 Old Fields S. Branch of Potomac R. S. Branch of Potomac R.

Elder Swamp N/A 28.0 N/A 4340000 642200 Mt. Storm Lake Cheat River Blackwater River VEPCO 1995 7.0 VA Electric Power 4337900 641300 Mt. Storm Cheat River Blackwater River Buffalo Coal 1981 9.0 Davis Trucking Co. 4332100 630900 Davis Cheat River Blackwater River Elk Run 1981 3.8 Island Crk Coal Co. 4342000 636250 Davis N. Branch of Potomac R. Elk Run

Meadowville N/A 6.5 N/A 4330920 593940 Nestorville Tygart Valley Laurel Creek Leading Creek 1995 8.6 Division of Hwys 4321563 602550 Montrose Tygart Valley Leading Creek Sugar Creek 1995 6.8 Division of Hwys 4328850 591470 Belington Tygart Valley Laurel Creek Sand Run 1992 3.0 Division of Hwys 4315060 573140 Buckhannon Tygart Valley Sand Run Triangle 1992 3.1 Division of Hwys 4316950 568500 Buckhannon Tygart Valley Buckhannon River Trus Joist MacMillan 1994 3.2 TJM Timber Co. 4318340 569560 Century Tygart Valley Buckhannon River

Muddlety N/A 10.4 N/A 4248480 516790 Widen Gauley River Muddlety Creek Enoch Branch 1997 3.4 Division of Hwys 4247300 514550 Widen Gauley River Muddlety Creek Bear Run 1993 6.2 WV Dept Env. Prot. 4305780 519750 Glenville Little Kanawha Little Kanawha a Site names in bold indicate reference wetlands for mitigation wetland sites (listed below) in each of 4 areas

34

Table 2. Universal Transverse Mercator (UTM) coordinates of frog, bird, and

vegetation sampling locations for 11 reference and 4 mitigation wetlands of West

Virginia, 2001-2002.

Sampling Frog Bird Vegetation Site Location UTM x UTM y UTM x UTM y UTM x UTM y

Altona Marsh 1 769021 4353041 768650 4353220 768910 4353968 2 768895 4353102 768895 4353102 768822 4353990 3 768765 4353166 769021 4353041 768519 4354049 4 768650 4353220 Bear Run 1 519909 4305421 520030 4305259 519931 4305302 2 519568 4305630 519823 430511 519993 4305220 3 519385 4305645 519834 4306012 4 519745 4305835 519864 4306208 5 519834 4306012 519385 4305645 6 519864 4306208 7 519860 4306457 8 519778 4306668 9 520028 4305216 Buffalo Coal 1 630468 4332098 630468 4332098 630586 4332228 2 630615 4332393 630615 4332393 630473 4332276 3 630550 4332301Elder Swamp 1 642831 4340116 642938 4340275 642855 4340183 2 642655 4340014 642455 4339898 642283 4339944 3 642938 4340275 642244 4340061 4 642455 4339898 642715 4340215 5 642560 4340127 6 642902 4340162Elk Run 1 635944 4341361 635944 4341361 635908 4341459Enoch Branch 1 514750 4247118 514750 4247118 514298 4247610 2 514725 4247588 514725 4247588 514329 4247575 3 514451 4247598 4 4E+06 514445 Leading Creek 1 602411 4321303 602416 4321263 602443 4321238 2 602419 4321176 602427 4321029 602383 4320929 3 602433 4321030 602388 4320824 602428 4321316 4 602451 4320910 602681 4321442 602318 4320657 5 602376 4320763 602414 4321077 6 602670 4321444 602652 4321213

35

Sampling Frog Bird Vegetation Site Location UTM x UTM y UTM x UTM y UTM x UTM y

7 602706 4321285 602613 4321207 8 602659 4321164 9 602618 4321153Meadowville 1 593788 4331027 593848 4330999 594089 4331112 2 593953 4331014 594102 4330912 594021 4331138 3 594102 4330912 594062 4331077 4 594080 4330830Muddlety 1 516686 4248376 516686 4248376 516701 4248734 2 516802 4248364 516769 4248376 516686 4248411 3 516719 4248751 Sand Run 1 573089 4315098 573089 4315098 572978 4315016 2 573102 4315024 3 573054 4315069Sugar Creek 1 591662 4328892 591662 4328892 591566 4328808 2 591566 4328885 591610 4328547 591575 4328902 3 591454 4328883 591345 4328874 4 591337 4328886 591337 4328829 5 591445 4328823 591450 4328780 6 591517 4328773 7 591570 4328540 8 591834 4328184 Trus Joist MacMillan 1 569507 4318093 569655 4318004 569666 4318077 2 569370 4318072 569554 4318107 3 569798 4318046 4 569565 4318016Triangle 1 568425 4316961 568425 4316961 568297 4316864 2 568361 4316886 3 568504 4316956 4 568543 4316977 5 568417 4316910VEPCO 1 641389 4337912 641233 4337916 641485 4337864 2 641233 4337911 641130 4337811 641299 4337910 3 641137 4337809 641156 4337958 4 641038 4337903 641097 4337786Walnut Bottom 1 673892 4334147 673888 4334197 674333 4334501 2 674009 4334281 674038 4334339 674271 4334480 3 674172 4334339 674239 4334576 4 674174 4334679

Table 2. Continued.

36

CHAPTER I

FIGURES

37

Figure 1. Study site locations for 11 mitigation and 4 reference wetlands in West


38

Figure 2. Location of the Altona Marsh reference wetland on the Middleway 7.5

minute quadrangle, West Virginia, 2001-2002.

39

Figure 3. Location of the Walnut Bottom mitigation wetland on the Old Fields 7.5


40

Figure 4. Location of the Elder Swamp reference wetland and the VEPCO mitigation

wetland on the Mt. Storm 7.5 minute quadrangle, West Virginia, 2001-2002.

41

Figure 5. Location of the Buffalo Coal mitigation wetland on the Davis 7.5 minute

quadrangle, West Virginia, 2001-2002.

42

Figure 6. Location of the Elk Run mitigation wetland on the Davis 7.5 minute


43

Figure 7. Location of the Meadowville reference wetland and the Sugar Creek

mitigation wetland on the Nestorville 7.5 minute quadrangle, West Virginia, 2001-

2002.

44

Figure 8. Location of the Leading Creek mitigation wetland on the Montrose 7.5


45

Figure 9. Location of the Sand Run mitigation wetland on the Buckhannon 7.5


46

Figure 10. Location of the Triangle and Trus Joist MacMillan mitigation wetlands on

the Century 7.5 minute quadrangle, West Virginia, 2001-2002.

47

Figure 11. Location of the Muddlety reference wetland and the Enoch Branch

mitigation wetland on the Widen 7.5 minute quadrangle, West Virginia, 2001-2002.

48

Figure 12. Location of the Bear Run mitigation wetland on the Glenville 7.5 minute


49

Figure 13. Photograph of the Altona Marsh reference wetland, West Virginia,

summer, 2001.

Figure 14. Photograph of the Walnut Bottom mitigation wetland, West Virginia,

summer, 2001.

50

Figure 15. Photograph of the Elder Swamp reference wetland, West Virginia,

summer, 2001.

Figure 16. Photograph of the VEPCO mitigation wetland, West Virginia, summer,

2001.

51

Figure 17. Photograph of the Buffalo Coal mitigation wetland, West Virginia,

summer, 2001.

Figure 18. Photograph of the Elk Run mitigation wetland, West Virginia, early

spring, 2001.

52

Figure 19. Photograph of the Meadowville reference wetland, West Virginia,

summer, 2001.

Figure 20. Photograph of the Leading Creek mitigation wetland, West Virginia,

winter, 2001.

53

Figure 21. Photograph of the Sugar Creek mitigation wetland, West Virginia,

summer, 2001.

Figure 22. Photograph of the Sand Run mitigation wetland, West Virginia, summer,

2001.

54

Figure 23. Photograph of the Triangle mitigation wetland, West Virginia, summer,

2001.

Figure 24. Photograph of the Trus Joist MacMillan mitigation wetland, West

Virginia, summer, 2001.

55

Figure 25. Photograph of the Muddlety reference wetland, West Virginia, summer,

2001.

Figure 26. Photograph of the Enoch Branch mitigation wetland, West Virginia,

summer, 2001.

56

Figure 27. Aerial photograph of the Bear Run mitigation wetland, West Virginia,

fall, 2001.

57

CHAPTER II

A COMPARISON OF VEGETATION COMMUNITITES IN

MITIGATION AND NATURAL WETLANDS IN THE MID-

APPALACHIANS




58

ABSTRACT

Wetland destruction has plagued the U.S. for decades, and the need to

compensate for these losses has only been embraced within the last 20 years.

Because so many compensatory mitigation wetlands have been created, there is a

need to assess the success of these valuable ecosystems. The goal of this study was to

evaluate the relative success of mitigation wetlands in West Virginia in supporting

hydrophytic vegetation communities. Naturally occurring reference wetlands were

used to compare vegetation community structure among 11 mitigation sites

throughout the state. Comparisons were made using a 2 × 2 factorial analysis of

variance (ANOVA) following PC-ORD software analyses. For all species sampled,

mean total percent cover across all sampling quadrats per wetland was similar

between mitigation ( x = 39.2, SE = 6.09) and reference ( x = 54.4, SE = 9.03)

wetlands (P = 0.195; Table 3). Species richness (P = 0.035), evenness (P = 0.033),

and diversity (P = 0.025) were higher in mitigation (richness: x = 12.9 species/plot,

SE = 1.07, evenness: x = 0.32, SE = 0.03, diversity: x = 1.83, SE = 0.11) than

reference (richness: x = 8.25, SE = 1.59, evenness: x = 0.17, SE = 0.05 diversity: x

= 1.29, SE = 0.17) wetlands. Mean weighted averages were similar between

mitigation ( x = 0.65, SE = 0.11) and reference ( x = 0.89, SE = 0.16) wetlands (P =

0.242). Differences in species composition between wetland types were reflected

through ordination using Detrended Correspondence Analysis (DCA). Ordination

also yielded correlations between species composition and age of mitigation

wetlands. Although mitigation and reference sites contained similar numbers of

This chapter is written the style of Ecological Applications.

59

nonnative species (P > 0.05), an evaluation of native species only yielded similar

species richness and evenness indices between wetland types (P > 0.05). Both

mitigation and natural wetlands met criteria for hydrophytic vegetation according to

the 1987 U.S. Army Corps of Engineers Wetland Delineation Manual. These data

suggest that mitigation wetlands in West Virginia adequately support hydrophytic

vegetation and appear to be developing towards reference standards.

Key words: constructed wetland, mitigation wetland, man-made wetland,

reference wetland, wetland mitigation, wetland management, hydrophytic vegetation

INTRODUCTION

Wetlands are extremely valuable to both people and wildlife. They provide

such functions as flood storage, ground-water recharge, nutrient cycling, pollutant

removal, and wildlife and recreational habitat (Mitsch and Gosselink 2000).

Unfortunately, there has been a > 50% decline in the U.S. wetland resource base

within the past 200 years (Dahl 1990). It was not until 1977, with the passage of

amendments to the Clean Water Act, that wetlands began to be protected (33 CFR

320). Specifically, Section 404 of the Clean Water Act (40 CFR Part 230.1)

authorized the Army Corps of Engineers to issue permits for dredging and filling

practices affecting wetlands. Permit requirements outlined by the government have

promulgated the construction of thousands of hectares of wetlands in the U.S. as a

need to mitigate for wetland losses. The �no-net-loss� policy for wetlands was

endorsed in the late 1980s, and it introduced wetland mitigation as the leading tool in

60

combating wetland loss in the U.S. (Jones and Boyd 2000, Mitsch and Gosselink

2000).

Because so many compensatory wetlands have been created, there is a need to

assess the success of these wetlands. But monitoring of mitigation wetlands has been

sporadic, and various mitigation programs have lacked the tools necessary to enforce

and monitor mitigation success (Lewis 1992, National Research Council 2001).

Those that have evaluated success found that permit-linked mitigation projects had

low success rates (Eliot 1985, Race 1985, Mager 1990, Holland and Kentula 1992,

Zedler and Callaway 1999, Robb 2002). One problem stems from the definition of

mitigation success itself, which often varies by project objectives. Whether these

objectives include the adequate development of soils or hydrology or the ability to

support wildlife, most researchers agree that mitigation wetland function should equal

or exceed those functions lost to development or destruction. Thus, a concerted effort

is underway to evaluate a variety of mitigation wetland functions in hopes of

understanding the dynamics involved in adequately replacing lost wetland function.

Vegetation community structure provides a valuable indicator of wetland

function. Vegetation plays a distinct role in the identification of wetlands (Hall and

Penfound 1939, Penfound 1952, Martin et al. 1953, Dix and Smeings 1967), and is

currently used in wetland delineation (USACE 1987, Tiner 1999). Research has

shown that higher structural diversity of vegetation leads to higher wildlife species

diversity (MacArthur and MacArthur 1961, Evans and Wilson 1982, Anderson et al.

1999, King et al. 2000, Naugle et al. 2000). Vegetation within wetlands is important

because its composition determines (1) type, quantity, and nutritive quality of plant

61

foods available (De Szalay and Resh 1997, Anderson and Smith 1998), (2)

distribution, density, and structure of cover (Hays et al. 1981, Anderson et al. 1999),

(3) quantity and type of substrate for invertebrates (Murkin et al. 1992, Anderson and

Smith 1999, 2000, King et al. 2000), and (4) water chemistry (Goslee et al.1997,

Castelli et al. 2000). For these reasons, vegetation analysis has been widely used to

assess wetland function (Wentworth et al. 1988, Reinartz and Warne 1993, Wilson

and Mitsch 1996, Goslee et al. 1997, Castelli et al. 2000, Campbell et al. 2002).

An evaluation of wetland function provides limited insight into mitigation

success unless a standard of comparison is used to gauge the relative success of

mitigation wetlands in performing a specific function. In an effort to evaluate the

success of created and restored wetlands, numerous studies evaluating a range of

wetland functions have embraced the use of naturally occurring reference wetlands to

represent optimal habitat conditions (Brinson 1993, Brinson and Rheinhardt 1996,

Wilson and Mitsch 1996, Ashworth 1997, Brown and Smith 1998, Stolt et al. 2000).

Likewise, much research has been conducted on the structure and composition of

vegetation communities in mitigation wetlands relative to reference wetlands (Confer

and Niering 1992, Parikh and Gale 1998, Brown 1999, Moore et al. 1999, Campbell

et al. 2002).

Few studies, however, have been conducted on wetland function and

mitigation success in the Appalachians, and only 1 major study was conducted in

West Virginia (R. H. Fortney, unpublished report), and it was limited in scope and

only evaluated 3 constructed wetlands. It is clear that an evaluation of vegetation

communities should provide valuable insight into the framework needed to monitor

62

mitigation success in the future. As such, I tested the null hypothesis that wetland

vegetative community composition and structure was similar between mitigation and

natural (reference) wetlands in West Virginia.

METHODS

Study sites

This study was conducted in West Virginia, which is situated in the mid-

Appalachian region of the U.S. Fifteen wetlands were evaluated across the state

including 11 mitigation (Walnut Bottom, VEPCO, Buffalo Coal, Elk Run, Leading

Creek, Sugar Creek, Sand Run, Triangle, Trus Joist MacMillan, Enoch Branch, and

Bear Run) wetlands and 4 reference (Altona Marsh, Elder Swamp, Meadowville, and

Muddlety) wetlands (Chapter I). All mitigation sites were constructed except for

Triangle, Elk Run, and Sand Run, which were combinations of created and restored

wetlands. The study sites were condensed into 4 areas for comparison with each area

representing a different geomorphic setting within the state. One reference wetland

was chosen for each area based on its similarity in location, elevation, size, vegetative

structure, and hydrology to mitigation sites. Since the reference wetlands are

relatively larger than mitigation sites, only portions of reference sites resembling

conditions to mitigation wetlands were selected for study.

Mitigation study sites were created as compensation for such human activities

as industrial development, mining, or road construction. Almost every wetland was

located near some form of human disturbance, with many lying adjacent to roads with

moderate to heavy traffic. To allow for a standardized minimum time of

63

development, all sites chosen were ≥5 years old. Sites ranged in age from 5-21 years

old ( x = 10.0, SE = 1.7) and in size from 3.0 to 9.5 ha ( x = 5.8, SE = 0.8). Elevation

ranged from 265-1,036 m ( x = 586, SE = 75.9). All were classified as palustrine

emergent or unconsolidated bottom wetlands (Cowardin et al. 1979).

Reference sites were selected based on their similarity in structure and

proximity to the mitigation sites. They ranged in elevation from 170-1,000 m ( x =

582, SE = 169.5), and size ranged from 6.5- 28.0 ha ( x = 15.1, SE = 4.7). All were

classified as palustrine emergent or palustrine scrub-shrub wetlands (Cowardin et al.

1979). Detailed mitigation and reference site descriptions are provided in Chapter I.

Vegetation community sampling

Vegetation sampling occurred in June and July of 2001, and in July of 2002.

Sampling was conducted according to Stephenson and Adams (1986). Plant

communities were first stratified based on distinct communities present.

Representative communities were sampled using randomly placed permanently

marked 0.05 ha quadrats (25 × 20 m). At each wetland, at least 1 quadrat was used to

sample each distinct plant community. More quadrats were established depending on

the size and variability of the community.

Within each quadrat all live stems of trees (≥ 10 cm diameter at breast height,

DBH) and small trees (2.5 to 9.9 cm DBH) were measured at dbh and counted to

species. In addition, saplings (individuals < 2.5 cm DBH but ≥ 1.0 m tall) were

counted. Within each 0.05 ha quadrat, 2 5.0 × 5.0 m plots were placed evenly along

the center line of the transect. Within these plots, seedlings (individuals > 10 cm but

64

less than < 1.0 m tall) and shrubs (including woody vines) were counted to species.

Five 1.0 × 1.0 m plots were placed along the same center line. Within these plots,

small seedlings (individuals ≤ 10 cm tall) were counted to species. In addition,

percent cover of herbaceous plants, exposed substrate, woody debris, and bryophytes

were recorded. Plant identifications were made using Radford et al. (1968),

Strausbaugh and Core (1977), and Gleason and Cronquist (1991). Nomenclature and

taxonomic authority were based on Kartesz (1999). All cover values for herbaceous

plants were estimated using the following cover class rating scale: 1-5% = 1, 6-25% =

2, 26-50% = 3, 51-75% = 4, 76-95% = 5, 96-100% = 6 (Daubenmire 1968). Percent

of hydrophytic vegetation sampled within quadrats also was calculated following the

basic rule in the 1987 U.S. Army Corps of Engineering Wetland Delineation Manual

(USACE 1987).

Vegetation mapping was conducted using a Geographic Information System

(GIS) and ArcView software. Maps of dominant vegetation communities were

mapped on aerial photos (1.0 m resolution) taken by the West Virginia Natural

Resources Analysis Center (NRAC) during leaf off in 2001 and 2002. If recent aerial

photography was unavailable, vegetation communities were digitized on 1996-1997

digital ortho-quarter quads (DOQQs) obtained from the West Virginia Department of

Environmental Protection (DEP). Wetlands also were classified and digitized

according to Cowardin et al. (1979).

Data analyses

Mitigation and reference wetlands were compared by calculating species

richness, diversity, and evenness using PC-ORD software (McCune and Mefford

65

1999) for each quadrat within the wetlands. Statistics were calculated for all species

combined and for native species only. Native species status was assigned based on

Harmon and Ford-Werntz (2002). Diversity was calculated using the Shannon-

Weiner Index (Shannon and Weaver 1949). Average cover was calculated for each

species and totaled to get a total coverage for each quadrat. These values were

averaged to obtain mean total coverage for each wetland. In addition, each species

was assigned the following wetland indicator status (WIS) values: Obligate = 1,

Facultative Wetland = 2, Facultative = 3, Facultative Upland = 4, and Upland = 5

(U.S. Fish and Wildlife Service 1996). From coverage and WIS values, weighted

averages (Carter et al. 1988, Wentworth et al. 1988, and Atkinson et al. 1993) were

calculated based on the following formula:

Weighted average = (y1u1 + y2u2 + ��.ymum)/100

where y1y2 = relative basal area (trees and small trees) or relative cover estimates

(herbaceous plants) for each species, and u1u2 = the WIS for each species (Atkinson et

al. 1993). Also using PC-ORD software, Detrended Correspondence Analysis (DCA)

was used to graphically evaluate similarities in vegetative composition (Hill 1979).

Detrended Correspondence Analysis is an eigenanalysis ordination technique that

uses reciprocal averaging and chi-square distance measures to spatially organize

vegetation quadrats based on species composition. Average cover values were used

as inputs in DCA and all rare species were downweighted.

A 2×2 factorial analysis of variance (ANOVA) model was used in SAS (SAS

Institute 1988) with area as a blocking factor. The independent variables tested were

year, type (mitigation vs. reference), and year× type interactions with dependent

66

variables being total cover, richness, diversity, evenness, and weighted averages.

Assumptions of normality were tested with the univariate procedure in SAS, and

Levene�s Test was used for homogeneity of variances. Square-root and quarter-root

transformations were used to convert dependent variables that did not meet the

aforementioned assumptions (Dowdy and Wearden 1991).

RESULTS

A total of 175 plant species was recorded in 60 quadrats within both

mitigation and reference wetlands (Appendix 1). In mitigation sites, 129 species were

recorded in 45 quadrats, 23 of which were nonnative (17.8%; Appendices 2-12).

Within reference sites, 62 species were sampled in 15 quadrats, 2 of which were

nonnative (3.2%; Appendices 13-16). Overall, the number of nonnative species were

not different in mitigation and reference wetlands (F1,10 = 3.22, P = 0.103; Table 1).

A total of 123 species were observed (seen) but not sampled in mitigation quadrats,

and 34 species were observed but not sampled in reference quadrats. A list of

vegetation species planted during wetland construction is provided in Appendix 17.

For all species sampled, total average cover was similar between mitigation

and reference wetlands (F1,10 = 1.93, P = 0.195; Table 1). Mean species richness

(F1,10 = 5.97, P = 0.035), evenness (F1,10 = 6.15, P = 0.033), and diversity (F1,10 =

6.92, P = 0.025) were higher in mitigation wetlands (Table 1). Mean weighted

averages were similar between wetland types (F1,10 = 1.54, P = 0.242).

Different results were obtained upon evaluating species native only to West

Virginia. Species richness (F1,10 = 4.7, P = 0.055) and evenness (F1,14 = 4.44 , P =

67

0.061) were similar between mitigation and reference wetlands (Table 1). However,

species diversity remained higher in mitigation wetlands (F1,10 = 5.15, P = 0.047).

Percent of species by wetland indicator status were calculated for all species,

both sampled and observed but not sampled, within quadrats (Table 1). Although

83.8% of the vegetation sampled was hydrophytic in mitigation wetlands, and 94.3%

was hydrophytic in reference wetlands, no difference was detected between wetland

types (F1,10 = 2.89, P = 0.119).

Results of Detrended Correspondence Analyses are shown in Figures 1-4.

Each point on the graph represents individual quadrats. Points that are close together

represent quadrats that have similar species composition, while points that are further

apart indicate quadrats that share fewer species in common. Ordination for all 60

quadrats in both wetland types are displayed in Figure 1 for all herbaceous species

and in Figure 2 for native species only. In Figure 1, mitigation sites were ordinated

below Axis 1, while reference sites were located above the axis (Axis 1: R2 = 0.08;

Axis 2: R2 = 0.18). The two major groupings along this axis reflect differences in

vegetative composition between mitigation and reference wetlands. Similarly,

mitigation sites appeared to show correlation with Axis 2, whereas reference sites

were concentrated in the upper right section of the ordination with a slight correlation

with axis 2. Figure 2 represents an ordination of native species only. Similar to

Figure 1, mitigation sites were ordinated below Axis 1 and appeared to show

correlation with Axis 2 (Axis 1: R2 = 0.07; Axis 2: R2 = 0.18). However, the

differences in clusters are less pronounced between wetland types, indicating a more

similar vegetation composition of native species.

68

Figures 3 and 4 represent ordination with wetland age as a secondary matrix

for all 45 plots within mitigation wetlands. Figure 3 represents ordination of

vegetation plots with wetland age as a categorical variable where wetlands were

evaluated based on whether they were < 10 years old or ≥ 10 years old. This figure

reveals a cluster of older wetlands in the bottom center of the ordination, while

younger wetlands are dispersed more evenly over the entire graph (Axis 1: R2 = 0.41;

Axis 2: R2 = 0.25). Thus, species composition appears to be more similar within

older wetlands than within younger ones. Figure 4 represents ordination of plots with

the actual age of every vegetation plot. This figure also supports the assertion that

wetland age affects species composition. Based on the ordination, wetland age is

correlated with axis 2 along an age gradient where older wetlands are situated on the

bottom of the graph and younger wetlands are located towards the top (Axis 1: R2 =

0.41; Axis 2: R2 = 0.25).

Submerged aquatic vegetation successfully developed at 10 of 11 mitigation

sites. Only VEPCO lacked submerged aquatic vegetation. These included such

species as water thread pondweed (Potamogeton diversifolius Raf.) and snailseed

pondweed (P. spirillus Tuck.). Woody vegetation also had been established, either

within or along the perimeter, at 10 of 11 constructed sites (Walnut Bottom lacked

shrubs). Dominant shrub species included alder (Alnus serrulat. Spreng.), St. John�s

wort (Hypericum densiflorum L.), and buttonbush (Cephalanthus occidentalis L.).

All 4 reference sites supported relatively more dense shrub thickets than mitigation

sites. Dominant shrub communities within reference sites consisted of silky cornel

(Cornus amomum Mill.), alder, arrow-wood (Viburnum recognitum Fern.), and

69

swamp rose (Rosa palustris Marsh.). Geographic Information System maps

representing dominant vegetation with bird, frog, and vegetation sampling points, as

well as Cowardin et al. (1979) wetland classifications for all 15 wetlands are in

Appendices 18-32.

DISCUSSION

It appears that hydrophytic vegetation has successfully been established at the

constructed wetland sites I evaluated in the mid-Appalachians. It is not surprising

that hydrophytic vegetation has been established so early in mitigation sites. Studies

show that hydrophytic vegetation often establishes within 3 to 5 years after

construction (Erwin and Best 1985, Confer and Niering 1992, Reinartz and Warne

1993, Mitsch et al. 1998, Brown 1999). Some studies have shown reference wetlands

to have more vegetative cover than constructed sites, which can be attributed to

differences in maturity (Confer and Niering 1992, Havens et al. 1995, Brown 1999).

However, I found similar vegetation coverage between wetland types. Indeed, this

could indicate vegetation development toward reference standards, but these wetlands

are relatively young and unstable, and as such, support a wider variety of species that

have adapted to these disturbed environments. This is supported by the higher

species richness and diversity found in mitigation sites. Furthermore, almost every

constructed site (except VEPCO and Buffalo Coal) is adjacent or connected to

streams, rivers, or other wetlands, that can act as seed sources for pioneer species.

Other studies also have shown higher species richness in constructed wetlands

(Parikh and Gale 1998). However, Jarman et al. (1991) and Brown (1999) found

70

similar richness values between wetland types in Massachusetts and New York,

respectively, and Campbell et al. (2002) found lower species richness in created

wetlands than in natural wetlands in Pennsylvania. Although age was a factor in

determining species richness among mitigation sites (younger sites displayed higher

species richness), location to seed sources probably accounted for lower richness in

mitigation sites overall in Pennsylvania (Campbell et al. 2002). Reinartz and Warne

(1993) also observed correlations with distance to seed sources. They found

decreases in species richness and diversity with increasing distance to nearest wetland

seed source. Indeed, nearby wetlands and streams can be excellent vectors of plant

propagules. As such, special plantings of herbaceous and woody vegetation, except

for initial vegetative cover and erosion control, may not be needed for certain

constructed wetlands. However, some newly created wetlands should be seeded with

native wetland species to prevent monoculture development and increase overall

diversity (Levine and Willard 1990, Reinartz and Warne 1993).

Evenness also was higher in mitigation sites. Hence, although mitigation sites

supported a higher number of species and a greater diversity than reference sites,

individual species were more evenly distributed among quadrats in mitigation sites.

Since reference sites are more stable, well-adapted species have been allowed

sufficient time to exclude species. Consequently, certain species display a clear

dominance over others. Some common dominant species that occurred at reference

sites included blue-joint grass (Calamagrostis canadensis Michx.), rice cutgrass

(Leersia oryzoides L.), marsh fern (Thelypteris palustris Schott), cattail (Typha

latifolia L.), and boat-leaved sphagnum (Sphagnum palustre L.). Cattail, for instance,

71

is tall at maturity, and has a low photosynthetic area with a clonally-spreading root

system. This allows it to form vegetative monocultures (Boutin and Keddy 1993).

Although cattail was prevalent in mitigation wetlands, monocultures had not yet

developed, except perhaps in Triangle. It will be important to monitor the spread of

this species since it is known to inhibit the development of diverse vegetation

communities by excluding other native species� colonization (Erwin 1990).

Overall, submerged aquatic vegetation (SAV) has successfully established

within most mitigation sites. One of the sites that contained minimal (0.7%) SAV

(Trus Joist MacMillan) supported a population of carp (Cyprinus carpio L.), which

are known to feed on SAV (McKnight and Hepp 1995). The VEPCO site probably

lacked SAV for a variety of reasons. These include light availability due to

suspended solids or chlorophyll concentrations, or other physical, geological, or

geochemical parameters (Koch 2001). Submerged aquatic vegetation has been on the

decline for many years and is known to increase water quality (Dennison et al. 1993).

As well, it is a vital component to the diet of numerous waterfowl species (McKnight

and Hepp 1995). The success of mitigation wetlands in West Virginia in supporting

SAV should be monitored to ensure the continued benefits associated with these

valuable wetland plant species.

The presence of woody vegetation was confirmed at almost every mitigation

wetland. Even the youngest site (5 years old; Enoch Branch) contained brookside

alder (Alnus serrulata) communities in and around the wetland, but I suspect that this

species was planted during construction based on linear stocking patterns along the

perimeter. However, another wetland of the same age (Walnut Bottom) did not

72

contain woody vegetation. Data on vegetation plantings were unavailable for this

site. There is a possibility that no shrubs were planted during its construction, so this

site simply may be too young to have developed shrub thickets. This is not surprising

considering woody vegetation generally takes longer to develop in constructed sites

(Niswander and Mitsch 1995). Shrub development has possibly been minimized at

Bear Run due to design constraints. This site consists of a series of steeply graded

open water ponds that have created hydrologic gradients incompatible with shrub

growth.

Although no statistical difference was detected in the number of nonnative

species between constructed and natural wetlands, the number of nonnative species

was higher in mitigation sites. In fact, only 2 nonnative species were observed at 1

reference site (Meadowville), whereas a combined total of 23 species were observed

at 10 of 11 constructed sites. The minimal coverage of hydrophytic vegetation, along

with a relatively small sampling effort (1 transect established), may explain why Bear

Run appears to lack nonnative species. The most common nonnative species were

purple loosestrife (Lythrum salicaria L.), clover (Trifolium spp. L.), crown vetch

(Coronilla varia L.), and hedge bedstraw (Galium mollugo L.). I suspect that a larger

data set would have yielded significant differences.

Weighted average and percentage of wetland indicator species were used as

indicators of hydrophytic vegetation. Both mitigation and reference sites contained >

50% OBL, FACW, and FAC species (excluding FAC-) thus meeting the hydrophytic

vegetation criteria outlined by the U.S. Army Corps of Engineers (1987). In fact,

every mitigation site met hydrophytic vegetation criteria according to the manual.

73

Similar results were obtained at constructed wetlands in Ohio (Wilson and Mitsch

1996) and Wisconsin (Reinartz and Warne 1993). It was interesting that weighted

averages were similar between mitigation and reference wetlands. Weighted

averages were expected to be lower in mitigation sites because they appeared to be

wetter. However, statistical results indicated that the percentage of hydrophytic

vegetation was similar between wetland types. Other studies have yielded differing

results between mitigation and natural wetlands (Brown 1999, Campbell et al. 2002).

Nonetheless, it appears that mitigation wetlands continue to support adequate

hydrophytic vegetation communities in West Virginia.

Using Detrended Correspondence Analysis, differences in vegetative

composition were revealed that supported results obtained using univariate

procedures. The ordination of vegetation quadrats in Figures 1 and 2, for instance,

likely reflects differences in species richness, diversity, and evenness observed

between these two wetland types using ANOVA models. Upon removing nonnative

species from statistical analyses, richness, diversity, and evenness were similar

between mitigation and reference wetlands. This similarity is illustrated in Figure 2

where wetland quadrats were ordinated using only native species. Detrended

Correspondence Analysis also revealed the effect of age on vegetation composition.

The ordination of quadrats in Figures 3 and 4 may indicate a trend towards decreased

richness and diversity with increasing wetland age. Although Reinartz and Warne

(1993) observed increases in total cover, richness, and diversity with constructed

wetland age, studies have shown that vegetation richness can decrease with time

(Parikh and Gale 1998). It is expected, however, that pioneer species will be

74

competitively excluded as time elapses in mitigation wetlands, thus narrowing the gap

in species composition between wetland types. Increased organic matter

accumulation may account for this, but many years may be required for sufficient

surface accumulation (Bishel-Machung et al. 1996, Atkinson and Cairns 2001). Data,

however, currently suggest a lack of organic matter accumulation in some mitigation

wetlands evaluated in this study (R.H. Fortney, unpublished report). The effects of

organic matter accumulation on vegetative structure at these wetlands definitely

should be monitored.

MANAGEMENT IMPLICATIONS

Compensatory mitigation is a leading tool in counteracting the destruction of

wetlands. There is a need to assess the success of mitigation wetlands in replacing

functions lost during wetland destruction. The establishment of hydrophytic

vegetation communities is crucial to the functioning of any wetland. It not only

determines water chemistry, it affects abundance and distribution of wildlife and

invertebrate communities. Many researchers would agree that defining mitigation

success should be made with caution, especially for relatively young wetlands (0-10

yrs). Wilson and Mitsch (1996) recommend giving freshwater wetlands 15-20 years

before judging their success, and Frenkel and Morlan (1991) recommend waiting at

least 50 years for certain forested and coastal wetlands. An ecological model

developed by Jorgensen (1994) shows that the further initial conditions are from a

natural state, the longer it will take for that system to reach or approach that steady

state. His model predicts at least 15 years would be needed to achieve natural

75

conditions. Research definitely shows that constructed wetlands should be allowed

time to develop, during which time it is imperative to continually assess permit-

compliance and the development of functional attributes.

The average age of studied mitigation sites in West Virginia was 10 years, and

although this is young relative to the optimal ages outlined above to assess mitigation

success, I am still confident adequate conclusions can still be made as to the current

trajectory of these sites. Although much can be learned about vegetation community

dynamics by studying newly created wetlands at any time period, I recommend

waiting a minimum of 10 years to accurately assess the status of vegetation

communities in mitigation wetlands relative to natural wetlands. This would allow

more time for the accumulation of organic matter, which is crucial to wetland

stabilizaton. Even then, caution should be made regarding stochastic events, beaver

(Castor canadensis) activity, or other factors that may influence community structure.

I also recommend seeding newly constructed wetlands with native plant species.

Constructed wetlands will eventually develop healthy native vegetation communities

under natural seeding conditions, but this may take years to occur, and manual

seeding can jump start the growth and production of native vegetation in a disturbed

environment that normally favors exotic species proliferation (Levine and Willard

1990, Reinartz and Warne 1993, Kaplan et al. 1998). Cattail, in particular, can

quickly prevent the establishment of other desirable native species by forming dense,

monotypic stands, so preemptive competition through manual seeding may allow

other perennial clonal species to occupy space that normally would be taken over by

cattail (Reinartz and Warne 1993). Since budgetary constraints are often placed on

76

wetland construction projects, it is important that manual seeding be relatively

inexpensive. A simple, low-cost method employed by Reinartz and Warne (1993)

consisted of simply scattering seeds of native species with no special preparation or

planting techniques. In their study, this technique increased species diversity,

richness, and cover of native wetland species within 2 years compared to unseeded

wetlands.

Future studies should monitor changes in vegetative composition and structure

within these mitigation sites. Some sites are located adjacent to major highways,

which may result in continued sedimentation and accumulation of pollutants

(Trombulak and Frissell 2000, Bridges and Semlitsch 2002). This could dramatically

affect vegetation development, although such accumulation is currently nonexistent

or minimal at the mitigation sites evaluated in this study. Moreover, the impact of

invasive species such as purple loosestrife and reed (Phragmites Trin.) and aggressive

colonizers such as reed canary-grass (Phalaris arundinacea L.) and cattail on overall

species richness, diversity, and evenness, should be monitored. Studies have shown

that within a relatively short time period (i.e., < 10 yrs), vegetation communities can

shift dramatically in composition (Confer and Niering 1992, Parikh and Gale 1998,

Moore et al. 1999). It will be important, as well, to continually monitor changes in

hydrology at these sites. The hydrologic regime in constructed wetlands greatly

affects the development of vegetation communities comparable with natural wetlands

(Confer and Niering 1992, Niswander and Mitsch 1995, Craft et al. 2002). Finally,

the occurrence of rare species should be monitored. This study precluded a

comparison of rare species� occurrence between mitigation and natural wetlands.

77

This comparison likely would have revealed the relative importance of natural

wetlands to rare plant communities in the state. Research definitely should continue

to monitor the progress of vegetation development in constructed wetlands relative to

naturally functioning systems. Indeed, the performance of mitigation wetlands would

be gauged more effectively if more reference wetlands were incorporated into future

studies. This would better encompass the variation in wetland function among

natural wetlands in the mid-Appalachians.

Future studies also should address differences in vegetative structure and

composition between the constructed wetlands and the wetlands destroyed that they

were designed to compensate for. Little information was obtained regarding status of

vegetation communities in impacted wetlands for this study. This has been a problem

for numerous mitigation studies (National Research Council 2001), thus emphasizing

the need for more reliable record keeping involving such important projects.

Nonetheless, by identifying specific methodologies to evaluate metrics indicative of

vegetation community health, and by providing a sound experimental design using

statistical procedures, this project provides an excellent opportunity for the

development of standardized protocols that will ensure adequate compliance with

Section 404 of the Clean Water Act. Future functional evaluations of these and other

mitigation wetlands in West Virginia will provide further insight into the dynamics

involved in constructing wetlands that most closely mimic natural systems. The

hydrogeomorphic approach to wetland function may provide a tool to accomplish this

goal, although no regional subclasses or functional models have yet been established

within the state.

78

Although wetland vegetation is critical in maintaining the basic processes of

wetland ecosystems, the presence of hydrophytic vegetation alone does not

necessarily indicate functional equivalence with naturally occurring wetlands

(D�Avanzo 1986, Reinartz and Warne 1993). Thus, it is important to evaluate other

functions of constructed wetlands. Chapters III and IV address this need by

evaluating the ability of mitigation wetlands in West Virginia to support invertebrate

and vertebrate communities.

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88





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89

CHAPTER II

TABLES

90

Table 1. Total cover, richness, evenness, and diversity per 0.05 ha quadrat of native

and nonnative species, as well as weighted averages and Wetland Indicator Statuses

for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002.

a Differing letters following means indicate a significant difference between mitigation and reference wetlands at the P < 0.05 level. bOBL = obligate, FACW = facultative wetland, FAC = facultative, FACU = facultative upland, and UPL = upland. cAs defined by the U.S. Army Corps of Engineers (1987): percent OBL, FACW, FAC+, and FAC.

Mitigationa Referencea

Index x SE x SE Total percent cover 39.2a 6.1 54.4a 9.0 Richness 13.0a 1.1 8.3b 1.6 Richness (natives) 12.0a 1.1 8.1a 1.5 Richness (nonnatives) 0.98a 0.26 0.19a 0.36 Evenness 0.32a 0.03 0.17b 0.05 Evenness (natives) 0.29a 0.04 0.17a 0.05 Diversity 1.83a 0.11 1.29b 0.07 Diversity (natives) 1.72a 0.12 1.27b 0.17 Weighted average 0.65a 0.11 0.89 0.16 Wetland Indicator Statusb OBL 43.8 5.1 55.2 7.7 FACW 34.7 3.0 35.2 7.2 FAC 7.1 1.3 3.4 2.6 FACU 11.0 2.4 5.0 3.1 UPL 3.4 1.2 0.6 0.6 Percent hydrophytic vegetationc 83.8a 3.2 94.3a 3.4

91

CHAPTER II

FIGURES

92

BC1

BC2

BC3

BR1

BR2

ES1 ES2ES3ES4

ES5

ES6

ES7

ER1

EB1

EB2

EB3

EB4LC1

LC2

LC3

LC4

LC5

LC6LC7

LC8

LC9

MV1

MV2

MV3

MV4

MD1

SR1

SR2

SR3SR4SC1

SC2

SC3SC4

SC5

TJM1

TJM2

TJM3TJM4

TR3

TR2

TR1

TR4

TR5

VP1

VP2VP3

VP4

WB1

WB2

WB3

WB4

AM1

AM2

AM3

Axis 1

Axis

2

MitigatedReference

Figure 1. Detrended Correspondence Analysis of vegetation quadrats for all species

within 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West Virginia,

2001-2002. Two letter abbreviations with numbers represent individual quadrats at

each wetland.

93

BC1

BC2

BC3

BR1BR2

ES1 ES2ES3

ES4 ES5

ES6

ES7ER1

EB1

EB2

EB3

EB4

LC1

LC2

LC3LC4

LC5LC6

LC7

LC8

LC9

MV1

MV2

MV3

MV4

MD1

SR1SR2

SR3SR4

SC1

SC2 SC3

SC4SC5

TJM1

TJM2

TJM3TJM4

TR3

TR2

TR1

TR4

TR5

VP1VP2 VP3

VP4

WB1

WB2WB3

WB4

AM1

AM2

AM3

Axis 1Ax

is 2

MitigatedReference

Figure 2. Detrended Correspondence Analysis of vegetation quadrats for native

species only within 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West

Virginia, 2001-2002. Two letter abbreviations with numbers represent individual

quadrats at each wetland.

94

BC1

BC2BC3

BR1

BR2

ER1

EB1

EB2

EB3

EB4

LC1

LC2

LC3LC4

LC5

LC6

LC7

LC8

LC9

SR1SR2

SR3

SR4

SC1SC2

SC3

SC4

SC5

TJM1

TJM2

TJM3

TJM4

TR3

TR2

TR1

TR4

TR5

VP1

VP2

VP3

VP4

WB1

WB2

WB3WB4

Axis 1Ax

is 2 Age

< 10 yrs old>= 10 yrs old


within 11 mitigation (n = 45) sites in West Virginia, 2001-2002. Quadrats were

ordinated using age as a categorical variable. Two letter abbreviations with numbers

represent individual quadrats at each wetland.

95

BC1

BC2

BC3

BR1

BR2

ER1

EB1

EB2

EB3

EB4

LC1

LC2

LC3LC4

LC5

LC6

LC7

LC8

LC9

SR1SR2

SR3

SR4

SC1

SC2

SC3

SC4SC5

TJM1

TJM2

TJM3

TJM4

TR3

TR2

TR1

TR4

TR5

VP1

VP2

VP3

VP4

WB1

WB2

WB3

WB4

Axis 1

Axis

2


within 11 mitigation (n = 45) sites in West Virginia, 2001-2002. Quadrats were

ordinated using actual age as a quantitative variable. Larger triangles represent older

quadrats. Two letter abbreviations with numbers represent individual quadrats at

each wetland.

96

CHAPTER III

AQUATIC MACROINVERTEBRATE COMMUNITY

STRUCTURE IN MITIGATION WETLANDS OF WEST

VIRGINIA




97

ABSTRACT

Many wetlands have been constructed in West Virginia as mitigation for a

variety of human disturbances, but no comprehensive evaluation on their success has

been conducted. Macroinvertebrates are extremely valuable to the functioning of

wetland ecosystems. As such, invertebrates were chosen as surrogates for wetland

health in the evaluation of benthic and nektonic invertebrate communities in 11

mitigation and 4 reference wetlands in West Virginia. Overall familial richness,

diversity, density and biomass were similar between mitigation and reference

wetlands (P > 0.05). Within open water habitats, benthic density was higher in

reference wetlands, but nektonic biomass was higher in mitigation wetlands (P <

0.05). Within benthic samples, Planorbidae density (P = 0.020) and biomass (P =

0.024) were higher across emergent habitats in reference wetlands. Benthic

Oligochaeta density (P = 0.012) and biomass (P = 0.001) were higher across open

water habitats in mitigation wetlands. All other benthic taxa were similar between

wetland types. Among the most common nektonic orders, Isopoda density (P =

0.015) and biomass (P = 0.025), as well as Odonata biomass (P = 0.039) were higher

in reference wetlands. Gastropoda biomass was higher in mitigation wetlands (P =

0.023). Ephemeroptera (P = 0.043), Hemiptera (P = 0.028), and Odonata (P = 0.040)

densities also were higher in mitigation wetlands, but only across emergent habitats.

Among the most abundant nektonic families collected, Physidae, Planorbidae, and

Corixidae density and biomass were higher in mitigation wetlands (P < 0.05).

Caenidae density (P = 0.029) and Coenagionidae biomass (P = 0.041) also were

higher in mitigation wetlands. In addition, Veliidae was higher in mitigation

This chapter is written in the style of Ecological Applications.

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wetlands, but only across emergent habitats (P = 0.049). Within mitigation wetlands,

emergent areas contained higher richness (benthic: P = 0.001; nektonic: P = 0.018)

and diversity (benthic: P = 0.001; nektonic: P = 0.006), as well as nektonic density (P

< 0.001) and biomass (P < 0.001) than open water areas. Differences in invertebrate

community structure between mitigation and reference wetlands are attributable to

differences in hydroperiod and vegetative community composition and structure.

These data indicated that mitigation wetlands currently support abundant and

productive invertebrate communities, and as such, provide quality habitat for wetland

dependent wildlife species, especially waterbirds and anurans. Wetland construction

should focus on maintaining moderate hydroperiods (6 months) with equal ratios of

emergent and open water habitat with diverse vegetation communities.

Key words: macroinvertebrates, invertebrates, mitigation wetland, wetland

construction, wetlands, wildlife

INTRODUCTION

Wetlands provide important habitat for numerous species of wildlife, fish,

waterfowl, shorebirds, and neotropical birds. Unfortunately, wetland destruction has

plagued the U.S. for many decades, but recent legislation has mandated the protection

of these valuable ecosystems. Today, wetlands and streams are the only ecosystems

regulated on both public and private lands in the U.S. (National Research Council

1995). After the Clean Water Act of 1972, the �no net loss� policy was enacted in the

late 1980s with the goal of sustaining positive gains in the wetland resource base. On

paper, the �no net loss� policy appears to be working with an estimated 50,000 ha of

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wetlands in the U.S. being gained from October 1993 to September 1999 (Mitsch and

Gosselink 2000). However, these statistics only reflect compensation of the area of

wetland lost, and do not pertain to gains or losses in wetland function. Numerous

studies have written about our inability to successfully mitigate for wetland

destruction (Race 1985, Erwin 1990, Reinartz and Warne 1993). Although the

definition of success varies depending upon project objectives, most agree that

compensatory wetlands should replace functions lost during wetland destruction. To

gain further insight into the success of our legislation in protecting wetlands, one

must evaluate this success in terms of wetland function. Since the 1980s, numerous

studies have sought to assess the success of mitigation wetlands in properly

supporting hydrology, soils, vegetation, and wildlife (Wentworth et al. 1988, Jarman

et al. 1991, Reinartz and Warne 1993, Niswander and Mitsch 1995, Wilson and

Mitsch 1996, Campbell et al. 2002). While these functions are crucial to wetland

ecosystem integrity, it may be logistically impossible to evaluate all of these

functions when determining the success of a mitigation wetland.

While wetland creation and restoration has been conducted widely throughout

the U.S., research has only begun to determine if compensatory wetlands are

replacing invertebrate habitat and communities of natural wetlands destroyed by

development (Streever and Crisman 1993, Reaves and Croteau-Hartman 1994,

Scatolini and Zedler 1996, Ashley et al. 2000, Fairchild et al. 2000). For a variety of

reasons, invertebrates are extremely important in the functioning of wetlands, and

thus can be viewed as surrogates for wetland health. First, from a logistic standpoint,

they make good study specimens because they are abundant, readily surveyed, and

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taxonomically rich (Dodson 2001). Long-term hydrologic cycles, water quality, and

habitat type associated with wetlands influence many adaptive strategies of

invertebrates (Wiggins et al. 1980, Doupe and Horwitz 1995, Brooks 2000). Hence,

researchers have used invertebrates to quantify and qualify water quality in wetland

ecosystems (Wallace et al. 1996). In turn, invertebrates contribute to other wetland

functions by assisting in litter decomposition, nutrient cycling (Cummins 1973,

Merritt et al. 1984) and plant community regulation (Weller 1994). Thus,

invertebrates indirectly aid in the transfer of nutrients from the sediments, detritus,

and water column to higher-level organisms. They also have direct impacts on

wildlife species that depend on them for food. Because numerous avian species,

particularly waterfowl and other waterbirds, depend on invertebrates for food

(Gonzalez et al. 1996, De Szalay and Resh 1996, Davis and Smith 1998, Anderson

and Smith 1998, 1999; Anderson et al. 2000), researchers can assess avian

productivity by sampling invertebrates. As well, they are important dietary

components of anurans (Green and Pauley 1987, Anderson et al. 1999, Lima and

Magnusson 2000), making them good indicators of anuran populations. Recently,

invertebrates have even been used as indicators in delineating wetland boundaries

(Euliss et al. 2002). It is clear that invertebrates play a vital role in wetland function

and thus, are integral in analyzing the health of these ecosystems. The extensive loss

of wetlands further increases the value of ecological functions performed by

remaining wetlands, and the production of aquatic invertebrates is one such function

that should not be ignored.

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Despite numerous studies indicating the significance of invertebrates in

shaping wetland ecosystem health, few studies have monitored the ability of restored

and constructed wetlands in supporting healthy invertebrate populations in the mid-

Appalachians (Johnson et al. 2000). Many studies that do exist preclude a

comprehensive evaluation of all invertebrate taxa, and instead, focus on specific taxa

deemed important to wetland health (Streever and Crisman 1993, Streever et al. 1995,

1996, Ashley et al. 2000, Fairchild et al. 2000, Johnson et al. 2000). Only 2 studies

have evaluated the success of constructed wetlands in West Virginia, and 1 of them

(R.H. Fortney, unpublished report) excluded an evaluation of invertebrates while the

other evaluated production of only 1 taxa in 1 constructed wetland (Johnson et al.

2000). As such, there is a need to evaluate the current ability of mitigation wetlands

in the mid-Appalachian, and in particular West Virginia, in supporting diverse

invertebrate populations. Likewise, in order to maintain the significant role

invertebrates play in the development of wetland ecosystems across this region, there

is a need to identify wetland habitat characteristics that are associated with existing

invertebrate populations. Therefore, researchers can develop adequate monitoring

protocols and construct future wetlands that are compatible with invertebrate

proliferation. This study sought to evaluate the success of mitigation wetlands in

supporting invertebrate communities in West Virginia. Natural (reference) wetlands

were used as standards of comparison since these areas are considered relatively

stable and undisturbed (Brinson 1993, Brinson and Rheinardt 1996, Wilson and

Mitsch 1996). Thus, the objective of this study was to test the null hypothesis that

invertebrate familial richness, diversity, density, and biomass were equal between

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mitigation and reference wetlands. These data should be helpful in the creation of

future mitigation wetlands, and also in the establishment of monitoring protocols for

these and other wetlands in the region.

METHODS

Study sites

Eleven mitigation (Walnut Bottom, VEPCO, Buffalo Coal, Elk Run, Leading

Creek, Sugar Creek, Sand Run, Triangle, Trus Joist MacMillan, Enoch Branch, and

Bear Run) and 4 reference (Altona Marsh, Elder Swamp, Meadowville, and

Muddlety) wetlands from the northern two-thirds of West Virginia were evaluated for

this study. A minimum standardized time of development of 5 years was chosen for

all mitigation study sites. They ranged in age from 5-21 years old ( x = 10.0, SE =

1.7), and ranged in size from 3.0-10.0 ha ( x = 5.8, SE = 0.80). Similarly, they

ranged in elevation from 265-1,036 m ( x = 586, SE = 75.9). Mitigation sites were

created to compensate for wetland losses sustained in West Virginia for many human

activities including highway development and industrial development, as well as

mining. Almost all mitigation study sites were located near some form of human

disturbance. In fact, many were located adjacent to roads with moderate to heavy

traffic. All were classified as either palustrine emergent or unconsolidated bottom

wetlands with seasonally to permanently flooded hydrologic regimes (Cowardin et al.

1979).

Each of the 4 areas was represented by 1 reference wetland, which was

chosen based on its similarity in location, elevation, size, vegetative structure, and

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hydrology to mitigation sites within that area (Chapter I). Only portions of reference

sites resembling conditions (i.e., size, hydrology, vegetation) similar to mitigation

sites were selected for study. All had established stable emergent, scrub-shrub, and

forested wetland communities. They ranged in elevation from 170-1,000 m ( x =

582, SE = 169.5) and ranged in size from 6.5-28.0 ha ( x = 15.1, SE = 4.7). All were

classified as palustrine emergent or scrub-shrub wetlands with seasonally to

permanently flooded hydrologic regimes (Cowardin et al. 1979). Detailed mitigation

and reference site descriptions are provided in Chapter I.

Invertebrate sampling

I conducted invertebrate sampling according to Anderson and Smith (1996,

2000) during the summers of 2001 and 2002. Specifically, I collected 620 samples in

July and September of 2001 and another 620 samples in April and June of 2002.

Samples were collected at different times both years to collect a greater diversity of

taxa. Wetlands were stratified based on wetland classification (Cowardin et al. 1979),

and specimens were collected at 10 random points within open water, emergent, and

scrub-shrub (if they existed) areas of each wetland. At each point, I used a 5 cm

diameter core (15 cm deep) and a 7.5 cm diameter water column sampler (Swanson

1983) to collect nektonic and benthic specimens, respectively. Water column

samples were sieved in the field using a 500-micron sieve (Huener and Kadlec 1992)

and preserved in 70% ethanol. Benthic samples were placed in bags, refrigerated, and

processed using an elutriator (Magdych 1981) within 10 days of collection (Anderson

and Smith 2000). Invertebrates were identified and counted to family using

McCafferty (1981), Pennak (1989), and Merritt and Cummings (1984). Familial

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richness was expressed as the number of families/wetland, and abundance (no.

individuals) was converted into density estimates (no./m² or no./L). Biomass (g/m² or

g/L) was obtained by oven-drying samples at 55°C for ≥48 hours to a constant mass

(0.0001 g) and using an analytical scale.

Statistical analyses

Mitigation and reference wetlands were compared using SAS (SAS Institute

1988). Invertebrate familial richness, diversity, biomass, and density were compared

using a split-plot Analysis of Variance (ANOVA) model, with wetland type

(mitigation vs. reference) as the first split and time as the second split. I incorporated

a repeated measures design for 2 survey periods, which were repeated both years.

The independent variables tested were wetland type and sampling period and type×

sampling period interactions with dependent variables being richness, diversity,

biomass, and density. Familial diversity was calculated using the Shannon-Weiner

Index (Shannon and Weaver 1949). To decrease variability, geographic area was

included as a blocking factor for all analyses, except when comparing invertebrate

indices between subtypes (emergent vs. open water) within mitigation wetlands. In

this case, site was used as a blocking factor. In addition to comparisons of all

invertebrate taxa, comparisons were made between wetland types for the most

abundant orders and families observed. All families used for this analysis contained

at least 100 individuals. I also used an ANOVA to test for differences between scrub-

shrub, emergent, and open water invertebrate communities within the Elder Swamp

reference wetland. If differences were observed in invertebrate communities,

Tukey�s (HSD) Honestly Significantly Difference test was used to test pairwise

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comparisons of means. Assumptions of normality were tested with the univariate

procedure in SAS (SAS Institute 1988), and Levene�s Test was used for homogeneity

of variances. Rank and log transformations were used to convert dependent variables

that did not meet the aforementioned assumptions (Dowdy and Wearden 1991).

Specifically, log transformations were used for within subtype comparisons, and rank

transformations were used to analyze familial density and biomass of common taxa.

RESULTS

Taxa occurrence A total of 10,824 benthic and nektonic individuals were sampled, 6,350 of

which occurred in mitigation sites and 4,474 occurred in reference sites. Within

benthic samples, 3,173 individuals from 38 families were sampled in mitigation

wetlands (Appendix 33) while 3,799 individuals from 25 families were sampled in

reference wetlands (Appendix 34). Within nektonic samples, 3,177 individuals from

70 families were sampled in mitigation wetlands (Appendix 35), and 675 individuals

from 50 families were sampled in reference wetlands (Appendix 36).

Mitigation versus reference wetlands

Overall benthic (P = 0.984; Table 1) and nektonic (P = 0.101; Table 2)

familial richness was similar across wetland complexes of mitigation and reference

wetlands. Similar results were obtained across emergent and open water areas.

Benthic diversity was higher in reference wetlands across wetland complexes (P =

0.046), but was similar across emergent (P = 0.102) and open water (P = 0.189) areas

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between wetland types (Table 1). Nektonic diversity was similar between mitigation

and reference wetlands across entire wetland complexes (P = 0.626), as well as

emergent (P = 0.523) and open water (P = 0.068) areas (Table 2). Benthic (Table 1)

and nektonic (Table 2) density (P ≥ 0.348) and biomass (P ≥ 0.228) were similar

between mitigation and reference wetlands. Within open water areas, nektonic

biomass was higher (P = 0.021) in mitigation wetlands, but benthic density was

higher (P = 0.031) in reference wetlands.

The 9 most abundant benthic families (of 4 orders) included Diptera

(Chironomidae), Gastropoda (Lymnaedae, Physidae, Planorbidae, Pomatiopsidae,

Valvatidae, and Viviparidae), Pelecypoda (Sphaeriidae), and Oligochaeta (not taken

to family). The top 13 nektonic families (of 9 orders) included Amphipoda

(Talitridae), Cladocera (not taken to family), Diptera (Chironomidae), Ephemeroptera

(Baetidae and Caenidae), Gastropoda (Physidae, Planorbidae, and Viviparidae),

Hemiptera (Corixidae and Veliidae), Isopoda (Asellidae), Odonata (Coenagrionidae),

and Pelecypoda (Sphaeriidae). The 2 most abundant benthic orders sampled in both

wetland types were Gastropoda and Oligochaeta (Table 1). The 2 most abundant

nektonic orders in mitigation wetlands were Gastropoda and Hemiptera while in

reference wetlands, Isopoda and Diptera were most abundant (Table 2).

Comparisons of each order individually yielded a higher benthic Oligochaeta

density (P = 0.012) and biomass (P = 0.001) in mitigation wetlands across open water

areas (Table 1). Nektonic Gastropoda biomass was higher (P = 0.023) across wetland

complexes in mitigation wetlands (Table 2). This was attributed to higher biomass in

open water areas. Within emergent areas, Ephemeroptera nektonic density (P =

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0.043) and Hemiptera density (P = 0.028) and biomass (P = 0.018) were higher in

mitigation wetlands (Table 2). However, nektonic Isopoda density (P = 0.015) and

biomass (P = 0.025), as well as Odonata biomass (P = 0.039) were higher in

reference sites across entire wetland complexes (Table 2). This was attributed to

higher numbers across emergent areas.

An evaluation of the 13 common nektonic families combined yielded a higher

(P = 0.021) biomass in mitigation wetlands within open water areas (Table 2).

Although benthic Planorbidae density (P = 0.020) and biomass (P = 0.024) were

higher in emergent areas of reference wetlands (Table 1), nektonic Planorbidae

density (P = 0.046) and biomass (P = 0.031) were higher across mitigation wetland

complexes (Table 2). This was attributed to higher numbers across open water areas

(density: P = 0.048; biomass: P = 0.025). Nektonic Physidae biomass was higher in

mitigation wetlands across entire wetland complexes (P = 0.015) as well as emergent

(P = 0.018) and open water (P = 0.037) areas (Table 2). Nektonic Physidae density

also was higher across mitigation wetland complexes (P = 0.021) and emergent areas

(P = 0.019), but reference wetlands contained higher (P = 0.039) nektonic Physidae

density in open water areas (Table 2). In addition, nektonic Corixidae density (P =

0.046) and biomass (P = 0.045), Coenagrionidae biomass (P = 0.041), and Caenidae

density (P = 0.029) were higher in mitigation wetland complexes (Table 2). Nektonic

Veliidae density was higher (P = 0.049) in mitigation wetland emergent areas.

Asellidae density (P = 0.015) and biomass (P = 0.025) were higher in reference

wetland complexes, but this was the only family observed within Isopoda, so results

are already reflected above within order comparisons.

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Emergent versus open water habitats Familial richness, diversity, density, and biomass also were compared

between emergent and open water areas within mitigation wetlands (Table 3). In this

comparison, richness (benthic: P = 0.001; nektonic: P = 0.018) and diversity (benthic:

P = 0.001; nektonic: P = 0.006) were higher in emergent areas. Overall nektonic

density (P < 0.001) and biomass (P < 0.001) also were higher in emergent areas.

Similar results were obtained for the top 13 nektonic families combined.

For comparisons among emergent, open water, and scrub-shrub subtypes

within the Elder Swamp reference wetland, richness (benthic: P = 0.499; nektonic: P

= 0.253), diversity (benthic: P = 0.792; nektonic: P = 0.116), and biomass (benthic: P

= 0.865; nektonic: P = 0.111) were similar among subtypes (Table 4). Similar results

were obtained for the most common taxa. However, nektonic density for all taxa (P =

0.034) and for the top 13 families (P = 0.005) was highest in emergent areas.

Specifically, for the top 13 families, scrub-shrub invertebrate densities scored in the

middle between emergent and open water areas. While emergent and scrub-shrub

densities were similar, both densities were higher than open water densities.

DISCUSSION

Mitigation versus reference wetlands These data indicated equally abundant, diverse, and productive invertebrate

communities in mitigation wetlands relative to reference wetlands. Despite reference

wetlands supporting a higher benthic density across open water areas, mitigation

benthic density was similar to reference wetlands across entire complexes. Nektonic

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density and biomass also were similar between wetland types across complexes, and

mitigation nektonic biomass actually exceeded reference biomass across open water

areas. Mitigation nektonic diversity also was similar to reference wetlands, both

across emergent and open water areas, and across entire complexes. Despite similar

benthic diversity across emergent and open water areas between wetland types,

reference benthic diversity exceeded mitigation diversity across wetland complexes.

An examination of specific taxa based on order and family provided further

insight into invertebrate community structure. Within these analyses emerged trends

that indicated higher abundance and productivity of invertebrates within mitigation

wetlands. These results are consistent not only across entire wetland complexes, but

within emergent and open water areas as well. While only 3 taxa were higher in

reference wetlands, 7 taxa were higher in mitigation wetlands, most of which were

nektonic specimens. Despite this trend, mitigation nektonic diversity was similar to

reference wetlands.

Of particular importance within mitigation wetlands was the abundance of

Hemiptera. Specifically, Corixidae and Veliidae were more abundant in mitigation

wetlands. These taxa are important components of the diet of dabbling ducks (Euliss

et al. 1991, Batzer et al. 1993), and actually are known to benefit from fish presence

(Zimmer et al. 2000). Although no formal surveys were conducted on fish

abundance, 10 of 11 mitigation wetlands contained fish populations. Studies, in

general, show mixed results regarding invertebrate responses to fish populations

(Wilcox 1992, Pierce and Hinrichs 1997, Batzer et al. 2000). Benthic Oligochaeta

density also was higher in mitigation wetlands, but only across open water areas. No

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obvious natural history components of these taxa account for their higher abundance

in mitigation wetlands. Nektonic Gastropoda was generally more abundant and

productive within mitigation wetlands as well. This was reflected by such large

numbers of Physidae across complexes and subtypes, although Planorbidae was

highly productive as well, especially within open water areas. It is clear that open

water played a key role in structuring Gastropoda populations among wetlands.

Gastropoda are grazers and generally found in shallow areas with moderate amounts

of aquatic vegetation (Pennak 1989). Mitigation wetlands generally had longer

hydroperiods with a more even mixture of emergent vegetation to open water than

reference wetlands. These conditions likely favored Gastropoda colonization and

probably reflect their ubiquitous distribution throughout emergent and open water

areas of mitigation wetlands. This phenomenon is not uncommon throughout wetland

studies (Anderson and Smith 2000, Nelson et al. 2000). Despite high numbers of

nektonic Physidae and Planorbidae, benthic Planorbidae density and biomass were

higher in reference wetlands, specifically in areas with emergent vegetation. This

trend was evident because of such unproportionally high numbers of Planorbidae in

emergent areas of Altona Marsh, a natural marl wetland with alkaline conditions.

Reference wetlands also supported more Asellidae (Isopoda), and a more productive

nektonic Odonata population. Brown et al. (1997) also observed higher Asellidae

abundance in natural wetlands in New York. Asellidae generally avoid open water

and remain hidden under rocks, emergent vegetation, or debris. Hence, higher

amounts of emergent vegetation in reference wetlands (Chapter IV) likely provided

more refugia for these taxa. In fact, almost all Asellidae were sampled within

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emergent areas of both wetland types. Despite a higher nektonic Odonata biomass,

benthic samples yielded higher Odonata densities in mitigation wetlands within

emergent areas. No trends in Odonata life history seem to account for these results.

A common taxa that is addressed throughout many invertebrate studies is

Chironomidae (Streever et al. 1995, Ashley et al. 2000, Batzer et al. 2000, Brooks

2000, Nelson et al. 2000). This taxa spends a majority of its life cycle in the aquatic

larval stage where it eventually ascends to the water surface to emerge after pupation

(Oliver 1971, Pinder 1986). Thus, it is available during different life stages to aquatic

birds with differing feeding behaviors. As such, Chironomidae are a preferred food

of young dabbling ducks (Batzer et al. 1993, King and Wrubleski 1998) and other

adult waterfowl and waterbirds (Ashley et al. 2000). They also readily colonize

newly created habitats if conditions are suitable (Danell and Sjoberg 1982) and are

important in the development of wetland physical and chemical properties (Fisher

1982). Thus, differences in Chironomidae communities of constructed and natural

wetlands have been assumed to reflect functional differences instead of poor initial

recruitment (Steever et al. 1996). The mitigation wetlands evaluated in this study

supported statistically similar Chironomidae density and biomass to reference

wetlands, despite having a density and biomass that were almost 3 and 6 times higher,

respectively in mitigation than reference wetlands. Nektonic Chironomidae samples

yielded more similar results between wetland types. Nevertheless, mitigation

wetlands in West Virginia currently contain abundant and well distributed

Chironomidae populations that should continue to serve as a valuable prey base for

avian and anuran populations.

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The rapid colonization of invertebrate communities is common in created and

restored wetlands (Streever et al. 1996, Brown et al. 1997, Fairchild et al. 1999,

Ashley et al. 2000). The proximity of mitigation wetlands to rivers, streams, and

other wetlands is known to facilitate colonization of invertebrates (Jeffries 1994,

Nelson et al. 2000). Almost all of the mitigation wetlands in this study, as well as

reference wetlands, were located near major water sources. The complex trophic

levels among invertebrate communities often dictate composition of invertebrate taxa.

Predatory taxa, for instance, depend on colonization by prey, herbivory taxa often

depend on vegetation succession, and taxa that collect fine algal and detrital particles

may depend on the development of adequate substrate conditions (Lake et al. 1989,

Fairchild et al. 2000). Because of the average 10-year development time of

mitigation wetlands included in this study, I expected temporal and spatial

development among mitigation wetlands across the state to be sufficient in supporting

diverse invertebrate taxa. In fact, representative taxa of predators, herbivores,

algivores, and detritivores all were present across mitigation wetlands.

Differences in vegetation composition and community structure between

mitigation and reference wetlands may account for some differences observed

between invertebrate taxa between wetland types. Mitigation wetlands supported

more diverse and species rich vegetation communities than reference wetlands

(Chapter II). Given the relatively higher number of invertebrates observed in

mitigation wetlands, one may conclude that, to a certain extent, the percentage of

aquatic vegetation may play less of a role in structuring invertebrate communities

than vegetation composition. This assertion is supported by results obtained by

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Brown et al. (1988), where increases in invertebrate richness and density were

observed with increasing diversity of aquatic vegetation communities. They, too,

concluded that diverse vertical structure associated with diverse vegetation

communities was more important in structuring invertebrate populations than surface

area of vegetation. Other studies have concluded similar results (Schramm et al.

1987, De Szalay and Resh 1996). The profound difference in vegetative community

composition between mitigation and reference wetlands likely plays a leading role in

structuring invertebrate populations. These differences will likely decrease through

time, however, as disturbed conditions in mitigation wetlands diminish and vegetation

competitive interactions manifest to create similar vegetation community composition

between wetland types.

Hydroperiod (length and duration of flooding) also is considered to be a major

factor structuring invertebrate communities. In addition to its effects on wildlife

communities (Chapter IV), wetland hydroperiod affects invertebrate taxon richness

(Spencer et al. 1999, Brooks 2000) as well as invertebrate density, biomass, and

production (Leeper and Taylor 1998, Anderson and Smith 2000). The general trend

in all of these studies was that invertebrate communities benefited from longer

hydroperiods. With increasing hydroperiod, concentric biotic zones can be created,

with the more ephemeral peripheral zones differing from central zones with more

permanent water (Brooks 2000). Thus, invertebrate communities can increase in

richness based entirely on life history requirements. Other benefits are associated

with longer hydroperiod, and these are discussed later. The mitigation wetlands

evaluated in this study were mostly semipermanently to permanently flooded

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(although some were seasonally flooded) while reference wetlands varied from

seasonally flooded (Meadowville) to permanently flooded (Muddlety). Hence,

because mitigation wetlands had longer hydroperiods, I expected to observe higher

familial richness, and perhaps more significant differences in overall diversity,

density and biomass. Although this was not the case, mitigation wetlands did support

more abundant and productive nektonic taxa than reference wetlands.

While abundant research exists pertaining to invertebrate use of wetlands, few

studies have evaluated invertebrate community structure in mitigation wetlands

relative to naturally functioning reference wetlands (Rossiter and Crawford 1981,

Kreil 1986, Streever et al. 1996, Brown et al. 1997, Fairchild et al. 2000, Zimmer et

al. 2000). Within these studies, no real trend has emerged regarding the success of

mitigation wetlands in supporting abundant and productive invertebrate populations.

Brown et al. (1997) and Zimmer et al. (2000) found overall similar invertebrate

abundances between restored and natural wetlands. Likewise, Fairchild et al. (2000)

observed similar Coleopteran richness and Streever et al. (1996) observed similar

Dipteran densities between constructed and natural wetlands in Pennsylvania.

Results of these studies are consistent with those obtained in my study. However,

Rossiter and Crawford (1981) and Kreil (1986) found higher invertebrate density and

diversity in natural wetlands. Nelson et al. (2000) also observed higher invertebrate

richness and abundance in natural wetlands, but only 2 constructed wetlands were

evaluated. Although some of these studies stratified invertebrate sampling by

vegetation communities or by vegetated and open water habitats, for statistical

purposes, samples were pooled across habitats. Hence, statistics analyzing

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invertebrates individually within these habitats were not performed. My study

compared mitigation and reference wetlands, not only within wetland subtypes

(vegetated and unvegetated), but across entire wetland complexes as well. For

instance, upon pooling samples taken from wetland subtypes, no statistical

differences emerged for either benthic or nektonic specimens, both for all taxa and for

the most common taxa. However, overall differences did emerge upon comparing

benthic and nektonic samples across wetland subtypes. Specifically, benthic density

was higher in reference wetlands across open water habitats, but nektonic biomass

was higher in mitigation wetlands. Hence, these data reveal the importance of open

water habitats in distinguishing invertebrate community structure between mitigation

and reference wetlands. Indeed, this discovery would have been ignored upon

comparing invertebrate communities across entire wetland complexes. Comparisons

of individual taxa also reflect the importance of these analyses. These data definitely

provide a clearer picture of the spatial variation in invertebrate community structure

in wetlands.

The complex interactions between vegetation and invertebrate communities

discussed above have important implications in shaping wildlife communities in

mitigation wetlands. As aforementioned, invertebrates are a primary food source for

anuran and avian populations. Thus, invertebrates, in addition to those factors

outlined in Chapter IV, likely affect wildlife abundance and distribution. As

mentioned in Chapter IV, waterbird and anuran abundance were higher in mitigation

wetlands. This may be attributable to a higher overall nektonic biomass observed

within mitigation wetlands. Granted, reference wetlands contained a higher overall

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benthic density in open water areas, benthic invertebrates may be more difficult to

access than nektons, especially for anurans. Although benthic invertebrates are

readily accessible to dabbling ducks, the relatively more diverse nektonic taxa of

invertebrates offered in mitigation wetlands may contribute more to the prey base for

these and other waterbirds dependent on invertebrates for food. Cox et al. (1998)

found a direct correlation between survival and growth of mallard (Anas

platyrhynchos) and abundance of aquatic invertebrates, and Anderson et al. (2000)

found a positive correlation between feather molt intensity of green wing teal (Anas

crecca) and aquatic invertebrate consumption. Ashley et al. (2000) observed similar

correlations between invertebrate densities and aquatic bird abundance. Invertebrates

are not only an important food resource for waterbirds, they are important for

terrestrial passerine species that are more peripherally associated with wetland habitat

(Euliss et al. 1999). These data indicate that higher invertebrate production in

mitigation wetlands may directly affect productivity of wildlife species that depend

on them for food, and thus, provide further insight into the ecological value of

constructed wetlands in West Virginia. Hence, these data indirectly suggest the

effectiveness of mitigation efforts in replacing aquatic avian and anuran habitat lost

due to development.

The absence of consistent differences between invertebrate populations of

mitigation and reference wetlands should not be interpreted as functional similarities

between wetland types. Wetlands are complex ecosystems with variable functions

that take decades to form. Wilson and Mitsch (1996) recommended giving

freshwater wetlands 15-20 years before judging their success, and Frenkel and

117

Morlan (1991) recommended waiting at least 50 years for certain forested and coastal

wetlands. Two wetlands included in this study were about 20 years old and an

additional 3 sites were ≥ 10 years old. Although my sites do not meet recommended

criteria for constructed wetland development time, nearly half are at least 10 years

old, and I think relatively conservative inferences can still be made regarding their

success in supporting invertebrate communities.

Emergent versus open water habitats

The variation in invertebrate distribution throughout wetlands was

exemplified by significant differences in community structure between emergent and

open water areas. It was not surprising that invertebrate abundance, diversity, and

production was so much higher in emergent areas. Numerous studies have observed a

direct relation between invertebrate production and aquatic vegetation (Wilcox 1992,

Streever et al. 1995, Zimmer et al. 2000). Specifically, Streever et al. (1995) sampled

invertebrate populations between vegetated and non-vegetated areas in a constructed

wetland in Florida and found higher abundances in emergent areas. These data, as

well as results from my study, support the need to stratify wetlands by structure to

account for spatial variation in invertebrate populations. Emergent areas likely

support more invertebrates because they enjoy decreased risk of predation, increased

vertical and spatial structure, and higher food resources, especially from submerged

aquatic vegetation (Crowder and Cooper 1982, Carpenter and Lodge 1986, Severson

1987). As well, emergent vegetation may increase survival of some invertebrate taxa

by increasing egg viability or diapausing individuals (Wiggins et al. 1980, Rehfisch

1994).

118

However, too much emergent vegetation may decrease dissolved oxygen

levels by shading oxygen producing submergent vegetation, thus inhibiting

invertebrate productivity, especially Dipteran larvae (Streever et al. 1996, Nelson et

al. 2000). In this study, reference wetlands contained higher percentages of emergent

aquatic vegetation than mitigation wetlands (Chapter IV), yet invertebrate production

was relatively low. This may be attributable to lower dissolved oxygen levels from

decreased amounts of open water. While emergent vegetation does provide important

food and cover to invertebrates, the importance of open water cannot be

underestimated. Indeed, studies have shown that dissolved oxygen has a strong

influence on invertebrate community structure (Nelson et al. 2000), and that open

water habitats provide higher dissolved oxygen levels necessary for subsistence of

productive invertebrate populations. In turn, this will benefit ducklings that tend to

forage on invertebrates in open water habitats (King and Wrubleski 1998). It is

important to note, however, that duckweed (Lemna spp. L.) or algal mat

developments in open water habitats may curtail light penetration, reducing

oxygenation via photosynthesis by submerged aquatic vegetation, thus harming

invertebrate populations, and subsequently, wildlife populations (Nelson et al. 2000).

One particular study actually found a direct correlation between invertebrate diversity

and submerged aquatic vegetation (Schwartz and Gruendling 1985). This further

stresses the importance of establishing submerged aquatic vegetation in mitigation

wetlands (Chapter II). Sartoris and Thullen (1998) suggested that even proportions of

emergent vegetation and open water habitats (i.e., hemimarsh) create optimal habitat

for invertebrates. They pointed out that hemimarsh conditions, in addition to

119

providing a mosaic of habitats for wildlife, create alternating aerobic and anoxic

environments for invertebrates and allow for nitrogen treatment and degradation of

organic matter. These habitat conditions are further asserted in Chapter IV and are

presumed to be responsible for higher abundances of anurans and waterbirds in

mitigation wetlands.

An evaluation of invertebrate populations among habitat subtypes within the

Elder Swamp reference wetland also was conducted. The objective of this analysis

was to assess the value of scrub-shrub areas to invertebrates relative to open water

and emergent areas. According to this analysis, scrub-shrub areas supported similar

overall invertebrate richness, diversity, density, and biomass to emergent and open

water habitats. Due to small sample sizes, the other 3 reference wetlands were not

included in this analysis. Hence, this analysis lacks sufficient replication to make

accurate inferences about the contribution of scrub-shrub areas to invertebrate

community structure. Nevertheless, scrub-shrub areas add valuable vertical and

horizontal structure to wetland complexes, and should be incorporated into mitigation

projects.

Future considerations

The identification of variables that influence abundance and distribution of

aquatic invertebrate communities is crucial to adequately managing wetlands, not

only for wildlife, but for numerous other important functions valuable to ecosystem

integrity. Other factors not considered in this study that are known to affect

invertebrate community structure include water chemistry (Lancaster and Scudder

1987, Euliss et al. 1991, Foster 1995), turbidity (Threlkfeld and Soballe 1988,

120

Zimmer et al. 2000), nutrient enrichment (Pettigrew et al. 1998), organic content

(Craft 2000), surrounding land management activities (De Szalay and Resh 1996),

and climate change (Eyre et al. 1993). Future studies on mitigation wetlands in West

Virginia should consider these abiotic factors that contribute to spatial and temporal

variation in invertebrate community structure, while not ignoring additional effects of

stochastic events on invertebrate populations. Such studies might include evaluations

of pH, substrate composition, dissolved oxygen, conductivity, or temperature to name

a few. Bioaccumulation of trace elements (silver, aluminum, mercury, selenium) also

should be monitored if wetlands are created adjacent to agricultural fields. Dodson

(2001), for instance, observed lower invertebrate taxon richness in wetlands near

agricultural use watersheds. In particular, agricultural practices are known to

decrease egg hatching (Dillon and Gibson 1985) and feeding success in invertebrates

by increasing turbidity and contamination by fertilizer and pesticide runoff (Dodson

2001). However, this factor was minimal in our study because only 1 mitigation site

was constructed adjacent to agricultural fields.

Furthermore, because congeneric species may have different tolerances to

environmental conditions, species-level identification should be considered in future

studies that focus in invertebrate populations in mitigation wetlands. Other studies

could address the effects of wetland construction techniques including soil

transplantation, dredging, or dike development. Brown et al. (1997), for instance,

found that transplantation of remnant wetland soil significantly increased invertebrate

abundance. Although this appears to speed initial colonization by invertebrates (and

plants), it may be unnecessary given the evidence supporting the rapid development

121

of hydrophytic vegetation in the absence of soil and plant transplantations. This is

evident, for instance, at Walnut Bottom, which is one of the youngest wetlands

evaluated in this study, and this site contained the highest abundance of invertebrates

of all wetlands evaluated.

It is encouraging that mitigation wetlands supported such abundant and

productive invertebrate populations. However, strong temporal variation can exist in

invertebrate populations (Scatolini and Zeddler 1996, Fairchild et al. 2000).

Although mitigation wetlands appear to support invertebrate populations comparable

to reference wetlands, this conclusion precludes analysis of rarer taxa within the

region, as well as describing discrepancies (if any exist) among frequencies of

differing trophic levels due to time lag. These points illustrate the need for extensive

sampling over long periods of time, not only to establish regional reference standards,

but to accurately describe invertebrate populations within mitigation wetlands.

Management options

Indeed, the differences in invertebrate communities between mitigation and

reference wetlands observed in this study stress the importance of maintaining

specific habitat characteristics that promote invertebrate production. Perhaps the

most important recommendation centers on maintaining diverse vegetation

communities intermixed with equal amounts of open water, while maintaining a

hydroperiod of 4 months with seasonal drying. A recommended technique to achieve

such goals is moist soil management. This management tool optimizes wetland

vegetative vertical and spatial structure. As well, it creates spatial and temporal

variations in wetland habitat that maximize vegetation and invertebrate communities,

122

and hence, wildlife distribution and abundance. Numerous studies have shown that

longer hydroperiod increases invertebrate diversity (Batzer and Resh 1992, Anderson

and Smith 2000, Brooks 2000). Anderson and Smith (2000) found that invertebrates

were most abundant and diverse in moist-soil managed wetlands with longer

hydroperiods, followed by moist-soil managed wetlands with shorter hydroperiods,

unmanaged wetlands with longer hydroperiods, and unmanaged wetlands with shorter

hydroperiods. These differences were due to differences in soil moisture and

subsequent vegetation growth. Moist-soil managed wetlands are known to contain

more abundant and diverse vegetation communities (Anderson 1997), which, as

previously mentioned, provide more food, cover, and reproductive habitat for

invertebrates. The species composition also is different in moist-soil managed

wetlands, with annual seed producing plants being favored that decompose more

readily over more robust perennial emergents that occur in nonmanaged wetlands.

And a longer hydroperiod (4 vs. 2 months; Anderson and Smith 2000) would

facilitate this decomposition (Anderson and Smith 2002), thus creating more detritus

through fragmentation (Murkin and Kadlec 1986, Nelson et al. 1990). In addition,

longer hydroperiod increases invertebrate abundance by facilitating colonization

(Rosenzweig 1996). However, other studies have shown that as hydroperiod

becomes too long (i.e., > 6 mo.), abundance and diversity of invertebrates will decline

in permanently (Reid 1983) to semipermanently (Neckles et al. 1990) flooded

wetlands. This is caused by decreases in emergent vegetation, lowered

decomposition rates (Anderson and Smith 2000, 2002) which leads to less detritus,

and increased predation and competition among other invertebrates and fish (Reid

123

1983, Neckles et al. 1990, Skelly 1997, Zimmer et al. 2000). Invertebrates are not the

only taxa that benefit from moist-soil managment. Waterbirds, too, benefit, not only

from increased abundance and production of invertebrates, but from more abundant

seed availability for foraging. Indeed, Anderson and Smith (2000) found that the

combination of moist-soil management with longer hydroperiod was the superior

management tool for increasing invertebrate populations. Moist-soil conditions

caused by water draw-downs should be created in early spring to promote plant seed

germination and invertebrate concentrations (Helmers 1992), followed by fall

flooding. Spring draw-down also coincides with peak shorebird migration for most

species (Helmers 1992). It is important to note that spring draw-downs would

negatively affect anuran breeding by creating less open water for egg mass

placement. I recommend either maintaining enough open water to facilitate anuran

breeding in large isolated wetland complexes where draw-downs occur, or

implementing a mitigation banking system where numerous wetlands in a landscape

are maintained under different management schemes to create a mosaic of habitat

suitable to support both waterbirds and anurans. Although it may not be feasible to

install water control structures and implement moist-soil management in some of the

mitigation sites evaluated in this study, moist-soil management should definitely be

considered in future mitigation projects in the state.

In addition to maintaining the appropriate hydroperiod to enhance invertebrate

habitat, future mitigation projects should consider water depth design specifications

(Chapter II). Zimmer et al. (2000), for instance, observed a negative correlation

between water depth and invertebrate abundance. Although no specific water depths

124

were provided, they found that shallow water depths were associated with higher

invertebrate abundance. Consistent with recommendations from Chapter IV, it is

recommended that wetlands include shallow (1-10 cm) and deep (11-30 cm) areas to

facilitate colonization by an array of invertebrate and wildlife taxa.

I also recommended that native aquatic vegetation be planted at newly

constructed wetlands (Chapter II). Not only will this benefit overall vegetation

diversity by decreasing the competitive advantage of less desirable species such as

broad-leaved cattail (Typha latifolia L.), it should provide refuge for invertebrates

while jump starting decomposition rates thereby creating more detritus for

invertebrate consumption.

To further increase the amount of detritus available to invertebrates, the

addition of organic amendments to wetlands (Cummings 1999) should be considered

in future mitigation projects. Crop residues, manures, or mulches (Plaster 1997)

should provide increased organic matter to newly created substrates thereby

increasing invertebrate abundance via detrital accumulation (Craft 2000).

In addition to habitat quality achieved at single wetlands, construction efforts

should focus on spatial relationships on a landscape level that facilitate colonization

and regional persistence of certain invertebrate taxa. This can be achieved by

constructing wetlands adjacent to other major water sources and away from

disturbances (i.e., agricultural fields and roads). The ecological importance of aquatic

invertebrates should not be ignored in replacing lost wetland habitat. Fortunately,

management recommendations outlined in Chapter IV are compatible with habitat

characteristics that maximize invertebrate production.

125

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137

CHAPTER III

TABLES

138

Table 1. Benthic invertebrate richness (no. families/wetland), diversity, density (no./m2) and biomass (g/m2) between mitigation (n =11) and reference (n =

4) wetlands across emergent areas, open water areas, and entire wetland complexes, 2001-2002 with comparisons of all invertebrate taxa and the 9 most

common taxa (i.e., >100 individuals).

Emergent Open water Total Mitigation Reference Mitigation Reference Mitigation Reference Invertebrate taxa Mean SE Mean SE F1,10 P Mean SE Mean SE F1,10 P Mean SE Mean SE F1,10 P Total invertebrates Density 54.7 18.4 160.6 147.5 1.49 0.250 37.1 11.5 139.5 132.1 6.34 0.031 45.9 14.0 157.8 145.3 0.97 0.348 Mass 2.190 1.480 16.423 16.390 1.30 0.280 0.645 0.343 5.092 5.069 3.29 0.100 1.417 0.895 10.787 10.757 1.65 0.228 Diversity 1.590 0.060 1.740 0.080 1.71 0.220 1.120 0.100 1.200 0.420 0.01 0.945 1.36 0.080 1.470 0.220 Common 9 taxa Density 66.6 18.6 164.0 144.8 1.82 0.207 52.9 11.6 154.6 140.6 3.13 0.108 62.6 13.3 174.3 149.7 0.68 0.430 Mass 2.603 1.652 16.419 16.390 1.85 0.204 0.857 0.403 5.393 5.331 3.09 0.109 1.741 0.942 11.297 11.232 1.67 0.225 Diptera Density 14.6 1.4 14.1 3.0 0.17 0.686 14.8 2.5 8.4 3.6 3.74 0.082 19.6 2.0 18.7 2.1 0.00 0.995 Mass 0.011 0.003 0.013 0.007 0.62 0.448 0.017 0.008 0.004 0.003 3.70 0.083 0.019 0.006 0.015 0.006 0.27 0.617 Chironomidae Density 10.1 1.8 8.0 3.1 0.01 0.913 14.5 2.6 6.0 3.1 3.06 0.111 16.8 1.8 11.3 3.1 1.42 0.261 Mass 0.004 0.001 0.003 0.001 0.02 0.879 0.018 0.008 0.003 0.003 2.88 0.120 0.017 0.008 0.005 0.002 0.86 0.375 Gastropoda Density 47.6 18.2 126.1 123.0 4.30 0.065 26.2 10.8 131.4 124.2 1.72 0.220 63.1 26.5 238.7 229.2 2.66 0.134 Mass 3.373 2.000 14.791 14.775 3.26 0.101 0.549 0.330 4.853 4.771 1.07 0.324 3.244 1.957 18.85 18.750 1.51 0.248 Lymnaedae Density 3.2 1.8 13.6 13.6 0.50 0.494 0.7 0.7 13.6 13.6 0.30 0.595 3.6 1.8 17.6 17.6 0.57 0.468 Mass 0.122 0.079 1.006 1.006 0.51 0.491 0.005 0.005 0.565 0.565 0.31 0.591 0.126 0.079 1.159 1.159 0.59 0.462 Physidae Density 17.8 9.5 40.2 40.2 2.39 0.153 8.3 4.4 11.4 11.4 0.95 0.353 18.8 8.9 46.6 46.6 2.18 0.171 Mass 2.120 1.902 11.102 11.102 1.94 0.194 0.182 0.153 0.129 0.129 1.17 0.306 1.439 1.194 11.136 11.136 2.01 0.187 Planorbidae Density 33.1 11.7 55.0 55.0 7.65 0.020 22.7 8.7 64.8 57.7 1.73 0.218 44.6 16.3 91.3 84.2 3.40 0.095 Mass 2.084 1.396 2.815 2.815 7.10 0.024 0.467 0.240 2.465 2.384 1.12 0.315 1.942 1.111 3.947 3.866 2.17 0.172 Pomatiopsidae Density 1.4 1.4 38.1 38.1 0.67 0.431 1.1 1.1 34.4 34.4 1.99 0.188 1.4 1.4 58.6 58.6 3.28 0.100 Mass 0.003 0.003 1.872 1.872 0.66 0.435 0.003 0.003 0.420 0.420 2.23 0.166 0.003 0.003 1.846 1.846 2.43 0.150 Valvatidae Density 0.6 0.4 4.0 4.0 0.18 0.679 0.0 0.0 25.3 25.3 2.18 0.171 0.6 0.4 26.1 26.1 2.25 0.164 Mass 0.004 0.004 0.046 0.046 0.14 0.713 0.000 0.000 0.255 0.255 2.26 0.164 0.004 0.004 0.265 0.265 2.10 0.178 Viviparidae Density 8.1 3.6 14.2 11.1 0.01 0.911 3.0 1.9 40.1 39.1 0.15 0.705 8.4 3.6 44.1 40.6 0.01 0.913 Mass 0.077 0.045 0.364 0.346 0.01 0.920 0.010 0.009 2.172 2.171 0.20 0.663 0.076 0.046 2.235 2.220 0.03 0.858 Oligochaeta Density 30.2 8.4 15.4 4.3 1.07 0.326 34.8 10.7 11.9 5.2 9.34 0.012 45.9 8.7 22.9 3.7 2.95 0.116

139

Emergent Open water Total Mitigation Reference Mitigation Reference Mitigation Reference Invertebrate taxa Mean SE Mean SE F1,10 P Mean SE Mean SE F1,10 P Mean SE Mean SE F1,10 P Mass 0.153 0.099 0.023 0.088 0.35 0.567 0.462 0.356 0.067 0.055 10.19 0.001 0.470 0.266 0.057 0.027 1.93 0.195 Pelecypoda Density 10.8 3.6 50.2 42.1 0.38 0.552 11.6 5.2 26.2 24.1 0.02 0.900 16.1 5.4 64.5 55.3 0.28 0.608 Mass 0.056 0.027 2.885 2.873 0.33 0.581 0.107 0.061 0.631 0.629 0.02 0.899 0.115 0.053 2.935 2.925 0.11 0.752 Sphaeriidae Density 10.8 3.6 49.4 41.3 0.38 0.554 11.6 5.2 21.2 19.1 0.02 0.890 16.1 5.4 59.5 50.2 0.08 0.786 Mass 0.057 0.027 2.885 2.873 0.29 0.601 0.107 0.061 0.627 0.626 0.02 0.896 0.116 0.053 2.932 2.922 0.27 0.617 a Bold numbering indicates a significant difference (P < 0.05).

Table 1.Continued.

140

Table 2. Nektonic invertebrate richness (no. families/wetland), diversity, density (no./L) and biomass (g/L) between mitigation (n = 11) and

reference (n = 4) wetlands across emergent areas, open water areas, and entire wetland complexes, West Virginia, 2001-2002 with comparisons

of all invertebrate taxa and the 13 most common taxa (i.e., >100 individuals).

Emergent Open water Total Order Mitigation Reference Mitigation Reference Mitigation Reference

Family x SE x SE F1,10 P x SE x SE F1,10 P x SE x SE F1,10 P Total invertebrates Richness 2.5a 0.1 2.1a 0.3 2.71 0.131 1.9a 0.3 1.1a 0.5 4.37 0.063 2.4a 0.1 1.9a 0.3 3.26 0.101 Diversity 2.46 0.11 2.33 0.04 0.44 0.523 1.95 0.18 1.16 0.43 4.20 0.068 2.52 0.10 2.45 0.05 0.25 0.626 Density 14.8 3.1 12.6 2.7 0.30 0.594 2.4 1.1 1.8 1.0 1.59 0.236 8.6 1.9 8.3 2.1 0.03 0.862 Mass 0.2586 0.1816 0.0551 0.0219 0.90 0.366 0.0226 0.0185 0.0051 0.0039 7.56 0.021 0.1407 0.1000 0.0359 0.0131 0.90 0.364 Common 13 taxa Density 16.5 4.0 13.0 2.6 1.49 0.250 3.1 1.1 3.9 2.1 2.22 0.167 12.1 3.2 10.9 2.0 0.29 0.603 Mass 0.3365 0.2248 0.0512 0.0313 3.64 0.086 0.0318 0.0216 0.0139 0.0125 7.44 0.021 0.1923 0.1110 0.0415 0.0268 4.22 0.067 Amphipoda Density 0.8 0.6 0.9 0.7 0.28 0.607 1.9 1.9 1.6 1.6 1.54 0.243 1.8 1.6 2.3 2.1 0.21 0.658 Mass 0.0003 0.0002 0.0005 0.0003 0.30 0.597 0.0145 0.0150 0.0058 0.0060 1.65 0.227 0.0103 0.0102 0.0063 0.0059 0.32 0.581 Talitridae Density 0.6 0.6 0.4 0.3 0.48 0.505 1.9 1.9 2.0 2.0 1.51 0.247 1.6 1.6 2.5 2.3 0.00 0.992 Mass 0.0002 0.0002 0.0004 0.0003 0.49 0.450 0.0148 0.0150 0.0076 0.0080 1.58 0.238 0.0102 0.0102 0.0082 0.0078 0.01 0.931 Cladocera Density 6.2 3.0 1.5 0.7 0.71 0.418 1.4 0.9 0.0 0.0 2.61 0.137 5.3 1.7 1.6 0.6 1.68 0.225 Mass 0.0057 0.0040 0.0002 0.0001 0.73 0.412 0.0007 0.0006 0.0000 0.0000 2.59 0.139 0.0040 0.0021 0.0002 0.0001 1.86 0.203 Diptera Density 6.3 1.4 5.9 0.9 0.21 0.658 0.8 0.3 0.7 0.4 0.06 0.804 5.4 1.2 6.3 1.1 0.43 0.528 Mass 0.0048 0.0016 0.0100 0.0074 0.02 0.879 0.0013 0.0010 0.0002 0.0010 0.53 0.485 0.0043 0.0014 0.0099 0.0075 0.01 0.913 Chironomidae Density 4.7 1.2 3.2 1.4 1.20 0.230 0.7 0.3 0.6 0.4 0.18 0.683 4.3 1.1 3.2 1.4 0.65 0.438 Mass 0.0039 0.0020 0.0012 0.0009 1.41 0.263 0.0011 0.0009 0.0002 0.0001 0.33 0.579 0.0039 0.0014 0.0011 0.0008 1.78 0.212 Ephemeroptera Density 4.2 1.1 3.5 2.1 5.36 0.043 1.3 0.3 0.7 0.5 1.91 0.197 4.0 0.6 4.2 1.8 1.60 0.235 Mass 0.0043 0.0016 0.0166 0.0155 3.07 0.110 0.0016 0.0010 0.0006 0.0004 2.44 0.150 0.0046 0.0015 0.0190 0.0147 0.58 0.464 Baetidae Density 1.8 1.1 2.2 1.1 0.19 0.670 0.5 0.3 0.2 0.2 3.06 0.111 1.6 0.8 2.4 1.0 0.25 0.630 Mass 0.0012 0.0009 0.0017 0.0007 0.22 0.649 0.0005 0.0004 0.0002 0.0007 2.78 0.127 0.0009 0.0006 0.0019 0.0007 0.17 0.689 Caenidae Density 2.7 0.6 0.7 0.7 5.08 0.048 1.0 0.3 0.6 0.6 0.92 0.360 2.9 0.4 0.9 0.9 6.50 0.029 Mass 0.0019 0.0010 0.0003 0.0003 4.26 0.066 0.0012 0.0007 0.0005 0.0005 0.94 0.355 0.0024 0.0009 0.0007 0.0007 3.77 0.081

141

Emergent Open water Total Order Mitigation Reference Mitigation Reference Mitigation Reference

Family x SE x SE F1,10 P x SE x SE F1,10 P x SE x SE F1,10 P Gastropoda Density 7.6 2.5 3.5 2.3 2.61 0.138 0.9 0.3 1.1 0.7 3.99 0.074 6.6 2.2 3.7 2.4 3.67 0.084 Mass 0.4012 0.2560 0.0196 0.0142 3.84 0.079 0.0309 0.0210 0.0128 0.0116 7.25 0.023 0.3232 0.2164 0.0211 0.0163 7.20 0.023 Physidae Density 3.1 1.3 1.3 1.3 7.82 0.019 0.3 0.2 0.4 0.4 5.61 0.039 2.7 1.1 1.3 1.3 7.53 0.021 Mass 0.0579 0.0280 0.0080 0.0080 7.94 0.018 0.0040 0.0034 0.0032 0.0030 5.89 0.037 0.0494 0.0244 0.0077 0.0077 8.56 0.015 Planorbidae Density 4.7 1.7 1.8 0.8 4.48 0.061 0.8 0.2 0.3 0.3 5.08 0.048 3.4 1.0 1.4 0.8 5.20 0.046 Mass 0.5388 0.4360 0.0036 0.0020 4.18 0.068 0.0417 0.0310 0.0009 0.0009 6.92 0.025 0.3097 0.2381 0.0038 0.0024 6.32 0.031 Viviparidae Density 3.5 1.6 3.5 2.4 0.40 0.540 0.1 0.1 0.8 0.5 1.01 0.339 3.5 1.6 3.5 2.6 0.72 0.416 Mass 0.0145 0.0090 0.0247 0.0170 0.17 0.689 0.0005 0.0003 0.0019 0.0012 0.79 0.394 0.0147 0.0085 0.0237 0.0164 0.35 0.567 Hemiptera Density 7.2 3.0 3.5 1.6 6.56 0.028 0.8 0.3 1.1 0.6 1.57 0.239 6.1 2.3 4.3 1.4 0.52 0.486 Mass 0.0380 0.0343 0.0004 0.0001 8.05 0.018 0.0011 0.0006 0.0008 0.0006 2.53 0.143 0.0300 0.0256 0.0012 0.0005 3.37 0.096 Corixidae Density 4.3 3.6 0.0 0.0 2.23 0.167 0.2 0.1 0.3 0.3 4.08 0.071 3.3 2.6 0.3 0.3 5.18 0.046 Mass 0.0480 0.0430 0.0000 0.0000 2.10 0.178 0.0001 0.0001 0.0006 0.0006 4.65 0.056 0.0349 0.0302 0.0006 0.0006 5.22 0.045 Veliidae Density 2.2 0.7 1.0 0.6 5.02 0.049 0.4 0.3 0.6 0.6 0.17 0.686 2.2 0.8 1.3 0.8 4.09 0.071 Mass 0.0002 0.0001 0.0001 0.0001 4.87 0.052 0.0001 0.0001 0.0002 0.0002 0.18 0.683 0.0003 0.0001 0.0002 0.0002 3.77 0.081 Isopoda Density 1.1 0.6 6.6 2.3 7.59 0.020 0.0 0.0 0.2 0.2 1.91 0.197 1.1 0.6 6.6 2.3 8.58 0.015 Mass 0.0012 0.0008 0.0144 0.0074 6.84 0.026 0.0000 0.0000 0.0001 0.0001 1.91 0.197 0.0012 0.0008 0.0144 0.0074 6.99 0.025 Asellidae Density 1.1 0.6 6.6 2.3 8.58 0.015 0.0 0.0 0.2 0.2 1.91 0.197 1.1 0.6 6.6 2.3 8.58 0.015 Mass 0.0012 0.0008 0.0144 0.0070 6.84 0.026 0.0000 0.0000 0.0001 0.0001 1.91 0.197 0.0012 0.0009 0.0144 0.0074 6.99 0.025 Odonata Density 3.9 0.6 2.1 0.8 5.56 0.040 0.7 0.2 0.4 0.4 1.05 0.331 3.1 0.5 2.0 0.7 2.63 0.136 Mass 0.0087 0.0023 0.0131 0.0101 5.27 0.045 0.0010 0.0004 0.0003 0.0003 1.76 0.214 0.0078 0.0022 0.0128 0.0102 5.65 0.039 Coenagrionidae Density 2.6 0.6 1.7 0.7 2.14 0.175 0.6 0.3 0.3 0.3 2.18 0.170 2.3 0.5 1.6 0.7 3.39 0.095 Mass 0.0029 0.0010 0.0018 0.0010 2.43 0.150 0.0009 0.0005 0.0001 0.0001 2.49 0.146 0.0030 0.0009 0.0018 0.0010 5.52 0.041 Pelecypoda Density 2.5 1.0 6.1 3.4 0.32 0.581 0.3 0.1 0.3 0.3 1.82 0.207 2.3 0.8 5.8 3.4 0.18 0.684 Mass 0.0224 0.0110 0.0750 0.0534 0.17 0.691 0.0041 0.0030 0.0011 0.0011 1.72 0.219 0.0195 0.0094 0.0702 0.0526 0.05 0.825 Sphaeriidae Density 2.3 1.0 6.1 3.4 0.61 0.452 0.3 0.1 0.3 0.3 1.82 0.207 2.1 0.8 6.0 3.3 0.52 0.486 Mass 0.0223 0.0110 0.0750 0.0530 0.31 0.588 0.0041 0.0030 0.0011 0.0011 1.74 0.217 0.0194 0.0094 0.0738 0.0523 0.13 0.728 a Bold numbering indicates a significant difference (P < 0.05).

Table 2. Continued.

142

Table 3. Benthic and nektonic invertebrate familial richness (no. families/wetland), diversity, density (benthic: no./m2;

nektonic: no./L) and biomass (benthic g/m2; nektonic: g/L) between emergent and open water areas of mitigation wetlands

(n = 11) in West Virginia, 2001-2002 with comparisons of all taxa and for the 9 most common (abundant) benthic and 13

most common nektonic taxa (i.e., >100 individuals).

Benthica Nektonica Emergent Open water Emergent Open water x SE x SE F1,10 P x SE x SE F1,10 P Total invertebrates Richness 2.1a 0.2 1.5b 0.1 22.89 0.001 2.5a 0.1 1.9b 0.3 8.01 0.018 Diversity 1.60a 0.19 1.12b 0.34 20.02 0.001 2.46a 0.36 1.95b 0.59 11.91 0.006 Density 54.7a 18.4 37.1a 11.5 1.51 0.247 14.8a 3.1 2.4b 1.1 72.70 < 0.0001 Mass 2.190a 1.484 0.645a 0.343 0.78 0.399 0.2586a 0.1816 0.0226b 0.0185 30.41 0.0003 Common taxa Density 66.6a 18.6 52.9a 11.6 0.89 0.368 16.5a 4.0 3.1b 1.1 37.64 0.0001 Mass 2.603a 1.652 0.857a 0.403 0.18 0.678 0.3365a 0.2248 0.0318b 0.0216 14.66 0.003 a The same letter following means indicates no difference between wetland types (P > 0.05).

143

Table 4. Benthic and nektonic invertebrate familial richness (no. families/wetland), diversity,

density (no./L), and biomass (g/L) among emergent, open water, and scrub-shrub areas of the

Elder Swamp reference wetland (n = 1), West Virginia, 2001-2002 with density and mass

comparisons of all taxa and for the 9 most common (abundant) benthic taxa and 13 most

common nektonic taxa (i.e., >100 individuals).

Total invertebrates Common taxa Diversity Richness Density Mass Density Mass Benthic x SE x SE x SE x SE x SE x SE Emergent 0.0a 0.0 1.3a 0.3 1.6a 0.3 0.0015a 0.0010 6.4a 3.7 0.0035a 0.0031Open water 0.49a 0.10 0.8a 0.3 3.5a 1.7 0.0025a 0.0022 12.5a 4.5 0.0092a 0.0071Scrub-shrub 0.48a 0.11 1.3a 0.3 9.6a 4.5 0.0039a 0.0027 20.7a 8.0 0.0086a 0.0061F 0.08 0.78 0.15 1.11 0.45 P 0.792 0.499 0.865 0.386 0.655 Nektonic Emergent 0.93 0.22 1.7a 0.4 5.1a 1.7 0.0063a 0.0045 6.2a 0.7 0.0026a 0.0013Open water 0.35 0.0 1.0a 0.0 0.2b 0.04 0.0001a 0.0001 1.1b 0.4 0.0003a 0.0002Scrub-shrub 1.14 0.09 1.4a 0.3 1.9ab 0.6 0.0021a 0.0015 4.9ac 1.3 0.0079a 0.0071F 2.85 1.64 5.31 2.94 12.56 1.66 P 0.116 0.253 0.034 0.111 0.005 0.258 a The same letter following means indicates no difference between wetland types (P >

0.05).

144

CHAPTER IV

WILDLIFE HABITAT USE IN MITIGATION AND NATURAL

WETLANDS OF WEST VIRGINIA




145

ABSTRACT

Most studies evaluating mitigation success have focused on hydrology, soils,

and vegetation with the premise that these functions dictate wildlife distribution and

abundance. While some monitoring of mitigation wetlands has occurred in West

Virginia, no comprehensive survey of wildlife usage has been conducted. I evaluated

avian and anuran communities, as well as habitat suitability for 8 wetland-dependent

wildlife species, in 11 mitigation and 4 natural wetlands throughout West Virginia.

All avian measurements are expressed as means per 50 m radius plot (0.78 ha).

Avian species richness (P = 0.711), diversity (P = 0.314), and abundance (P = 0.856)

were similar between mitigation (richness: x = 8.79, SE = 0.31; diversity: x = 2.41,

SE = 0.41; abundance: x = 21.1, SE = 1.7) and natural (richness: x = 8.77, SE = 0.48;

diversity: x = 2.15, SE = 0.37; abundance: x = 22.2, SE = 3.9) wetlands. Mean

abundance for the 20 most common avian species sampled was similar (P = 0.963)

between mitigation ( x = 10.4, SE = 1.2) and natural wetlands ( x = 10.4, SE = 1.6).

Out of these common species, wood duck (Aix sponsa; P = 0.037) and American

goldfinch (Carduelis tristis; P = 0.013) were higher in mitigation (wood duck: x =

0.87, SE = 0.36; American goldfinch: x = 0.54, SE = 0.11) than natural (wood duck:

x = 0.0, SE = 0.0; American goldfinch: x = 0.34, SE = 0.15) wetlands, whereas song

sparrow (Melospiza melodia; P = 0.035) was higher in natural ( x = 2.43, SE = 0.22)

than mitigation ( x = 1.25, SE = 0.11) wetlands. Waterbird (P = 0.013) and

waterfowl (P = 0.013) abundance were higher in mitigation (waterbird: x = 3.97, SE

= 1.1; waterfowl: x = 3.46, SE = 1.1) than natural (waterbird: x =0.34, SE = 0.18;

This chapter was written in the style of The Journal of Wildlife Management.

146

waterfowl: x = 0.19, SE = 0.16) wetlands. Playback surveys for inconspicuous

waterbirds yielded 2 rail species at 2 mitigation wetlands. Anuran species richness (P

= 0.023), Wisconsin index (WI) value (P < 0.001), and abundance (P < 0.001) were

higher in mitigation (richness: x = 2.01, SE = 0.09; WI: x = 0.52, SE = 0.03;

abundance: x = 4.75, SE = 0.66) than natural (richness: x = 1.47, SE = 0.14; WI: x =

0.40, SE = 0.17; abundance: x = 4.69, SE = 1.18) wetlands. For individual species

observed, American bullfrog (Rana catesbeiana; WI: P = 0.033; A: P = 0.038), green

frog (R. clamitans; WI: P = 0.012; A: P = 0.018), and pickerel frog (R. palustris; WI:

P = 0.003; A: P = 0.005) were higher in mitigation wetlands, whereas spring peeper

(Pseudacris crucifer), gray treefrog (Hyla chrysoscelis), wood frog (R. sylvatica), and

American toad (Bufo americanus) were similar between wetland types (P > 0.05).

Habitat Suitability Index (HSI) scores for all 8 species combined were similar (F =

0.57, P = 0.489) between mitigation and natural wetlands. Red-winged blackbird

(Agelaius phoeniceus; P = 0.001) and beaver (Castor canadensis; P = 0.037) HSI

values were higher in natural (blackbird: x = 0.15, SE = 0.05; beaver: x = 1.0, SE =

0.0) than mitigation (blackbird: x = 0.03, SE = 0.01; beaver: x = 0.74, SE = 0.06)

wetlands, whereas muskrat (Ondatra zibethicus), great blue heron (Ardea herodias),

wood duck (Aix sponsa), mink (Mustela vison), snapping turtle (Chelydra

serpentina), and red-spotted newt (Notophthalmus viridescens) were similar between

wetland types (P > 0.05). Differences in vegetation and invertebrate community

composition and structure likely contribute to differences in wildlife populations

between wetland types.

JOURNAL OF WILDLIFE MANAGEMENT 00(0):000-000

147

Key Words: mitigation, mitigation wetland, habitat use, birds, frogs, habitat

suitability index, wetland-dependent species, mitigation success

Wetlands are important ecosystems that provide valuable habitat for wildlife.

The destruction of wetlands across the U.S., however, has undermined the survival of

some fish, shellfish, furbearing mammals, waterfowl, and amphibians that rely

exclusively on these areas for survival (Mitsch and Gosselink 2000). The Clean

Water Act of 1972 was the first major legislation that protected our nation�s wetland

resource base, but it was not until the �no net loss� policy of the late 1980s that the

government actively sought to mitigate for these losses that have devastated the status

of wetland-dependent wildlife across the country.

Under the new policy, thousands of hectares of wetlands have been

constructed to compensate for wetland destruction, but little monitoring has been

conducted on the success of these newly created wetlands, particularly in West

Virginia (National Research Council 2001). Most studies that have addressed

mitigation success have focused on wetland function with respect to hydrology, soils,

and vegetation (Cummings 1999, Moore et al. 1999, Zedler and Callaway 1999, Stolt

et al. 2000, Campbell et al. 2002). These parameters are excellent indicators of

wetland function, but they yield limited insight into a wetland�s direct ability to

support wildlife populations. Indeed, it is assumed that adequate vegetation,

hydrology, and location will precipitate wildlife colonization of newly created

wetlands (Erwin 1990, Hammer 1992). But information regarding the ability of

mitigation wetlands to replace lost wildlife habitat is lacking (National Research

Council 2001). Of particular concern is the replacement of waterbird and anuran

148

habitat in the face of continued declines as a result of wetland destruction (Dahl 1990,

Bortner et al. 1991, Semlitch 2002). For reasons listed below, these taxa are

extremely important in the functioning of wetland ecosystems. Information

pertaining to the ability of compensatory wetlands to support specific wetland-

dependent wildlife species including some furbearers (i.e., beaver, muskrat, mink)

also is lacking. By creating a repeatable and credible methodology that can be used

to quantify wetland-dependent wildlife habitat, comparisons of wildlife habitat can be

made between created and natural wetlands that allow an assessment of wildlife

habitat replaced through compensatory mitigation. This knowledge, in turn, could

contribute to wetland design and monitoring techniques that address wildlife needs.

Numerous bird species require wetlands as their primary habitat. Eighty

percent of breeding birds in North America, and more than 50% of the 800 protected

migratory birds rely on wetlands (Wharton et al. 1982). Perhaps due to an increased

habitat diversity provided by the water surface (Ferguson et al. 1975, Weller 1999),

wetlands support higher avian species diversity (MacArthur 1964, Mensing et al.

1998) and densities (Udevitz and Michael 1982, Mensing et al. 1998) than their

upland counterparts. Wetland birds are good indicators of function because, as a

group, they exhibit a wide range of habitat requirements, and have adapted to the

variety of vegetative cover types and water regimes wetlands provide (Anderson et al.

1996, Davis and Smith 1998, Melvin and Webb 1998, Anderson and Smith 1999,

Weller 1999, Naugle et al. 2000). Wetland birds have unique diets as well. Many are

herbivorous or omnivorous and eat a variety of foods including seeds, fruit,

invertebrates, amphibians, and small mammals (Gonzalez et al. 1996, De Szalay and

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Resh 1997, Davis and Smith 1998, Anderson and Smith 1999, Weller 1999, Anderson

et al. 2000).

Like avian species, anurans are relatively easy to sample and possess unique

habitat requirements. Because wetlands provide hibernation, foraging, breeding, and

interspersion habitat for different life stages, anurans rely exclusively on wetlands for

all or part of their life-cycle (Michael and Smith 1985, Dodd and Cade 1998,

Lehtinen et al. 1999, Semlitsch 2002). Hence, anuran populations can provide insight

into water quality and temporal variations in hydrology (Beattie and Tyler-Jones

1992, Anderson et al. 1999a, Semlitsch 2002). They feed on numerous invertebrate

species (Anderson et al. 1999b, Lima and Magnusson 2000), and are an important

food source for invertebrates and vertebrates alike (Bridges 1999, Lardner 2000).

This makes them a valuable link between invertebrate populations and higher

vertebrates in a complex food web (Weller 1999). In addition, physiological

attributes such as their permeable skin and ectothermic metabolism make them

particularly vulnerable to habitat alterations, and thus excellent indicators of

environmental health (Hall 1980, Heyer et al. 1994, Semlitsch 2002). Indeed, these

taxa are of particular importance when assessing wetland health because they are

intricately involved in complex wetland functions. They are relatively easy to

sample, are conspicuous by sight and sound, and simple to recognize in the field.

Hence, these species supply consistent and reliable data sets that are compatible with

field research.

A direct evaluation of wildlife numbers is only one way to assess the success

of mitigation wetlands in supporting wildlife populations. Another way is to evaluate

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wildlife habitat. Numerous wildlife habitat models have been developed in recent

years that quantify habitat for either entire wildlife taxa or specific species. The

development of models is important because researchers must often assign relative

values to habitat to support objectives for mitigation. Some such models, to name a

few, include the Wetland Evaluation Technique (Adamus 1983, Adamus and

Stockwell 1983), Habitat Assessment Technique (Cable et al. 1989), and the Avian

Richness Evaluation Model (Adamus 1993). A species-specific model commonly

used today is the Habitat Suitability Index (HSI) model developed by the U.S. Fish

and Wildlife Service (1981). Based on natural history requirements for a particular

species, this model uses habitat parameters considered pertinent to a species survival

to calculate an index ranging from 0 to 1 (a 1 represents optimal habitat). Depending

on the HSI model, the habitat parameters evaluated may have significant implications

for other wildlife taxa as well, which can provide further insight into overall habitat

quality for wildlife for a given area.

There is a need to evaluate the success of mitigation wetlands in supporting

wildlife taxa that are considered good indicators of wetland health. This success can

be determined through surveys of wildlife populations and through the evaluation of

wildlife habitat (Adamus 1993, Wilson and Mitsch 1996, VanRees-Siewert and

Dinsmore 1996, Stevens et al. 2002). Natural wetlands are often used as standards of

comparison because these areas are considered relatively stable and undisturbed

(Brinson 1993, Brinson and Rheinardt 1996, Wilson and Mitsch 1996). The goal of

this study was to evaluate the success of mitigation wetlands in West Virginia in

supporting healthy wildlife communities. This functional attribute was determined by

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comparing avian and anuran populations between mitigation and natural wetlands,

and by evaluating habitat quality of 8 wetland-dependent wildlife species using HSI

models. As such, I tested the null hypotheses that anuran and avian richness,

diversity, and abundance were similar between mitigation and natural wetlands. The

equality of HSI scores also was tested, both for each individual species, and for all 8

species combined.

STUDY AREA

I evaluated 11 constructed and partially restored mitigation wetlands (Walnut

Bottom, VEPCO, Buffalo Coal, Elk Run, Leading Creek, Sugar Creek, Sand Run,

Triangle, Trus Joist MacMillan, Enoch Branch, and Bear Run) and 4 natural wetlands

(Altona Marsh, Elder Swamp, Meadowville, and Muddlety) in northern West

Virginia. I condensed these sites into 4 areas representing 3 geomorphic settings

within the state. These settings are indicated by 3 physiographic regions described by

Fenneman (1938): Western Hills, Appalachian Plateau, and Ridge and Valley, but for

statistical purposes, all mitigation wetlands were compared to all natural wetlands. I

chose 4 natural wetlands based on limited disturbance and their similarity in location,

elevation, vegetative structure, and hydrology to mitigation sites. Because the natural

wetlands were considerably larger than mitigation sites, I only used areas within

natural wetlands that were compatible in size to mitigation sites.

Mitigation study sites were created as compensation for human activities

including facility construction, road construction, or mining. Almost every wetland

was located near some form of human disturbance, with some lying adjacent to roads

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with moderate to heavy traffic (Chapter I). Many are extensively used for

recreational use, adding to the level of disturbance. Mitigation sites ranged from 5-21

years old ( x = 10.0, SE = 1.7). All mitigation sites were ≥5 years old and ranged in

size from 3.0-9.5 ha ( x = 5.8, SE = 0.8). Elevation ranged from 265-1,036 m ( x =

586, SE = 75.9). All mitigation wetlands were classified as palustrine emergent or

palustrine unconsolidated bottom wetlands (Cowardin et al. 1979).

Natural wetlands chosen for study were located near mitigation sites within

each area, usually within the same watershed. All had established stable emergent,

scrub-shrub, and forested wetland communities. The portions of each wetland that

were evaluated ranged from 6.5 to 28.0 ha ( x = 15.1, SE = 4.7) in size and ranged

from 170-1,000 m ( x = 582, SE = 169.5) in elevation. All natural wetlands were

classified as palustrine emergent or palustrine scrub-shrub wetlands (Cowardin et al.

1979). Detailed study site descriptions are provided in Chapter I.

METHODS

Avian Communities

I evaluated avian communities by sampling breeding bird populations using

point count surveys (Ralph et al. 1995). I visited wetlands twice between 5 May and

27 June, 2001-2002, when breeding birds were most active. I conducted 10-min point

counts that occurred between 30 min before sunrise and 1000 hours, under acceptable

weather conditions (Ralph et al. 1995). I established a minimum of 1 ( x = 2.4, SE =

0.31) 0.78 ha point count station (50 m radius) at each wetland, which was spaced ≥

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250 m for independent bird surveys (Ralph et al. 1993). At each wetland, I

determined a sufficient number of sampling stations to cover the entire wetland area.

I conducted playback surveys for some waterbirds that are generally missed

with traditional bird count methodologies. Immediately following point counts, I

conducted call-response surveys for Virginia rail (Rallus limicola), king rail (R.

elegans), and sora (Porzana carolina) at the same stations used for point counts to

determine rail presence/absence and relative abundance. Surveys also were

conducted for American bittern (Botaurus lentiginosus), least bittern (Ixobrychus

exilis), and pied-billed grebe (Podilymbus podiceps). I conducted surveys according

to protocol outlined by Gibbs and Melvin (1993). I played species-specific calls

using a portable cassette player located 0.75 m above ground or water for 50 sec per

call, followed by 10 sec of silence. Calls were played with a maximum sound

pressure of 80 dB 1 m from the recorder. I played each species� call in a random

order 1 time/station. I used the American Ornithologists Union (2002) checklist for

common and scientific names of birds.

Anuran Communities

I evaluated anuran communities using nocturnal call count surveys. Surveys

followed standardized protocols developed by the U.S. Fish and Wildlife Service

(Casey and Record, unpublished report) to evaluate species presence or absence and

relative abundance. I visited wetlands 5-24 April, 7-30 May, and 5-18 June, 2001-

2002 to account for temporal breeding differences among species. These dates were

selected based on recommended temperature ranges for different survey periods (i.e.,

period 1: >5°C; period 2: >10°C; period 3: >12.8°C; Casey and Record, unpublished

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report). I collected data for 3 min at each sampling point following a 1-2 min settling

period. I identified frogs to species and evaluated relative abundances by assigning a

Wisconsin Index value of intensity to each species� call (Mossman 1994). I assigned

a ranking of 1 to species with nonoverlapping calls and when an exact count of

individuals could be made, a ranking of 2 to species whose calls overlapped and only

estimations of numbers could be made, and a 3 to species that were calling in full

chorus. If a WI value of 3 was assigned to a species, I used a mandatory abundance

estimate of 50. I conducted surveys between 30 min after sunset and midnight. I

used The Society for the Study of Amphibians and Reptiles (2000) for common and

scientific names of frogs.

Habitat Quality

I chose HSI models that had broad taxonomic coverage and included 1 reptile

(snapping turtle, Graves and Anderson 1987), 1 amphibian (red-spotted newt, Sousa

1985), 3 mammals (beaver, Allen 1983; muskrat, Allen and Hoffman 1984; mink,

Allen 1984), and 3 bird species: 1 wading bird (great blue heron, Short and Cooper

1985), 1 waterfowl species (wood duck, Sousa and Farmer 1983), and 1 passerine

(red-winged blackbird, Short 1985). All species had wide distributions throughout

West Virginia, and possessed life-history components (i.e., foraging, reproduction,

and interspersion) that were compatible with habitat features present in the wetlands

selected for this study.

I measured a combined total of 38 habitat variables for all 8 HSI models

during summer, 2001 (Table 1). I obtained estimates of percent coverage (i.e., tree

canopy, shrub cover, emergent and submergent vegetation, broad-leafed monocots,

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percent wood duck brood and winter cover) for all HSI models using the line-

intercept method (Hays et al. 1981) and aerial photography. Percent trees with a

diameter at breast height (DBH) between 2.5 and 15.2 cm, average height of shrub

canopy, and species composition of woody vegetation ≤ 200 m of the water�s edge

were evaluated for the beaver model accordingly. From the edge of the wetland

basin, I randomly placed 200 m long transects that extended out of the wetland and

into the nearest forested cover type, if one existed. For statistical purposes, a

minimum of 30 DBH samples and shrub height samples were collected. I measured

these variables according to protocols by Robel et al. (1993). Beginning 10 m from

the edge of the wetland basin and at each 20 m point on the transect thereafter, I

measured DBH of the nearest tree to the nearest 0.1 cm. This was done along the

entire length of the 200 m line or to the end of the woody cover, whichever came

first. A minimum of 3 transect lines were established to fulfill the need for 30 tree

DBH samples. The proportion of these measurements in the 2.5 to 15.2 cm DBH size

class was calculated. At the same 20 m increment points, height and species of the

nearest shrub also was measured.

For the snapping turtle model, I measured mean water temperature at mid-

depth to the nearest 0.1ºC in August using a thermometer. Temperature was taken

every 5.0 m along the transect lines established for line-intercept measurements. I

obtained percent silt in the substrate using a 5.0 cm core sampler (15 cm deep) at 10

random points each within emergent and open water subtypes. Substrate samples

were oven dried to a constant mass at 55 ºC for ≥48 hr and sieved through a 63-

micron sieve (Graves and Anderson 1987). The mass of the silt (g) passing through

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the sieve was divided by the total mass of the collected sample. I measured mean

current velocity (cm/sec) at mid-depth by calculating the speed of a neutrally buoyant

object at mid-stream (Graves and Anderson 1987). Specifically, the time it takes for

a 3.8 cm diameter bobber to move between 2 fixed points, 3 m apart was measured

(Hays et al. 1981) at 5 random locations within each wetland subtype. A maximum

of 1 min was allowed for the bobber to move between the 2 points (Graves and

Anderson 1987). Velocity was calculated as distance divided by time.

For the red-winged black bird model, I determined carp (Cyprinus carpio)

presence using visual encounter surveys. I determined presence of dragonflies

(Odonata) using data collected during macroinvertebrate sampling (Chapter III).

All distance estimates (i.e., to forested cover type, small streams, permanent

water, between potential great blue heron nest sites (grove of trees ≥ 5 m tall; ≥ 0.4

ha in size) and foraging areas, between potential great blue heron nest sites and actual

and/or previous great blue heron nest sites) were made using a tape measure, aerial

photography, or by using data obtained by the West Virginia Division of Natural

Resources (Hays et al. 1981). I assessed disturbance-free zones (i.e., 100, 150, and

250 m) for the great blue heron model using aerial photos. Likewise, I used visual

observations to evaluate the presence of adequate great blue heron foraging areas

(i.e., clear water with a suitable prey population of small fish ≤25 cm and a firm

substrate). A 0.5 was assigned to this variable if fish were not present. For the

beaver, muskrat, mink, snapping turtle, and red-winged blackbird HSI models, I used

visual observations to evaluate fluctuations in water regime for each wetland.

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For the wood duck HSI model, I measured the number of potentially suitable

nesting tree cavities/0.4 ha (minimum entry openings of 7.6 × 10.0 cm) using 6

randomly placed 0.05 ha quadrats within the nearest forest ≤500 m of the edge of the

wetland basin. A total count of the number of artificial nest boxes (predator proofed

and maintained) was conducted at each wetland. The total area of the wetland was

used to extrapolate the number of artificial nests/0.4 ha, as necessary by the wood

duck HSI model. For all species evaluated, a minimum SI value of 0.75 was used to

conclude adequate habitat suitability for specific species, and values less than 0.25

were indicative of poor habitat quality. Optimal SI values for all variables measured

are included in Table 1.

Statistical Analyses

Mitigation and natural wetlands were compared using SAS (1988). For all

avian analyses, I included only those birds sampled within the 50 m radius (0.78 ha)

plots. I used a split-plot analysis of variance design (ANOVA) to test for differences

in avian richness (no. species/0.78 ha plot), abundance (no. birds/0.78 ha plot), and

diversity (per 0.78 ha plot) between mitigation and natural wetlands. Avian diversity

was calculated using the Shannon-Weiner Index (Shannon and Weaver 1949). Avian

species included in the waterbird analysis were Canada goose, mallard (Anas

platyrhynchos), wood duck, black duck (A. rubripes), green heron (Butorides

virescens), great blue heron, belted kingfisher (Ceryle alcyon) spotted sandpiper

(Actitis macularia), Virginia rail, and sora. Canada goose, mallard, wood duck, and

black duck were included in the waterfowl analysis.

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I used a 2-way ANOVA with a repeated measures design to compare anuran

richness because 3 survey periods were repeated both years. For avian and anuran

analyses, the independent variables tested were year, type (mitigation vs. reference),

and year × type interactions with the dependent variables varying depending on

which taxa was being analyzed. I used individual wetlands as experimental units.

Because Wisconsin Index (WI) and anuran abundance metrics were categorical

variables, I used logistic regression to compare mitigation and natural wetlands.

Abundance estimates were obtained using SAS and grouped into intervals (i.e., 2-5,

6-15, 16-25, 26-35, and 50), which allowed them to be treated as categorical

variables. Only the mid-point of each interval was used for analyses. Logistic

regression also was needed because of unequal variances associated with WI and

abundance variables. I used an area × year × sampling period combination as a

blocking factor for logisic regression. For all other avian and anuran analyses,

geographic area was a blocking factor.

For HSI value comparisons, I used a 1-way ANOVA with geographic area as

a blocking factor to test the wetland type effect. Because HSI variables were

collected for only 1 year, no year effect was tested. Assumptions of normality were

tested with the univariate procedure in SAS, and Levene�s Test was used for

homogeneity of variances. Rank, square-root, and quarter-root transformations were

used to convert dependent variables that did not meet the aforementioned

assumptions (Dowdy and Wearden 1991). Specifically, square-root transformations

were incorporated in anuran WI comparisons, and rank transformations were used to

analyze avian communities.

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RESULTS

Avian Communities

I observed a total of 91 species of birds in mitigation and natural wetlands

(Appendix 37). In mitigation sites, 2,074 individuals from 86 species were sampled

(Appendix 38), and in natural sites, 771 individuals from 62 species were sampled

(Appendix 39). For all species sampled, mean species richness (F1,10 = 0.15, P =

0.711), diversity (F1,10 = 1.1, P = 0.314) , and abundance (F1,10 = 0.03, P = 0.856)

were similar between mitigation and natural wetlands (Table 2). Mean abundance for

the 20 most common avian species sampled was similar (F1,10 = 0.07, P = 0.800)

between mitigation and natural wetlands (Table 2). Out of these common species,

wood duck (F1,10 = 5.80, P = 0.037) and American goldfinch (F1,10 = 9.24, P = 0.013)

were more abundant in mitigation wetlands, whereas song sparrow (F1,10 = 5.94, P =

0.035) was more abundant in natural wetlands (Table 2). Great blue heron abundance

was similar (F1,10 = 0.28, P = 0.610) between wetland types. All other common

species also were similar (F1,10 ≤ 4.57, P ≥ 0.058) between wetland types. Passerine

abundance (72 species combined) was similar (F1,10 = 0.41, P = 0.537) between

mitigation and natural wetlands. However, waterbird (F1,10 = 9.08, P = 0.013) and

waterfowl (F1,10 = 9.23, P = 0.013) abundance were higher in mitigation wetlands

than natural wetlands.

Two rail species were sampled at 2 mitigation wetlands. Three sora were

sampled at Buffalo Coal during the first surveys of both years. Similarly, 3 sora were

sampled at Walnut Bottom during the first survey of year 2. Five and 2 Virginia rail

were sampled at Buffalo Coal during the second surveys of years 1 and 2,

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respectively. No rail species were sampled at natural wetlands, and no bittern or

pied-billed grebe were sampled at any wetland.

Anuran Communities

Seven species of anurans were heard, all of which occurred in both mitigation

(Appendix 40) and natural (Appendix 41) wetlands. These included spring peeper,

gray treefrog, American bullfrog, wood frog, green frog, American toad, and pickerel

frog. Mean species richness was higher in mitigation ( x = 2.01 species/point, SE =

0.09) than natural ( x = 1.47, SE = 0.14) wetlands (F1,10 = 7.18, P = 0.023). In

addition, Wisconsin Index (WI) values (Χ2 = 14.51, P < 0.001) and abundance (Χ2 =

11.35, P < 0.001) were higher in mitigation than natural wetlands (Table 3).

Wisconsin Index and abundance (A) comparisons also were made for each species

detected (Table 3). For these indices, American bullfrog (WI: Χ2 = 4.56, P = 0.033;

A: Χ2 = 4.30, P = 0.038), green frog (WI: Χ2 = 6.36, P = 0.012; A: Χ2 = 5.64, P =

0.018), and pickerel frog (WI: Χ2 = 8.73, P = 0.003; A: Χ2 = 8.08, P = 0.005) were

higher in mitigation than natural wetlands, whereas spring peeper (WI: Χ2 = 0.61, P =

0.434; A: Χ2 = 1.46, P = 0.228), gray treefrog (WI: Χ2 = 0.88, P = 0.348; A: Χ2 =

0.60, P = 0.440), wood frog (WI: Χ2 = 2.87, P = 0.090; A: Χ2 = 2.76, P = 0.097), and

American toad (WI: Χ2 = 3.66, P = 0.056; A: Χ2 = 3.58, P = 0.059) were similar

between wetland types (Table 3).

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Habitat Quality Habitat Suitability Index scores for all 8 species combined were similar (F =

0.57, P = 0.469) between mitigation and natural wetlands (Table 4). Red-winged

blackbird (F1,10 = 21.3, P = 0.001) and beaver (F1,10 = 5.77, P = 0.037) Suitability

Index (SI) values were higher in natural wetlands, whereas muskrat (F1,10 = 3.13, P =

0.107), mink (F1,10 = 1.58, P = 0.238), great blue heron (F1,10 = 0.56, P = 0.472),

wood duck (F1,10 = 0.76, P = 0.403), snapping turtle (F1,10 = 3.66, P = 0.085), and red-

spotted newt (F1,10 = 2.17, P = 0.172) SI values were similar between wetland types

(Table 4). Complete statistical results of all applicable HSI variables (i.e., actual

mean values) between mitigation and natural wetlands are provided in Appendix 42.

Comparisons of mean SI values per variable between wetland types are provided in

Appendix 43. Results for all variables measured for each HSI model by wetland

study site are included in Appendices 44-51.

Red-winged Blackbird.-- The red-winged blackbird model considered blackbird food and reproduction

requirements. According to the model, mitigation and natural wetlands contained

poor quality habitat. While mitigation wetlands contained optimal surface water

(variable 2) and food availability (variable 3), percent emergent vegetation (variable

5) was moderate (Table 3). Three variables limited mitigation wetland performance

in this model. These included percent emergent vegetation (variable 5), percent

broad-leaved monocots (variable 1), and presence of carp (variable 3).

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Beaver.--

The beaver HSI model considered the availability of water and winter food.

Although mitigation wetlands scored a lower beaver SI score than natural wetlands,

they still contained suitable beaver habitat. The amount of tree (variable 1) and shrub

(variable 4) cover within 100 m and 200 m of mitigation sites was within adequate

range of beaver requirements (Table 1). Likewise, the species composition of woody

vegetation (variable 5) within mitigation sites consisted primarily of brookside alder

(Alnus serrulata) and speckled alder (A. incana), which increased the SI value of this

variable. Two variables, however, limited mitigation wetland performance in the

beaver HSI model. These included the percentage of trees with a DBH between 2.5

and 15.2 cm (variable 2) and the percentage of shrub crown cover (variable 3).

Muskrat.--

The muskrat HSI model was divided into 2 components: food and cover.

While mitigation wetlands contained adequate water surface (variable 2) and

emergent vegetation (variable 1) to satisfy muskrat cover requirements, they lacked

the composition of vegetation (variable 3) most desirable as food to muskrat (Table

3).

Mink.--

Similar to the muskrat HSI model, the mink model assessed the suitability of

wetlands to sustain adequate mink food and cover. Both wetland types contained

suitable mink habitat. Specifically, they contained adequate surface water (variable

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1), persistent emergent vegetation (variable 2), and percent tree/shrub cover within

100 m of the water�s edge (variable 3; Table 1).

Great Blue Heron.--

The great blue heron HSI model consisted of 2 major components: food and

reproduction. According to the model, mitigation wetlands contained adequate heron

foraging habitat. Both wetland types contained potential nesting sites within a

reasonable distance of foraging locations (variable 1), and both possessed

environmental conditions suitable to support prey populations (variable 2) while

allowing disturbance-free foraging (variable 3; Table 1). Mitigation sites scored low

reproduction SI values. While all sites contained forests ≥0.4 ha within 250 m of the

wetland edge (variable 4), and while most nesting sites met disturbance-free criteria

(variable 5), the distance between potential nesting sites and actual or previous

nesting sites (variable 6) exceeded optimal criteria for all study sites. I found that the

closest heronries on record to most sites were located in Doddridge, Calhoun, and

Randolph Counties, which were ≥32.0 km from these study sites (West Virginia

Division of Natural Resources, unpublished report).

Wood Duck.--

The wood duck HSI model was subdivided into breeding and wintering

models. According to the wood duck model, mitigation wetlands contained suitable

year-round wood duck habitat. This was attributable to the suitability of mitigation

wetlands in supporting adequate breeding and wintering habitat. While mitigation

sites appeared to support moderate wood duck breeding habitat based on the breeding

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model SI value, this was attributable to low SI values for only a few wetlands. The

main factor limiting the breeding habitat quality was the density of potential nesting

sites, both natural and artificial (variable 3; Table 1). While all but 1 mitigation site

(Walnut Bottom) contained at least some potential natural cavities either within or

around the wetlands, only 5 of 11 mitigation sites (VEPCO, Buffalo Coal, Triangle,

Sugar Creek, and Sand Run) contained artificial nest boxes. Despite relatively low

nest site densities, the percentage of potential brood cover (variable 4) in mitigation

sites was high. In turn, these factors led to variable SI values for the percentage of

wetland areas containing optimal nesting (variable 5) and brood rearing (variable 6)

habitat. Because of the limiting factor approach to model output calculation, mean

breeding SI values were low. Like the breeding model, the winter model scored

variable SI values across mitigation wetlands. Because final model SI values were

determined based on the higher values between breeding and wintering models,

overall wood duck SI values were relatively high in mitigation wetlands.

Red-spotted Newt.--

The red-spotted newt HSI model considered the suitability of habitat for cover

and reproduction. According to the model, suitable red-spotted newt habitat existed

within mitigation wetlands. Similar to natural wetlands, mitigation wetlands were

always <2 m in depth (variable 1), contained an adequate percentage of aquatic

vegetative cover (variable 2), including submerged aquatic vegetation, and were

located within a reasonable distance of forested cover types (variable 3; Table 1).

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Snapping Turtle.--

The snapping turtle HSI model was divided into 4 components for evaluation:

food, winter cover, reproduction, and interspersion. Snapping turtles scored a low

overall SI value in both mitigation and natural wetlands. Because snapping turtles are

opportunistic feeders, the model considered water temperature (variable 1), water

velocity (variable 2), and percent aquatic vegetation (variable 3) as important factors

associated with turtle feeding. Mean water temperature and velocity were within the

optimal range of snapping turtle preferences in mitigation wetlands, while percent

aquatic vegetation scored an above average rating (Table 1). Similarly, both wetland

types were situated near small streams (variable 6), thus increasing the reproductive

SI value, and all wetlands contained permanent water in at least some portion of the

complex (variable 7). This increased the interspersion SI value. The main limiting

factor in this model occurred within the winter cover component. While mitigation

and natural sites were deep enough to prevent complete freezing (variable 4), both

wetland types contained relatively low percentages of silt in the substrate (variable 5).

DISCUSSION

Avian Communities

Almost every avian metric I measured in mitigation wetlands was equal to or

greater than natural wetlands. No differences emerged in total species richness,

diversity, and abundance probably because of similarities in landscape position. Both

wetland types were generally located near forested stands, so wetland, edge, and

forest-interior species had an equal chance of being sampled between wetland types.

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Similarly, both wetland types were either adjacent or connected to other wetlands,

streams or large rivers. Although some studies have found human disturbance to

negatively affect wildlife numbers (Wilson and Mitsch 1996), the proximity of

mitigation and natural sites to human disturbances (i.e., major roads) appeared to

have minimal effects on avian numbers. Although it is known that wetland size

affects avian richness (MacArthur and Wilson 1967, Tyser 1983, Delphey and

Dinsmore 1993), the fact that natural wetlands were about 3 times larger than

mitigation wetlands had little effect on avian metrics relative to mitigation wetlands.

Mitigation wetlands, however, supported higher waterbird and waterfowl

abundance than natural wetlands. Because mitigation sites are so young (5-20 years

of age), they differed significantly in their vegetation community structure than

natural sites (Chapter II). Not only did mitigation sites contain more open water and

support less emergent aquatic vegetation than natural wetlands, they contained higher

plant species richness and diversity than natural wetlands. In fact, mitigation

wetlands contained 40.8% open water, whereas natural wetlands contained only

11.6% open water. This has been found to be true of most natural wetlands in the

Appalachian Region (Cole and Brooks 2000).

An evaluation of waterbird abundance within mitigation sites supports the

assertion that open water affects waterbird abundance. The lowest waterbird

abundances occurred in 2 mitigation wetlands with the lowest percentages of open

water (Chapter V). These sites also contained relatively low amounts of submerged

aquatic vegetation. VanRees-Siewert and Dinsmore (1996) showed that, although

total bird richness increased with increasing emergent vegetation, waterfowl and

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shorebirds preferred younger restored wetlands with more open water and mud flats.

Overall, mitigation wetlands in this study were closer to hemimarsh conditions where

an equal percentage of open water to emergent vegetation exists. Hemimarsh

conditions provide the best combination of food and cover for waterbirds (Kaminski

and Price 1981, Bookhout et al. 1989, Murkin et al. 1997). Based on these and other

studies, many have concluded that �wetter is better� in terms of constructing

wetlands. As a result, mitigation wetlands are often structurally dissimilar to the

natural wetlands they are designed to mimic, thus indicating an inability to

functionally replace those wetlands that were destroyed (Cole and Brooks 2000).

This stresses the importance of not having too much open water in mitigation

wetlands.

Waterbird abundance also may be affected by higher vegetative richness and

diversity indices observed in mitigation wetlands over natural wetlands (Chapter II).

These differences may result in an increase in the type, quantity, and quality of plant

foods while at the same time maximizing the distribution, density, and structure of

cover available for waterbirds in mitigation wetlands (De Szalay and Resh 1997,

Brown 1999). Differences in vegetation community structure may have created

favorable water chemistry and hydroperiod conditions in mitigation sites as well

(Goslee et al.1997, Castelli et al. 2000).

Similarly, I observed a higher overall nektonic macroinvertebrate biomass

within open water areas of mitigation wetlands (Chapter IV). Within both emergent

and open water areas, we observed more nektonic Planorbidae (orb snails) and

Physidae (physids), Corixidae (water boatman), Coenagrionidae (damselflies), and

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Caenidae (mayflies) in mitigation wetlands. Within open water areas, benthic

Oligochaetes (aquatic worms) also were higher in mitigation wetlands. This is

particularly important because studies have shown that these taxa are important

components in waterbird diets (Euliss et al. 1991, Anderson et al. 2000). These

differences in macroinvertebrate populations may account for differences in waterbird

abundance observed between mitigation and natural wetlands.

Other studies comparing waterbirds between mitigation and natural wetlands

have shown conflicting results. Similar to my study, Havens et al. (1995) observed

similar overall species diversity between mitigation and natural wetlands in Virginia,

but higher wading bird abundances occurred in constructed marshes. However,

Confer and Niering (1992) included waterbirds in their assessment of wildlife in

constructed and natural wetlands in Connecticut, and they observed higher wildlife

activity (overall species richness) in natural wetlands. They attributed low wildlife

indices in constructed wetlands to their isolation and relative small size. While other

studies also have shown higher avian richness and diversity in natural wetlands

(Delphey and Dinsmore, 1993, Melvin and Webb 1998), others have yielded similar

avian indices between wetland types (Perry et al. 1996, Brown and Smith 1998). It is

likely that, given the similarities in landscape position between wetland types, the

increased richness and diversity of vegetation offered in our mitigation sites was

balanced by the increased percentage of emergent vegetation in natural wetlands, thus

resulting in similar overall avian community structure between wetland types.

Great blue heron and wood duck were of particular interest because the

quality of habitat for these species was evaluated using HSI models. Although

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densities of great blue heron were higher in mitigation sites, no statistical difference

emerged. These similarities are reflected by similarities in HSI values between

wetland types. Details explaining these similarities are outlined below in the habitat

quality section of this chapter. Similar to waterbirds, differences in percent emergent

vegetation and vegetation community structure probably account for higher wood

duck abundance observed in mitigation wetlands. In fact, no wood duck were

sampled in any natural wetlands. Further speculations regarding wood duck

abundance are explained below in the habitat quality section of this chapter.

Little is known about the abundance and distribution of rails, bitterns, and

pied-billed grebes in West Virginia. While other studies have found colonization by

rail and bittern species into constructed and restored wetlands (Delphey and

Dinsmore 1993, Dick 1993, Zedler 1993, Vanrees-Siewert and Dinsmore 1996, White

and Bayley 1999), use of mitigation wetlands in West Virginia was unknown prior to

this study. While all of these species may breed throughout the state (Buckelew and

Hall 1994), they have been confirmed as breeding only in Tucker and Jefferson

Counties (Buckelew and Hall 1994). Hence, my results were somewhat expected,

especially given the amount of seemingly suitable habitat present in mitigation

wetlands in those areas (Kaufman, 1996, Linz et al. 1997). Both Buffalo Coal

(Tucker County) and Walnut Bottom (Hardy County) contained an even mixture of

open water to shallow emergent areas dominated by broad-leaved cattail (Typha

latifolia) and common rush (Juncus effusus). I expected to encounter breeding rails,

bitterns, or grebes in at least 1 of the natural wetlands located in either Tucker (Elder

Swamp) or Jefferson (Altona Marsh) Counties, although Altona Marsh may have

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lacked sufficient open water to support pied-billed grebe. Elder Swamp was located

in Tucker County 12.0 km from Buffalo Coal. It is possible that this Sphagnum

dominated bog lacked the shallow emergent areas necessary for breeding and

protection to sustain these species. The other natural wetlands either contained too

many shrubs or emergent vegetation, or were too deep. Future monitoring of these

elusive species may confirm their breeding in these and other wetlands throughout the

state.

These data indicate that mitigation wetlands in West Virginia, despite their

proximity to human disturbances, are supporting healthy avian communities,

particularly waterbirds. High avian numbers in mitigation wetlands are likely due to

wetland size and landscape position, as well as vegetative structure and diversity and

invertebrate community structure. Future studies should correlate changes in

vegetation and invertebrate communities to avian community structure.

Anuran Communities

It is not surprising that anurans have colonized mitigation wetlands so rapidly.

In fact, spring peepers, American bullfrogs, American toads, and gray treefrogs may

colonize created wetlands ≤2 years after construction (Perry et al. 1996, Mierzwa

2000, Pechmann et al. 2001). Colonization rates are generally affected by distance to

other ponds, dispersal habitat, dispersal capabilities, site fidelity of a particular

species, and size of source populations (Laan and Verboom 1990). The proximity of

my study sites to streams, rivers, and other wetlands along with the relatively large

size of mitigation sites likely contributed to rapid dispersal and colonization

(Wolfenbarger 1949, Lacki et al. 1992, Gibbs 1993, Stevens et al. 2002).

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I expected to encounter Fowler�s toad (Bufo fowleri) and mountain chorus

frog (Pseudacris brachyphona) as these species are well distributed throughout the

state. Likewise, I expected to encounter upland chorus frog (Pseudacris triseriata

feriarum) within wetlands located along the eastern panhandle (Green and Pauley

1987). Because cricket frogs (Acris crepitans) also are known to breed along the

eastern panhandle, I expected to observe them within 1 natural (Altona Marsh) or 1

mitigation (Walnut Bottom) wetland located in this area. In fact, 1 cricket frog was

observed at Altona Marsh, but it was not detected during anuran surveys. It is

possible that spadefoot toads (Scaphiopus holbrookii) use at least some mitigation or

natural wetlands within the state, but their explosive short-term breeding cycle,

fossorial lifestyle, and overall scarcity in the state make this species difficult to detect

(Green and Pauley 1987).

Mitigation wetlands in West Virginia contained higher anuran mean richness,

Wisconsin Index, and abundance values than natural wetlands. Similar to my study,

Stevens et al. (2002) observed a higher overall mean richness as well as green frog

abundance in restored than natural wetlands. Although they observed a positive

correlation between green frog abundance and percentage of cattail in restored

wetlands, my results suggest cattail may have a relatively minimal effect on green

frog abundance. Because mitigation wetlands (13.6%) contained less cattail than

natural wetlands (42.8%), yet they sustained more green frog, I think open water may

play a larger role in determining abundance of green frog, as well as American

bullfrog and pickerel frog. Lacki et al. (1992) also observed more green frogs in a

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constructed wetland in Ohio, and Pechmann et al. (2001) observed more American

bullfrogs in constructed than natural wetlands in South Carolina.

Because American toads, spring peepers, and wood frogs are less dependent

on permanent water sources (Gilhen 1984, Cook 1984), I expected these species to be

relatively more abundant than other anuran species in natural wetlands. Consistent

with this speculation, relative abundance of these species were similar between

mitigation and natural wetlands.

Many important factors may account for anuran community differences

observed between mitigation and natural wetlands. Primarily, studies have shown

that open water is positively correlated with amphibian abundance (Lacki et al. 1992,

Stevens et al. 2002). As aforementioned, mitigation wetlands more closely resembled

hemimarsh conditions by containing more open water than natural wetlands. Like

avian communities, anuran communities benefit from these conditions (Stumpel and

Van Der Voet 1998). Although hydrologic data are incomplete for our study sites,

these data may indicate an extended hydroperiod in mitigation wetlands, which may

prevent drying and subsequent tadpole mortality prior to metamorphosis. Thus,

species with longer larval periods such as American bullfrog, green frog, and pickerel

frog may have been excluded from natural wetlands with shorter hydroperiods

(Babbit and Tanner 2000, Semlitsch 2002). This may not necessarily be a limiting

factor because pond drying is a natural process that eliminates or reduces predation

on and competition among larval amphibians (Semlitsch 2000). On the contrary,

maintaining wetlands with extremely long hydroperiods may be harmful to anuran

populations because it may facilitate colonization of aquatic invertebrate and fish

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predators (Semlitsch 2002). Water depth also plays an important role in amphibian

colonization (Stevens et al. 2002). Deeper water prevents complete freezing, which

provides winter hibernacula for anurans (Cook 1984, Cunjak 1986). I found that both

mitigation and natural wetlands contained areas with sufficient hibernacula, but based

on water depth estimations, mitigation wetlands contained deeper water with more

potential wintering habitat. Furthermore, shorter distance to forests and higher

percentage of shrub cover increases anuran richness by providing cover and dispersal

corridors for post-breeding or newly metamorphosed individuals (Stevens et al.

2002). This may be of particular importance to wood frogs, which disperse long

distances via forested cover types to other wetlands (Berven and Grudzien 1990,

DeMaynadier and Hunter 1999). As well, forested perimeters may buffer wetlands

from agricultural activities, which have been linked to larval death and limb

deformities in amphibians (Berrill et al. 1997, Ouellet et al. 1997). They also may

buffer against negative impacts associated with cattle grazing. Wood frog and chorus

frog populations, in particular, are known to be sensitive to this disturbance (Ambrose

and Paskowski 1998). As mentioned in the avian discussion, mitigation and natural

wetlands shared similar landscape positions adjacent to forests. While all natural

sites were bordered immediately by forests, mitigation wetlands averaged only 14.5

m to the nearest forest. Thus, anurans in both wetland types likely benefit from

forested perimeters. Although natural wetlands contained a higher percentage of

shrub cover (27.8 vs. 7.5 in mitigation sites), lack of open water is likely limiting

anuran numbers. Shrub communities had successfully been established at 9 of 11

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mitigation wetlands, and percent coverage should increase as these wetlands mature

(Chapter II). This will be valuable in maintaining future diverse anuran habitat.

Similar to waterbird communities, differences in anuran communities may be

attributed to differences in invertebrate (Chapter IV) and vegetation (Chapter II)

communities between mitigation and natural sites. Because frogs depend on

invertebrates for their diet (Anderson et al. 1999b, Lima and Magnusson 2000), it is

expected that anuran abundance and distribution could reflect higher invertebrate

nektonic biomass densities across open water areas of mitigation wetlands. Similarly,

higher vegetative species richness and diversity may provide more diverse

microhabitats for oviposition, foraging, growth, and refuge (Stratman 2000).

Few anuran species (i.e., cricket frog, American bullfrog, green frog) can

coexist with predatory fish species (Semlitsch 2002), but studies offer conflicting

evidence as to the effect of predatory fish on anuran populations (Hecnar and

M�Closkey 1997, Lehtinen et al. 1999, Pechmann et al. 2001, Semlitsch 2002).

Despite fish populations in 9 of 11 (Vepco and Buffalo Coal did not contain fish)

mitigation wetlands and 3 of 4 (Meadowville did not contain fish) natural wetlands,

these sites continue to support healthy anuran populations. In fact, some of the

highest frog index values were obtained in wetlands that contained fish. It is

important to note that some mitigation sites consisted of numerous open water cells,

some of which did not contain fish. These areas may be used as a refuge for breeding

frogs, thus minimizing potential negative impacts caused by fish populations.

Furthermore, high anuran populations in wetlands that contain fish may be attributed

to an increase in the macroinvertebrate prey base, which can result indirectly from

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increases in predatory fish populations (Batzer et al. 2000). A more detailed study

would be needed to accurately assess the impact of fish populations on anuran

communities among mitigation wetlands in West Virginia. Even if data were to show

a negative impact of fish populations on anurans, it would be difficult to prevent the

invasion of fish into wetlands mitigation adjacent to streams or rivers.

Numerous mitigation sites were built on-site as mitigation for the construction

of a major highway in West Virginia. However, the proximity of mitigation wetlands

to major roads did not seem to adversely affect current anuran abundance. In fact, 2

sites (Sand Run and Triangle) scored among the highest richness and WI values,

respectively, of all mitigation sites. However, studies have correlated low amphibian,

as well as reptile numbers to road density (Fahrig et al. 1995, Lehtinen et al. 1999,

Haxton 2000, Trombulak and Frissel 2000). The limiting factor, however, is not

necessarily the traffic, although amphibian mortality due to vehicular collisions is not

uncommon (Fahrig et al. 1995). Roads, acting as barriers to dispersal, may have

long-term effects on metapopulation dynamics by deteriorating the genetic integrity

of localized populations (Trombulak and Frissell 2000). In addition, roads potentially

change soil density, temperature and water content, surface waters, patterns of run-

off, and sedimentation, as well as adding heavy metals to roadside environments

(Trombulak and Frissell 2000, Bridges and Semlitsch 2002). Problems associated

with dispersal may not manifest themselves within anuran populations located at my

study sites because of their proximity to streams, rivers, and other wetlands.

However, research should monitor road-related stresses to the environment and their

potential effect on anuran populations within mitigation wetlands. Although wetland

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construction near roads can potentially have long-term negative impacts, there are

numerous logistical benefits associated with on-site design and construction. As well,

on-site mitigation sites can facilitate colonization by philopatric anuran species.

Despite my confidence in the incorporation of a sampling scheme that

accurately encompassed temporal variation in anuran breeding for this study, future

survey schedules should incorporate local water-temperature and humidity

measurements, as studies have indicated their influence on anuran breeding variation

(Green 1997, Lepage et al. 1997). Furthermore, without information on reproductive

success, I cannot adequately assess the long-term success of mitigation wetlands in

supporting anuran populations. On a metapopulation scale, some sites could be

acting as sinks (Pulliam 1988). Additional survey techniques including pitfall traps,

dip nets, or egg mass searches could accompany call-count surveys in future studies.

This would provide researchers with information on dispersal and recruitment in

addition to distribution and abundance. As well, future studies should address

surrounding land-use of mitigation sites. Surrounding uplands have a large influence

on anuran breeding distribution, particularly for those that have an adult terrestrial

phase. Nevertheless, recent concern over declining amphibian populations has drawn

attention to the need to compensate for loss of amphibian habitat. My data provide,

both an assessment of the success of mitigation wetlands in West Virginia in

supporting anuran communities, and a sound framework for future research that

monitors anuran community responses to structural changes in these wetlands through

time.

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Habitat Quality

Habitat Suitability Index (HSI) models offer a simple and repeatable method

of comparing the relative habitat quality of specific species between mitigation and

natural wetlands. The HSI models chosen for this study represent a variety of

wetland�dependent taxonomic groups that are considered good indicators of wetland

function.

It was not surprising that model outputs for all species combined were similar

between mitigation and natural wetlands. Because the target species possessed a

broad range of habitat requirements, I expected certain species to score higher in

mitigation wetlands while others would score higher values in natural wetlands.

Indeed, this was the case, but statistical differences were only detected for red-winged

blackbird and beaver.

Red-winged Blackbird.--

According to the red-winged blackbird HSI model, mitigation and natural

wetlands contained poor blackbird habitat, but with natural wetlands containing

higher quality habitat than mitigation wetlands. First, natural wetlands contained

more than twice the percentage of broad-leaved monocots than mitigation wetlands.

This can primarily be attributed to higher amounts of cattail in natural wetlands. Red-

winged blackbirds generally nest in emergent wetlands with tall, dense herbaceous

vegetation, preferably cattail (Short 1985, Stanislav and Picman 1997). Cattail also is

important to other species. Although cattail can form monotypic stands that exclude

desirable diverse native species (Boutin and Keddy 1993), it can provide cover for

wintering waterfowl and amphibians. In addition, carp were absent from every

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natural wetland, whereas they were present in 1 mitigation site (Trus Joist

MacMillan). Carp can disturb submerged aquatic vegetation (McKnight and Hepp

1995), which may decrease habitat for emergent aquatic insects that blackbirds prefer

to forage.

Although mitigation and natural wetlands scored low SI values, breeding bird

surveys confirmed healthy red-winged blackbird populations in both wetland types.

In fact, blackbird abundance was similar between natural and mitigation wetlands

(Chapter V). This may indicate poor calibration during the development phase of this

model. In its current state, this model weighs each variable equally, and too little

weight may be given to surface water and Odonate variables. It is tempting, based on

red-winged blackbird abundances observed at these sites, to conclude that high

quality habitat exists, thus questioning the validity of the model. However, a much

larger study would be needed to adequately test this assumption. Although the

objective of this study was not to validate the red-winged blackbird HSI model, I still

conclude that mitigation and natural wetlands both contain suitable blackbird habitat.

Beaver.--

The beaver HSI model also yielded a higher mean SI value in natural

wetlands. Specifically, the percentage of trees with a DBH between 2.5 and 15.2 cm

DBH was higher in natural wetlands within 100 and 200 m of the wetland basin.

Similarly, the percentage of shrubs was higher in natural wetlands, both within the

wetland basin, and within 100 and 200 m of the water�s edge. Beavers forage on

trees and shrubs throughout the year, but more so during the winter when herbaceous

vegetation may be limiting (Allen 1983, Barnes and Mallik 2001). Although

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mitigation wetlands contained fewer trees within the desired DBH scale, they

contained similar percentages of overall upland tree canopy coverage. Beavers are

not the only species that can benefit from increased tree and shrub cover. A higher

percentage of canopy coverage in and around the wetland should attract diverse

guilds of songbirds while at the same time offering protection to some game species

that may use these wetlands. Mitigation wetlands should develop shrub thickets

through time, thus progressing towards the replacement of additional lost wetland

functions by offering continued wildlife benefits associated with these communities.

Unlike the red-winged blackbird HSI model, the beaver model resulted in a

more expected, and perhaps, more realistic SI value. Beavers were confirmed at 6

mitigation sites (Elk Run, Sand Run, Triangle, Trus Joist MacMillan, Enoch Branch,

and Bear Run) and at 3 of 4 natural sites (Altona Marsh, Elder Swamp, and

Muddlety), so model outputs appear to reflect beaver habitat use of mitigation and

natural wetlands. This outcome may be positive or negative, depending on one�s

view of beaver-wetland ecosystem interactions.

Muskrat.--

The muskrat HSI model yielded similar SI values between mitigation and

natural wetlands. Both wetland types contained adequate cover for muskrat, because

similar to waterfowl and anuran requirements, hemimarsh conditions provided

optimal foraging and cover habitat for muskrats (Allen and Hoffman 1984).

Mitigation and natural wetlands also contained at least some surface water year

round. The main limiting factor for the muskrat model was the food component.

Specifically, the percentage of emergent vegetation consisting of cattail, common 3-

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square (Scirpus americanus), or olney bulrush (S. olneyi) was low in both wetland

types. These species have frequently been documented as a highly preferred food and

cover source for muskrats (Bellrose 1950, Sather 1958, Campbell and MacArthur

1994, 1998). The low output by this variable is arguable, however, because muskrat

sign was observed at many sites. Too much emphasis may have been placed on

vegetation composition during model development. Although cattail, common 3-

square, and olney bulrush are the preferred food items of muskrat, they will forage on

other aquatic emergent species as well as some terrestrial species (Perry 1982). Virgl

and Messier (1997) concluded that food was not a key factor limiting distribution of

muskrat. Yet, the model scores this variable only a 0.1 when preferred vegetation

species are limiting. I recommend a minimum baseline value of 0.5 instead of 0.1

when evaluating this variable. This would better reflect the diverse food preferences

of muskrat in the face of variable limiting food resources, and hence, more accurately

reflect muskrat habitat use of mitigation wetlands.

Mink.--

The mink HSI model also yielded SI values similar between mitigation and

natural wetlands. Both wetland types contained surface water year round, and both

contained similar amounts of persistent emergent vegetation within the wetland basin,

as well as similar percentages of tree and shrub crown cover within 100 m of the

wetland. It is assumed by the model that the amount of persistent emergent

vegetation was sufficient to support an adequate prey base while at the same time

offering protective cover. Similarly, the amount of forest and shrub cover ≤100 m

from the wetland edge provided sufficient terrestrial food base during the fall and

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winter (Melquist et al. 1981, Allen 1984). This also may provide important vertical

and spatial structure for songbirds, amphibians, and other mammals. Mink diet is

diverse and includes aquatic (fish, crayfish, amphibians), semiaquatic (waterfowl,

muskrat), and terrestrial (rabbits, rodents) prey species (Allen 1984, Jedrzejewska et

al. 2001, Sidorovich et al. 2001). They also adapt well to variable environments,

especially prey availability, and are known to be highly mobile (Allen 1984). In

addition, mink are nocturnal, so they are difficult to detect. Thus, they were

confirmed at only 2 mitigation sites (Walnut Bottom, Leading Creek), and at no

natural sites. Nevertheless, mitigation wetlands appear to contain quality mink

habitat.

Great Blue Heron.--

In addition, the great blue heron HSI model output was similar between

mitigation and natural wetlands. Within the foraging component of the model,

mitigation and natural wetlands contained similar mean distances between potential

nesting and foraging areas of 36.7 and 37.5 m, respectively. These values reflect the

close proximity of forests to my study sites. This may benefit other wildlife species

by providing nearby escape cover while at the same time providing cover for

predators. The foraging component of the heron model also incorporates water depth

and color, substrate type, and presence of fish into variable 2. For this variable, the

researcher is left with an �all or none� approach that precludes any continuum that

may exist within these criteria. Some wetlands, for instance, contained suitable water

and substrate conditions but no fish. And even though a wetland may not currently

contain fish, there still is potential to support fish in the future due to transplantations

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or flooding. Add this to the fact that heron will forage on prey other than fish such as

amphibians or reptiles (Kushlan 1978, Szelistowski and Meylan 1996), I decided to

score this variable a 0.5, even if fish were not present. Indeed, the shallow, clear

water within these mitigation wetlands is ideal foraging habitat not just for great blue

heron. Other waterbirds, including mallards, wood ducks, green herons, belted

kingfishers, rails, or migrating shorebirds benefit from these conditions.

Additionally, continued growth of submerged aquatic vegetation is favored, which

also is a valuable food source for these and other waterbirds. Finally, while roads

with moderate traffic were <100 m from mitigation wetland edges, suitable heron

foraging areas existed within the interior of these sites, and thus, met disturbance-free

criteria at all mitigation sites.

Although mitigation and natural wetlands contained sufficient great blue

heron foraging habitat, they scored low reproduction component SI values. As

aforementioned, the distance between potential nesting sites to actual or previous

nesting sites was too great to provide optimal heron nesting habitat. Great blue

herons rarely travel far to establish new rookeries once an old one is vacated (Custer

et al. 1980, Kelsall and Simpson 1980), and they rarely travel distances >16 km to

forage. I suspect closer heronries exist near our study sites than those obtained from

the West Virginia Division of Natural Resources, and thus conclude that this variable

may underrepresent actual heron habitat suitability within both wetland types. Since

accurate rookery information is probably lacking for West Virginia, I cannot fault

model development for this inconsistency.

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Field observations confirmed the suitability of mitigation wetlands in

supporting great blue herons. Herons were observed (but not sampled) at 2 mitigation

sites (Bear Run and Triangle) and 1 natural site (Altona Marsh), and were actually

sampled at 7 mitigation sites (Walnut Bottom, Buffalo Coal, Elk Run, Leading

Creek, Sand Run, Trus Joist MacMillan, and Enoch Branch) and 1 natural site

(Muddlety). In most cases, herons were observed foraging or flying nearby.

Therefore, it appears that required disturbance-free zones surrounding foraging areas

accurately predicted heron foraging tolerance. However, no rookeries or nests were

observed at any of the study sites. Even though mitigation wetlands generally met

nesting disturbance-free zone criteria, it appears that herons are not using these

wetlands to breed. The heron HSI model does not provide any past research to

support its arbitrary selection of 150 and 250 m disturbance-free zones. I suspect

larger buffer zones may be needed to adequately support heronries, perhaps as much

as 800 m (Skagen et al. 2001). This assertion could be incorporated into future great

blue heron HSI model evaluations, thereby more accurately predicting heron nesting

tolerances. More studies are needed to confirm heron nesting tolerance to human

disturbance. I conclude that although the great blue heron HSI model possibly

deflates reproductive suitability as it pertains to this study due to lack of actual or

previous rookery locations, and although the model probably inflated reproduction

suitability via liberal disturbance-free zones, this model appeared to accurately reflect

heron habitat use of mitigation wetlands in West Virginia.

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Wood Duck.--

The wood duck HSI model was calculated based on breeding and wintering

habitat suitability. It was not surprising, specifically due to the amount of brood

cover, that mitigation wetlands scored such high SI values relative to natural

wetlands. Model variables stressed the importance of natural and artificial nest

cavities as well as creating structural variability within wetlands to promote adequate

wood duck breeding habitat. Because the density of potential nesting cavities was

relatively low in both wetland types, the percentage of wetland area containing

potential nesting habitat was low. However, according to the wood duck model,

optimal nesting habitat is achieved when the percentage of potential nesting habitat

reaches only 20%. Mitigation wetlands generally met this criterion, and as such

contained suitable wood duck nesting habitat. Nonetheless, numerous studies have

shown the importance of artificial nest boxes to wood duck breeding success

(Stephens 1998, Heusmann 2000, Zicus 2000), which stresses the importance of not

only installing wood duck nesting boxes in mitigation wetlands, but in situating

wetlands near forested cover types where wood duck can have easy access to nesting

locations.

The wood duck model considered potential wood duck brood cover to consist

of a combination of emergent vegetation, shrub cover, overhanging tree crowns, and

woody downfall. The amount of emergent vegetation and shrub cover in natural

wetlands was too dense to be considered optimal brood cover. According to the

wood duck model, optimal brood coverage exists where percentages of cover are

between 50 and 75%. Mitigation wetlands generally met this criterion, whereas

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natural wetlands did not, although the criterion was met through emergent vegetation

coverage, not shrub coverage. Harper et al. (1998) stressed the importance of live,

woody shrub cover in constructed wetlands to wood duck roosting. This further

asserts the need to establish shrub communities in newly created wetlands. The lower

end of brood coverage requirement (50%) for optimal brood coverage is consistent

with optimal habitat conditions for numerous taxa aforementioned. It is important to

note, however, that mitigation wetlands contained suitable brood coverage because of

emergent vegetation and shrub coverage, not because of overhanging tree crowns and

woody downfall. While 4 of 11 mitigation wetlands did contain some woody

downfall, the amount of cover was minimal and sporadic. Two of the 4 natural

wetlands contained at least some woody downfall. Studies show that structural

diversity within and around a wetland not only provides brood cover for wood duck,

it increases overall wildlife production by providing breeding and hibernation habitat,

and food and cover for mammals, birds, amphibians, and invertebrates (Wilcox and

Meeker 1992, France 1997, Babbitt and Tanner 1998, Froneman et al. 2001). This

stresses the importance of establishing woody downfall and other debris in newly

created wetlands.

According to the wood duck HSI model, mitigation wetlands also contained

suitable wood duck wintering habitat. Wintering habitat was described as similar to

brood habitat, but only persistent emergent vegetation was considered, in addition to

shrub cover, overhanging tree crowns, and woody downfall. Again, natural wetlands

were limited by the relatively dense coverage of emergent vegetation and shrub

cover. However, unlike the breeding model, the winter model did not consider the

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percentage of wetland area containing potential winter cover. Assuming similar

suitability graphs would exist in brood and winter coverages, both wetland types

would have scored higher winter SI values if this variable had been incorporated into

the model. As such, this model may underestimate the amount of winter cover

available to wood ducks across all wetlands evaluated.

Field observations confirmed the suitability of wood duck breeding habitat in

mitigation wetlands. Surveys were not conducted in the winter, so wintering habitat

suitability could not be �confirmed�. Wood duck adults were confirmed in breeding

bird surveys at 8 of 11 mitigation sites (Walnut Bottom, Buffalo Coal, Leading Creek,

Sugar Creek, Triangle, Trus Joist MacMillan, Enoch Branch, and Bear Run), and

broods were observed at 2 sites (Walnut Bottom and Leading Creek). Wood ducks

were confirmed nesting in artificial nest boxes at 1 mitigation site (Sugar Creek), and

all boxes were used by at least some bird species. As aforementioned, mitigation

sites contained significantly higher wood duck abundances than natural wetlands.

This appears consistent with the higher total SI values observed in mitigation

wetlands, although differences between SI values were not significant. However,

differences in total model SI values were attributable to differences in wintering

habitat suitability, not breeding suitability. Despite natural wetlands having similar

breeding habitat suitability to mitigation wetlands, no wood ducks were sampled in

natural wetlands. This may indicate either that the wood duck model is

overestimating breeding suitability, or that wood ducks were simply missed during

breeding bird surveys at natural sites. The latter seems less likely considering the fact

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that no wood duck were observed at natural sites, even during visits outside of

breeding surveys.

Vegetative composition may be affecting wood ducks distribution and

abundance as well, and they likely are benefiting from the establishment of diverse

vegetation (Chapter II) and invertebrate communities (Chapter IV) in mitigation

wetlands. In fact, studies have shown the importance of vegetation and invertebrates

to wood duck diet (Drobney and Fredrickson 1979, Harper et al. 1998), especially in

the absence of hard and soft mast. Considering the success of mitigation wetlands in

supporting vegetation and invertebrate communities relative to natural wetlands, I

suspect that mitigation wetlands in West Virginia will continue to provide quality

wood duck habitat.

Red-spotted Newt.--

Results from the red-spotted newt HSI model indicate that mitigation wetlands

contain suitable habitat for this species. Red-spotted newts are most abundant in

shallow wetlands with permanent water that contain dense aquatic vegetation (Sousa

1985). Aquatic vegetation is important not only for cover, but for reproduction as

well. Populations of newts with a terrestrial eft stage will migrate to nearby upland

areas, where they will remain for ≤7 years while seasonally returning to wetland

habitat to breed (Healy 1974, Waldick et al. 1999). This further emphasizes the

importance of establishing emergent and submerged aquatic vegetation in mitigation

wetlands, as well as the need to situate mitigation wetlands near healthy forest

ecosystems. It is important to note that the newt model did not directly evaluate red-

spotted newt food preferences (i.e., invertebrate abundance). It was assumed that

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adequate water and vegetation conditions would facilitate colonization by

invertebrates. Indeed, this was probably the case, as mitigation wetlands were found

to support healthy invertebrate populations (Chapter IV). Specifically, mitigation

sites contained a diverse array of taxa including flies (Diptera), springtails

(Collembola), beetles (Coleoptera), and snails (Gastropoda), all of which are

preferred food items of this opportunistic feeder (Sousa 1985, Kessler and Munns

1991). Despite mitigation sites scoring high newt SI values, breeding newts were

confirmed at only 2 mitigation sites (Sugar Creek and Walnut Bottom) and no natural

sites. Presence of fish, proximity to roads, or wetland size may be limiting newt

abundance and distribution (Gibbs 1998, Hager 1998, Smith et al. 1999), but these

factors were not considered as major influences on newt habitat use for this model. I

think that my lack of red-spotted newt observations in mitigation wetlands likely does

not reflect poor model performance by yielding inflated SI values. Instead, newts

probably use more mitigation wetlands than were observed. More detailed surveys

should confirm widespread use of mitigation wetlands throughout the state.

Snapping Turtle.--

The snapping turtle HSI model also yielded similar SI values between

mitigation and natural wetlands, and both wetland types, according to the model,

contained low quality snapping turtle habitat. This can be attributed to low

percentages of silt in the substrate. The variables evaluated in this model provide

important information, not only about snapping turtle, but about other wildlife species

as well. Mitigation wetlands contained a mean water temperature (27.7 °C) that was

within optimal range of snapping turtle, which is about 25-30 °C (Graves and

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Anderson 1987). This temperature range could potentially be suitable for other

aquatic turtles including painted turtles (Chrysemys picta), red-eared sliders

(Trachemys scripta), wood turtles (Clemmys insculpta), map turtles (Graptemys

geographica), and spotted turtles (Clemmys guttata), whose general thermal threshold

are between 15-20 °C (Ernst et al. 1994). As well, low mean water velocities were

observed across mitigation wetlands, indicating their suitability in supporting

snapping turtles. Stationary water also is suitable for numerous snakes, frogs, and

salamanders that can maximize foraging efficiency by conserving energy that would

otherwise be expended moving against high flow rates or pursuing immobile but

current-borne food items (Graves and Anderson 1987). I also observed deep enough

water in at least some portions of mitigation wetlands to provide adequate hibernacula

for snapping turtle. This may be important for other turtles, as well as some

amphibians that may use ice-free areas for hibernation (Cook 1984, Cunjak 1986). In

addition, mitigation wetlands scored high SI values for both reproduction and

interspersion components of the snapping turtle model. Because mitigation sites were

situated in close proximity to small streams and permanent water, they provided

excellent reproduction and dispersal habitat for reptiles and amphibians in general

(Hager 1998, Kasano 1998, Finkler 2001, Semlitsch 2002). The main limiting factor

affecting the performance of this model was the lack of silt observed in the substrate

of both mitigation and natural wetlands. In fact, if this variable is at an optimal level

(100%), the overall snapping turtle SI value almost doubles. Graves and Anderson

(1987) recognized that the exact silt content required to satisfy turtle burrowing

requirements is unknown, and as such, they assumed a linear relationship between

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percent silt and hibernacula suitability. I think this variable may not be limiting

snapping turtle habitat quality due to insufficient data gathering during model

development. I, too, was unable to find current literature regarding exact silt content

requirements. My observations of snapping turtle actually using mitigation sites

further supports the assertion that this model may be deflating snapping turtle usage

of mitigation wetlands. I observed snapping turtles during the summer at 6 of 11

mitigation sites (Walnut Bottom, Elk Run, Sugar Creek, Sand Run, Triangle, and

Trus Joist MacMillan) and at 1 natural site (Muddlety). Snapping turtles may not be

using mitigation sites to hibernate, but it appears that mitigation wetlands in West

Virginia provide adequate habitat for at least some life-history requirements (i.e.,

foraging, reproduction, and interspersion).

Conclusions.--

By definition, suitable habitat is indicative only of a species� presence/absence

(Hall et al. 1997). According to this definition, mitigation wetlands, in general,

provided suitable habitat for all 8 species evaluated. I recognize the intrinsic misuse

of the term, habitat �suitability� index, and instead recommend considering the

models as a habitat �quality� index, but only as it pertains to the relative quality of

habitat between mitigation and natural wetlands. My results indicate that mitigation

wetlands provided suitable, high quality, habitat for beaver, mink, and red-spotted

newt, and I concur with these model outputs based on correlations between habitat

characteristics displayed by the mitigation wetlands and with natural-history

requirements for these species, and by direct observations. I believe, however, that

red-winged blackbird and muskrat HSI models possibly provided inaccurate

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representations of habitat suitability using similar reasoning. For these species�

models, variables addressing species composition of emergent vegetation played a

key role in limiting SI values, possibly due to improper model calibration or inherent

flaws in predicting animal behavior under stresses associated with competition or

limiting resources. I can speculate that the snapping turtle model also was inaccurate

because this species was observed using mitigation wetlands during the summer, but

this species, indeed, may not be using mitigation wetlands for hibernation. Similarly,

great blue heron, although confirmed foraging within mitigation sites, are probably

not using mitigation wetlands as breeding locations. The goal of this study was not to

validate these models, but to gauge the relative quality of habitat between mitigation

and natural wetlands. As such, I conclude that natural wetlands provided better red-

winged blackbird and beaver habitat than mitigation wetlands. The other major goal

was to evaluate trends in habitat characteristics shared by mitigation wetlands that

may be valuable in monitoring wildlife in general. It is clear that mitigation wetland

habitat characteristics evaluated for these models currently meet or exceed natural

wetland reference standards. However, it is important to note the potential flaws of

those models that yielded low SI values. Overall, the mitigation wetlands evaluated

in this study provided valuable habitat for most life-history requirements for all

species evaluated.

Despite the discrepancies involved in the validity of using HSI models,

current regulations affecting resource management decisions require wildlife habitat

assessments that are repeatable and scientifically credible. If properly developed,

applied, and tested, HSI models can provide an efficient and inexpensive method for

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satisfying these requirements. Indeed, HSI models are widely used in environmental

impact statements (Brooks 1997, Morrison et al. 1998), forest planning, (Roloff et al.

1999), and even population viability analysis (Akcakaya 1995).

About 160 HSI models have been developed, but few have been tested. The

assumptions of these models have enormous implications, and critics argue that

management decisions should not be based on untested models. Using different

validation, verification, and calibration techniques, some researchers have found

positive correlations between model predictions and actual measures of wildlife

distributions, densities, and abundance (Cook and Irwin 1985, Verner et al. 1986,

Brennan 1991, Thomasma et al. 1991), while others have found negative correlations

(Seitz et al. 1982, Clark and Lewis 1983, Bart et al. 1984, Robel et al. 1993). Some

explanations for these discrepancies have been offered, including inadequate

population sampling (Cook and Irwin 1985, Lancia and Adams 1985), sampling in a

limited range of habitat conditions (Clark and Lewis 1983), improper representation

of wildlife-habitat relationships by model equations (Bart et al. 1984, Warwick and

Cade 1988, Van Horne and Weins 1991), misinterpretation of results (Cook and Irwin

1985, Capen et al. 1986), applying models to inappropriate spatial scales (Weins

1986, Roloff 1994), or the inadequate consideration of data variability (Bender et al.

1996).

Roloff and Kernohan (1999) used specific criteria to evaluate HSI validation

studies conducted between 1982 and 1995. These included the evaluation of model

components, input data variability, use of statistical power, spatial scale, range of

HSIs incorporated, type of population index used, and duration of population data

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collection. They found that the weakest component of all HSI validation studies was

inadequate consideration of input data variability and how this variability affects final

HSI interpretation. Specifically, most studies, in assessing model parameters (habitat

variables), failed to account for variability in sample means. In doing so, they failed

to provide confidence intervals to HSI scores, statistical tests on differences between

scores, or a quantifiable description of how differences in HSI scores may be related

to sampling deficiencies. Roloff and Kernohan (1999) attribute some of these

deficiencies to small sample sizes and the lack of defined replicates used to

effectively cover the complete range of habitat conditions.

My study incorporated defined replicates (wetlands) that encompassed a wide

range of habitat variation throughout West Virginia. This enabled statistical

differences in HSI scores to be evaluated, thus providing justification for inferences

to be made regarding the reflection of HSI scores on differences in habitat quality.

Although I noted the presence of any target species within study sites, I did not seek

to validate the models. Instead, the goal was to compare relative habitat quality

between wetland types, and to discuss trends in habitat variables that most influence

model output. At the very least, the multitude of habitat variables that are quantified

during model application can be applied to multivariate techniques that correlate

wildlife indices to environmental data. These data are extremely important in the

continued monitoring of these valuable ecosystems.

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CONCLUSIONS

Numerous studies have written about our inability to successfully mitigate for

wetland destruction (Race 1985, Erwin 1990, Reinartz and Warne 1993, Wilson and

Wilson 1996). Although the definition of success varies depending upon project

objectives, most agree that compensatory wetlands should replace functions lost

during wetland destruction. These data indicate that mitigation wetlands in West

Virginia currently support avian and anuran populations, as well as diverse habitat

characteristics indicative of increased habitat quality for a variety of wildlife species.

Indeed, mitigation sites contained some higher wildlife indices than natural sites, and

this could reflect actual differences in wildlife populations resulting from wetland

age, design, or location within the landscape. It is likely that wildlife distribution and

abundance reflect differences in vegetation and invertebrate community structure

between mitigation and natural wetlands, and future monitoring should focus on

monitoring the interactions between wildlife populations and these biotic factors. The

monitoring of the effects of beaver activity on vegetation structure is of particular

importance in evaluating future wildlife communities.

I should caution that it is premature to assess the full outcome of mitigation

efforts within the state. First, these data represent a short-term trend resulting from

only 2 years of data collection. Thus, these data do not encompass the temporal

variation in avian and anuran community structure. Pechmann et al. (2001)

recommended several years of census data on amphibians before meaningful

comparisons between mitigation and natural sites can be made. Similarly, D�Avanzo

(1990) and Zedler (1993) suggested a monitoring duration of 20 years for mitigation

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wetlands. Unfortunately, financial or logistical restraints often preclude long-term

monitoring capabilities.

Second, created wetlands often take at least a decade before they function

compatible to natural wetlands. Wilson and Mitsch (1996) recommend giving

freshwater wetlands 15-20 years before judging their success, and Frenkel and

Morlan (1991) recommend waiting ≥50 years for certain forested and coastal

wetlands. Two wetlands included in this study were about 20 years old and an

additional 3 sites were ≥10 years old. Although my sites do not meet recommended

criteria for mitigation wetland development time, nearly half are ≥10 years old, and I

think relatively conservative inferences can still be made regarding their success.

Finally, the variation in structure among mitigation and natural wetlands adds

to the difficulty in assessing mitigation success. This is particularly important in the

establishment of reference standards (Smith et al. 1995, Brinson and Rheindhardt

1996). Natural short-term processes such as seasonal cycles of precipitation and

temperature, coupled with long-term processes including population dynamics,

erosion and depositional processes, succession, or drought/wet cycles can cause

variation in the functional capacity of natural wetlands (Smith et al. 1995). This type

of variability is common in many wetland ecosystems including coastal marshes

(Oviatt et al. 1977), cypress swamps (Ewel and Odum 1984), prairie potholes

(Kantrud et al. 1989), and playa wetlands (Haukos and Smith 1992). Another factor

researchers must consider in establishing reference standards concerns anthropogenic

disturbance (Smith et al. 1995). Because most wetlands have been exposed to

hundreds of years of continued disturbance, their functions have been fundamentally

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changed, so it may be difficult to construct wetlands based on undisturbed standards.

Although some misuses of using natural wetlands as reference standards are possible,

reference wetlands can guide mitigation, both during and after the process by making

explicit the goals of mitigation and by evaluating the progress of mitigation wetlands

through proper monitoring (Brinson and Rheinhardt 1996). Similar variation in

wetland structure also can occur within mitigation wetlands thus providing further

evidence as to the difficulty in duplicating natural systems, especially since

alternative stable states are commonly observed in ecological communities (Drake

1990). These points illustrate the complexity in assessing mitigation success based

on reference wetlands and reiterate the need to document and compare losses of

wildlife habitat during wetland destruction to creation of wildlife habitat via

compensatory mitigation.

Indeed, temporal variation in wildlife habitat use, wetland development time,

and structural variation compound the logistics in evaluating the success of mitigation

wetlands. Nevertheless, the similarities in wildlife indices observed in this study

suggest preliminary development of mitigation sites towards reference standards. I

anticipate these data will help guide the creation of standardized protocols for the

continued monitoring of these and other mitigation wetlands, not only in West

Virginia, but also across the Appalachians.

MANAGEMENT IMPLICATIONS

Although the main goal of wetland mitigation is to construct or restore

wetlands that replace wetland functions lost to destruction, documentation of existing

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functions at impacted wetlands often does not exist. In these cases, I think it is

important to maximize wildlife habitat at compensatory wetlands, inspite of our

inability to truly mimic these systems. The implementation of different management

techniques should facilitate colonization and proliferation of diverse wildlife taxa

among current or future mitigation wetlands. I recommend constructing wetlands

≤50 m from forested cover types with a 300 m disturbance free zone that excludes

major roads. Wetlands should be ≥10 ha in size and be connected or adjacent to

streams, rivers, or other wetlands. I recommend maintaining hemimarsh conditions

with a 50/50 ratio of open water to emergent vegetation. Low water velocity and a

hydroperiod from 4 months to 1-2 years with water levels encompassing shallow (1-

10 cm) and deep (11-30 cm) areas also are recommended. This should be

accomplished under moist-soil management if water levels can be manipulated

(Chapter III). Wetland slopes of 10:1-20:1 are optimal. I also recommend enhancing

structural diversity by adding logs and rock piles in and around wetlands. Silt also

should be added to wetlands with poor hibernacula for herpetofauna. In addition,

earthen islands, Schwimmkampen, and nesting boxes should be included. Detailed

descriptions of the above management recommendations are provided below.

To further assess wetland mitigation success in terms of compensating for lost

wildlife function, it is imperative to conduct on-site wildlife surveys of the impacted

wetland that the mitigation site is designed to mitigate for. Detailed surveys of avian

and anuran communities should include documentation of lost habitat for specific

species with a particular focus on rare or inconspicuous species. This would better

enable researchers to assess a mitigation wetland�s ability to replace specific wildlife

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habitat while taking into account the status of those species being affected. An

assessment of overall species richness, diversity, and abundance can be a useful tool

in gauging relative success of mitigation wetlands in supporting wildlife, but these

indices can overshadow specific losses to wetland-dependent wildlife species. For

instance, relatively high anuran richness values observed at mitigation sites does not

reflect their ability to provide adequate habitat for wood frog. In fact, along with

American bullfrog, wood frog scored the lowest Wisconsin Index value of all species

observed. Because wood frogs are more terrestrial than many �true� frogs, they tend

to inhabit forested wetlands within West Virginia (Green and Pauley 1987). Thus, a

short-term net loss of wood frog habitat may result if inadequate compensation exists

for these important wetland types. Robb (2002) observed a 71% failure rate in

created palustrine forested wetlands in Indiana. Although little data exists on forested

wetland success within West Virginia, this trend should raise awareness as to the

difficulty in replacing lost habitat for specific wildlife species. Similar arguments

could be made concerning inconspicuous rail species. Although individuals were

observed within 2 mitigation sites, we know little about the habitat use by rails of

those wetlands that were destroyed. We are then left with bittersweet observations

that reflect the success among mitigation sites in providing adequate rail habitat, but

provide little insight into compensatory success.

This also is reflected in evaluating habitat models. Granted, habitat models

can be effective tools in assessing the relative habitat quality for specific species

between mitigation and natural wetlands, but this provides little insight into the actual

replacement of habitat for those specific species. I recommend an evaluation of

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habitat suitability index models for as many species that resources allow, both on the

wetland being impacted and on the replacement wetland. Although it is difficult to

assess the adequacy of mitigation wetland ecosystems in West Virginia in replacing

impacted wetlands, I hope that self-sustaining natural processes and species

interactions will continue to persist and mimic those of natural wetlands in West

Virginia.

Seasonal differences in avian use exist between mitigation and natural

wetlands (Perry et al. 1996, Melvin and Webb 1998). I suggest the inclusion of fall

surveys to account for winter migrating waterbirds. This would provide a more

comprehensive view of the temporal variation in wetland use, hence adding more

insight into the success of mitigation wetlands in supporting avian communities. I

expect that fall surveys would provide further evidence as to the success of mitigation

wetlands in supporting waterbirds.

Numerous strategies should be implemented in future mitigation projects to

facilitate the persistence of beneficial wildlife habitat in mitigation wetlands. First,

wetland size is an important factor dictating colonization, inhabitation, and dispersal

of wildlife (MacArthur and Wilson 1967, Tyser 1983, Kreil et al. 1986, Delphey and

Dinsmore 1993). I recommend constructing wetlands ≥10 ha in size. Although

mitigation ratios may require less wetland area to be created, replacement wetland

size could reflect the combined replacement ratios of multiple projects to achieve a

desired size. This could be a modification of the current mitigation banking system

that proactively creates multiple wetlands in a landscape as mitigation for future

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development projects. Alternatively, larger wetlands could be created to proactively

mitigate for the destruction of several smaller wetlands.

Furthermore, it is important to construct wetlands adjacent or connected to

streams, rivers, or other wetlands. This proximity is particularly important not only in

providing connectivity to neighboring populations, but in offering refuge during

unfavorable climatic conditions. It also offers protection against pollution, habitat

destruction, or changes in water levels. Second, developers should strive to create

hemimarsh conditions where an approximate 50:50 ratio of open water to emergent

vegetation exists. My study clearly indicates that this type of vegetative structure is

optimal for a variety of taxa including waterbirds, amphibians (i.e., frogs, red-spotted

newt), mammals (i.e., muskrat), and invertebrates.

Maintaining an adequate hydroperiod is important as well. Although longer

hydroperiods can ensure survival of certain anuran species, it may facilitate

colonization by unwanted predatorial fish. I recommend maintaining wetlands with

an array of hydroperiods from 4 months to 1-2 years to ensure successful recruitment

of all local species with differing habitat requirements, including invertebrate species

(Chapter III, Semlitsch 2002). This, perhaps, could be accomplished under a

mitigation banking system. Moist-soil management should be implemented in areas

where water level manipulation is feasible (Chapter III). It is important to assess the

potential impact of beaver in establishing appropriate hydrology at future mitigation

sites. I observed beaver impact at almost all of the mitigation sites. This species can

dramatically alter the hydroperiod of any landscape, both pre- and post-mitigation, so

caution is warranted in assessing hydrologic success upon creating a wetland.

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Water depth also plays an important role in determining wildlife use, affecting

both waterbird species composition and anuran breeding and hibernation. I

recommend creating wetlands with varying water depths to facilitate use by a variety

of species. Shallow (1-10 cm) and deep (11-30 cm) areas should both exist.

Although even deeper areas could be created, this may prevent periodic drying, which

would inhibit diverse hydrophytic vegetation development. However, deeper areas

can provide anuran breeding habitat in wetlands when spring draw-downs render

most of the wetland moist to promote seed germination. Again, this reiterates the

need to either maintain diverse habitats within each mitigation wetland, or maintain a

series of adjacent wetlands with diverse habitat conditions under different

management schemes, perhaps under a mitigation banking system.

Wetland slope also has been shown to affect wildlife populations. Kreil et al.

(1986) recommended slopes of 10:1 to 20:1 for mitigation wetlands to create variable

gradients for diverse vegetative growth to maximize invertebrate richness. This

would benefit waterbird and anuran species by increasing forage as well as

minimizing blockage to amphibian dispersal. Gentle slopes also are compatible with

goals of moist-soil management.

In addition, wetlands should be created near forests, preferably within 50 m.

A maximum buffer of 164 m was recommended by Semlitsch (2002). First, this will

protect wetlands against negative impacts associated with agricultural run-off.

Second, I observed that wetlands with increased tree and shrub cover <100 m from

the basin edge provided better cover, foraging, and breeding habitat for numerous

wildlife species including beaver, mink, red-spotted newt, and great blue heron. This

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also is important in establishing coarse woody debris and leaf litter, which further

enhances dispersal corridors for post-breeding or newly metamorphosed amphibians.

Diverse guilds of songbirds and game species would benefit as well, especially once

sufficient shrub cover has developed within the wetland complexes themselves.

Water velocity also should be considered in establishing adequate wetland

hydrology. My study, like many others, showed that low mean water velocity is

beneficial to numerous wildlife taxa, particularly amphibians and some turtle species

(i.e., snapping turtle). A channelized flow may be necessary in creating necessary

hydrology within the wetland basin, but gradients should be established that dissipate

water over a large enough surface area to create hydrologic gradients that promote

diverse vegetation.

Structural complexity is another important component in the functioning of

wetlands. Studies show that structural diversity within and around a wetland

increases wildlife production by providing breeding and hibernation habitat, and food

and cover for mammals, birds, amphibians, and invertebrates. Although structural

complexity was not formally evaluated in this study, it appeared that most mitigation

sites were lacking structure. As mentioned in the wood duck model section, only 4 of

11 mitigation sites contained woody downfall and coverage was minimal. I

recommend adding numerous logs and rock piles in and around wetlands to enhance

wildlife habitat.

I also recommend adding silt to wetlands that contain poor hibernacula for

reptiles and amphibians. Sensitivity analyses showed that an increase in silt

drastically improved the habitat quality for snapping turtles. Numerous other turtle

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species, as well as anurans, would benefit from increased silt. The amount of silt

should depend on wetland landscape position and the amount of water flowing in and

out of the system.

Earthen islands should be included in future mitigation wetlands to enhance

and protect nesting and loafing areas for waterbirds. They should be situated in the

middle of large open water areas ≥9.0 m from the shore in water 0.5 to 0.75 m deep

(Hammond and Mann 1956, Jones 1975). An alternative to earthen islands is

Schwimmkampen structures (Hoeger 1988). These are commercially available

triangular shaped rafts that can be arranged to provide nesting and loafing habitat for

ducks and geese. The islands are made of corrosion-proof plastics that protect against

weathering and microorganism damage. The vegetation installed on the top of the

islands is rot-resistant plant material that can be replaced or enhanced by natural

vegetation if desired (Hoeger 1988).

Wood duck nest boxes also should be included in future mitigation wetlands.

Boxes should be constructed from wood, preferably bald cypress (Taxodium

distichum) and mounted to a wooden pole for support. I recommend using rough-cut

lumber for construction. The opening of the box (7.6 cm ×10.0 cm) should be in the

front to facilitate maintenance and should face the east. A metallic cone predator

guard should be placed about 1 m above water. Ideally, boxes should be cleaned of

nesting materials (i.e., down feathers, egg membranes and shells, and unhatched eggs)

at least once after the peak of nesting and immediately following the breeding season

(Utsey and Hepp 1997). The wood duck I model recommends a minimum of 5

successful nests/0.4 ha for optimal wood duck habitat (Sousa and Farmer 1983).

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Considering the availability of potential nesting sites in natural cavities surrounding

the wetlands that are constructed adjacent to forest, I recommend installing ≥1 nest

box/wetland.

Depending on what wildlife species researchers want to manage for, predatory

fish may or may not want to be included in mitigation wetlands. While fish can serve

as a valuable prey source for wading birds, they can negatively impact amphibian

populations. Although my study preliminarily shows that fish have a minimal effect

on anuran populations, without recruitment data, this cannot be confirmed. Fish will

readily pioneer wetlands located adjacent to streams or rivers during flood events, so

they may be difficult to control. I recommend, however, that carp be excluded from

mitigation wetlands because they can inhibit submerged aquatic vegetation growth,

thus negatively affecting biota up the entire food chain.

Human disturbances, especially roads, can influence distribution and

abundance of wildlife. My data indicated with respect to anurans, negative effects

associated with roads may be minimal in the short-term. However, definitive results

from other studies point to long-term dispersal problems, especially if wetlands are

isolated from other water sources. This point further supports the need to maintain

connectivity of mitigation wetlands to other wetlands or waterways. Road effects can

be more immediate, however, as in the case of the great blue heron. Although

mitigation wetlands provided valuable foraging habitat, I suspected breeding habitat

was limited by human disturbance, despite a high SI value associated with this

variable. I recommend that, in the case of highway mitigation, wetlands be

constructed �off-site� with a minimum 300 m buffer around the edge of the wetland

205

basin. This should adequately encourage colony-nesting birds to breed adjacent to

mitigation wetlands while minimizing other abiotic factors such as pollution and

sedimentation. However, I understand that constructing wetlands �on site� as

mitigation for highway construction can have logistical benefits associated with

establishing hydrology and an adequate seed bank. In addition, philopatric amphibian

species that faithfully return to one particular area to breed would benefit, as well as

migratory waterfowl that repreatedly return to a specific wetland to breed, forage, or

loaf. Whether the benefits associated with constructing wetlands �off site� outweigh

�on-site� benefits, is case specific, and should be dictated by overall objectives of the

mitigation project.

Our ability to mimic natural systems is inhibited by the nature of natural

wetlands themselves. Since we can never recreate years of geomorphological

processes, the best we can do is to create wetlands with a chance of developing into

self-sustaining functioning systems. In doing so, wildlife requirements cannot be

ignored because their existence is testimony as to the success (i.e., healthiness) of the

multitude of abiotic processes that drive wetland succession. Indeed, wildlife�s

function in wetland mitigation should be embraced as a major player in contributing

to this dynamic ecosystem. Mitigation wetlands in West Virginia were created as

mitigation for an array of human activities. Despite the variation associated with

different design techniques and mitigation objectives, these wetlands shared a variety

of habitat characteristics that enabled them to support diverse wildlife populations.

The need to document wildlife use of impacted wetlands is crucial to conserving

specific wetland-dependent species whose habitat requirements are often ignored.

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This need may only be surpassed by the need to recognize the crucial components

outlined in this chapter in maintaining wetland ecosystem integrity.

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CHAPTER IV

TABLES

229

Table 1. Optimal Suitability Index (SI) scores of 38 habitat variables evaluated for

Habitat Suitability Index models on 8 wildlife species in mitigation (n = 11) and

natural (n = 4) wetlands in West Virginia, 2001-2002.

HSI model variables Optimal SI score Beaver V1: percent tree cover a. within wetland basin 40-60% b. within 100 m 40-60% c. within 200 m 40-60% V2: percent trees 2.5-15.2 cm dbh a. within wetland basin 100% b. within 100 m 100% c. within 200 m 100% V3: percent shrub cover a. within wetland basin 40-60% b. within 100 m 40-60% c. within 200 m 40-60% V4: shrub canopy height (m) a. within wetland basin 2-4 m b. within 100 m 2-4 m c. within 200 m 2-4 m V5: woody vegetation species composition a. within wetland basin >50% aspen, b. within 100 m willow, cottonwood, c. within 200 m or alder V6: mean annual water fluctuation small Muskrat V1: percent emergent vegetation 50-80% V2: percent year with water 100% V3: percent Scirpus validus, S. americanus, 80-100% Typha latifolia Mink V1: percent year with water 75-100% V2: percent persistent emergent vegetation 50-75% V3: percent tree/shrub cover <100 m 75-100% Great blue heron V1: distance between forage area/nest site <1.0 km

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HSI model variables Optimal SI score V2: presence of shallow, clear water with fish n/a V3: 100 m foraging disturbance free zone yes V4: presence of forest within 250 m yes V5: 150, 250 m nesting disturbance free zone yes V6: distance (km) between potential <1.0 km and actual/previous nest site Red-winged blackbird V1: percent broad-leaf monocots >50% V2: percent year with water >50% V3: presence of carp no V4: presence of Odonates yes V5: percent emergent vegetaion 40-60% Wood duck V1: number of potential nesting cavities/0.4 ha n/a V2: number of nest boxes/0.4 ha n/a V3: density of potential nest sites (no./0.4 ha) >5.0 V4: percent potential brood cover 50-75% V5: percent potential winter cover 50-75% V6: distance b/w cover types <0.8 km V7: percent area optimum nesting habitat >20% V8: percent area optimum brood habitat 100% Snapping turtle V1: water temperature (°C) during summer 25-35 V2: water velocity (cm/s) during summer 0.0 V3: percent vegetation in littoral zone 100% V4: water depth vs. ice depth water > ice V5: percent silt in substrate 100% V6: distance (m) to small stream 0.0 V7: distance (m) to permanent water 0.0 Red-spotted newt V1: percent water < 2m deep 100% V2: percent vegetation in littoral zone >75% V3: distance (m) to forest <50

Table 1. Continued.

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Table 2. Richness (no. species/0.78 ha), diversity (per 0.78 ha), and abundance

(no.birds/0.78 ha) comparisons for avian communities between mitigation (n = 11)

and natural (n = 4) wetlands in West Virginia, 2001-2002.

Mitigationa Naturala Species or Group x SE x SE Richness 8.79a 0.31 8.77a 0.48 Diversity 2.41a 0.41 2.15a 0.37 Abundance All birds 21.13a 1.69 22.2a 3.89 Waterbirdsb 3.97a 1.14 0.34b 0.18 Waterfowlc 3.46a 1.10 0.19b 0.16 Passerinesd 15.89a 1.18 20.84a 3.85 Top 20 species 17.32a 1.59 18.57a 3.91 Red-winged blackbird Agelaius phoeniceus 4.61a 0.73 6.24a 1.23 European starling Sturnus vulgaris 0.99a 0.39 3.16a 3.16a Song sparrow Melospiza melodia 1.25a 0.11 2.43b 0.22 Canada goose Branta canadensis 2.02a 0.02 0.16a 0.16 Common yellowthroat Geothlypis trichas 0.71a 0.10 1.06a 0.29 Tree swallow Tachycineta bicolor 1.68a 0.38 0.53a 0.21 Cedar waxwing Bombycilla cedrorum 0.50a 0.14 0.06a 0.04 American crow Corvus brachyrhynchos 0.02a 0.01 0.16a 0.11 Indigo bunting Passerina cyanea 0.50 0.11 0.63a 0.19 Wood duck Aix sponsa 0.87a 0.36 0.0b 0.00 American goldfinch Carduelis tristis 0.54a 0.11 0.34a 0.15 Red-eyed vireo Vireo olivaceus 0.40a 0.08 0.25a 0.08 Willow flycatcher Empidonax traillii 0.36a 0.09 1.02 0.23 Mallard Anas platyrhynchos 0.57a 0.16 0.03a 0.03 Yellow warbler Dendroica petechia 0.45a 0.10 0.94a 0.23 Gray catbird Dumetella carolinensis 0.33a 0.08 0.79a 0.20 Northern cardinal Cardinalis cardinalis 0.18a 0.05 0.32a 0.14 American robin Turdus migratorius 0.44a 0.11 0.21a 0.10 Barn swallow Hirundo rustica 0.68a 0.31 0.09a 0.07 Eastern towhee Pipilo erythrophthalmus 0.23a 0.06 0.16a 0.08 Great blue herone Ardea herodias 0.12a 0.06 0.03a 0.03 a The same letter following means indicates no difference between wetland types (P > 0.05). bIncludes only those birds that depend on water for all or most of their life requisites. cIncludes only birds in the family Anatidae. dIncludes only birds in the order Passeriformes. e Great blue heron was not among the top 20 species but was included in analyses because it was evaluated using a Habitat Suitability Index model.

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Table 3. Wisconsin Index value and abundance per wetland for all anuran species combined

and for each of 7 species heard at mitigation (n = 11) and natural (n = 4) wetlands, West


Wisconsin Index Abundance Mitigationa Naturala Mitigationa Naturala Common Name Scientific Name x SE x SE x SE x SE All frogs 0.52a 0.03 0.40b 0.07 4.75a 0.66 4.69b 1.18Spring Peeper Psuedacris c. crucifer 1.83a 0.16 1.86a 0.27 22.9a 3.32 28.4a 6.95Gray Treefrog Hyla chrysoscelis 0.17a 0.06 0.16a 0.09 0.39a 0.16 0.33a 0.19Bull Frog Rana catesbeiana 0.13a 0.05 0.05b 0.03 0.21a 0.09 0.10b 0.06Wood Frog Rana sylvatica 0.13a 0.06 0.08a 0.05 0.45a 0.29 0.21a 0.14Green Frog Rana clamitans melanota 0.84a 0.12 0.50b 0.13 7.82a 2.37 3.56b 1.29American Toad Bufo a. americanus 0.18a 0.05 0.04a 0.03 0.48a 0.17 0.05a 0.04Pickerel Frog Rana palustris 0.35a 0.09 0.09b 0.03 0.82a 0.21 0.24a 0.09a The same letter following means indicates no difference between wetland types (P > 0.05).

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Table 4. Mean Suitability Index (SI) values between mitigation (n = 11) and natural

(n = 4) wetlands of Habitat Suitability Index models for 8 wildlife species, West


Mitigationa Naturala x SE x SE

Red-winged blackbird 0.03a 0.01 0.15b 0.05 Beaver 0.74a 0.06 1.0b 0.0 Muskrat 0.35a 0.04 0.55a 0.12 Mink 0.79a 0.05 0.89a 0.04 Great-blue heron 0.26a 0.02 0.23a 0.05 Wood duck 0.82a 0.07 0.68a 0.11 Snapping turtle 0.60a 0.01 0.53a 0.04 Red-spotted newt 0.90a 0.05 0.80a 0.11 All species combined 0.56a 0.02 0.60a 0.03 a The same letter following means indicates no difference between wetland types (P >

0.05)

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CHAPTER V

VEGETATION, INVERTEBRATE, AND WILDLIFE

COMMUNITY RANKINGS AND HABITAT ANALYSIS OF

MITIGATION WETLANDS IN WEST VIRGINIA




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ABSTRACT

Numerous efforts have been made in West Virginia to construct and restore

compensatory wetlands as mitigation for natural wetlands destroyed through highway

development, timbering, mining, and other human activities. Because such little

effort has been made to evaluate these wetlands, there is a need to evaluate the

success of these systems. The objective of this study was to determine if mitigation

wetlands in West Virginia were adequately supporting ecological communities

relative to naturally occurring reference wetlands and to attribute specific

characteristics in wetland habitat with trends in wildlife abundance across wetlands.

Specifically, avian and anuran communities, as well as habitat quality for 8 wetland-

dependent wildlife species were evaluated. To supplement this evaluation, vegetation

and invertebrate communities also were assessed. Wetland ranks were assigned

based on several parameters including richness, abundance, diversity, density, and

biomass, depending on which taxa was being analyzed. Mitigation wetlands

consistently scored better ranks than reference wetlands across all communities

analyzed. Canonical correspondence analysis revealed no correlations between

environmental variables and community data. However, trends relating wetland

habitat characteristics to community structure were observed. These data support

previous chapters that revealed the success of mitigation wetlands in supporting

diverse vegetation, invertebrate, and wildlife communities and reiterates the need to

maintain specific habitat characteristics that are compatible with wildlife colonization

and proliferation.

This chapter is written in the style of Wetlands Ecology and Management.

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Key words: constructed wetland, man-made wetland, mitigation wetland,

reference wetland, restored wetland, wetland mitigation, wetland management

INTRODUCTION An enormous array of wildlife depends on wetlands for all or part of their

lives. Dwindling populations of wetland-dependent wildlife populations have

resulted from years of losses in the wetland resource base across the U.S. (Mitsch and

Gosselink, 2000). In an attempt to mitigate for losses in wetland habitat, current

legislation has mandated the construction of thousands of hectares of wetlands. To

evaluate these wetlands, researchers have attempted to describe and quantify wetland

functions relative to naturally occurring reference wetlands. Such functions

commonly evaluated include soil (Stolt et al., 2000), hydrology (Ashworth, 1997),

vegetation (Campbell et al., 2002), wildlife (Delphey and Dinsmore, 1993), or

combinations of these (Brinson, 1993; Brinson and Rheinardt, 1996; Wilson and

Mitsch, 1996). Although these functions have been evaluated exclusively in

numerous studies, few studies have engaged in a comprehensive evaluation of

multiple wetland functions to assess mitigation success. The term �success� in itself,

is quite variable, and often varies by project objectives (National Research Council,

2001). This study addressed mitigation success in terms of a wetland�s ability to

support diverse vegetation, avian, anuran, and invertebrate communities at a

functional equivalency to naturally functioning reference wetlands.

Vegetation communities were evaluated not only because they directly

determine the distribution and abundance of wildlife populations by providing

essential food and cover (MacArthur and MacArthur, 1961; Evans and Wilson, 1982;

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Anderson et al., 1999a, King et al., 2000; Naugle et al., 2000), they indirectly affect

wildlife by contributing to a variety of other wetland functions including quantity and

type of substrate for invertebrates (Murkin et al., 1992; Anderson and Smith, 1998,

1999, 2000; King et al., 2000) and water chemistry (Goslee et al., 1997; Castelli et al.,

2000). For a variety of reasons, invertebrates are extremely important in the

functioning of wetlands as well and thus, similar to vegetation communities, can be

viewed as surrogates to wetland health. They are particularly sensitive to long-term

hydrologic cycles, water quality, and habitat type (Wiggens et al., 1980; Doupe and

Horwitz, 1995; Brooks, 2000), which is often associated with vegetative structure and

composition. In turn, invertebrates contribute to other wetland functions by assisting

in litter decomposition, nutrient cycling (Cummins 1973; Merritt et al., 1984) and

plant community regulation (Weller, 1994). Thus, invertebrates aid in the transfer of

nutrients from the sediments, detritus, and water column to higher-level organisms.

They also have direct impacts on wildlife species that depend on them for food. In

particular, waterfowl and other waterbirds (De Szalay and Resh, 1996; Davis and

Smith, 1998; Anderson and Smith, 1999; Anderson et al., 2000), as well as anurans

(Anderson et al., 1999a; Lima and Magnusson, 2000), depend on invertebrates for

food. It is clear that invertebrates play a vital role in wetland function and are integral

in analyzing the health of these ecosystems.

Considering more than 50% of the 800 protected migratory birds rely on

wetlands (Wharton et al., 1982), it is clear that an avian component is necessary in the

evaluation of mitigation wetlands. Avian communities are good indicators of wetland

function because, as a group, they exhibit a wide range of habitat requirements, and

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have adapted to the variety of vegetative cover types and water regimes wetlands

provide (Anderson et al., 1996; Davis and Smith, 1998; Melvin and Webb, 1998;

Anderson and Smith, 1999; Weller, 1999; Naugle et al., 2000). As well, they have

diverse diets with many being herbivorous or omnivorous, preferring such foods as

seeds, fruit, invertebrates, amphibians, and small mammals (Gonzalez et al., 1996;

Anderson et al., 1996; De Szalay and Resh, 1997; Davis and Smith, 1998; Anderson

and Smith, 1999; Weller, 1999).

Like many avian species, anurans rely exclusively on wetlands (Michael and

Smith, 1985; Dodd and Cade, 1998; Lehtinen et al., 1999; Semlitsch, 2002),

specifically for hibernation, foraging, breeding, and interspersion habitat for different

life stages. In turn, anuran populations provide insight into water quality and

temporal variations in hydrology (Beattie and Tyler-Jones, 1992; Anderson et al.,

1999a; Semlitsch, 2002). While anurans often feed on numerous invertebrate species

(Anderson et al., 1999b; Lima and Magnusson, 2000), they are an important food

source for numerous other invertebrates and vertebrates alike (Bridges, 1999;

Lardner, 2000), thus making them a valuable link in a complex food web (Weller,

1999).

The development of wildlife habitat models is important because researchers

must often assign relative values to habitat to support objectives for mitigation. Some

models that have been created include the Wetland Evaluation Technique (Adamus,

1983; Adamus and Stockwell, 1983), Habitat Assessment Technique (Cable et al.,

1989), and the Avian Richness Evaluation Model (Adamus, 1993). Species-specific

models commonly used today are the Habitat Suitability Index (HSI) models

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developed by the U.S. Fish and Wildlife Service (1981). Based on natural history

requirements for a particular species, these models use habitat parameters considered

pertinent to a species survival to calculate an index ranging from 0 to 1 (a 1 represents

optimal habitat). Depending on the HSI model, the habitat parameters evaluated may

have significant implications for other wildlife taxa as well, which can provide further

insight into overall habitat quality for wildlife for a given area.

Only 2 studies have evaluated the success of mitigation wetlands in West

Virginia, and 1 of them (R.H. Fortney, West Virginia University unpublished report)

excluded an evaluation of invertebrates while the other exclusively evaluated

production of only 1 invertebrate taxa in 1 constructed wetland (Johnson et al., 2000).

As such, there is a need to evaluate the current ability of mitigation wetlands in the

mid-Appalachians, and in particular West Virginia, to support diverse vegetation and

wildlife communities. Likewise, to maintain the significant role wildlife plays in the

development of wetland ecosystems across this region, there is a need to identify

wetland habitat characteristics that are associated with wildlife distribution and

abundance. Therefore, researchers can develop adequate monitoring protocols and

construct future wetlands that are compatible with wildlife proliferation. The

objective of this study was to determine which wetlands were best and to determine

why wildlife were distributed in which wetlands. In doing so, I sought to attribute

specific characteristics in wetland habitat with trends in wildlife abundance across

wetlands. Specifically, avian and anuran communities, as well as habitat quality for 8

wetland-dependent wildlife species were evaluated. To supplement this evaluation,

vegetation and invertebrate communities also were assessed. This study was

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designed to assist in the creation of future monitoring protocols for mitigation

wetlands in West Virginia and to guide in the development of future mitigation

projects with the highest probability of success.

METHODS

Study sites

West Virginia can be classified into 3 regions (Fenneman, 1938). The

unglaciated Western Hill section is the largest province in West Virginia, and

includes the Appalachian Plateau between the Ohio River and the mountainous area

to the east. Most of the hills in the northern and western portions of the state are

≤450 m in elevation. Southern sections of this region, however, reach elevations

≥900 m and can exceed 1000 m. The Allegheny Mountain section includes the high

mountains that lie in the Cheat River system and in the headwaters of the North

Branch of the Potomac River. This section contains the highest elevations in West

Virginia with many ridges reaching between 1,200 m and 1,375 m in elevation. This

section contains the Allegheny Mountains that extend northward from West Virginia

into western Maryland and central Pennsylvania. The Ridge and Valley region is

located east of the Allegheny Front, and is drained primarily by the Potomac River.

This region is a lowland area that, as its name implies, contains numerous

interspersed ridges that form a narrow belt along the eastern margin of the state. The

elevation of valley floors ranges from 300 to 400 m with ridges reaching ≥1,219 m in

elevation.

Eleven mitigation wetlands were evaluated in this study: Walnut Bottom,

VEPCO, Buffalo Coal, Elk Run, Leading Creek, Sugar Creek, Sand Run, Triangle,

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Trus Joist MacMillan, Enoch Branch, and Bear Run. These wetlands were created or

restored as compensation for wetland losses sustained for different human activities

including highway development, facility construction, and mining. Almost every

mitigation site was located near some form of human disturbance. In fact, many are

located adjacent to roads with moderate to heavy traffic. A minimum standardized

time of development of 5 years was chosen for all sites. Wetlands ranged in age from

5 - 21 years ( x = 10.0, SE = 1.7; Table 1) and ranged in elevation from 265 -1036 m

( x = 586, SE = 75.9). Size ranged from 3.0 - 9.5 ha ( x = 5.8, SE = 0.80). All

mitigation wetlands were classified as palustrine emergent or unconsolidated bottom

(Cowardin et al., 1979).

Four naturally occurring reference wetlands were selected for comparisons

with mitigation wetlands: Altona Marsh, Elder Swamp, Meadowville, and Muddlety.

Each reference wetland represented a geomorphic setting (as described above) within

the state and was selected relative to mitigation wetlands within that setting. Hence,

within each of 4 areas, reference wetlands were selected based on their similarity in

hydrology and structure to respective mitigation wetlands. All were located within

similar basins or watersheds of respective constructed sites. Since reference wetlands

were considerably larger than mitigation sites, only portions, when feasible,

comparable in size to constructed sites were used for study. Reference sites ranged in

elevation from 170 -1000 m ( x = 582, SE = 169.5; Table 1) and ranged in size from

6.5 - 28.0 ha ( x = 15.1, SE = 4.7. All reference wetlands were classified as

palustrine emergent or scrub-shrub wetlands (Cowardin et al., 1979). Detailed

descriptions of mitigation and reference wetlands are provided in Chapter I.

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Vegetation community sampling

I conducted vegetation sampling in June and July of 2001, and in July of

2002. Sampling was conducted according to techniques incorporated by Stephenson

and Adams (1986). Plant communities were stratified based on distinct communities

present, and representative communities were sampled using permanently marked

0.05 ha quadrats (25 × 20 m). At each wetland, at least 1 quadrat was used to sample

each distinct plant community. Within each quadrat all live stems of trees (≥ 10 cm

diameter at breast height, DBH) and small trees (2.5 to 9.9 cm DBH) were measured

at dbh and counted to species. In addition, saplings (individuals < 2.5 cm DBH but ≥

1.0 m tall) were counted. Within each 0.05 ha quadrat, 2 5.0 × 5.0 m plots were

placed evenly along the center line of the transect. Within these plots, seedlings

(individuals > 10 cm but less than < 1.0 m tall) and shrubs (including woody vines)

were counted to species. Five 1.0 × 1.0 m plots were placed along the same center

line. Within these plots, small seedlings (individuals ≤ 10 cm tall) were counted to

species. In addition, percent cover of herbaceous plants, exposed substrate, woody

debris, and bryophytes were recorded within 1.0 × 1.0 m plots. Detailed

descriptions of vegetation community sampling are provided in Chapter II.

Wetland delineation

Wetland boundaries were determined using recent aerial photos (1.0 m

resolution) taken by the West Virginia Natural Resources Analysis Center (NRAC)

during leaf off in 2001 and 2002 and by using ground truth data collected during

mapping of dominant vegetation communities. Boundaries were outlined according

to the presence and distribution of hydrophytic vegetation communities and mapped

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using Geographic Information Systems (GIS) and ArcView software (Chapter II). If

recent aerial photography was unavailable, wetland boundaries were digitized on

1996-1997 digital ortho-quarter quads (DOQQs) obtained from the West Virginia

Department of Environmental Protection (DEP). The objective of wetland boundary

determination was to compare current wetland size (ha) with sizes required by

permits issued by the U.S. Army Corps of Engineers and West Virginia Division of

Natural Resources. As well, dry areas were measured within wetland basins in order

to assess the percentage of wetland area actually existing within the basin.

Invertebrate sampling

I conducted invertebrate sampling according to Anderson and Smith (1996,

2000) during the summers of 2001 and 2002. Specifically, I collected 620 samples in

July and September of 2001 and another 620 samples were collected in April and

June of 2002. Samples were taken at different times both years to maximize

representative taxa. Wetlands were stratified based on wetland classification

(Cowardin et al., 1979), and specimens were collected at 10 random points within

open water, emergent, and scrub-shrub (if they existed) areas of each wetland. At

each point, I used a 5 cm diameter core (15 cm deep) and a 7.5 cm diameter water

column sampler (Swanson, 1983) to collect nektonic and benthic specimens,

respectively. Water column samples were sieved in the field using a 500-micron

sieve (Huener and Kadlec, 1992) and preserved in 70% ethanol. Benthic samples

were placed in bags, refrigerated, and processed within 10 days of collection

(Anderson and Smith, 2000). Biomass was obtained by oven-drying samples at 55°C

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for ≥48 hours to a constant mass and using an analytical scale. Details of

invertebrate sampling methodologies are provided in Chapter III.

Avian and anuran communities

I evaluated avian communities by sampling breeding bird populations using

point count (0.78 ha plots) surveys (Ralph et al., 1995). I visited wetlands twice

between late May and late June, 2001 and 2002, when breeding birds were most

active. I conducted 10-min point counts that occurred between 30 min before sunrise

and 1000 hours, under acceptable weather conditions (Ralph et al., 1995). I evaluated

anuran communities using nocturnal call count surveys that followed standardized

protocols developed by the U.S. Fish and Wildlife Service (Casey and Record,

unpublished data). To account for temporal breeding differences between species,

each wetland was visited once during the months of March, April, and May, 2001 and

2002. I collected data for 3 minutes at each sampling point following a 1-2 min

settling period. Frogs were identified to species and evaluated relative abundances by

assigning a Wisconsin Index value of intensity to each species� call (Mossman, 1994).

Detailed descriptions of avian and anuran sampling schemes are included in Chapter

IV.

Habitat quality

Habitat quality was assessed using species-specific Habitat Suitability Index

(HSI) models. The models chosen had broad taxonomic coverage and included 1

reptile (snapping turtle, Chelydra serpentina, Graves and Anderson, 1987), 1

amphibian (red-spotted newt, Notophthalmus virdescens, Sousa, 1985), 3 mammals

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(beaver, Castor Canadensis, Allen, 1983; muskrat, Ondatra zibethicus, Allen and

Hoffman, 1984; mink Mustela vison, Allen, 1984), and 3 bird species (1 wading bird:

great blue heron, Ardea herodias, Short and Cooper, 1985; 1 waterfowl species: wood

duck, Aix sponsa, Sousa and Farmer, 1983; 1 passerine: red-winged blackbird,

Agelaius phoeniceus, Short, 1985). All evaluated species had wide distributions

throughout West Virginia, and possessed life-history components (i.e., foraging,

reproduction, and interspersion) that were compatible with habitat features present in

the wetlands selected for this study. Numerous methodologies were incorporated in

quantifying the 38 variables encompassing the 8 models (see Chapter IV).

Statistical analyses

Vegetation metrics (species richness, diversity, and evenness were calculated

using PC-ORD software (McCune and Mefford, 1999) for each of 45 and 15 quadrats

within mitigation and reference wetlands, respectively. Metrics were calculated for

all species and for native species only. Species diversity was calculated using the

Shannon Index (Shannon and Weaver, 1949). Average cover was calculated for each

species and totaled to get a total coverage for each plot. These values were averaged

to obtain mean total coverage for each wetland. Each herbaceous species was

assigned a wetland indicator status value (WIS): Obligate = 1, Facultative Wetland =

2, Facultative = 3, Facultative Upland = 4, and Upland = 5 (U.S. Fish and Wildlife

Service, 1996). From coverage and WIS values, mean weighted averages (Carter et

al., 1988; Wentworth et al., 1988, and Atkinson et al., 1993) were calculated based on

the following formula:

WA = (y1u1 + y2u2 + ��.ymum)/100

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where y1y2 = relative basal area (trees and small trees) or relative cover estimates

(herbaceous plants) for each species, and u1u2 = the WIS for each species (Atkinson et

al., 1993).

Species richness was calculated for avians and anurans by averaging the total

number of species observed in each sampling plot per wetland. Invertebrate richness

was calculated in a similar manner, but taxa were classified only to family. Avian

abundance was calculated by averaging the total number of individuals observed in

each sampling plot per wetland. Similar to vegetation diversity, avian and

invertebrate diversity was calculated using the Shannon Index. Anuran abundance

was calculated separately both by Wisconsin Index calling intensity values of

particular species (Mossman 1994), and by actual estimations of calling individuals.

Details involving ranking classifications and abundance estimations are provided in

Chapter IV. Invertebrate density and biomass were calculated for both benthic and

nektonic samples separately.

For the purposes of this study, metric means were not compared between

mitigation and reference wetlands. A detailed account of statistical mean

comparisons between vegetation, invertebrate, and wildlife communities is provided

in Chapters II, III, and IV, respectively. Instead, metric means for each wetland were

ranked on a scale of 1 to 15 based on observed means of each wetland relative to

other mitigation and reference wetland means. A rank of 1 was given to wetlands that

scored the best or highest value for a particular metric, whereas a 15 was given to

wetlands that scored the worst or lowest value relative to other evaluated wetlands.

Wetlands with similar means were averaged and ranked the same number, so in some

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instances, scales may not extend all the way to 15. Separate ranks were calculated

individually for vegetation, invertebrate, avian, and anuran communities, as well as

for habitat quality in order to gauge the relative success of individual wetlands in

supporting a particular community. Furthermore, an overall rank representing means

across all metrics were assigned to each wetland.

Vegetation ranking was based on combining ranks for species richness,

evenness, diversity, and weighted averages (Table 2). Overall avian ranks were

calculated by averaging total species richness, diversity, and abundance ranks, as well

as abundance ranks for waterbirds, waterfowl, and passerines (Table 3). Overall

anuran ranks were based on mean rankings of total species richness, Wisconsin Index

(WI) value, and abundance, as well as WI and abundances for the 7 frog species

sampled (Table 4). These species included spring peeper (Psuedacris crucifer), gray

treefrog (Hyla chrysoscelis), American bullfrog (Rana catesbeiana), wood frog (Rana

sylvatica), green frog (Rana clamitans), American toad (Bufo americanus), and

pickerel frog (Rana palustris). Overall invertebrate ranks represented combined

rankings of familial richness, diversity, density and biomass for nektonic and benthic

samples (Table 5). Habitat Suitability Index (HSI) ranks were based on mean ranks

for all 8 species evaluated (Table 6). A completely randomized Analysis of Variance

(ANOVA) model followed by the Tukey�s (HSD) Honestly Significantly Difference

test was used to test for differences among individual wetland rank means.

Assumptions of normality were tested with the univariate procedure in SAS, and

Levene�s Test was used for homogeneity of variances. These analyses were

performed using SAS (SAS Institute, 1988).

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I used Canonical Correspondence Analysis (CCA; ter Braak, 1986), using PC-

ORD software to correlate environmental variables to avian, anuran, and invertebrate

abundance. Canonical Correspondence Analysis is a multivariate direct ordination

method that performs a least-squares linear regression of environmental variables on

site (wetland) scores determined through correspondence analysis (Gauch, 1982).

Species are ordered on axes constrained by linear combinations of environmental

factors. The eigenvalues associated with each axis indicate the relative ability of the

axis to order or separate species distributions. Intraset correlation coefficients

represent the strength of environmental variables in structuring the ordination.

Ordination diagrams (joint plots) are interpreted by viewing the distribution of

species around environmental vectors. Species are plotted based on the relative value

of weighted averages along a particular axis. Thus, the closer a species is to a

particular vector or axis, the more closely associated it is to that variable (ter Braak

1986). In addition, the length of each vector is a measure of how much species

distributions differ along that environmental variable. Hence, longer vectors

represent more important environmental variables.

I ordinated avian, waterbird, and anuran abundances across all 15 wetlands to

5 environmental variables: % emergent vegetation, % open water, vegetation

diversity, benthic invertebrate diversity, and nektonic invertebrate diversity.

Abundances also were ordinated across mitigation sites only to 7 environmental

variables: age, size, % emergent vegetation, % open water, vegetation diversity,

benthic invertebrate diversity, and nektonic invertebrate diversity. Invertebrate

abundance was ordinated across all 15 wetlands to 4 environmental variables: %

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emergent vegetation, % submergent vegetation, % open water, and vegetation

diversity. Similarly, invertebrate abundance was ordinated across mitigation sites

only to 6 environmental variables: age, size, % emergent vegetation, % submergent

vegetation, % open water, and vegetation diversity. Only species present in ≥ 10%

of wetlands were used in this analysis due to the potential negative effect of outliers

(Gauch, 1982). I used eigenvalues, percentage of variation explained in species data,

and intraset correlations of environmental variables to each axis to assess the relative

importance of environmental variables in structuring species composition. A Monte

Carlo simulation (McCune and Mefford 1999) with 1000 permutations was used to

test the null hypothesis that there was no relationship between species and

environmental matrices (P = 0.05). Although P values were reported for all 3 axes,

the significance of correlations between matrices was determined only by axis 1 P

values because this axis accounted for the most variation in all analyses (B. McCune,

Oregon State University personal communication).

RESULTS

Wetland rankings Total mean ranks combining vegetation, anuran, avian, invertebrate, and

habitat rankings were similar between all wetlands (F14,60 = 1.26, P = 0.260; Table 7).

Nonetheless, Leading Creek, Trus Joist MacMillan, Triangle, Walnut Bottom, and

Elk Run scored the lowest (best) 5 overall ranks of all wetlands (Table 7). Triangle

and Trus Joist MacMillan scored similar ranks, as did Walnut Bottom and Elk Run.

The lowest overall rank was assigned to Leading Creek whereas the fourth and fifth

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lowest were Walnut Bottom and Elk Run. On the contrary, Elder Swamp,

Meadowville, Sugar Creek, Altona Marsh and Sand scored the 5 highest (worst)

ranks, with Elder Swamp scoring the highest rank of all wetlands. Altona Marsh and

Sand Run scored similar scores. The other 3 wetlands scored ranks in the middle.

The remaining results below are presented in a similar manner as above using the

same scales.

Vegetation rankings were significantly different among the best and worst

wetlands (F14,75 = 6.66, P < 0.001; Table 7). VEPCO, Elk Run, and Trus Joist

MacMillan scored lower (better) vegetation ranks than Sugar Creek, Muddlety,

Altona Marsh, and Meadowville, which scored the highest (worst) vegetation ranks.

Enoch Branch and Sand Run also scored relatively low ranks, but these were only

statistically lower than Muddlety and Sugar Creek.

Invertebrate rankings also were different among the best and worst wetlands

(F14,105 = 5.15, P < 0.001; Table 7). Walnut Bottom, Triangle, Elk Run, and Altona

Marsh ranks were significantly lower than Elder Swamp, Enoch Branch, and VEPCO.

Bear Run also scored a low rank, which was significant only to Elder Swamp and

Enoch Branch.

Avian rankings were different among the best and worst wetlands as well

(F14,75 = 3.03, P = 0.001; Table 7). Trus Joist MacMillan, Elk Run, and Walnut

Bottom scored ranks significantly lower than the worst wetlands, Elder Swamp and

VEPCO. Although not significant, Buffalo Coal and Leading Creek scored fourth

and fifth lowest ranks while Enoch Branch and Sugar Creek scored the third and

fourth highest ranks.

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In addition, anuran ranks were different among the best and worst wetlands

(F14,240 = 5.13, P < 0.001; Table 7). The wetlands with the 2 lowest ranks, Enoch

Branch and Leading Creek, were statistically lower than the wetlands with the 2

highest ranks, Altona Marsh and Meadowville. Although results were not significant,

Walnut Bottom, Buffalo Coal, and Muddlety scored the next lowest anuran ranks of

all wetlands. Similarly, next to Altona Marsh and Meadowville, VEPCO, Elk Run,

and Bear Run scored the next highest anuran ranks of all wetlands.

Habitat Suitability Index ranks were similar among all wetlands (F14,105 =

1.76, P < 0.055; Table 7). Nonetheless, Leading Creek, Altona Marsh, Muddlety,

VEPCO, Sugar Creek, and Triangle scored the lowest ranks and Sand Run, Bear Run,

Elk Run, Meadowville, and Buffalo Coal scored the highest habitat ranks.

Canonical Correspondence Analysis The Monte Carlo simulation of all 3 axes indicated that environmental

variables predicted species all taxa abundance no better than sets of scores randomly

assigned to samples, both for all wetlands and for mitigation sites only. The

probabilities of achieving the relationships by chance for all avians, waterbirds,

anurans, benthic invertebrates, and nektonic invertebrates are provided in Tables 8-

12, respectively. Ordination diagrams of species distributions and environmental

variables (vectors) for all avians (all wetlands: Figure 1; mitigation wetlands: Figure

2), waterbirds (all wetlands: Figure 3), anurans (all wetlands: Figure 4; mitigation

wetlands: Figure 5), benthic invertebrates (all wetlands: Figure 6; mitigation

wetlands: Figure 7), and nektonic invertebrates (all wetlands: Figure 8; mitigation

wetlands: Figure 9). Species and environmental codes for all avians and waterbirds,

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anurans, benthic invertebrates, and nektonic invertebrates are provided in Tables 13-

15. Common and scientific names for avians and anurans are presented in Appendix

52.

Wetland delineation Wetland boundaries of all study sites are presented in Chapter II in conjuntion

with maps of dominant vegetation communities. Information on the sizes of wetlands

as required under permits issued for compensatory mitigation could only be obtained

for Buffalo Coal and Elk Run. According to permits, Buffalo Coal and Elk Run were

required to be 12.1 ha and 6.1 ha, respectively. The current estimated size of these

sites as determined through methods aforementioned was 9.0 ha and 3.8 ha,

respectively. Although permit requirements on wetland size were unable to be

obtained for the remaining 9 mitigation wetlands, mitigation plans indicating size

specifications for construction were obtained for VEPCO and Trus Joist MacMillan.

According to GAI Consultants Inc (1993), the intended size of VEPCO at time of

construction was 7.8 ha. Similarly, Montgomery Watson (1996) reported the

restoration of >2.4 ha of wetlands for Trus Joist MacMillan. Current estimated sizes

of VEPCO and Trus Joist MacMillan were 7.0 ha and 3.2 ha, respectively.

Seven of 11 mitigation wetlands were wet across all or most of the wetland

basin. The amount of existing dry areas within the basins were significant for only 4

mitigation wetlands: Elk Run, Leading Creek, Sugar Creek, and Trus Joist

MacMillan. These wetlands contained dry areas of 1.0, 2.0, 1.0, and 1.2 ha,

respectively. Using the estimated sizes of delineated wetlands (Chapter II), the

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percentage of the wetland basins that were actually wet was 79.2, 81.4, 87.2, and

72.7%, respectively for these wetlands.

DISCUSSION

Wetland rankings Mitigation wetlands generally scored higher overall ranks than reference

wetlands, with reference wetlands scoring ranks in the middle. These ranks reflect

the general trend of higher vegetation and wildlife metrics in mitigation than

reference wetlands observed in Chapters II-IV.

Despite moderate vegetation and invertebrate rankings, Leading Creek scored

the lowest (best) overall rank of all wetlands evaluated. Indeed, this site scored

among the best sites in avian and anuran rankings and actually scored the best HSI

rank of all sites. Leading Creek scored number 1 rankings for beaver, great blue

heron, wood duck, snapping turtle, and red-spotted newt models. Variables that

attributed to these results are provided in Chapter IV, but surrounding trees and

shrubs definitely contributed to this statistic. Leading Creek provided excellent

combinations of large size and habitat heterogeneity for avians and anurans. In

addition to artificial nest boxes, this site contained numerous artificial and natural

perching structures that likely attributed to avian diversity. As well, it contained

well-balanced percentages of open water and emergent vegetation.

Triangle and Trus Joist MacMillan scored the next best ranks of all wetlands.

Triangle provided a heterogeneous environment with varying hydrologic regimes

along complex gradients. Although Triangle contained less than optimum amounts of

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open water, it did contain moderate amounts of shrub cover and abundant submerged

aquatic vegetation. As such, it scored the second best invertebrate rank (next to

Walnut Bottom) and the fourth best habitat quality rank of all wetlands. Avian and

anuran ranks were moderate. This site should be monitored closely for potential

impacts by beaver and the adjacent major highway. Trus Joist MacMillan scored a

similar overall rank to Triangle. Despite poor anuran and habitat ratings, Trus Joist

MacMillan scored the best avian rank and the third best vegetation rank of all

wetlands. The moderate anuran rating was likely attributed to predatory fish, and

perhaps even to sampling bias caused by the loud factory nearby, which interfered

with the ability to hear some individual�s calls. A major contributing factor to such a

good avian ranking could be the number of snags present throughout the eastern,

open-water portion of the wetland. Numerous birds were observed utilizing these

snags for nesting, foraging, or perching. Indeed, many studies have revealed the

importance of snags to avians (Hudman and Chandler, 2002; Bell and Whitmore,

2000; North et al., 2000). This site also scored the best beaver and wood duck HSI

rankings of all wetlands. Numerous variables contributed to this result (Chapter IV).

Unfortunately, this wetland was used quite extensively for recreation. Tracks from

All Terrain Vehicles (ATVs) were observed on multiple occasions both in and around

the wetland. It also is moderately fished. Considering the value of this wetland to

wildlife, I recommend fencing off this wetland to prevent further structural damage.

Another potential problem for this site is beaver. A breached beaver dam on the

eastern outflow has significantly impacted the hydrology at this site, and without

proper mitigation, this site may continue to desiccate at an alarming rate.

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Walnut Bottom and Elk Run scored similar ranks above Triangle and Trus

Joist MacMillan. Walnut Bottom is not only the largest of all mitigation wetlands, it

provides a heterogeneous environment (despite one of the highest vegetation

rankings) composed of multiple open water and emergent cells of varying shape and

sizes. It also is one of the most isolated of all sites (next to Bear Run), and contains

abundant submerged aquatic vegetation, hemimarsh conditions, variable water

depths, and snags. As a result, this site scored the best invertebrate ranking, and the

third best anuran and avian rankings. Because this site contains 3 cells on a gradient

separated by culverts, it may be compatible with moist-soil management. One

negative aspect of this site is its landscape position. Because Walnut Bottom is

located in an agricultural landscape with minimal surrounding shrub and tree

coverage, this site scored a moderate HSI ranking due to lack of food and cover for

beaver and mink. This site also may suffer from negative affects associated with

agricultural run-off (Chapter IV). Elk Run, like Trus Joist MacMillan, scored a poor

anuran rank, probably due to predatory fish and low amounts of emergent vegetation

(Chapter IV). But this site also contained abundant open water with numerous snags,

and was positioned immediately adjacent to a forest. As such, it scored the second

best avian rank of all sites, along with the third best invertebrate rank. Elk Run

scored the second best vegetation rating of all wetlands, which was unexpected

considering this wetland is one of the oldest of all sites and is essentially a large pond

containing hydrophytic vegetation only along the perimeter. As such, a low mean

weighted average was expected, but considering that only 1 vegetation plot was

established on the lower cell and no sampling replicates existed for this site,

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conclusions regarding vegetation establishment should be made with caution. This

clearly shows that vegetation rankings can provide misleading conclusions regarding

the successful establishment of vegetation communities.

Environmental data

Canonical Correspondence Analysis yielded weak correlations between

species and environmental data throughout all taxa analyzed. Some factors that may

account for such weak correlations include species dominance overriding

environmental factors, factor interactions, unmeasured variables, and chance

(Kazmierczak et al., 1995). I believe that a larger sample size would have revealed

the importance of these variables. Although statistical significance did not emerge

regarding wetland habitat characteristics, it is clear that these attributes play a large

role in structuring wildlife communities (Chapters II-IV). Indeed these data indicate

that size, as well as percent emergent vegetation, submerged aquatic vegetation, open

water, and shrub cover, in addition to the presence of snags and artificial nesting and

perching structures, may play important roles in determining the habitat quality for a

variety of communities in the wetlands I evaluated. Wetland size is known to affect

overall avian richness (MacArthur and Wilson, 1967; Tyser, 1983; Delphey and

Dinsmore,1993). In addition, percent emergent vegetation is known to affect

waterbird and waterfowl distribution (Kaminski and Price, 1981; Bookhout et al.,

1989; Murkin et al., 1997), as well as anuran abundance (Stumpel and Van Der Voet,

1998). Other studies have linked invertebrate community structure to quality and

quantity of aquatic vegetation (Brown et al., 1988; Wilcox, 1992; Streever et al.,

1995; Zimmer et al., 2000), including submergent vegetation (Carpenter and Lodge,

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1986). My study, however, found no such links between wildlife distribution and

abundance and environmental factors.

A look at wildlife population trends within the wetlands themselves provides

evidence of the importance in constructing wetlands with specific habitat attributes to

enhance wildlife colonization and proliferation. For instance, Bear Run consisted of

12 semipermanently flooded to permanently flooded ponds separated by a series of

dikes, and there was a clear difference in vegetative structure between southern and

northern cells. While the northern cells were mainly open water ponds, the 3 upper

cells to the southeast were dominated by emergent vegetation consisting of cattail

(Typha latifolia) and spikerush (Eleocharis quadrangulata). It was clear that frogs

and invertebrate, particularly nektons, utilized the 3 upper cells more frequently. This

contention is supported in Chapter III by results that showed much higher invertebrate

abundances in emergent areas. However, a statistical evaluation of anurans was

unable to be conducted because of difficulty in distinguishing anuran calls from open

water and emergent areas within individual cells. Similar results were obtained at

Sand Run, where a clear border exists between a large open water area to the west

and an area dominated by emergent vegetation (i.e., Juncus effusus) to the east.

Furthermore, although no statistical significance emerged correlating

emergent vegetation to anuran abundance, a trend did appear to exist in correlating

these 2 variables. For example, with the exception of VEPCO, the wetlands with the

poorest rankings (i.e., Altona Marsh, Meadowville, Bear Run, Sugar Creek, and Elk

Run) fell at the extreme ends of the spectrum with regards to percent emergent

vegetation (i.e., ≤ 22.3 or ≥ 81.0) One variable that was not quantified was the

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amount of snags present among wetlands. Indeed, the 2 wetlands that scored the best

avian ranks (Trus Joist MacMillan and Elk Run) were the only 2 wetlands that

contained abundant snags. These data, combined with those data presented in

Chapters II-IV show trends in habitat characteristics that contribute to wildlife

colonization and proliferation. These trends are incorporated into habitat

management recommendations for future mitigation wetlands (Chapter IV).

Mitigation success The wetland rankings outlined above provide an objective view into the

success of individual mitigation sites in performing ecological functions relative to

one another. As mentioned, Leading Creek, Trus Joist MacMillan, Triangle, Walnut

Bottom, and Elk Run scored the best overall ranks of all wetlands. For the most part,

I agree with results from wetland ranks regarding the success of individual wetlands.

However, using best professional judgement in conjuntion with wetland ranks, I have

created a list of what I think are the most successful mitigation wetlands. The

following is a list of all 11 mitigation sites in order from most successful (best) to

least successful (worst): Walnut Bottom, Buffalo Coal, Leading Creek, Enoch

Branch, Triangle, Sugar Creek, Trus Joist MacMillan, Bear Run, Elk Run, VEPCO,

and Sand Run. The rationale behind this list lies mostly with specifications on size,

heterogeneity, and disturbance. For instance, larger, more heterogeneous wetlands

with fewer disturbances were more successful than smaller, more monotypic wetlands

(i.e. too much open water or emergent vegetation, or lacking diverse hydrologic

gradients). In creating this list, I also prioritized these specifications into what I

thought were most important in determining the success of mitigation wetlands. For

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example, heterogeneity is more important than size, which is more important than

disturbance. Besides Trus Joist MacMillan and Elk Run, these specifications were

fairly accurate in predicting the positions of individual wetlands along the rank

spectrum (i.e., larger, more heterogeneous wetlands scored better ranks).

The success of individual wetlands from an area perspective, as opposed to

ecological function, was not determined for most mitigation sites because issuing

permits and mitigation plans were unavailable. Both Buffalo Coal and Elk Run area

determinations fell short of size requirements outlined in permits issued by the U.S.

Army Corps of Engineers. VEPCO, too, fell short of size projections according to

mitigation plans, but only slightly. Trus Joist MacMillan was the only wetland out of

the 4 to meet area requirements, at least according to the wetland mitigation plan.

Due to lack of available information on size specifications, it is difficult, to gauge the

relative success of individual wetlands in meeting size requirements. Although this

information would be important from a regulatory standpoint, it yields little insight

into functional success of a particular wetland relative to other sites.

Conclusions

An underlying assumption with respect to evaluating the success of mitigation

wetlands based on vegetation and wildlife rankings, is that first, all ranks are

weighted equally. Of course, some components may be more important than others

and should therefore be weighted more heavily. For instance, overall avian and

anuran species abundances are weighted similar to individual or guild species

abundances. Although total species abundance could be weighted more heavily since

it represents a combination of all species observed, it would be difficult to calibrate

260

the value of metrics accurately, and thus, would lead to spurious results. Hence,

metrics were weighted equally, and despite the implicit error in this assumption,

comparisons can still be made as to the relative success of mitigation wetlands in

supporting wildlife communities.

Another assumption of these analyses is that wetlands that scored lower ranks

were �better� or �more successful� than wetlands that scored higher ranks. An

important aspect to consider is development time. These data provided insight into

the community dynamics of these mitigation wetlands at only one point in time.

Based on results obtained in Chapter II, it was clear that development time affects

vegetation community structure and composition, and these results are reflected in the

ranks assigned to individual wetlands. Specifically, 3 of 4 reference wetlands scored

among the highest vegetation ranks of all 15 wetlands, which reflects the lower

species richness and diversity values observed in reference wetlands in Chapter II.

Two of the 4 wetlands (Elder Swamp and Meadowville) scored the lowest rankings

for all metrics combined. An evaluation of these wetlands in 10 or 20 years may

yield entirely different rankings all together as autogenic and allogenic factors

influence vegetative structure and composition, and hence, wildlife distribution and

abundance. Thus, I do not think that poor rankings of reference wetlands reflects

inadequate selection of reference wetlands. I Nonetheless, these data provide

researchers with a current index of the success of mitigation wetlands in West

Virginia in supporting wildlife communities.

The strength of the overall index rankings lies in the comprehensive nature of

the ranks themselves. By combining vegetation, invertebrates, avians, and anurans,

261

researchers are provided with a comprehensive view of the ecological functions of

these wetlands. This allows researchers to document trends in wetland structure that

improve general habitat quality for wildlife, or to assess more specific trends that

contribute to improving habitat quality for one particular taxa (i.e., anurans). This

provides more latitude in creating management objectives for constructed wetlands.

Specifically, if future mitigation efforts focus on replacing anuran habitat, as opposed

to general wildlife habitat, one could look for correlations between anuran

distribution and abundance and wetland structure. The anuran rankings provided in

this study could be applicable in such a scenario.

Future research is needed to provide researchers with a clearer understanding

of the dynamics involved in creating mitigation wetlands with high quality wildlife

habitat. Based on a literature review and data presented in this study, I compiled a list

of future research needs in order of importance to assist in the construction and

evaluation of future mitigation wetlands:

1) Identify site-specific wildlife habitat lost to wetland destruction and

implement mitigation ratios that reflect habitat quantity and quality.

2) Determine the effect of dispersal corridors and constructed wetland

size on wildlife distribution and abundance.

3) Compare wildlife communities of mitigation banking systems to

those in isolated constructed wetlands.

4) Study the effects of moist soil management on vegetation and

invertebrate production in constructed wetlands.

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5) Study the effects of agricultural and road run-off on water quality in

wetlands constructed adjacent to agricultural fields and roads,

respectively.

6) Examine the effects of native vegetation plantings on constructed

vegetation community structure.

7) Evaluate recruitment of amphibians in constructed wetlands via

larval sampling or egg mass surveys.

The mitigation wetlands created in West Virginia currently act as good

models for future wetland development. My data showed that, overall, the ecological

function these wetlands performed was at or near reference standards. I hope

researchers will incorporate management recommendations provided throughout this

thesis into future mitigation wetlands. As well, I hope future studies outlined above

will be undertaken to enhance our knowledge of wetland ecosystems, thus ensuring

the compensation of wildlife habitat lost to wetland destruction and preserving the

integrity of wetland ecosystems for years to come.

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274

CHAPTER V

TABLES

275

Table 1. List of 11 mitigation and 4 reference wetland study sites in West Virginia, including site name, year constructed, size

(ha), source builder, Universal Transverse Mercator (UTM) coordinates, 7.5 minute quadrangle, basin, and watershed, 2001-

2002.

Site name Year Size (ha) Source UTM Y UTM X Quad Basin Watershed

Mitigation Sites Walnut Bottom 1997 9.5 Division of Hwys 4334210 673914 Old Fields S. Branch of Potomac R. S. Branch of Potomac R. VEPCO 1995 7.0 VA Electric Power 4337900 641300 Mt. Storm Cheat River Blackwater River Buffalo Coal 1981 9.0 Davis Trucking Co. 4332100 630900 Davis Cheat River Blackwater River Elk Run 1981 3.8 Island Crk Coal Co. 4342000 636250 Davis N. Branch of Potomac R. Elk Run Leading Creek 1995 8.6 Division of Hwys 4321563 602550 Montrose Tygart Valley Leading Creek Sugar Creek 1995 6.8 Division of Hwys 4328850 591470 Belington Tygart Valley Laurel Creek Sand Run 1992 3.0 Division of Hwys 4315060 573140 Buckhannon Tygart Valley Sand Run Triangle 1992 3.1 Division of Hwys 4316950 568500 Buckhannon Tygart Valley Buckhannon River Trus Joist MacMillan 1994 3.2 TJM Timber Co. 4318340 569560 Century Tygart Valley Buckhannon River Enoch Branch 1997 3.4 Division of Hwys 4247300 514550 Widen Gauley River Muddlety Creek Bear Run 1993 6.2 WV Dept Env. Prot. 4305780 519750 Glenville Little Kanawha Little Kanawha

Reference Sites Altona Marsh N/A 15.2 N/A 4353000 768600 Middleway Shenandoah River Shenandoah River Elder Swamp N/A 28.0 N/A 4340000 642200 Mt. Storm Lake Cheat River Blackwater River Meadowville N/A 6.5 N/A 4330920 593940 Nestorville Tygart Valley Laurel Creek Muddlety N/A 10.4 N/A 4248480 516790 Widen Gauley River Muddlety Creek

276

Table 2. Actual means and ranks of vegetation richness (no.species/plot), evenness, evenness (native species only), diversity,

diversity (native species only), and weighted average, as well as total mean and scaled ranksa for 11 mitigation and 4 reference

wetlands in West Virginia, 2001-2002.

Mitigation Wetlands

Walnut Bottom VEPCO

Buffalo Coal Elk Run

Leading Creek

Sugar Creek

Sand Run Triangle

Trus JoistMacMillan

Enoch Branch

Bear Run

x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE Richness 8.8 2.3 15.0 1.7 9.3 1.2 16.0 4.2 14.8 3.4 13.8 4.3 11.8 4.5 16.2 3.3 19.5 4.9 10.8 3.1 8.5 0.5 Rank 11.0 4.0 10.0 3.0 5.0 6.0 7.0 2.0 1.0 9.0 13.0 Evenness 0.71 0.1 0.84 0.2 0.77 0.1 0.77 0.1 0.75 0.1 0.44 0.1 0.78 0.1 0.71 0.1 0.74 0.2 0.78 0.2 0.78 0.2 Rank 10.0 1.0 5.5 5.5 7.0 15.0 3.0 10.0 8.0 3.0 3.0 Evenness (natives) 0.69 0.2 0.83 0.2 0.76 0.06 0.75 0.2 0.74 0.2 0.44 0.1 0.78 0.2 0.70 0.2 0.73 0.2 0.78 0.2 0.78 0.2 Rank 11.0 1.0 5.0 6.0 7.0 15.0 3.0 10.0 8.0 3.0 3.0 Diversity 1.6 0.1 2.3 0.1 1.7 0.1 2.2 0.1 2.0 0.1 1.2 0.1 1.7 0.1 2.0 0.04 2.3 0.1 1.8 0.02 1.7 0.03 Rank 10.5 1.5 8.0 3.0 4.5 14.0 8.0 4.5 1.5 6.0 8.0 Diversity (natives) 1.5 0.1 2.2 0.01 1.7 0.1 2.1 0.1 2.0 0.1 1.2 0.1 1.7 0.1 1.9 0.1 2.2 0.1 1.8 0.1 1.7 0.1 Rank 11.0 1.5 8.0 3.0 4.0 14.0 8.0 5.0 1.5 6.0 8.0 Weighted average 0.73 0.1 0.46 0.1 0.42 0.1 0.40 0.1 0.75 0.1 1.5 0.1 0.41 0.1 1.1 0.2 1.1 0.1 0.45 0.1 0.29 0.1 Rank 9.0 8.0 6.0 4.0 10.0 14.5 5.0 11.5 11.5 7.0 2.0 Mean rank 10.4 0.3 2.8 1.1 7.1 0.8 4.1 0.6 6.3 0.9 13.1 1.4 5.6 0.9 7.2 1.6 5.3 1.8 5.7 0.9 6.2 1.7 Scaled rank 11.0 1.0 8.0 2.0 7.0 15.0 4.0 9.0 3.0 5.0 6.0

277

Table 2. Extended. Reference Wetlands

Altona Marsh

Elder Swamp Meadowville Muddlety

x SE x SE x SE x SE Richness 8.7 1.2 6.6 1.6 11.0 1.3 6.0 0.8 Rank 12.0 14.0 8.0 15.0 Evenness 0.68 0.2 0.71 0.1 0.62 0.1 0.47 0.1 Rank 12.0 10.0 13.0 14.0 Evenness (natives) 0.68 0.2 0.71 0.2 0.61 0.1 0.47 0.1 Rank 12.0 9.0 13.0 14.0 Diversity 1.5 0.1 1.3 0.1 1.6 0.1 0.84 0.1 Rank 12.0 13.0 10.5 15.0 Diversity (natives) 1.5 0.1 1.3 0.1 1.5 0.1 0.84 0.1 Rank 11.0 13.0 11.0 15.0 Weighted average 1.4 0.04 0.35 0.1 1.5 0.4 0.28 0.1 Rank 13.0 3.0 14.5 1.0 Mean rank 12.0 0.3 10.3 1.7 11.7 0.9 12.3 2.3 Scaled rank 13.0 10.0 12.0 14.0 aWetlands with similar mean ranks were assigned similar scaled ranks.

278

Table 3. Actual mean and ranks of benthic and nektonic invertebrate richness (no.families/wetland), diversity, density, and mass, as well

as total mean and scaled ranksa for 11 mitigation and 11 reference wetlands in West Virginia, 2001-2002.

Mitigation Wetlands

Walnut Bottom VEPCO

Buffalo Coal

Elk Run

Leading Creek

Sugar Creek Sand Run Triangle


Enoch Branch

Metric x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE Benthic Richness 2.8 0.1 1.6 0.3 1.4 0.1 2.0 0.4 1.9 0.3 1.6 0.2 1.3 0.2 2.6 0.3 2.2 0.1 1.4 0.1 Rank 2.0 8.5 11.5 5.0 6.0 8.0 14.0 3.0 4.0 11.5 Diversity 1.3 0.3 1.5 0.4 1.6 0.4 1.6 0.3 1.5 0.5 1.0 0.1 1.7 0.3 1.8 0.4 1.3 0.2 1.4 0.2 Rank 13.5 10.5 7.0 7.0 10.5 15.0 4.0 3.0 13.5 12.0 Density (no./m2) 169.4 32.1 15.9 6.4 12.9 3.1 57 12.9 26.1 7.1 35.2 16.2 8 3.3 60.2 18.3 75.3 7.7 14.8 6.8 Rank 2.0 10.0 13.0 5.0 8.0 6.0 14.0 4.0 3.0 11.5 Mass (g/ m2) 10.16 4.7 0.017 0.01 0.024 0.01 2.104 0.85 0.123 0.07 0.831 0.64 0.141 0.10 0.908 0.47 0.941 0.40 0.021 0.01Rank 2.0 14.0 12.0 3.0 9.0 6.0 8.0 5.0 4.0 13.0 Nektonic Richness 2.8 0.2 1.8 0.1 3.0 0.4 2.6 0.2 2.4 0.3 1.8 0.0 2.4 0.2 3.2 0.6 2.1 0.6 1.8 0.1 Rank 3.0 12.0 2.0 5.5 7.5 12.0 7.5 1.0 9.0 12.0 Diversity 2.5 0.8 2.0 0.6 2.4 0.7 2.6 0.3 2.9 0.4 2.8 0.6 2.7 0.5 2.8 0.4 1.9 0.5 2.4 0.6 Rank 8.5 14.0 11.5 6.5 1.5 3.5 5.0 3.5 15.0 11.5 Density (no./L) 21.1 5.1 4.4 1.7 14.4 6.7 9.8 2.9 4.0 1.1 4.2 0.8 2.1 0.4 12.3 6.4 14.4 6.0 1.7 0.4 Rank 1.0 10.0 2.5 6.0 12.0 11.0 14.0 5.0 2.5 15.0 Mass (g/L) 1.135 0.98 0.005 0.0 0.021 0.01 0.106 0.06 0.025 0.01 0.051 0.04 0.009 0.01 0.026 0.01 0.1070 0.04 0.009 0.01Rank 1.0 14.0 11.0 3.0 10.0 6.0 12.0 9.0 2.0 13.0 Total mean rank 4.1 1.6 11.6 0.8 8.8 1.6 5.1 0.5 8.1 1.1 8.4 1.4 9.8 1.5 4.2 0.8 6.6 1.8 12.4 0.4 Scaled rank 1.0 13.0 10.0 3.0 8.0 9.0 12.0 2.0 6.0 14.5

279

Table 3. Extended.

Mitigation

Cont. Reference Wetlands Bear Run Altona Marsh Elder Swamp Meadowville Muddlety Metric x SE x SE x SE x SE x SE Benthic Richness 1.7 0.3 4.5 0.4 1.4 0.2 1.4 0.2 1.6 0.3 Rank 7.0 1.0 11.5 11.5 8.5 Diversity 1.6 0.5 1.9 0.6 1.6 0.5 1.6 0.5 2.0 0.7 Rank 7.0 2.0 7.0 7.0 1.0 Density (no./m2) 30.4 12.7 593.5 236.0 3.7 0.9 14.8 19.2 Rank 7.0 1.0 15.0 11.5 9.0 Mass (g/m2) 0.322 0.15 43.06 25.9 0.002 0.0 0.028 0.0 0.062 0.02Rank 7.0 1.0 15.0 11.0 10.0 Nektonic Richness 2.6 0.3 1.5 0.5 1.5 0.3 2.0 0.1 2.7 0.4 Rank 5.5 14.5 14.5 10.0 4.0 Diversity 2.9 0.5 2.4 0.6 2.5 0.6 2.4 0.5 2.6 0.6 Rank 1.5 11.5 8.5 11.5 6.5 Density (no./L) 6.6 0.6 9.5 3.4 2.4 0.7 12.6 1.8 8.7 3.2 Rank 9.0 7.0 13.0 4.0 8.0 Mass (g/L) 0.053 0.03 0.065 0.03 0.003 0.0 0.047 0.02 0.029 0.02Rank 5.0 4.0 15.0 7.0 8.0 Total mean rank 6.1 0.8 5.3 1.2 12.4 1.1 9.2 1.0 6.9 1.1 Scaled rank 5.0 4.0 14.5 11.0 7.0 aWetlands with similar mean ranks were assigned similar scaled ranks.

280

Table 4. Actual means and ranks of avian richness (no. birds/0.78 ha plot) and diversity, and abundance (no.indiv./0.78 ha plot) for all

birds, waterbirds, waterfowl, and passerines, as well as total mean and scaled ranksa of 11 mitigation and 4 reference wetlands in West


Mitigation Wetlands

Walnut Bottom VEPCO

Buffalo Coal

Elk Run

Leading Creek

Sugar Creek

Sand Run Triangle

Trus JoistMacMillan

Enoch Branch

Bear Run

Metric x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE x SE Richness 9.9 1.2 5.3 0.9 7.9 0.5 12.3 0.6 8.1 0.6 8.2 0.7 9.0 0.7 8.6 1.1 12.9 1.4 9.4 0.8 8.8 0.8 Rank 5.0 15.0 13.0 2.0 12.0 11.0 7.0 9.5 1.0 6.0 8.0 Diversity 2.1 0.2 2.33 0.3 2.18 0.1 2.45 0.3 2.75 0.5 2.7 0.5 1.93 0.1 1.91 0.1 2.48 0.4 2.64 0.5 3.08 0.3 Rank 11.0 8.0 10.0 7.0 2.0 3.0 12.5 14.0 6.0 4.5 1.0 Abundance all birds 40.3 5.0 7.4 1.3 27.3 6.3 28.0 2.4 16.5 1.1 13.0 1.5 20.8 3.3 23.5 5.4 29.9 4.4 12.6 1.3 13.3 0.8 Rank 1.0 15.0 5.0 4.0 10.0 12.0 8.0 7.0 3.0 13.0 11.0 Waterbirdsb 19.5 17.8 0.8 0.4 9.3 4.9 3.3 2.6 3.6 0.5 0.8 0.6 0.8 0.5 1.4 0.7 2.6 1.2 1.1 0.7 0.7 0.3 Rank 1.0 9.0 2.0 4.0 3.0 9.0 9.0 6.0 5.0 7.0 11.0 Waterfowlc 18.4 7.8 0.5 0.2 8.5 4.8 2.5 2.5 3.1 0.5 0.8 0.6 0.8 0.5 1.1 0.6 1.6 1.1 0.4 0.2 0.5 0.3 Rank 1.0 9.0 2.0 4.0 3.0 7.0 7.0 6.0 5.0 10.0 9.0 Passerinesd 18.6 5.7 6.4 1.0 17.5 3.2 22.5 1.5 12.5 0.7 11.2 1.3 19.3 3.5 21.4 4.7 25.1 3.7 9.3 1.0 11.2 0.6 Rank 7.0 15.0 8.0 4.0 10.0 11.5 6.0 5.0 2.0 14.0 11.5 Total mean rank 4.3 1.7 11.8 1.4 6.7 1.8 4.2 0.7 6.7 1.8 8.9 1.4 8.3 0.9 7.9 1.4 3.7 0.8 9.1 1.6 8.6 1.6 Scaled rank 3.0 14.0 4.5 2.0 4.5 12.0 8.0 7.0 1.0 13.0 9.0

281

Table 4. Extended. Reference Wetlands

Altona Marsh

Elder Swamp Meadowville Muddlety

Metric x SE x SE x SE x SE Richness 10.1 0.5 5.4 0.7 10.4 0.8 8.6 0.8Rank 4.0 14.0 3.0 9.5 Diversity 2.21 0.2 1.93 0.2 2.64 0.3 1.82 0.2Rank 9.0 12.5 4.5 15.0 Abundance all birds 26.2 2.0 10.0 2.6 16.7 0.9 35.9 12.7 Rank 6.0 14.0 9.0 2.0 waterbirds 0.6 0.6 0.3 0.1 0.1 0.1 0.4 0.4Rank 12.0 14.0 15.0 13.0 waterfowl 0.6 0.6 0.1 0.1 0.0 0.0 0.0 0.0Rank 8.0 11.0 12.0 12.0 passerines 23.9 2.4 9.8 2.5 15.2 0.4 34.5 12.9Rank 3.0 13.0 9.0 1.0 Total mean rank 7.0 1.4 13.1 0.5 8.8 1.8 8.8 2.4Scaled rank 6.0 15.0 10.5 10.5 aWetlands with similar mean ranks were assigned similar scaled ranks. bIncludes only those birds that depend on water for all or most of their life requisites. cIncludes only birds in the family Anatidae. dIncludes only birds in the order Passeriformes.

282

Table 5. Actual means and ranks of anuran richness (no.species/wetland), Wisconsin Index (WI),

and abundance for all species and for 7 individual species, as well as total mean and scaled ranksa

of 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002.

Mitigation Wetlands

Walnut Bottom VEPCO


Leading Creek Sugar Creek Sand Run Triangle


Index x SE x SE x SE x SE x SE x SE x SE x SE x SERichness 2.4 0.3 1.7 0.2 1.9 0.2 1.5 0.2 2.2 0.2 1.9 0.2 2.3 0.3 1.8 0.4 2.0 0.4Rank 2.0 11.5 7.0 13.0 4.0 8.0 3.0 9.0 5.0 Total WI 0.57 0.1 0.46 0.1 0.62 0.1 0.48 0.1 0.56 0.1 0.43 0.04 0.45 0.1 0.62 0.2 0.45 0.1Rank 4.0 8.0 2.5 7.0 5.5 12.0 9.5 2.5 9.5 Spring peeper 1.5 0.3 2.1 0.2 2.5 0.2 2.3 0.3 2.2 0.1 1.5 0.2 1.4 0.3 1.7 0.6 1.3 0.5Rank 10.5 6.0 2.5 4.0 5.0 10.5 13.0 8.0 14.0 Gray treefrog 0.58 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.26 0.1 0.26 0.1 0.25 0.1 0.0 0.0 0.0 0.0Rank 1.0 11.8 11.8 11.8 4.5 4.5 6.5 11.8 11.8 American bullfrog 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.04 0.02 0.33 0.1 0.0 0.0 0.17 0.2Rank 11.8 11.8 11.8 11.8 6.0 8.0 2.5 11.8 4.0 Wood frog 0.0 0.0 0.54 0.2 0.42 0.2 0.0 0.0 0.21 0.1 0.15 0.1 0.0 0.0 0.0 0.0 0.0 0.0Rank 11.5 1.0 2.0 11.5 4.0 5.0 11.5 11.5 11.5 Green frog 0.67 0.3 0.54 0.1 1.25 0.4 1.0 0.4 0.74 0.1 0.63 0.1 0.75 0.3 1.83 0.6 0.5 0.3Rank 9.0 12.0 2.0 3.0 6.0 10.0 5.0 1.0 13.0 American toad 0.5 0.2 0.04 0.04 0.17 0.1 0.0 0.0 0.07 0.04 0.11 0.1 0.17 0.2 0.33 0.3 0.33 0.2Rank 1.0 11.5 5.0 14.0 9.0 7.5 5.0 2.5 2.5 Pickerel frog 0.75 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.33 0.1 0.28 0.1 0.25 0.1 0.5 0.3 0.83 0.4Rank 2.0 13.5 13.5 13.5 5.0 7.0 8.0 4.0 1.0 Total abundance 4.01 1.1 4.54 1.0 8.1 1.9 5.6 2.1 4.91 0.8 2.98 0.5 3.06 1.0 7.21 2.5 2.19 1.2Rank 9.0 8.0 1.0 5.0 7.0 11.0 10.0 4.0 14.0 Spring peeper 13.9 5.2 26.9 4.6 37.1 5.7 31.0 8.8 29.3 3.6 17.0 2.9 15.1 5.8 21.3 9.5 11.2 7.9Rank 13.0 7.0 3.0 4.0 6.0 11.0 12.0 8.0 14.0 Gray treefrog 1.8 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.43 0.1 0.57 0.2 0.27 0.1 0.0 0.0 0.0 0.0Rank 1.0 12.0 12.0 12.0 6.5 4.5 8.0 12.0 12.0 American bullfrog 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.14 0.1 0.06 0.04 0.45 0.2 0.0 0.0 0.17 0.2Rank 12.0 12.0 12.0 12.0 7.0 8.0 3.0 12.0 6.0 Wood frog 0.0 0.0 3.2 2.1 0.83 0.5 0.0 0.0 0.55 0.3 0.2 0.1 0.0 0.0 0.0 1.0 0.0 0.9Rank 11.5 1.0 2.0 11.5 4.0 7.0 11.5 11.5 11.5 Green frog 9.3 5.5 1.6 0.6 17.9 6.9 8.2 4.1 2.9 0.7 2.2 0.4 4.1 1.8 26.3 10.7 1.8 1.2Rank 3.0 14.0 2.0 5.0 10.0 12.0 7.0 1.0 13.0 American toad 1.1 0.6 0.04 0.0 0.17 0.1 0.0 0.0 0.14 0.1 0.24 0.1 1.1 1.1 1.7 1.7 0.5 0.3Rank 2.5 11.5 7.5 14.0 9.0 6.0 2.5 1.0 4.0 Pickerel frog 2.1 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.95 0.3 0.64 0.2 0.45 0.2 1.2 0.0 1.7 0.0Rank 1.0 13.5 13.5 13.5 5.0 7.0 8.0 3.5 2.0 Total rank 6.2 0.9 9.8 1.0 6.5 1.2 9.8 1.0 6.1 0.4 8.2 0.6 7.4 0.9 6.8 1.1 8.8 1.2Scaled rank 3.0 12.5 4.0 12.5 2.0 8.0 7.0 6.0 10.0

283

Table 5. Extended. Mitigation cont. Reference Wetlands Enoch Branch Bear Run Altona Marsh Elder Swamp Meadowville Muddlety

Index x SE x SE x SE x SE x SE x SERichness 2.7 0.5 1.8 0.2 1.0 0.2 1.7 0.2 1.3 0.2 1.9 0.3Rank 1.0 10.0 15.0 11.5 14.0 6.0 Total WI 0.69 0.1 0.37 0.03 0.28 0.1 0.44 0.1 0.30 0.1 0.56 0.1Rank 1.0 13.0 15.0 11.0 14.0 5.5 Spring peeper 2.5 0.2 1.04 0.1 1.5 0.3 1.9 0.3 1.5 0.3 2.6 0.2Rank 2.5 15.0 10.5 7.0 10.5 1.0 Gray treefrog 0.33 0.2 0.2 0.1 0.0 0.0 0.0 0.0 0.25 0.1 0.39 0.1Rank 3.0 8.0 11.8 11.8 6.5 2.0 American bullfrog 0.44 0.1 0.33 0.1 0.0 0.0 0.0 0.0 0.08 0.1 0.11 0.1Rank 1.0 2.5 11.8 11.8 7.0 5.0 Wood frog 0.11 0.1 0.0 0.0 0.0 0.0 0.22 0.1 0.08 0.1 0.0 0.0Rank 6.0 11.5 11.5 3.0 7.0 8.0 Green frog 0.78 0.3 0.57 0.1 0.33 0.2 0.72 0.2 0.21 0.1 0.72 0.2Rank 4.0 11.0 14.0 7.5 15.0 7.5 American toad 0.06 0.1 0.17 0.1 0.04 0.0 0.11 0.1 0.0 0.0 0.0 0.0Rank 10.0 5.0 11.5 7.5 14.0 14.0 Pickerel frog 0.61 0.2 0.31 0.1 0.08 0.1 0.17 0.1 0.0 0.0 0.11 0.1Rank 3.0 6.0 11.0 9.0 13.5 10.0 Total abundance 7.74 1.6 1.87 0.3 2.94 0.8 4.99 1.2 2.91 0.9 7.93 1.7Rank 3.0 15.0 12.0 6.0 13.0 2.0 Spring peeper 41.9 4.4 8.3 2.0 17.4 4.5 29.7 5.6 18.8 4.9 47.5 4.5Rank 2.0 15.0 10.0 5.0 9.0 1.0 Gray treefrog 0.88 0.4 0.43 0.2 0.0 0.0 0.0 0.0 0.57 0.3 0.75 0.4Rank 2.0 6.5 12.0 12.0 4.5 3.0 American bullfrog 0.76 0.3 0.78 0.2 0.0 0.0 0.0 0.0 0.22 0.2 0.19 0.1Rank 2.0 1.0 12.0 12.0 4.0 5.0 Wood frog 0.24 0.2 0.0 0.0 0.0 0.0 0.61 0.5 0.22 0.2 0.0 0.0Rank 5.0 11.5 11.5 3.0 6.0 11.5 Green frog 9.1 4.1 2.5 0.6 3.0 2.1 4.0 1.5 0.52 0.2 6.8 1.1Rank 4.0 11.0 9.0 8.0 15.0 6.0 American toad 0.06 0.1 0.25 0.1 0.04 0.04 0.17 0.1 0.0 0.0 0.0 0.0Rank 10.0 5.0 11.5 7.5 14.0 14.0 Pickerel frog 1.2 0.5 0.78 0.2 0.21 0.1 0.44 0.2 0.0 0.0 0.31 0.1Rank 3.5 6.0 11.0 9.0 13.5 10.0 Total rank 3.7 0.7 9.0 1.1 11.8 0.4 8.4 0.7 10.6 1.0 6.6 1.0Scaled rank 1.0 11.0 15.0 9.0 14.0 5.0 a Wetlands with similar mean ranks were assigned similar scaled ranks.

284

Table 6. Actual Habitat Suitability Index (HSI) values and ranks of 8 species, as well as total and scaled ranksa of 11

mitigation and 4 reference wetlands in West Virginia, 2001-2002.

Mitigation Wetlands

Walnut Bottom VEPCO


Leading Creek

Sugar Creek

Sand Run Triangle


Metric x SE x SE x SE x SE x SE x SE x SE x SE x SERed-winged blackbird 0.10 0.03 0.10 0.01 0.03 0.03 0.01 0.03 0.01 Rank 4.0 8.5 4.0 13.0 8.5 8.5 13.0 8.5 13.0 Beaver 0.58 1.0 0.69 0.49 1.0 0.63 0.51 0.78 1.0 Rank 13.0 1.0 10.0 15.0 1.0 11.0 14.0 9.0 1.0 Muskrat 0.31 0.32 0.29 0.27 0.32 0.32 0.31 0.67 0.3 Rank 10.5 7.5 13.5 15.0 7.5 7.5 10.5 2.0 12.0 Mink 0.75 0.98 0.72 0.55 0.92 0.96 0.5 0.92 0.87 Rank 11.0 2.0 12.0 14.0 4.5 3.0 15.0 4.5 7.0 Great-blue heron 0.32 0.22 0.22 0.32 0.32 0.32 0.16 0.16 0.16 Rank 1.0 9.5 9.5 1.0 1.0 1.0 12.5 12.5 12.5 Wood duck 0.92 1.0 1.0 0.65 1.0 0.30 0.60 0.98 1.0 Rank 7.0 1.0 1.0 10.0 1.0 15.0 11.5 5.0 1.0 Snapping turtle 0.56 0.59 0.61 0.6 0.71 0.65 0.54 0.6 0.61 Rank 11.0 8.0 4.5 6.5 1.0 2.0 12.0 6.5 4.5 Red-spotted newt 1.0 0.93 0.54 1.0 1.0 1.0 0.89 1.0 0.69 Rank 1.0 9.0 15.0 1.0 1.0 1.0 10.0 1.0 12.0 Mean HSI value 0.57 0.10 0.63 0.20 0.52 0.10 0.49 0.10 0.66 0.10 0.53 0.10 0.44 0.10 0.64 0.10 0.58 0.10 Total mean rank 7.3 1.7 5.8 1.3 8.7 1.8 9.4 2.1 3.2 1.1 6.1 1.8 12.3 0.6 6.1 1.3 7.9 1.8 Scaled rank 8.0 3.5 11.0 13.0 1.0 5.5 15.0 5.5 10.0

285

Table 6. Extended. Mitigation Cont. Reference Wetlands

Enoch Branch

Bear Run

Altona Marsh Elder Swamp Meadowville Muddlety

Metric x SE x SE x SE x SE x SE x SE Red-winged blackbird 0.01 0.01 0.30 0.10 0.10 0.10 Rank 13.0 13.0 1.0 4.0 4.0 4.0 Beaver 0.87 0.62 1.0 1.0 1.0 1.0 Rank 8.0 12.0 1.0 1.0 1.0 1.0 Muskrat 0.29 0.48 0.87 0.62 0.39 0.32 Rank 13.5 4.0 1.0 3.0 5.0 7.5 Mink 0.8 0.68 0.82 0.86 0.89 1.0 Rank 10.0 13.0 9.0 8.0 6.0 1.0 Great-blue heron 0.32 0.32 0.32 0.32 0.11 0.16 Rank 1.0 1.0 1.0 1.0 15.0 12.5 Wood duck 0.94 0.59 0.40 0.90 0.60 0.80 Rank 6.0 13.0 14.0 8.0 11.5 9.0 Snapping turtle 0.57 0.57 0.45 0.53 0.49 0.63 Rank 9.5 9.5 15.0 13.0 14.0 3.0 Red-spotted newt 1.0 0.87 1.0 0.62 0.58 0.98 Rank 1.0 11.0 1.0 13.0 14.0 8.0 Mean HSI value 0.60 0.10 0.52 0.10 0.65 0.10 0.62 0.10 0.52 0.10 0.62 0.20Total mean rank 7.8 1.7 9.6 1.6 5.4 2.2 6.4 1.7 8.8 1.9 5.8 1.5 Scaled rank 9.0 14.0 2.0 7.0 12.0 3.5 aWetlands with similar mean ranks were assigned similar scaled ranks.

286

Table 7. Vegetation, invertebrate, avian, anuran, and Habitat Suitability Index (HSI) ranks, as well as total mean and scaled

ranksb for 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002.

Mitigation Wetlands Walnut Bottom VEPCO Buffalo Coal Elk Run Leading Creek Sugar Creek Sand Run Triangle x SE x SE x SE x SE x SE x SE x SE x SE Vegetation ranka 10.4abcd 0.3 2.8e 1.1 7.1abcde 0.8 4.1de 0.6 6.3bcde 0.9 13.1a 1.4 5.6cde 0.9 7.2abcde 1.6 Invertebrate ranka 4.1c 1.6 11.6ab 0.8 8.8abc 1.6 5.1c 0.5 8.1abc 1.1 8.4abc 1.4 9.8abc 1.5 4.2c 0.8 Avian ranka 4.3b 1.7 11.8a 1.4 6.7ab 1.8 4.2b 0.7 6.7ab 1.8 8.9ab 1.4 8.3ab 0.9 7.9ab 1.4 Anuran ranka 6.2bcd 0.9 9.8abc 1.0 6.5bcd 1.2 9.8bcd 1.0 6.1cd 0.4 8.2abc 0.6 7.4abcd 0.9 6.8bcd 1.1 HSI ranka 7.3ab 1.7 5.8ab 1.3 8.7ab 1.8 9.4ab 2.1 3.2b 1.1 6.1ab 1.8 12.3a 0.6 6.1ab 1.3 Total mean ranka 6.5a 1.2 8.4a 1.5 7.6a 0.6 6.5a 1.0 6.1a 1.1 8.9a 0.9 8.7a 0.8 6.4a 0.7 Scaled ranka 4.5 10.0 6.0 4.5 1.0 13.0 11.5 2.5

287

Table 7. Extended. Mitigation Wetlands Cont. Reference Wetlands

Trus Joist

MacMillan Enoch Branch Bear Run Altona Marsh Elder Swamp Meadowville Muddlety

x SE x SE x SE x SE x SE x SE x SEVegetation ranka 5.3de 1.8 5.7cde 0.9 6.2bcde 1.7 12.0abc 0.3 10.3abcd 1.7 11.7abc 0.9 12.3ab 2.3Invertebrate ranka 6.6abc 1.8 12.4a 0.4 6.1bc 0.8 5.3c 1.2 12.4a 1.1 9.2abc 1.0 6.9abc 1.1Avian ranka 3.7b 0.8 9.1ab 1.6 8.6ab 1.6 7.0ab 0.9 13.1ab 0.4 8.8ab 1.4 8.8ab 2 Anuran ranka 8.8abc 1.2 3.7d 0.7 9.0abc 1.1 11.8a 0.4 8.4abc 0.7 10.6ab 1.0 6.6bcd 1 HSI ranka 7.9ab 1.8 7.8ab 1.7 9.6ab 1.6 5.4ab 2.2 6.4ab 1.7 8.8ab 1.9 5.8ab 1.5Total mean ranka 6.4a 0.6 7.7a 1.5 7.9a 0.3 8.7a 1.4 10.6a 1.3 9.7a 0.7 8.3a 1.0Scaled ranka 2.5 7.0 8.0 11.5 15.0 14.0 9.0 aDifferent letters following means indicate a significant difference at P = 0.05. b Wetlands with similar mean ranks were assigned similar scaled ranks.

288

Table 8. Summary of parameters including general structure and intraset correlation coefficients for all environmental

variables in the canonical correspondence analysis of all avian species abundance within all wetlands (n = 15) and for

mitigation wetlands only (n = 11) in West Virginia, 2001-2002.

Axis 1 Axis 2 Axis 3 General structure All wetlands Mitigation only All wetlands Mitigation only All wetlandsMitigation onlyEigenvalue 0.191 0.279 0.110 0.211 0.097 0.137 Monte Carlo Test result (P valuea) 0.841 0.764 0.907 0.391 0.415 0.255 % Variance explained 12.1 21.4 6.9 16.2 6.1 10.6 Predictor variables (correlation coefficients) Size 0.800 0.651 0.303 Age 0.163 -0.317 -0.706 % Emergent vegetation -0.503 -0.091 -0.526 -0.219 -0.053 0.61 Vegetation diversity 0.367 -0.325 -0.627 -0.720 0.209 0.173 % Open water 0.689 -0.031 0.312 0.439 0.442 -0.477 Benthic invertebrate diversity -0.736 -0.149 0.032 -0.176 -0.053 -0.175 Nektonic invertebrate diversity 0.395 -0.211 -0.152 0.668 -0.413 0.074 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].

289

Table 9. Summary of parameters including general structure and intraset correlation

coefficients for all environmental variables in the canonical correspondence analysis

of waterbird species abundance within 11 mitigation and 4 reference wetlands in

West Virginia, 2001-2002.

General structure Axis 1 Axis 2 Axis 3 Eigenvalue 0.265 0.082 0.057 Monte Carlo Test result (P valuea) 0.570 0.622 0.170 % Variance explained 23.5 30.8 35.9 Predictor variables (correlation coefficients) % Emergent vegetation 0.629 -0.030 0.419 Vegetation diversity 0.728 0.402 -0.281 % Open water -0.307 -0.186 -0.340 Benthic invertebrate diversity 0.018 -0.178 -0.636 Nektonic invertebrate diversity 0.393 -0.888 0.147 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].

290


variables in the canonical correspondence analysis of anuran species abundance within all wetlands (n = 15) and for mitigation

wetlands only (n = 11) in West Virginia, 2001-2002.

Axis 1 Axis 2 Axis 3 General structure All wetlands Mitigation only All wetlands Mitigation only All wetlands Mitigation only Eigenvalue 0.040 0.088 0.025 0.048 0.016 0.030 Monte Carlo Test result (P valuea) 0.843 0.819 0.307 0.390 0.057 0.036 % Variance explained 15.0 32.2 9.5 17.5 6.2 11.0 Predictor variables (correlation coefficients) Size 0.234 -0.167 0.339 Age -0.327 -0.374 -0.571 % Emergent vegetation -0.273 -0.003 -0.244 -0.365 0.115 0.382 Vegetation diversity 0.092 0.154 -0.564 -0.597 0.66 -0.071 % Open water 0.564 0.048 0.295 0.621 0.303 -0.229 Benthic invertebrate diversity 0.211 -0.71 -0.478 -0.282 -0.677 -0.219 Nektonic invertebrate diversity 0.814 -0.433 0.106 -0.514 -0.230 -0.253 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].

291


variables in the canonical correspondence analysis of benthic invertebrate familial abundance within all wetlands (n = 15) and

for mitigation wetlands only (n = 11) in West Virginia, 2001-2002.

Axis 1 Axis 2 Axis 3 General structure All wetlands Mitigation only All wetlands Mitigation only All wetlands Mitigation only Eigenvalue 0.292 0.332 0.099 0.178 0.063 0.056 Monte Carlo Test result (P valuea) 0.413 0.116 0.131 0.035 0.032 0.547 % Variance explained 27.0 36.5 9.1 19.6 5.8 6.2 Predictor variables (correlation coefficients) Size 0.628 0.353 -0.291 Age -0.263 -0.823 -0.246 % Emergent vegetation -0.717 -0.548 -0.641 0.292 0.190 0.271 Vegetation diversity 0.544 -0.397 0.084 -0.363 0.281 -0.133 % Submergent vegetation 0.266 0.735 0.772 -0.573 -0.486 -0.095 % Open water 0.522 0.758 0.814 -0.225 -0.124 -0.091 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].

292


variables in the canonical correspondence analysis of nektonic invertebrate familial abundance within all wetlands (n = 15) and

for mitigation wetlands only (n = 11) in West Virginia, 2001-2002.

Axis 1 Axis 2 Axis 3 General structure All wetlands Mitigation only All wetlands Mitigation only All wetlands Mitigation only Eigenvalue 0.350 0.458 0.200 0.247 0.106 0.185 Monte Carlo Test result (P valuea) 0.089 0.126 0.141 0.563 0.338 0.289 % Variance explained 18.2 26.8 10.3 14.5 5.5 10.8 Predictor variables (correlation coefficients) Size 0.396 0.641 -0.578 Age -0.661 -0.142 -0.537 % Emergent vegetation -0.037 -0.060 -0.494 0.116 0.730 -0.128 Vegetation diversity 0.395 -0.499 0.665 -0.008 -0.289 0.414 % Submergent vegetation -0.566 0.504 0.314 -0.515 -0.761 -0.005 % Open water -0.367 0.425 -0.282 -0.278 0.328 0.426 a P = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue [i.e., P = (1 + no. permutations >= observed)/(1 + no. permutations)].

293

Table 13. Species codes and common names of all avian and waterbird species

included in canonical correspondence analysis of 11 mitigation and 4 reference


Code Common name Code Common name acfl Acadian flycatcher gwwa Green-winged warbler alfl Alder flycatcher howr House wren amcr American crow inbu Indigo bunting amgo American goldfinch kill Killdeer amre American redstart mall Mallard amro American robin mawa Magnolia warbler baor Baltimore oriole modo Mourning dove bars Barn swallow noca Northern cardinal bcch Black-capped chickadee nofl Northern flicker beki Belted kingfisher nomo Northern mockingbird bggn Blue-gray knatcatcher oven Ovenbird blja Blue jay piwo Pileated woodpecker brcr Brown creeper rbwo Red-bellied woodpecker brth Brown thrasher revi Red-eyed vireo bwwa Blue-winged warbler rthu Ruby-throated hummingbird cago Canada goose rwbl Red-winged blackbird cawr Carolina wren rwsw Northern rough-winged swallowcewx Cedar waxwing sasp Savannah sparrow chsp Chipping sparrow scta Scarlet tanager chsw Chimney swift sosp Song sparrow cogr Common grackle spsa Spotted sandpiper coye Common yellowthroat swsp Swamp sparrow deju Dark-eyed junco tres Tree swallow dowo Downy woodpecker tuti Tufted titmouse eaki Eastern kingbird wavi Warbling vireo eaph Eastern phoebe wbnu White-breasted nuthatch eato Eastern towhee wevi White-eyed vireo eust European starling wifl Willow flycatcher fisp Field sparrow wodu Wood duck gcfl Great crested flycatcher woth Wood thrush grca Gray catbird ytvi Yellow-throated vireo grhe Green heron ytwa Yellow-throated warbler gtbh Great blue heron ywar Yellow warbler

294

Table 14. Species codes and common names of 7 anuran species included in

canonical correspondence analysis of 11 mitigation and 4 reference wetlands in West


Code Common name ambu American bullfrog amto American toad grat Gray treefrog grfr Green frog nspe Spring peeper pifr Pickerel frog wofr Wood frog

295

Table 15. Species codes and common names of benthic and nektonic invertebrates

included in canonical correspondence analysis of 11 mitigation and 4 reference


Code Family Code Family aeshn Aeshnidae hebr Hebridae aphi Aphididae helo Helodidae arach Arachnid 2 hydra Hydracarina asell Asellidae hydro Hydrometridae baet Baetidae hydrop Hydrophilidae belo Belostomatidae isot Isotomidae brac Braconidae lest Lestidae caen Caenidae libel Libellulidae caeni Caenidae lymn Lymnaedae cerat Ceratopogonidae merm Mermithidae chao Chaobaridae meso Mesoveliidae chir Chironomidae nauc Naucoridae chryso Chrysomelidae nemat Nematoda clad Cladocera noter Noteridae coen Coenagrionidae noto Notonectidae conch Conchostraca olig Oligochaeta cordu Cordulegastridae phys Physidae cordul Corduliidae plan Planorbidae corix Corixidae podu Poduridae culic Culicidae pomat Pomatiopsidae cycl Cyclopoida proto Protoneuridae delph Delphacidae pyral Pyralidae dixi Dixidae salid Saldidae dytis Dytiscidae sciom Sciomyzidae elmi Elmidae siph Siphlonuridae empid Empididae sisur Sisuridae ephy Ephydridae sphae Sphaeriidae erpob Erpobdellidae strati Stratiomyidae gam Gammaridae taba Tabanidae gerr Gerridae taban Tabanidae glos Glossiphoniidae tal Talitridae hali Haliplidae tipul Tipulidae

296

Table 15. Continued. Code Family union Unionidae unk1 Unknown 1 unk2 Unknown 2 valv Valvatidae veli Veliidae vivi Viviparidae

297

CHAPTER V

FIGURES

298

gtbh

grhe

cago

wodu

mall

killspsa

modo

chsw

rthu

beki

rbwo

dowo

nofl

piwo

acfl

alfl

wifl

eaph

gcfl

eaki

wevi

ytvi

wavi

revi

blja

amcr

tres

rwsw

bars

bcch

tuti

brcr

wbnu

cawr

howr

bggn

woth

amro

grca

nomo

brth

eust

cewx

bwwa

gwwa ywar

mawa

ytwa

amre

oven

coye

scta

eato

chsp

fisp

sosp

sasp

swsp

deju

noca

inbu

rwbl

cogr

baor

amgo

emvegvegh

open

invertbh

invertnh

Axis 1

Axis

2

Figure 1. Canonical correspondence analysis ordination of all avian species on 11

mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 5

environmental variables: open = % open water; emveg = % emergent vegetation;

vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh =

invertebrate nektonic diversity. The angle of the vectors with the axes is indicative of

their correlation with the axes where vectors that are parallel with an axis are

correlated and those that are perpendicular are uncorrelated. The length of vectors is

proportional to the relationship between that variable and avian community

composition. Species codes are defined in Table 13.

299

gtbh

grhe

cago

wodu

mall

kill

spsa

modo

chsw

rthu

beki

rbwo

dowo

nofl

piwo

acfl

alfl

wifl

eaph

gcfl

eaki

wevi

ytvi

wavi

reviblja

amcr

tres

rwsw

bars

bcch

tuti

wbnu

cawr

howr

bggn

woth

amro

grca

nomo

brth

eust

cewx

bwwa

ywar

mawa

ytwa

amre

coye

scta

eato

chsp fisp

sosp

sasp

swsp

deju

noca

inbu

rwbl

cogr

baor

amgosize

vegh

open

invertnh

Axis 1

Axis

2

Figure 2. Canonical correspondence analysis ordination of all avian species on 11

mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental

variables: age, size, open = % open water; emveg = % emergent vegetation; vegh =

vegetation diversity; invertbh = invertebrate benthic diversity; invertnh = invertebrate

nektonic diversity. The angle of the vectors with the axes is indicative of their

correlation with the axes where vectors that are parallel with an axis are correlated

and those that are perpendicular are uncorrelated. The length of vectors is



300

gtbh

grhe

cago

wodu

mall

spsa

beki

vegh

invertnh

Axis 1

Axis

2

Figure 3. Canonical correspondence analysis ordination of all waterbird species on

11 mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental






proportional to the relationship between that variable and waterbird community


301

nspe

grat

ambu

wofr

grfr

amto

pifr

vegh

open

invertbh

invertnh

Axis 1

Axis

2

Figure 4. Canonical correspondence analysis ordination of all anuran species on 11

mitigation and 4 reference wetlands in West Virginia, 2001-2002, based on 5

environmental variables: open = % open water; emveg = % emergent vegetation;

vegh = vegetation diversity; invertbh = invertebrate benthic diversity; invertnh =

invertebrate nektonic diversity. The angle of the vectors with the axes is indicative of

their correlation with the axes where vectors that are parallel with an axis are

correlated and those that are perpendicular are uncorrelated. The length of vectors is



302

nspe

gratambu

wofr

grfr

amto pifr

vegh

open

invertbh

invertnh

Axis 1

Axis

2

Figure 5. Canonical correspondence analysis ordination of all anuran species on 11

mitigation wetlands in West Virginia, 2001-2002, based on 7 environmental






proportional to the relationship between that variable and anuran community


303

gamm

chryso

elmi

unk1

cerat

chironculici

empid

ephyr

strati

taban

tipul

unk2

caeni

lymn

phys

plan

pomatvalv

vivip

erpobmerm

nemat

cordul

libell

oliga

sphaeunion

emveg

opensubm

Axis 1Ax

is 2

Figure 6. Canonical correspondence analysis ordination of benthic invertebrate

families on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002,

based on 4 environmental variables: open = % open water; emveg = % emergent

vegetation; subm = % submergent vegetation; vegh = vegetation diversity. The angle

of the vectors with the axes is indicative of their correlation with the axes where

vectors that are parallel with an axis are correlated and those that are perpendicular

are uncorrelated. The length of vectors is proportional to the relationship between

that variable and invertebrate community composition. Species codes are defined in

Table 15.

304

chryso

elmi

unk1

cerat

chiron

culici

empid

ephyr

taban

tipul

unk2

caeni

lymn

phys

plan

valv

vivip

nemat

cordul

libell

oliga

sphae

union

age

emveg

open

subm

Axis 1

Axis

2

Figure 7. Canonical correspondence analysis ordination of benthic invertebrate

families on 11 mitigation wetlands in West Virginia, 2001-2002, based on 6

environmental variables: age, size, open = % open water; emveg = % emergent






Table 15.

305

gam

tal

hydra

arachclad

dytis

elmi

hali

helo

hydropnoter

isot

podu

conch

cycl

cerat

chao

chirculic

dixi

ephy

sciom

taba

baet

caen

siph

lymn

phys

plan

vivi

aphi

belo

corix

delphgerr

hebr

hydro

meso

nauc

noto

salid

veliglos

brac

asell

pyral

sisur

aeshn

coen

cordu

cordul

lest

libel

proto

olig

sphae

veghopen

subm

Axis 1Ax

is 2

Figure 8. Canonical correspondence analysis ordination of nektonic invertebrate

families on 11 mitigation and 4 reference wetlands in West Virginia, 2001-2002,

based on 4 environmental variables: open = % open water; emveg = % emergent






Table 15.

306

tal

hydra

arach

clad

dytis

elmihali

helo

hydrop

noter

isot

podu

conch

cycl

cerat

chao

chir

culic

dixi

sciom

taba

baet

caen

siph

lymn

phys

plan

viviaphi

belo

corix

gerr

hebr

hydro meso

nauc

noto

salid

veli

glos

brac

asell

pyral

aeshn

coen

cordu

cordul

lest

libel

proto

olig

sphae

size

age

vegh

subm

Axis 1Ax

is 2

Figure 9. Canonical correspondence analysis ordination of nektonic invertebrate

families on 11 mitigation wetlands in West Virginia, 2001-2002, based on 6

environmental variables: age, size, open = % open water; emveg = % emergent






Table 15.

307

APPENDICES

308

Appendix 1. Average percent cover/1.0 m2 quadrat of all herbaceous vegetation

species sampled in 11 mitigation (n = 45) and 4 reference (n = 15) wetlands in West


Mitigation Reference Species x SE x SE Agrimonia gryposepala 0.19 0.17 0.32 0.32 Agrostis gigantea 0.40 0.15 0.00 0.00 Agrostis hyemalis 0.00 0.00 0.02 0.02 Allium cernuum var. cernuum 0.01 0.01 0.00 0.00 Ambrosia artemisifolia 0.09 0.05 0.00 0.00 Andropogon virginicus var. virginicus 0.07 0.05 0.00 0.00 Antennaria solitaria 0.01 0.01 0.00 0.00 Anthoxanthum odoratum ssp. odoratum 0.09 0.05 0.00 0.00 Apios americana 0.06 0.04 0.00 0.00 Apocynum cannabinum 0.25 0.20 0.07 0.07 Asclepias incarnata 0.06 0.03 0.00 0.00 Asclepias syriaca 0.01 0.01 0.00 0.00 Aster 1 0.01 0.01 0.00 0.00 Aster puniceus 0.00 0.00 0.02 0.02 Aster sp. 0.02 0.02 0.00 0.00 Aster umbellatus var. umbellatus 0.11 0.08 0.00 0.00 Barbarea vulgaris 0.01 0.01 0.00 0.00 Bidens frondosa 0.11 0.08 0.00 0.00 Bidens sp. 0.34 0.21 0.00 0.00 Boehmeria cylindrica 0.11 0.06 1.88 1.15 Calamagrostis canadensis var. canadensis 0.00 0.00 4.12 4.12 Caltha palustris 0.00 0.00 0.40 0.40 Cardamine rotundifolia 0.01 0.01 0.00 0.00 Carex argyrantha 0.00 0.00 0.02 0.02 Carex canescens ssp. canescens 0.03 0.03 0.57 0.57 Carex folliculata 0.01 0.01 0.27 0.27 Carex frankii 0.01 0.01 0.00 0.00 Carex gynandra 0.09 0.06 0.00 0.00 Carex intumescens 0.01 0.01 0.00 0.00 Carex lurida 0.34 0.11 0.00 0.00 Carex scoparia var. scoparia 0.56 0.18 0.35 0.30

309

Mitigation Reference Species x SE x SE Carex shortiana 0.02 0.02 0.00 0.00 Carex squarrosa 0.04 0.04 0.00 0.00 Carex stipata 0.01 0.01 0.00 0.00 Carex stricta 0.42 0.22 4.23 2.19 Carex tribuloides 0.01 0.01 0.05 0.05 Carex vulpinoidea var. vulpinoidea 0.61 0.18 0.00 0.00 Clematis virginiana 0.00 0.00 0.40 0.40 Clinopodium vulgare 0.01 0.01 0.00 0.00 Conium maculatum 0.01 0.01 0.00 0.00 Coronilla varia 0.38 0.24 0.00 0.00 Crepis capillaris 0.01 0.01 0.00 0.00 Danthonia compressa 0.03 0.03 0.17 0.12 Danthonia spicata 0.01 0.01 0.00 0.00 Daucus carota 0.02 0.02 0.00 0.00 Dichanthelium clandestinum 0.63 0.33 0.00 0.00 Dichanthelium sphaerocarpon var. sphaerocarpon 0.11 0.11 0.00 0.00 Diphasiastrum digitatum 0.01 0.01 0.00 0.00 Dipsacus fullonum ssp. sylvestris 0.39 0.39 0.00 0.00 Drosera rotundifolia var. rotundifolia 0.00 0.00 0.22 0.17 Dulichium arundinaceum 0.00 0.00 0.02 0.02 Echinochloa crus-galli var. crus-galli 0.68 0.49 0.00 0.00 Eleocharis compressa 0.01 0.01 0.00 0.00 Eleocharis obtusa 1.06 0.37 0.00 0.00 Eleocharis quadrangulata 0.27 0.27 0.00 0.00 Eleocharis tenuis var. tenuis 1.14 0.30 0.10 0.10 Epilobium coloratum 0.07 0.04 0.32 0.32 Equisetum fluviatile 0.00 0.00 0.83 0.83 Erechtites hieraciifolia var. hieraciifolia 0.04 0.03 0.00 0.00 Erigeron aureus 0.01 0.01 0.00 0.00 Eriophorum virginicum 0.00 0.00 1.03 0.80 Eupatorium coelestinum 0.01 0.01 0.00 0.00 Eupatorium fistulosum 0.08 0.07 0.00 0.00 Eupatorium maculatum var. maculatum 0.00 0.00 0.23 0.23 Eupatorium perfoliatum 0.31 0.17 0.00 0.00 Euthamia graminifolia var. graminifolia 0.41 0.19 0.00 0.00

Appendix 1. Continued.

310

Mitigation Reference Species x SE x SE Galium aparine 0.01 0.01 0.00 0.00 Galium mollugo 0.22 0.11 0.72 0.52 Galium obtusum ssp. obtusum 0.05 0.05 0.00 0.00 Galium tinctorium 0.91 0.24 0.97 0.40 Gaultheria procumbens 0.00 0.00 0.05 0.05 Geum canadense var. canadense 0.01 0.01 0.00 0.00 Geum laciniatum 0.04 0.04 0.00 0.00 Geum rivale 0.00 0.00 0.33 0.33 Glyceria grandis var. grandis 0.11 0.08 0.42 0.22 Glyceria striata 0.01 0.01 0.02 0.02 Gratiola virginiana var. virginiana 0.00 0.00 0.23 0.23 Helenium autumnale 0.04 0.04 0.00 0.00 Heteranthera reniformis 0.21 0.20 0.00 0.00 Holcus lanatus 0.01 0.01 0.00 0.00 Hypericum mutilum 0.36 0.15 0.00 0.00 Hypericum punctatum 0.01 0.01 0.00 0.00 Impatiens capensis 0.71 0.31 2.13 1.36 Impatiens pallida 0.00 0.00 3.30 2.32 Iris pseudacorus 0.10 0.10 0.00 0.00 Juncus acuminatus 0.06 0.06 0.00 0.00 Juncus balticus 0.00 0.00 1.30 1.02 Juncus brachycarpus 0.01 0.01 0.00 0.00 Juncus brevicaudatus 0.36 0.24 0.10 0.10 Juncus effusus var. effusus 4.82 0.73 0.25 0.16 Juncus secundus 0.01 0.01 0.00 0.00 Juncus subcaudatus var. subcaudatus 0.41 0.12 0.05 0.05 Juncus tenuis 0.71 0.33 0.00 0.00 Leersia oryzoides 2.64 1.03 2.85 2.08 Lemna minor 0.29 0.15 0.00 0.00 Lespedeza cuneata 0.19 0.18 0.00 0.00 Leucanthemum vulgare 0.04 0.03 0.00 0.00 Linum medium 0.01 0.01 0.00 0.00 Lonicera japonica 0.01 0.01 0.00 0.00 Ludwigia alternifolia 0.16 0.09 0.00 0.00 Ludwigia palustris 2.07 0.52 0.38 0.21 Lycopodium clavatum var. clavatum 0.00 0.00 0.13 0.13 Lycopodium obscurum 0.00 0.00 0.60 0.60 Lycopus americanus 0.02 0.01 0.00 0.00


311

Mitigation Reference Species x SE x SE Lycopus uniflorus var. uniflorus 0.33 0.13 0.00 0.00 Lycopus virginicus 0.07 0.05 0.50 0.47 Lysimachia nummularia 0.17 0.11 0.00 0.00 Lythrum salicaria 1.52 0.94 0.00 0.00 Mimulus ringens var. ringens 0.27 0.12 0.35 0.26 Myosotis scorpioides 0.23 0.16 0.00 0.00 Onoclea sensibilis 0.16 0.11 0.10 0.10 Oxalis stricta 0.08 0.04 0.02 0.02 Panicum microcarpon 0.04 0.04 0.00 0.00 Panicum rigidulum var. rigidulum 0.43 0.15 0.00 0.00 Panicum virgatum var. virgatum 0.67 0.28 0.00 0.00 Phalaris arundinacea 6.99 2.71 0.00 0.00 Plantago lanceolata 0.13 0.06 0.00 0.00 Platanthera lacera var. lacera 0.02 0.01 0.00 0.00 Poa alsodes 0.02 0.02 0.00 0.00 Polygonum amphibium 0.02 0.01 0.00 0.00 Polygonum hydropiper 0.11 0.07 0.00 0.00 Polygonum hydropiperoides 1.59 1.09 0.03 0.02 Polygonum lapathifolium 0.10 0.10 0.00 0.00 Polygonum punctatum 0.06 0.04 0.02 0.02 Polygonum sagittatum 0.27 0.13 1.68 0.95 Polygonum scandens 0.00 0.00 0.02 0.02 Polygonum tenue var. tenue 0.03 0.03 0.00 0.00 Potamogeton spirillus 0.18 0.17 0.00 0.00 Potentilla simplex 0.59 0.27 0.00 0.00 Prunella vulgaris 0.04 0.02 0.00 0.00 Pteridium aquilinium 0.03 0.03 0.77 0.53 Pycnanthemum pycnanthemoides 0.07 0.07 0.00 0.00 Rubus hispidus 0.32 0.15 3.88 1.44 Rubus sp. 0.08 0.05 0.02 0.02 Rumex acetosella 0.01 0.01 0.00 0.00 Rumex crispus 0.12 0.08 0.00 0.00 Sagittaria latifolia var. latifolia 0.03 0.02 0.47 0.43 Scirpus acutus 0.00 0.00 0.23 0.23 Scirpus americanus 0.17 0.17 0.03 0.03 Scirpus atrocinctus 0.18 0.10 0.00 0.00 Scirpus cyperinus 0.62 0.22 0.02 0.02 Scirpus expansus 0.01 0.01 0.00 0.00


312

Mitigation Reference Species x SE x SE Scutellaria galericulata 0.00 0.00 0.07 0.07 Scutellaria lateriflora var. lateriflora 0.01 0.01 0.00 0.00 Selaginella apoda 0.01 0.01 0.00 0.00 Senecio aureus 0.05 0.04 0.00 0.00 Setaria faberi 0.01 0.01 0.00 0.00 Setaria glauca 0.01 0.01 0.00 0.00 Sisyrinchium angustifolium 0.18 0.13 0.00 0.00 Solanum carolinense var. carolinense 0.11 0.06 0.00 0.00 Solidago canadensis var. canadensis 0.17 0.17 1.53 1.53 Solidago rugosa ssp. rugosa 0.07 0.03 0.00 0.00 Solidago sp. 0.03 0.03 0.12 0.12 Solidago tall 0.17 0.17 0.00 0.00 Solidago uliginosa var. uliginosa 0.21 0.12 1.00 0.67 Sparganium americanum 0.26 0.24 1.25 1.25 Spirodela polyrrhiza 0.13 0.12 0.00 0.00 Teucrium canadense var. canadense 0.02 0.02 0.00 0.00 Thelypteris palustris var. pubescens 0.00 0.00 3.97 2.98 Toxicodendron radicans ssp. radicans 0.01 0.01 0.00 0.00 Triadenum virginicum 0.11 0.05 0.05 0.05 Trifolium arvense 0.02 0.01 0.00 0.00 Trifolium campestre 0.03 0.02 0.00 0.00 Trifolium pratense 0.16 0.13 0.00 0.00 Trifolium repens 0.17 0.13 0.00 0.00 Typha augustifolia 0.08 0.08 0.00 0.00 Typha latifolia 1.27 0.70 6.82 3.84 Vaccinium oxycoccos 0.04 0.04 0.00 0.00 Verbesina alternifolia 0.17 0.12 0.12 0.12 Vernonia noveboracensis 0.14 0.08 0.00 0.00 Viola cucullata 0.01 0.01 0.12 0.08 Viola macloskeyi ssp. pallens 0.05 0.04 0.00 0.00 Viola sororia 0.14 0.11 0.00 0.00 Viola sp. 0.02 0.01 0.00 0.00 Wolffia brasiliensis 0.24 0.24 0.00 0.00


313

Appendix 2. Species list, origin (O), and average cover (AC) per 0.05 ha plot of all

herbaceous vegetation species sampled, and vegetation species that were seen but not

sampled (SBNS) per plot at the Walnut Bottom mitigation wetland, 2001-2002.

Plot Species O AC Plot Species O AC

1 Agrostis gigantea N 1.5 4 Mimulus ringens var. ringens N 0.3

1 Phalaris arundinacea N 29.5 4 Scirpus cyperinus N 0.5 1 Polygonum hydropiper N 3.0 4 Typha latifolia N 6.8 1 Scirpus atrovirens N 3.8 SBNS 2 Agrostis gigantea N 0.3 Ambrosia artemisifolia N 2 Barbarea vulgaris E 0.3 Bidens sp. 2 Bidens sp. N 8.3 Carex frankii N 2 Carex frankii N 0.3 Carex vulpinoidea N 2 Echinochloa crus-galli var. crus-galli N 5.8 Cyperus strigosus N 2 Eleocharis obtusa N 1.8 Epilobium coloratum N 2 Erigeron aureus N 0.3 Erechtites hieraciifolia N 2 Iris pseudacorus E 4.5 Erigeron annuus N 2 Juncus tenuis N 3.5 Eupatorium perfoliatum N 2 Lycopus americanus N 0.3 Juncus effusus N 2 Mimulus ringens var. ringens N 0.3 Juncus marginatus N 2 Panicum virgatum var. virgatum N 7.0 Juncus subcaudatus N 2 Polygonum hydropiper N 0.8 Ludwigia palustris N 2 Polygonum tenue var. tenue N 1.5 Lycopus americana N 2 Rumex crispus E 3.3 Panicum virgatum N 3 Artemisia annua N 0.3 Penthorum sedoides N 3 Bidens sp. N 4.8 Polygonum tenue N 3 Carex folliculata N 0.3 Rumex crispus E 3 Carex vulpinoidea var. vulpinoidea N 1.8 Scirpus atrovirens N 3 Echinochloa crus-galli var. crus-galli N 21.5 Scirpus tabernaemontani N 3 Eleocharis obtusa N 6.0 Typha latifolia N 3 Epilobium coloratum N 1.8 Verbena hastata N 3 Juncus tenuis N 0.3 Verbena urticifolia N 3 Polygonum hydropiperoides N 2.0 3 Rumex crispus E 2.0 4 Agrostis gigantea N 3.0 4 Bidens sp. N 2.0 4 Eleocharis obtusa N 4.8 4 Juncus effusus var. effusus N 1.5 4 Juncus subcaudatus var. subcaudatus N 1.8 4 Lemna minor N 14.3 4 Ludwigia palustris N 5.0

aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and Ford-Werntz 2002)

314



sampled (SBNS) per plot at the VEPCO mitigation wetland, 2001-2002.

Plot Species Oa AC Plot Species Oa AC

1 Aster umbellatus var. umbellatus N 0.3 3 Carex gynandra N 2.3 1 Carex lurida N 0.3 3 Carex scoparia var. scoparia N 5.0 1 Carex lurida N 0.3 3 Euthamia graminifolia var. graminifolia N 0.5 1 Carex scoparia var. scoparia N 1.0 3 Galium mollugo E 2.5 1 Dichanthelium clandestinum N 0.5 3 Hypericum mutilum N 0.3 1 Euthamia graminifolia var. graminifolia N 1.5 3 Juncus brevicaudatus N 1.5 1 Galium tinctorium N 0.3 3 Juncus effusus var. effusus N 7.5 1 Glyceria canadensis N 0.3 3 Lycopus uniflorus var. uniflorus N 0.3 1 Hypericum mutilum N 2.3 3 Rubus hispidus N 1.5 1 Impatiens capensis N 0.3 3 Solidago uliginosa var. uliginosa N 0.3 1 Juncus brevicaudatus N 3.8 3 Triadenum virginicum N 0.5 1 Juncus effusus var. effusus N 7.5 3 Vernonia noveboracensis N 1.8 1 Juncus subcaudatus var. subcaudatus N 1.8 3 Viola macloskeyi ssp. pallens N 2.0 1 Juncus tenuis N 1.8 4 Carex gynandra N 1.8 1 Leersia oryzoides N 0.3 4 Carex scoparia var. scoparia N 0.8 1 Lycopus uniflorus var. uniflorus N 3.5 4 Dichanthelium clandestinum N 0.3 1 Scirpus atrocinctus N 1.5 4 Eleocharis tenuis var. tenuis N 5.0 1 Solidago incana ssp. incana N 0.5 4 Euthamia graminifolia var. graminifolia N 0.3 1 Solidago uliginosa var. uliginosa N 0.8 4 Galium mollugo E 2.0 1 Triadenum virginicum N 1.0 4 Juncus brevicaudatus N 10.31 Viola macloskeyi ssp. pallens N 0.3 4 Juncus effusus var. effusus N 6.3 2 Agrostis gigantea N 0.3 4 Leersia oryzoides N 1.5 2 Aster umbellatus var. umbellatus N 0.5 4 Lycopus uniflorus var. uniflorus N 2.0 2 Carex gynandra N 0.3 4 Rubus hispidus N 0.5 2 Carex lurida N 0.5 4 Solidago uliginosa var. uliginosa N 2.3 2 Carex scoparia var. scoparia N 3.5 4 Vaccinium oxycoccos N 1.8 2 Eleocharis compressa N 0.3 SBNS 2 Euthamia graminifolia var. graminifolia N 5.0 Aronia melanocarpa N 2 Galium tinctorium N 0.5 Carex gynandra N 2 Hypericum mutilum N 2.0 Coronilla varia E 2 Juncus acuminatus N 2.5 Danthonia compressa N 2 Juncus effusus var. effusus N 5.0 Drosera rotundifolia N 2 Juncus subcaudatus var. subcaudatus N 2.0 Eupatorium perfoliatum N 2 Lycopus uniflorus var. uniflorus N 1.0 Eupatorium pilosum N 2 Solidago incana ssp. incana N 1.0 Glyceria grandis N 2 Solidago uliginosa var. uliginosa N 0.5 Hypericum densiflorum N 2 Triadenum virginicum N 0.8 Hypericum mutilum N

315


SBNS continued Oa

Impatiens capensis N Leucanthemum vulgare E Onoclea sensibilis N Osmunda cinnamomea N Prunella vulgaris N Rosa multiflora E Rubus hispidus N Scirpus atrocinctus N Scirpus cyperinus N Scirpus tabernaemontani N Solidago incana N Veronia noveboracensis N aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and

Ford-Werntz 2002)

316



sampled (SBNS) per plot at the Buffalo Coal mitigation wetland, 2001-2002.

Plot Species O AC Species O

1 Aster umbellatus var. umbellatus N 3.8 SBNS 1 Carex scoparia var. scoparia N 0.5 Acer rubrum N 1 Carex stricta N 4.5 Carex lurida N 1 Danthonia compressa N 1.5 Carex lurida N 1 Diphasiastrum digitatum N 0.3 Glyceria grandis N 1 Juncus effusus var. effusus N 12.0 Hypericum mutilum N 1 Potentilla simplex N 1.8 Juncus subcaudatus N 1 Rubus hispidus N 1.8 Lycopus uniflora N 1 Solidago uliginosa var. uliginosa N 5.0 Polygala cruciata N 2 Carex canescens ssp. canescens N 1.5 Solidago rugosa N 2 Carex scoparia var. scoparia N 0.8 Solidago uliginosa N 2 Carex stricta N 7.5 Sparganium americanum N 2 Galium mollugo E 3.8 2 Glyceria canadensis N 1.5 2 Juncus effusus var. effusus N 7.5 2 Phalaris arundinacea N 3.8 2 Scirpus atrocinctus N 0.3 2 Triadenum virginicum N 1.8 3 Carex scoparia var. scoparia N 0.5 3 Carex stricta N 3.8 3 Galium tinctorium N 0.3 3 Juncus brevicaudatus N 0.3 3 Juncus effusus var. effusus N 6.3 3 Juncus subcaudatus var. subcaudatus N 0.3 3 Phalaris arundinacea N 0.3 3 Rubus hispidus N 0.3 3 Scirpus expansus N 0.3 3 Solidago uliginosa var. uliginosa N 0.5 3 Triadenum virginicum N 0.3 3 Viola cucullata N 0.3

aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and

Ford-Werntz 2002)

317



sampled (SBNS) per plot at the Elk Run mitigation wetland, 2001-2002.

Plot Species Oa AC 1 Carex lurida N 0.8

1 Carex scoparia N 2.0

1 Carex vulpinoidea 0.5

1 Eleocharis tenuis N 0.5

1 Eupatorium perfoliatum N 1.8

1 Galium mollugo E 1.8

1 Galium tinctorium N 1.0

1 Glyceria grandis N 3.5

1 Juncus effusus N 0.5

1 Leersia oryzoides N 11.8

1 Lycopus uniflorus N 0.5

1 Onoclea sensibilis N 3.8

1 Polygonum sagittatum N 0.3

1 Scirpus atrocinctus N 1.8

1 Sparganium americanum N 0.3

1 Triadenum virginicum N 0.5

1 Typha latifolia N 0.3

SBNS Agrostis hyemalis N Aster sp. Epilobium coloratum N Impatiens capensis N Mimulus ringens N Scutellaria laterifolia N aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and

Ford-Werntz 2002)

318



sampled (SBNS) per plot at the Leading Creek mitigation wetland, 2001-2002.

Plot Species Oa AC1 Agrostis gigantea N 0.8

1 Anthoxanthum odoratum ssp. odoratum E 0.3

1 Artemisia annua N 0.5

1 Asclepias incarnata N 0.3

1 Aster umbellatus var. umbellatus N 0.5

1 Carex vulpinoidea var. vulpinoidea N 3.0

1 Coronilla varia E 1.8

1 Dichanthelium clandestinum N 3.0


1 Dichanthelium sphaerocarpon var. sphaerocarpon N 5.0

1 Eleocharis tenuis var. tenuis N 0.5

1 Impatiens capensis N 0.5

1 Juncus effusus var. effusus N 3.3

1 Juncus tenuis N 1.8

1 Lonicera japonica N 0.5

1 Panicum virgatum var. virgatum N 6.0

1 Platanthera lacera var. lacera N 0.3

1 Potentilla simplex N 6.0

1 Prunella vulgaris N 0.5

1 Rubus hispidus N 0.3

1 Senecio aureus N 1.8

1 Solidago incana ssp. incana N 0.8

1 Solidago sp. 1.5

1 Trifolium campestre E 1.0

1 Trifolium repens E 2.0

1 Vernonia noveboracensis N 1.5

1 Viola sororia N 5.0

2 Polygonum hydropiperoides N 48.8

3 Eleocharis obtusa N 9.0

3 Heteranthera reniformis N 9.0

3 Juncus subcaudatus var. subcaudatus N 2.3


3 Ludwigia palustris N 11.3



3 Potamogeton spirillus A 0.5

3 Sagittaria latifolia var. latifolia N 0.5

319

Plot Species Oa AC

4 Agrostis gigantea N 0.8

4 Apios americana N 1.5

4 Boehmeria cylindrica N 0.5

4 Carex lurida N 2.3

4 Carex scoparia var. scoparia N 2.0

4 Carex stricta N 3.0





4 Euthamia graminifolia var. graminifolia N 0.5


4 Hypericum mutilum N 0.3



4 Oxalis stricta N 1.0

4 Panicum rigidulum var. rigidulum N 3.5

4 Platanthera lacera var. lacera N 0.3

4 Polygonum sagittatum N 2.3


4 Rubus sp. 1.5

4 Scutellaria lateriflora var. lateriflora N 0.3

4 Sisyrinchium angustifolium N 0.3

4 Toxicodendron radicans ssp. radicans N 1.5


5 Bidens sp. N 0.5

5 Carex intumescens N 0.3


5 Carex tribuloides N 0.3










5 Lycopus uniflorus var. uniflorus N 0.3

5 Panicum microcarpon N 1.8


5 Sagittaria latifolia var. latifolia N 0.5


320

Plot Species Oa AC

5 Scirpus cyperinus N 2.3







7 Eleocharis tenuis var. borealis N 6.0

7 Epilobium coloratum N 0.5







7 Juncus tenuis N 1.5



7 Oxalis stricta N 0.0



7 Scutellaria lateriflora var. lateriflora N 0.3

7 Trifolium arvense E 0.3

7 Viola cucullata N 0.3




8 Carex lurida N 3.5




8 Epilobium coloratum N 0.3

8 Erechtites hieraciifolia var. hieraciifolia N 1.5









8 Plantago lanceolata E 1.8


321

Plot Species Oa AC


8 Sisyrinchium angustifolium N 0.5

8 Solanum carolinense var. carolinense N 0.3

8 Trifolium arvense E 0.5

8 Trifolium campestre E 0.3

8 Viola sp. 0.3




9 Asclepias incarnata N 0.3

9 Asclepias syriaca N 0.3 9 Carex vulpinoidea var. vulpinoidea N 4.5 9 Crepis capillaris E 0.3 9 Dichanthelium clandestinum N 0.3 9 Eupatorium fistulosum N 0.3 9 Holcus lanatus E 0.5 9 Hypericum mutilum N 0.5 9 Juncus effusus var. effusus N 0.3 9 Juncus tenuis N 2.0 9 Leucanthemum vulgare E 1.3 9 Oxalis stricta N 0.3 9 Panicum rigidulum var. rigidulum N 3.0 9 Panicum virgatum var. virgatum N 6.3 9 Plantago lanceolata E 1.3 9 Potentilla simplex N 5.3 9 Prunella vulgaris N 0.3 9 Prunella vulgaris N 0.3 9 Rumex acetosella E 0.3 9 Senecio aureus N 0.5 9 Solanum carolinense var. carolinense N 1.8 9 Solidago incana ssp. incana N 0.8 9 Trifolium pratense E 5.5 9 Trifolium repens E 4.8 9 Viola sp. 0.5

SBNS Anthoxanthum odoratum E Asclepias incarnata N Aster sp. Carex intumescens N Carex intumescens N Carex lurida N Carex scoparia N


322

Species Oa AC

Carex tribuloides N Carex vulpinoidea N Cirsium pumilum N Cornus amomum N Coronilla varia E Dichanthelium clandestinum N Dulichium arundinaceum N Eleocharis obtusa N Erigeron anuus N Eupatorium perfoliatum N Euthamia graminifolia N Galium tinctorium N Heteranthera reniformis N Holcus lanatus E Hypericum densiflorum N Hypericum mutilum N Hypericum perforatum N Impatiens capensis N Juncus effusus N Juncus subcaudatus N Juncus tenuis N Leersia oryzoides N Leucanthemum vulgare E Ludwigia alternifolia N Lycopus uniflorus N Mimulus ringens N Oxalis stricta N Polygonum sagittatum N Potamogeton spirillus A Potentilla simplex N Rosa multiflora E Rosa palustris N Rumex crispus E Sagittaria latifolia N Salix nigra N Senecio aureus N Solanum carolinense N Solidago incana N Sparghanium americana N Vernonia noveborancensis N aN = species is native to West Virginia, E = exotic species not native to West

Virginia (Harmon and Ford-Werntz 2002)


323



sampled (SBNS) per plot at the Sugar Creek mitigation wetland, 2001-2002.


1 Agrimonia gryposepala N 0.3 2 Juncus effusus var. effusus N 1.5

1 Agrostis gigantea N 1.0 2 Phalaris arundinacea N 68.8

1 Anthoxanthum odoratum ssp. odoratum E 0.3 2 Scirpus cyperinus N 5.5

1 Apocynum cannabinum N 9.0 3 Asclepias incarnata N 0.3

1 Asclepias incarnata N 1.5 3 Boehmeria cylindrica N 0.8

1 Boehmeria cylindrica N 2.5 3 Eleocharis tenuis var. tenuis N 2.8

1 Carex lurida N 0.3 3 Galium tinctorium N 3.5

1 Carex scoparia var. scoparia N 0.3 3 Juncus effusus var. effusus N 0.3

1 Carex scoparia var. scoparia N 0.3 3 Mimulus ringens var. ringens N 0.8

1 Carex shortiana N 0.8 3 Oxalis stricta N 0.3

1 Carex vulpinoidea var. vulpinoidea N 2.3 3 Phalaris arundinacea N 50.0

1 Dichanthelium clandestinum N 10.3 3 Scirpus cyperinus N 6.8

1 Euthamia graminifolia var. graminifolia N 1.5 3 Typha latifolia N 1.5

1 Galium tinctorium N 5.8 4 Boehmeria cylindrica N 0.5

1 Hypericum mutilum N 0.3 4 Eleocharis tenuis var. tenuis N 1.8

1 Hypericum punctatum N 0.3 4 Galium tinctorium N 3.5

1 Juncus effusus var. effusus N 6.5 4 Juncus effusus var. effusus N 1.5

1 Juncus subcaudatus var. subcaudatus N 0.5 4 Juncus tenuis N 0.3

1 Juncus tenuis N 0.5 4 Ludwigia palustris N 1.8

1 Leersia oryzoides N 1.5 4 Lycopus uniflorus var. uniflorus N 0.3

1 Ludwigia palustris N 5.0 4 Mimulus ringens var. ringens N 2.0

1 Lycopus uniflorus var. uniflorus N 3.5 4 Panicum rigidulum var. rigidulum N 1.5

1 Mimulus ringens var. ringens N 3.3 4 Phalaris arundinacea N 61.8

1 Onoclea sensibilis N 0.3 4 Potentilla simplex N 0.3

1 Oxalis stricta N 1.0 4 Scirpus cyperinus N 1.8

1 Phalaris arundinacea N 26.0 4 Typha latifolia N 0.5

1 Rubus hispidus N 0.8 5 Boehmeria cylindrica N 0.3

1 Scirpus cyperinus N 3.8 5 Eleocharis tenuis var. tenuis N 0.8

1 Solanum carolinense var. carolinense N 0.3 5 Galium tinctorium N 1.5

1 Solidago tall 0.3 5 Juncus effusus var. effusus N 0.5

1 Teucrium canadense var. canadense E 0.8 5 Leersia oryzoides N 1.5

1 Viola papilionacea N 0.3 5 Ludwigia palustris N 0.3

2 Carex scoparia var. scoparia N 1.3 5 Panicum rigidulum var. rigidulum N 1.5

2 Carex stricta N 0.3 5 Phalaris arundinacea N 63.3

2 Carex vulpinoidea var. vulpinoidea N 0.5 5 Scirpus cyperinus N 2.5

2 Eleocharis tenuis var. tenuis N 3.0 SBNS 2 Galium tinctorium N 4.8 Alnus serulata N

324

SBNS continued Oa

Asclepias incarnata N Asclepias incarnata N Barbarea vulgaris E Carex intumescens N Clinopodium vulgare N Cornus amomum N Drosera rotundifolia N Hypericum perforatum N Impatiens capensis N Ludwigia alternifolia N Ludwigia palustris N Lycopus uniflora N Mimulus ringens N Panicum rigidulum N Salix nigra N Sambucus canadensis N Sisrinchium angustifolium N Typha latifolia N Verbena hastata N Verbena urticifolia N Veronia noveboracensis N aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and

Ford-Werntz 2002)


325



sampled (SBNS) per plot at the Sand Run mitigation wetland, 2001-2002.

Plot Species Oa AC Plot Species Oa AC1 Juncus effusus var. effusus N 12.75 4 Juncus secundus N 0.25

1 Leersia oryzoides N 1.00 4 Juncus subcaudatus var. subcaudatus N 0.75

1 Lemna minor N 1.00 4 Juncus tenuis N 0.501 Ludwigia palustris N 8.00 4 Leersia oryzoides N 2.251 Lycopus uniflorus var. uniflorus N 0.25 4 Ludwigia alternifolia N 1.501 Lysimachia nummularia E 0.50 4 Ludwigia palustris N 0.252 Juncus effusus var. effusus N 7.50 4 Lythrum salicaria E 3.002 Lemna minor N 2.25 4 Mimulus ringens var. ringens N 0.252 Ludwigia palustris N 7.25 4 Panicum rigidulum var. rigidulum N 0.253 Andropogon virginicus var. virginicus N 1.75 4 Phalaris arundinacea N 0.503 Apios americana N 0.50 4 Polygonum hydropiper N 0.253 Apocynum cannabinum N 0.25 SBNS 3 Carex lurida N 0.50 Acer saccharinum N 3 Carex scoparia var. scoparia N 0.25 Alnus serrulata N 3 Carex vulpinoidea var. vulpinoidea N 0.75 Apocynum cannabinum N 3 Eleocharis tenuis var. tenuis N 4.50 Asclepias incarnata N 3 Hypericum mutilum N 0.50 Brasenia schreberi A 3 Impatiens capensis N 1.75 Carex baileyi N 3 Juncus effusus var. effusus N 3.75 Carex lurida N 3 Juncus tenuis N 1.00 Cephalanthus occidentalis N 3 Ludwigia alternifolia N 3.25 Chelone glabra N 3 Mimulus ringens var. ringens N 2.00 Coronilla varia E 3 Panicum rigidulum var. rigidulum N 2.25 Cyperus strigosus N 3 Platanthera lacera var. lacera N 0.25 Dichanthelium clandestinum N 3 Polygonum hydropiper N 0.25 Eleocharis tenuis N 3 Potentilla simplex N 0.25 Erigeron annuus N 3 Pteridium aquilinium N 1.50 Fraxinus americana N 3 Rubus hispidus N 6.25 Galium tinctorium N 4 Apios americana N 0.50 Helenium flexuosa N 4 Carex lurida N 2.25 Hypericum densiflorum N 4 Carex vulpinoidea var. vulpinoidea N 0.50 Lemna minor N 4 Eleocharis tenuis var. tenuis N 0.25 Linum medium N 4 Eupatorium perfoliatum N 0.25 Ludwigia alternifolia N 4 Galium tinctorium N 0.50 Lycopus uniflora N 4 Impatiens capensis N 0.25 Lysimachia nummularia E 4 Juncus brachycarpus N 0.25 Lythrum salicaria E 4 Juncus effusus var. effusus N 8.25 Onoclea sensibilis N Osmunda cinnamomea N Penstemon digitalis N Phalaris arundinacea N Quercus rubra N Rumex crispus E

Sambucus canadensis N Scirpus tabernaemontani N Scutellaria laterifolia N

326


SBNS cont. Species O Sparganium americana N Thelypteris noveboracensis N Typha latifolia N aN = species is native to West Virginia,

E = exotic species not native to West Virginia

(Harmon and Ford-Werntz 2002)

327



sampled (SBNS) per plot at the Triangle mitigation wetland, 2001-2002.


1 Asclepias incarnata N 0.3 3 Ludwigia alternifolia N 0.8 1 Carex lurida N 2.0 3 Ludwigia palustris N 10.01 Carex scoparia var. scoparia N 0.3 3 Lycopus virginicus N 0.3 1 Carex tribuloides N 0.3 3 Lythrum salicaria E 3.8 1 Carex vulpinoidea var. vulpinoidea N 0.8 3 Myosotis scorpioides E 0.3 1 Eleocharis obtusa N 0.3 3 Phalaris arundinacea N 1.5 1 Eleocharis tenuis var. tenuis N 2.3 3 Polygonum amphibium N 0.5 1 Galium tinctorium N 1.5 3 Sagittaria latifolia var. latifolia N 0.3 1 Impatiens capensis N 10.8 3 Scirpus cyperinus N 0.3 1 Juncus effusus var. effusus N 15.8 3 Typha latifolia N 28.81 Juncus tenuis N 0.3 4 Agrostis gigantea N 4.3 1 Leersia oryzoides N 0.3 4 Apocynum cannabinum N 2.0 1 Ludwigia palustris N 4.5 4 Carex lurida N 0.3 1 Lycopus virginicus N 2.3 4 Carex scoparia var. scoparia N 1.5 1 Lysimachia nummularia E 3.8 4 Carex vulpinoidea var. vulpinoidea N 0.5 1 Lythrum salicaria E 38.3 4 Clinopodium vulgare N 0.3 1 Myosotis scorpioides E 6.8 4 Coronilla varia E 6.0 1 Polygonum sagittatum N 0.3 4 Dipsacus fullonum ssp. sylvestris E 17.51 Scirpus americanus N 7.8 4 Eleocharis tenuis var. tenuis N 1.5 1 Scirpus atrocinctus N 0.8 4 Euthamia graminifolia var. graminifolia N 1.8 1 Typha latifolia N 1.3 4 Galium tinctorium N 0.3 1 Vernonia noveboracensis N 0.3 4 Geum laciniatum N 2.0 2 Agrimonia gryposepala N 0.3 4 Impatiens capensis N 5.3 2 Bidens frondosa N 0.3 4 Juncus effusus var. effusus N 1.5 2 Eupatorium coelestinum N 0.3 4 Juncus tenuis N 2.8 2 Eupatorium fistulosum N 3.3 4 Ludwigia alternifolia N 0.5 2 Eupatorium perfoliatum N 5.5 4 Lycopus virginicus N 0.8 2 Helenium autumnale N 1.8 4 Lythrum salicaria E 4.5 2 Juncus effusus N 9.3 4 Myosotis scorpioides E 3.3 2 Polygonum amphibium N 0.3 4 Oxalis stricta N 0.3 2 Setaria glauca E 0.5 4 Panicum rigidulum var. rigidulum N 0.3 2 Solidago canadensis N 7.5 4 Phalaris arundinacea N 9.5 3 Boehmeria cylindrica N 0.3 4 Poa alsodes N 0.8 3 Cardamine rotundifolia N 0.3 4 Polygonum hydropiper N 0.5 3 Carex lurida N 0.3 4 Polygonum punctatum N 0.5 3 Carex scoparia var. scoparia N 0.3 4 Pycnanthemum pycnanthemoides N 3.0 3 Juncus effusus var. effusus N 3.3

328

Plot Species Oa AC

4 Solanum carolinense var. carolinense N 2.3 4 Verbesina alternifolia N 3.0 SBNS Agrimonia gryposepala N Allium ceruum N Apocynum cannabinum N Barbarea vulgaris E Carex gynandra N Carex projecta N Cephalanthus occidentalis N Cornus amomum N Coronilla varia E Dipsacus fullonum E Erigeron annuus N Eupatorium fistulosum N Eupatorium perfoliatum N Euthamia graminifolia N Gentian andrewsii N Juncus subcaudatus N Leucanthemum vulgare E Mentha piperita E Onoclea sensibilis N Phalaris arundinacea N Polygonum amphibium N Pycnanthemum pycnanthemoides N Sagittaria latifolia N Sambucus canadensis N Scirpus americanus N Senecio aurea N Solanum carolinense N Spiraea alba N Verbena hastata N Verbena urticifolia N Veronia noveboracensis N

aN = species is native to West Virginia, E = exotic species not native to West Virginia

(Harmon and Ford-Werntz 2002)


329



sampled (SBNS) per plot at the Trus Joist MacMillan mitigation wetland, 2001-2002.


1 Agrimonia gryposepala N 0.3 2 Eleocharis obtusa N 6.0

1 Allium cernuum var. cernuum N 0.3 2 Eleocharis tenuis var. tenuis N 0.5

1 Andropogon virginicus var. virginicus N 1.5 2 Galium tinctorium N 0.8

1 Anthoxanthum odoratum ssp. odoratum E 1.3 2 Hypericum mutilum N 0.5

1 Aster sp.1 0.3 2 Impatiens capensis N 0.0

1 Carex lurida N 0.3 4 Polygonum hydropiperoides N 3.0

1 Carex scoparia var. scoparia N 0.3 4 Polygonum lapathifolium N 4.5

1 Carex shortiana N 0.3 4 Polygonum sagittatum N 3.3

1 Carex stipata N 0.3 4 Rumex crispus E 0.3

1 Carex vulpinoidea var. vulpinoidea N 0.5 2 Juncus effusus var. effusus N 21.5

1 Clinopodium vulgare N 0.3 2 Leersia oryzoides N 7.0

1 Conium maculatum N 0.3 2 Ludwigia palustris N 7.5

1 Danthonia spicata N 0.5 2 Lycopus americanus N 0.5

1 Daucus carota E 0.8 2 Lythrum salicaria E 0.3

1 Dichanthelium clandestinum N 10.8 2 Polygonum hydropiperoides N 5.0

1 Galium aparine N 0.5 2 Polygonum sagittatum N 0.5

1 Galium tinctorium N 0.8 2 Scirpus cyperinus N 1.5

1 Hypericum punctatum N 0.3 2 Sparganium americanum N 0.3

1 Juncus effusus var. effusus N 0.5 3 Agrimonia gryposepala N 7.5

1 Juncus tenuis N 1.0 3 Bidens frondosa N 1.5

1 Lespedeza cuneata E 0.5 3 Carex lurida N 0.3

1 Leucanthemum vulgare E 0.8 3 Carex squarrosa N 1.8

1 Linum medium N 0.3 3 Carex vulpinoidea var. vulpinoidea N 3.3

1 Lycopus uniflorus var. uniflorus N 0.5 3 Dichanthelium clandestinum N 1.5

1 Panicum rigidulum var. rigidulum N 3.5 3 Eupatorium perfoliatum var. perfoliatum N 0.3

1 Plantago lanceolata E 1.5 3 Euthamia graminifolia var. graminifolia N 6.8

1 Potentilla simplex N 8.5 3 Galium tinctorium N 1.8

1 Prunella vulgaris ssp. vulgaris N 0.8 3 Geum canadense var. canadense N 0.5

1 Rubus sp. 2.0 3 Hypericum mutilum N 0.8

1 Setaria faberi E 0.3 3 Impatiens capensis N 7.5

1 Solanum carolinense var. carolinense N 0.3 3 Juncus effusus var. effusus N 0.5

1 Solidago gramminifolia N 0.8 3 Leersia oryzoides N 2.0

1 Solidago tall 7.5 3 Lysimachia nummularia E 3.3

1 Trifolium pratense E 1.8 3 Mimulus ringens var. ringens N 0.3

2 Bidens frondosa N 3.3 3 Oxalis stricta N 0.3

2 Boehmeria cylindrica N 0.3 3 Panicum rigidulum var. rigidulum N 3.5

2 Echinochloa crus-galli var. crus-galli N 3.0 3 Polygonum hydropiperoides N 0.5

330

Plot Species Oa AC SBNS Oa

3 Polygonum punctatum N 0.5 Achillea millefolium E 3 Polygonum sagittatum N 4.8 Agrostis gigantea N 3 Rubus sp. 1.5 Apocynum cannabinum N 3 Scirpus cyperinus N 3.0 Asclepias incarnata N 3 Typha latifolia N 3.0 Carex intumescens N 3 Vernonia noveboracensis N 3.0 Carex scoparia N

4 Echinochloa crus-galli var. crus-galli N 0.3 Cornus amomum N

4 Erechtites hieraciifolia var. hieraciifolia N 0.3 Erechtites hieraciifolia N

4 Galium tinctorium N 0.3 Erigeron annuus N 4 Impatiens capensis N 1.5 Eupatorium fistulosum N 4 Juncus effusus var. effusus N 7.5 Heteranthera reniformis N 4 Leersia oryzoides N 40.3 Juncus acuminatis N 4 Ludwigia palustris N 3.3 Juncus nodosus N 4 Lycopus uniflorus var. uniflorus N 3.0 Juncus subcaudatus N Juncus tenuis N Lespedeza cuneata E Leucanthemum vulgare E Lycopus uniflora N Lythrum salicaria E Mimulus ringens N Penthorum sedoides N Rosa palustris N Scirpus tabernaemontani N Teuchrium canadense E Typha latifolia N Verbena hastata N Verbena urticifolia N Veronia noveboracensis N


Ford-Werntz 2002)


331



sampled (SBNS) per plot at the Enoch Branch mitigation wetland, 2001-2002.


1 Aster sp. 0.3 3 Sisyrinchium angustifolium N 5.5

1 Coronilla varia E 9.3 3 Solanum carolinense var. carolinense N 0.3

1 Eleocharis tenuis var. tenuis N 0.3 3 Verbesina alternifolia N 4.5

1 Epilobium coloratum N 0.5 4 Eleocharis obtusa N 6.3

1 Juncus effusus var. effusus N 1.8 4 Eleocharis tenuis var. tenuis N 1.5

1 Juncus tenuis N 0.5 4 Juncus effusus var. effusus N 3.8

1 Lespedeza cuneata E 8.3 4 Juncus subcaudatus var. subcaudatus N 0.3

1 Ludwigia palustris N 0.3 4 Leersia oryzoides N 0.3

1 Panicum rigidulum var. rigidulum N 0.3 4 Ludwigia palustris N 2.5

1 Panicum virgatum var. virgatum N 6.3 4 Sparganium americanum N 10.8

1 Plantago lanceolata E 1.5 SBNS 1 Rubus hispidus N 0.8 Acer rubrum N 1 Sisyrinchium angustifolium N 2.0 Apios americana N 1 Viola sororia N 0.3 Apocynum cannabinum N 2 Eleocharis obtusa N 1.8 Asclepias incarnata N 2 Eleocharis tenuis var. tenuis N 1.8 Boehmeria cylindrica N 2 Juncus effusus var. effusus N 5.5 Carex intumescens N 2 Juncus subcaudatus var. subcaudatus N 2.0 Carex scoparia N 2 Leersia oryzoides N 0.8 Carex vulpinoidea N 2 Ludwigia palustris N 0.0 Eleocharis tenuis N 2 Sparganium americanum N 0.3 Galium tinctorium N 3 Agrimonia gryposepala N 0.3 Hypericum mutilum N 3 Antennaria solitaria N 0.3 Juncus effusus N 3 Apios americana N 0.3 Leucanthemum vulgare E 3 Aster sp. 0.8 Ludwigia alternifolia N 3 Carex lurida N 0.3 Ludwigia palustris N 3 Galium tinctorium N 6.0 Mimulus ringens N 3 Hypericum mutilum N 5.0 Onoclea sensibilis N 3 Juncus brevicaudatus N 0.3 Panicum rigidulum N 3 Juncus effusus var. effusus N 4.8 Potamogeton diversifolius N 3 Mimulus ringens var. ringens N 3.3 Rosa multiflora E 3 Onoclea sensibilis N 3.3 Sagittaria latifolia N 3 Oxalis stricta N 0.8 Scirpus tabernaemontani N 3 Panicum virgatum var. virgatum N 1.8 Solanum carolinense N 3 Rubus hispidus N 0.8 3 Scirpus cyperinus N 0.3 3 Selaginella apoda N 0.3 aN = species is native to West Virginia, E = exotic

species not native to West Virginia (Harmon and Ford-

332



sampled (SBNS) per plot at the Bear Run mitigation wetland, 2001-2002.

Plot Species Oa AC


1 Eleocharis quadrangulata N 12.0


1 Lemna minor N 3.8


1 Potamogeton spirillus A 7.5

1 Spirodela polyrrhiza N 0.3





2 Lemna minor N 5.3


2 Spirodela polyrrhiza N 5.5

2 Typha angustifolia N 3.8


2 Wolffia brasiliensis N 10.8

SBNS

Carex lurida N

Carex tribuloides N

Cyperus strigosus N

Galium tinctorium N

Mimulus ringens N

Sagittaria graminea N aN = species is native to West Virginia, E = exotic species not native to West Virginia (Harmon and

Ford-Werntz 2002)

333



sampled (SBNS) per plot at the Altona Marsh reference wetland, 2001-2002.

Plot Species Oa AC 1 Boehmeria cylindrica N 15 1 Galium tinctorium N 1.5 1 Juncus balticus var. littoralis N 15 1 Leersia oryzoides N 0.5 1 Lycopus virginicus N 0.5 1 Scirpus acutus N 3.5 1 Thelypteris palustris var. pubescens N 42.5 2 Boehmeria cylindrica N 10 2 Galium tinctorium N 5 2 Impatiens pallida N 12.5 2 Juncus balticus var. littoralis N 4.5 2 Ludwigia palustris N 2 2 Lycopus virginicus N 7 2 Mimulus ringens var. ringens N 0.5 2 Sagittaria latifolia var. latifolia N 6.5 2 Scirpus americanus N 0.5 2 Thelypteris palustris var. pubescens N 17 2 Typha latifolia N 37.5 3 Caltha palustris var. palustris N 6 3 Equisetum fluviatile N 12.5 3 Eupatorium maculatum var. maculatum N 3.5 3 Impatiens pallida N 33.5 3 Mimulus ringens var. ringens N 0.5 3 Sagittaria latifolia var. latifolia N 0.5 3 Scutellaria galericulata N 1 3 Typha latifolia N 1


Ford-Werntz 2002)

334



sampled (SBNS) per plot at the Elder Swamp reference wetland, 2001-2002.


1 Eriophorum virginicum N 1.3 6 Juncus effusus var. effusus N 1.5

1 Rubus hispidus N 12.3 6 Juncus subcaudatus var. subcaudatus N 0.8

1 Solidago uliginosa var. uliginosa N 0.3 6 Rubus hispidus N 1.5

2 Drosera rotundifolia var. rotundifolia N 0.8 6 Triadenum virginicum N 0.8

2 Eriophorum virginicum N 12.0 6 Typha latifolia N 9.8

2 Gaultheria procumbens N 0.8 6 Viola cucullata N 0.8

2 Rubus hispidus N 7.5 7 Danthonia compressa N 1.8

3 Carex canescens ssp. canescens N 8.5 7 Lycopodium obscurum N 9.0

3 Carex trisperma var. trisperma N 0.3 7 Pteridium aquilinium N 6.8

3 Drosera rotundifolia var. rotundifolia N 2.5 7 Rubus hispidus N 16.5

3 Eriophorum virginicum N 2.3 7 Solidago uliginosa var. uliginosa N 9.8

3 Juncus brevicaudatus N 1.5 SBNS

3 Rubus hispidus N 5.0 Amelanchier laevis N

4 Agrostis hyemalis N 0.3 Aster umbellatus N

4 Aster puniceus N 0.3 Carex crinita N

4 Carex argyrantha N 0.3 Carex gynandra N

4 Carex folliculata N 1.5 Carex scoparia N

4 Carex scoparia var. scoparia N 0.3 Carex vulpinoidea N

4 Galium tinctorium N 1.3 Cypredium acaule N

4 Glyceria canadensis N 1.8 Eriophorum virginicum N

4 Glyceria striata N 0.3 Galium tinctorium N

4 Impatiens capensis N 2.3 Gentian andrewsii N

4 Leersia oryzoides N 11.5 Glyceria grandis N

4 Polygonum sagittatum N 1.8 Hypericum densiflorum N

4 Rubus hispidus N 3.5 Juncus effusus N

4 Solidago sp. 1.8 Lycopodium obscurum N

4 Solidago uliginosa var. uliginosa N 1.5 Osmunda cinnamomea N

4 Typha latifolia N 0.3 Polygonum sagittatum N

4 Viola cucullata N 1.0 Populus tremuloides N

5 Danthonia compressa N 0.8 Solidago incana N

5 Lycopodium clavatum var. clavatum N 2.0 Tradenum virginicum N

5 Pteridium aquilinum var. latiusculum N 4.8 Vaccinium oxycoccus N

5 Rubus hispidus N 12.0 Viburnum dentatum N

5 Solidago uliginosa var. uliginosa N 3.5 6 Dulichium arundinaceum N 0.3


335



sampled (SBNS) per plot at the Meadowville reference wetland, 2001-2002.


1 Carex scoparia var. scoparia N 4.5 4 Clematis virginiana N 6.0

1 Carex stricta N 17.0 4 Galium mollugo E 7.3

1 Carex tribuloides N 0.8 4 Galium tinctorium N 0.5

1 Eleocharis tenuis var. tenuis N 1.5 4 Geum rivale N 5.0

1 Epilobium coloratum N 4.8 4 Impatiens capensis N 17.3

1 Galium tinctorium N 3.5 4 Oxalis stricta N 0.3

1 Glyceria canadensis N 0.3 4 Polygonum sagittatum N 13.0

1 Impatiens capensis N 12.5 4 Rubus sp. 0.3

1 Leersia oryzoides N 30.0 4 Solidago canadensis var. canadensis N 23.0

1 Ludwigia palustris N 2.3 4 Verbesina alternifolia N 1.8

1 Mimulus ringens var. ringens N 4.0 SBSN 1 Polygonum sagittatum N 3.5 Asclepias incarnata N 1 Typha latifolia N 6.3 Calamagrostis canadensis N 2 Boehmeria cylindrica N 1.8 Carex gynandra N 2 Calamagrostis canadensis var. canadensis N 61.8 Carex lurida N 2 Carex stipata N 0.5 Carex scoparia N 2 Carex stricta N 11.8 Cornus amomum N 2 Galium mollugo E 3.5 Epilobium coloratum N 2 Galium tinctorium N 2.5 Juncus effusus N 2 Glyceria canadensis N 1.8 Onoclea sensibilis N 2 Impatiens pallida N 3.5 Rosa palustris N 2 Juncus effusus var. effusus N 0.3 Sambucus canadensis N 2 Leersia oryzoides N 0.8 Scirpus cyperinus N 2 Polygonum sagittatum N 7.0 Scutellaria laterifolia N 2 Scirpus cyperinus N 0.3 3 Carex stricta N 6.0 3 Galium tinctorium N 0.3 3 Glyceria canadensis N 2.5 3 Gratiola virginiana var. virginiana N 3.5 3 Mimulus ringens var. ringens N 0.3 3 Polygonum hydropiperoides N 0.3 3 Polygonum scandens E 0.3 3 Typha latifolia N 47.5 4 Agrimonia gryposepala N 4.8 4 Apocynum cannabinum N 1.0 4 Boehmeria cylindrica N 1.5 4 Carex stricta N 28.5


336



sampled (SBNS) per plot at the Muddlety reference wetland, 2001-2002.


Ford-Werntz 2002)

Plot Species Oa AC 1 Juncus effusus var. effusus N 2.0


1 Onoclea sensibilis N 1.5


1 Polygonum punctatum N 0.3

1 Sparganium americanum N 18.8

SBNS Boehmeria cylindrica N Carex lupulina N Polygala polygama N Rosa palustris N Scutellaria laterifolia N

337

Appendix 17. Woody and herbaceous vegetation species that were planted at 3 mitigation wetland sites, West Virginia, 2001-2002.

Species Number Planted Type Common name Scientific name Triangle Sand Run VEPCO Trees Black willow Salix nigra 45 Pin oak Quercus palustris 80 Swamp white oak Quercus bicolor Red maple Acer rubrum 250 Silver maple Acer sacharinum 225 40 Serviceberry Amelanchier laevis 204 Shrubs Buttonbush Cephalanthus occidentalis 2,275 200 Black edlerberry Sambucus canadensis 1300 300 Red chokeberry Aronia arbutifolia 270 Pipestem Spiraea alba 100 Winterberry Ilex verticllata 30 Alders (smooth/speckled) Alnus serrulata/incana 275 Highbush cranberry Viburnum trilobum 115 Gray dogwood Cornus foemina 400 Herbaceous Duck potato Sagittaria latifolia 1300 100 Common threesquare Scirpus americanus 3000 Sedge Carex lurida 350 Woolgrass Scirpus atrovirens 1250 500 Sensitive fern Onoclea sensibilis 350 Seed Switchgrass Panicum virgatum 15 Ibs/acre 15 Ibs/acre 15 Ibs/acre Redtop Agrostis alba 10 Ibs/acre 10 Ibs/acre Wild millet Echinochloa crusgalli 10 Ibs/acre 10 Ibs/acre Japanese millet Echinochloa frumentacea 1/2 bushel/acre Annual rye Lolium mutliflorum 280 Ibs/acre

338

Appendix 18-1. Bird, frog, and vegetation sampling points as well as dominant

vegetation at the Altona Marsh reference wetland, West Virginia, 2001-2002.

339

Appendix 18-2. Wetland classification (Cowardin et al. 1979) where PEM =

palustrine emergent, PF = palustrine forested, PSS = palustrine scrub-shrub, and PUB

= palustrine unconsolidated bottom, of the Altona Marsh reference wetland, West


340


vegetation at the Walnut Bottom mitigation wetland, West Virginia, 2001-2002.


palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine

unconsolidated bottom, of the Walnut Bottom mitigation wetland, West Virginia,

2001-2002.

Maps were unable to be obtained for this site.

341


vegetation at the Elder Swamp reference wetland, West Virginia, 2001-2002.

342


palustrine emergent, PF = palustrine forested, PSS = palustrine scrub-shrub, and PUB

= palustrine unconsolidated bottom of the Elder Swamp reference wetland, West


343


vegetation at the VEPCO mitigation wetland, West Virginia, 2001-2002.

344

Appendix 21-2. Wetland classification (Cowardin et al. 1979) where N/A = no

applicable classification, PEM = palustrine emergent, PSS = palustrine scrub-shrub,

and PUB = palustrine unconsolidated bottom of the VEPCO mitigation wetland, West


345


vegetation at the Buffalo Coal mitigation wetland, West Virginia, 2001-2002.

346



and PUB = palustrine unconsolidated bottom of the Buffalo Coal mitigation wetland,


347


vegetation at the Elk Run mitigation wetland, West Virginia, 2001-2002.

348



and PUB = palustrine unconsolidated bottom of the Elk Run mitigation wetland,

WestVirginia, 2001-2002.

349


vegetation at the Meadowville reference wetland, West Virginia, 2001-2002.

350


applicable classification, PEM = palustrine emergent, and PSS = palustrine scrub-

shrub, of the Meadowville reference wetland, West Virginia, 2001-2002.

351


vegetation at the Leading Creek mitigation wetland, West Virginia, 2001-2002.

352



and PUB = palustrine unconsolidated bottom of the Leading Creek mitigation

wetland, West Virginia, 2001-2002.

353


vegetation at the Sugar Creek mitigation wetland, West Virginia, 2001-2002.

354



and PUB = palustrine unconsolidated bottom of the Sugar Creek mitigation wetland,


355


vegetation at the Sand Run mitigation wetland, West Virginia, 2001-2002.

356



and PUB = palustrine unconsolidated bottom of the Sand Run mitigation wetland,


357


vegetation at the Triangle mitigation wetland, West Virginia, 2001-2002.

358



and PUB = palustrine unconsolidated bottom of the Triangle mitigation wetland,


359


vegetation at the Trus Joist MacMillan mitigation wetland, West Virginia, 2001-2002.

360


palustrine emergent, PSS = palustrine scrub-shrub, PUB = palustrine unconsolidated

bottom, and PUS = palustrine unconsolidated shore, of the Trus Joist MacMillan

mitigation wetland, West Virginia, 2001-2002.

361


vegetation at the Muddlety reference wetland, West Virginia, 2001-2002.

362


palustrine emergent, PSS = palustrine scrub-shrub, and PUB = palustrine

unconsolidated bottom of the Muddlety reference wetland, West Virginia, 2001-2002.

363


vegetation at the Enoch Branch mitigation wetland, West Virginia, 2001-2002.

364



and PUB = palustrine unconsolidated bottom of the Enoch Branch mitigation

wetland, West Virginia, 2001-2002.

365


vegetation at the Bear Run mitigation wetland, West Virginia, 2001-2002.

366


applicable classification, PEM = palustrine emergent, and PUB = palustrine

unconsolidated bottom of the Bear Run mitigation wetland, West Virginia, 2001-

2002.

367

Appendix 33. Number of benthic individuals collected by family and wetland from emergent (E) and open water (O) areas, as well as for the entire

complex (total) for 11 mitigation wetlands in West Virginia, 2001-2002.

Walnut

Bottom Vepco Buffalo Coal Elk Run Leading Creek Sugar Creek Sand Run Triangle

Trus Joist MacMillan Enoch Branch Bear Run TOTAL

Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total

Arachnid Hydracarina 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1

Coleoptera Chrysomelidae 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 4 0 4 1 0 1 10 0 10

Coleoptera Curculionidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1

Coleoptera Dytiscidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 2 0 2 Coleoptera Elmidae 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 Coleoptera Hydrophilidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Coleoptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 3 4 Diptera Ceratopogonidae 1 1 2 5 0 5 1 1 2 1 0 1 2 0 2 0 5 5 3 0 3 9 1 10 3 1 4 4 1 5 0 3 3 29 13 42 Diptera Chaobridae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 Diptera Chironomidae 1 11 12 13 27 40 9 10 19 15 9 24 8 2 10 3 1 4 2 1 3 1 4 5 3 5 8 11 13 24 2 4 6 68 87 155 Diptera Culicidae 0 0 0 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 Diptera Empididae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 1 1 1 0 1 0 0 0 0 1 1 4 2 6 Diptera Ephydridae 0 0 0 2 0 2 0 2 2 10 1 11 3 0 3 12 0 12 1 0 1 4 3 7 3 0 3 2 0 2 4 0 4 41 6 47 Diptera Psychodidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Diptera Sciomyzidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 Diptera Tabanidae 1 0 1 1 0 1 1 0 1 1 0 1 4 0 4 2 2 4 1 0 1 0 0 0 2 0 2 0 0 0 0 0 0 13 2 15 Diptera Tipulidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 2 0 2 Diptera UNKNOWN 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 3 0 3 Ephemeroptera Caenidae 0 1 1 0 0 0 0 2 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 4 Ephemeroptera Ephemerillidae 0 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 3 Gastropoda Lymnaedae 12 0 12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 4 5 2 0 2 0 0 0 2 0 2 17 4 21 Gastropoda Physidae 199 94 293 0 0 0 0 0 0 4 1 5 1 0 1 2 0 2 5 5 10 50 27 77 55 0 55 0 0 0 8 2 10 324 129 453 Gastropoda Planorbidae 278 285 563 9 1 10 1 3 4 132 18 150 17 7 24 6 9 15 17 5 22 19 22 41 48 2 50 0 2 2 28 80 108 555 434 989 Gastropoda Pomatiopsidae 10 8 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 10 8 18 Gastropoda Valvatidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 Gastropoda Viviparidae 63 8 71 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 13 7 20 34 0 34 0 0 0 19 0 19 129 16 145 Gastropoda UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1

368

Walnut Bottom Vepco Buffalo Coal Elk Run



Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total

Hemiptera Notonectidae 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Hirudinodea Erpobdellidae 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 Hirudinodea Glossiphoniidae 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Lepidoptera Pyralidae 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Nematoda Mermithidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 1 1 2 Nematoda Nematoda 0 0 0 0 0 0 0 0 0 2 1 3 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 5 1 6 Odanata Coenagrionidae 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Odanata Corduliidae 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3 1 4 5 Odanata Libellulidae 0 1 1 0 0 0 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3 Oligochaeta Oligochaeta 65 19 84 24 12 36 3 36 39 20 28 48 69 20 89 25 144 169 3 4 7 28 79 107 253 48 301 25 25 50 15 9 24 530 424 954 Pelecypoda Sphaeriidae 0 2 2 0 0 0 1 7 8 48 55 103 17 7 24 4 0 4 0 0 0 41 58 99 10 0 10 0 0 0 4 2 6 125 131 256 Pelecypoda Unionidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 2 0 2 2 1 3 Trichoptera Leptoceridae 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Trichoptera Phryganeidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 UNKNOWN UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 3 3 TOTALS 633 431 1064 59 41 100 18 63 81 241 117 358 128 36 164 59 162 221 34 16 50 171 207 378 416 57 473 48 45 93 86 104 190 1893 1279 3172


369

Appendix 34. Number of nektonic individuals collected by family and wetland from emergent (E), open water (O), and scrub-shrub

(SS) areas, as well as for the entire complex (total) for 4 reference wetlands in West Virginia, 2001-2002.

Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS total Amphipoda Gammaridae 1 0 1 0 0 1 1 0 0 0 0 0 0 0 1 0 1 2 Amphipoda Talitridae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Coleoptera Chrysomelidae 0 0 0 0 0 0 0 0 0 0 4 0 0 4 4 0 0 4 Coleoptera Elmidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Decapoda Astracidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Diptera Ceratopogonidae 0 1 1 1 0 3 4 1 0 1 3 2 0 5 5 3 3 11 Diptera Chironomidae 3 1 4 1 5 1 7 9 0 9 7 13 1 21 20 19 2 41 Diptera Ephydridae 3 0 3 1 0 0 1 12 0 12 4 1 0 5 20 1 0 21 Diptera Scatophagidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Diptera Stratiomyidae 0 1 1 0 0 0 0 1 0 1 0 0 0 0 1 1 0 2 Diptera Tabanidae 1 1 2 0 0 0 0 2 0 2 2 0 0 2 5 1 0 6 Diptera UNKNOWN 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Ephemeroptera Caenidae 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 2 0 2 Gastropoda Lymnaedae 130 55 185 0 0 0 0 0 0 0 0 0 0 0 130 55 0 185 Gastropoda Physidae 435 73 508 0 0 0 0 0 0 0 0 0 0 0 435 73 0 508 Gastropoda Planorbidae 450 597 1047 0 2 0 2 0 0 0 0 11 4 15 450 610 4 1064Gastropoda Pomatiopsidae 319 264 583 0 0 0 0 0 0 0 0 0 0 0 319 264 0 583 Gastropoda Valvatidae 5 122 127 0 0 0 0 0 0 0 0 0 0 0 5 122 0 127 Gastropoda Viviparidae 105 327 432 0 0 0 0 2 0 2 2 2 0 4 109 329 0 438 Hirudinodea Erpobdellidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Isopoda Asellidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Megaloptera Sialidae 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 Nematoda Nematoda 0 0 0 0 0 0 0 1 0 1 1 7 0 8 2 7 0 9 Oligochaeta Oligocheata 11 17 28 1 3 10 14 28 0 28 23 20 4 47 63 40 14 117 Pelecypoda Sphaeriidae 419 180 599 0 1 0 1 5 0 5 8 1 6 15 432 182 6 620 Pelecypoda Unionidae 7 36 43 0 0 0 0 0 0 0 0 0 0 0 7 36 0 43

370

Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS total UNKNOWN UNKNOWN 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 TOTALS 1893 1675 3568 5 11 15 31 62 0 62 57 59 15 131 2017 1745 30 3792


371

Appendix 35. Number of nektonic individuals collected by family and wetland from emergent (E) and open water (O) areas, as well as for the

entire complex (total) for 11 mitigation wetlands in West Virginia, 2001-2002.

Walnut Bottom Vepco Buffalo Coal Elk Run Leading Creek Sugar Creek Sand Run Triangle


Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total Amphipoda Gammaridae 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 Amphipoda Talitridae 2 159 161 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 159 162 Arachnid Hydracarina 0 0 0 0 0 0 21 6 27 1 8 9 0 0 0 0 0 0 1 0 1 5 11 16 0 0 0 1 0 1 1 3 4 30 28 58 Arachnid Arachnid 0 1 1 4 1 5 2 0 2 0 0 0 1 0 1 5 0 5 1 0 1 5 1 6 1 0 1 0 0 0 2 0 2 21 3 24 Arguloida Argulidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Cladocera NA 2 83 3 2 5 7 102 27 129 17 7 24 1 0 1 9 0 9 2 0 2 5 32 37 45 0 45 0 0 0 2 0 2 187 154 341 Coleoptera Carabidae 1 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 4 Coleoptera Chrysomelidae 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Coleoptera Dytiscidae 6 3 9 2 1 3 15 1 16 7 0 7 14 0 14 0 1 1 0 0 0 5 0 5 2 0 2 0 0 0 3 0 3 54 6 60 Coleoptera Elmidae 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 0 2 0 2 4 1 5 Coleoptera Gyrinidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 Coleoptera Haliplidae 0 27 27 0 0 0 2 2 4 3 0 3 3 0 3 0 0 0 5 2 7 6 11 17 1 0 1 0 0 0 5 10 15 25 52 77 Coleoptera Helodidae 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 Coleoptera Hydrophilidae 4 0 4 1 0 1 0 1 1 0 0 0 1 0 1 1 1 2 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 8 2 10 Coleoptera Noteridae 0 0 0 0 0 0 6 1 7 1 0 1 0 2 2 1 0 1 0 0 0 4 0 4 0 0 0 0 0 0 2 0 2 14 3 17 Coleoptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 Collembola Isotomidae 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3 Collembola Poduridae 0 0 0 0 0 0 7 3 10 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 4 11 Conchostraca Conchostraca 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 0 0 0 0 0 0 0 1 1 1 5 6 Copepoda Cyclopoida 2 10 12 2 5 7 12 2 14 3 5 8 1 1 2 2 0 2 1 0 1 2 0 2 2 0 2 0 0 0 6 2 8 33 25 58 Diptera Athericidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Diptera Ceratopogonidae 0 0 0 0 0 0 6 2 8 6 3 9 0 0 0 1 0 1 1 0 1 1 1 2 0 0 0 0 0 0 1 0 1 16 6 22 Diptera Chaobaridae 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 8 6 4 10 Diptera Chironomidae 10 16 26 48 19 67 148 20 168 10 12 22 6 1 7 6 0 6 14 2 16 6 52 58 7 0 7 15 0 15 6 8 14 276 130 406 Diptera Culicidae 6 4 10 3 0 3 22 1 23 1 1 2 13 1 14 4 0 4 0 0 0 1 2 3 1 0 1 1 0 1 2 0 2 54 9 63 Diptera Dixidae 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 Diptera Ephydridae 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Diptera Sciomyzidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2

372




Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total Diptera Stratiomyidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Diptera Tabanidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 2 1 3 Diptera Tipulidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 Diptera UNKNOWN 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 2 1 3 Ephemeroptera Baetidae 13 72 85 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 1 1 2 1 5 6 3 0 3 0 0 0 7 12 19 25 92 117 Ephemeroptera Caenidae 1 0 1 1 3 4 6 47 53 36 15 51 0 6 6 3 4 7 16 19 35 4 56 60 1 0 1 8 1 9 14 10 24 90 161 251 Ephemeroptera Siphlonuridae 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 Ephemeroptera UNKNOWN 0 0 0 1 0 1 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 Gastropoda Lymnaedae 2 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 3 2 5 Gastropoda Physidae 28 41 69 0 0 0 0 0 0 0 0 0 3 0 3 7 1 8 9 2 11 10 1 11 14 1 15 0 0 0 6 10 16 77 56 133

Gastropoda Planorbidae 25 46 71 0 0 0 0 2 2 58 9 67 19 2 21 14 13 27 18 6 24 5 13 18 2 0 2 4 17 21 44 22 66 189 130 319 Gastropoda Viviparidae 32 8 40 0 0 0 0 2 2 3 0 3 1 1 2 1 0 1 5 0 5 9 3 12 15 0 15 0 0 0 3 0 3 69 14 83 Hemiptera Aphididae 0 0 0 0 0 0 3 0 3 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 Hemiptera Belostomatidae 1 0 1 0 0 0 0 0 0 0 0 0 0 2 2 1 0 1 0 0 0 1 0 1 0 0 0 1 0 1 1 0 1 5 2 7 Hemiptera Corixidae 1 6 7 1 3 4 13 1 14 2 2 4 0 2 2 0 2 2 0 0 0 0 0 0 82 4 86 0 0 0 0 0 0 99 20 119 Hemiptera Delphacidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 Hemiptera Gerridae 0 2 2 0 0 0 4 1 5 3 1 4 2 0 2 2 0 2 3 0 3 0 0 0 0 0 0 8 0 8 0 0 0 22 4 26 Hemiptera Hebridae 1 3 4 0 0 0 2 0 2 4 1 5 0 0 0 4 0 4 5 1 6 2 0 2 0 0 0 3 0 3 8 2 10 29 7 36 Hemiptera Hydrometridae 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 1 0 1 2 0 2 0 0 0 1 0 1 0 0 0 6 0 6 Hemiptera Mesoveliidae 2 0 2 0 0 0 0 0 0 0 1 1 0 0 0 3 0 3 4 0 4 1 3 4 1 1 2 5 0 5 7 1 8 23 6 29 Hemiptera Naucoridae 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 2 Hemiptera Nepidae 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Hemiptera Notonectidae 0 2 2 0 0 0 2 0 2 2 0 2 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 7 2 9 Hemiptera Saldidae 0 0 0 0 0 0 2 1 3 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 1 0 0 0 5 2 7 Hemiptera Veliidae 1 0 1 0 0 0 3 0 3 5 1 6 2 1 3 4 0 4 20 0 20 33 43 76 0 0 0 14 0 14 15 10 25 97 55 152 Hemiptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 4 0 4 4 1 5 Hirudinea Glossiphoniidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 1 3 4 Hymenoptera Braconidae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 2 0 2 Hymenoptera Formicidae 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Hymenoptera Mymaridae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Isopoda Asellidae 1 0 1 0 0 0 0 0 0 0 0 0 16 0 16 36 0 36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 53 0 53 Lepidoptera Pyralidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 3 0 3


373




Order Family E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total E O total Neuroptera Sisuridae 0 0 0 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 Odonata Aeshnidae 0 0 0 4 0 4 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 6 0 6 Odonata Coenagrionidae 3 37 40 2 9 11 10 10 20 17 2 19 5 2 7 5 2 7 4 2 6 1 12 13 5 0 5 3 2 5 15 0 15 70 78 148 Odonata Cordulegastridae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 1 3 0 0 0 0 0 0 0 0 0 3 1 4 Odonata Corduliidae 0 1 1 0 0 0 0 1 1 3 0 3 0 0 0 0 0 0 1 0 1 2 6 8 1 0 1 0 0 0 4 0 4 11 8 19 Odonata Lestidae 0 2 2 0 1 1 0 0 0 1 0 1 1 0 1 1 2 3 0 0 0 0 0 0 1 0 1 2 0 2 0 0 0 6 5 11 Odonata Libellulidae 4 0 4 2 0 2 3 1 4 4 1 5 2 0 2 3 1 4 5 1 6 16 8 24 2 0 2 0 0 0 13 1 14 54 13 67 Odonata Protoneuridae 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 Odonata UNKNOWN 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3 0 3 Oligochaeta Oligochaeta 0 1 1 0 0 0 27 2 29 4 0 4 0 1 1 2 2 4 2 0 2 2 2 4 0 0 0 0 0 0 6 0 6 43 8 51 Ostracoda Ostracoda 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Pelecypoda Sphaeriidae 0 0 0 0 0 0 1 6 7 38 20 58 7 1 8 1 3 4 0 0 0 23 2 25 1 0 1 0 0 0 2 4 6 73 36 109 Pelecypoda Unionidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Plecoptera Chloroperlidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Plecoptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Trichoptera Phryganeidae 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 UNKNOWN UNKNOWN 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 TOTALS 153 531 602 83 48 131 428 140 568 236 91 327 108 23 131 119 36 155 127 38 165 162 275 437 190 6 196 71 22 93 190 100 290 1867 1310 3177


374

Appendix 36. Number of individuals collected by family and wetland from emergent (E), open water (O), and scrub-shrub (SS) areas,

as well as for the entire complex (total) for 4 reference wetlands in West Virginia, 2001-2002.

Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS totalAmphipoda Gammaridae 3 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 Amphipoda Talitridae 3 35 38 0 0 0 0 0 0 0 6 0 0 6 9 35 0 44 Amphipoda UNKNOWN 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Arachnid Hydracarina 0 0 0 3 0 0 3 0 0 0 0 1 0 1 3 1 0 4 Arachnid Arachnid 0 0 0 1 0 0 1 0 0 0 2 0 0 2 3 0 0 3 Cladocera N/A 0 0 0 4 0 0 4 1 0 1 1 1 0 2 6 1 0 7 Coleoptera Dytiscidae 3 0 3 1 1 1 3 2 0 2 8 1 0 9 14 2 1 17 Coleoptera Elmidae 1 0 1 1 0 0 1 0 0 0 1 0 0 1 3 0 0 3 Coleoptera Haliplidae 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 Coleoptera Helodidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Coleoptera Hydrophilidae 1 0 1 1 0 0 1 0 0 0 0 1 0 1 2 1 0 3 Coleoptera Staphylinidae 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 Collembola Isotomidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Collembola Poduridae 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 Copepoda Cyclopoida 2 0 2 1 0 4 5 0 0 0 4 0 0 4 7 0 4 11 Diptera Ceratopogonidae 1 0 1 3 0 0 3 1 0 1 0 0 0 0 5 0 0 5 Diptera Chironomidae 0 0 0 13 4 5 22 1 0 1 41 10 6 57 55 14 11 80 Diptera Culicidae 2 0 2 14 2 2 18 1 0 1 2 0 1 3 19 2 3 24 Diptera Dixidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Diptera Ephydridae 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1

375

Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS totalDiptera Ptychopteridae 0 0 0 0 0 0 0 6 0 6 0 0 0 0 6 0 0 6 Diptera Tabanidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Diptera UNKNOWN 0 0 0 1 0 1 2 1 0 1 0 0 0 0 2 0 1 3 Ephemeroptera Baetidae 1 1 2 0 0 6 6 4 0 4 9 2 1 12 14 3 7 24 Ephemeroptera Caenidae 0 0 0 0 0 0 0 0 0 0 7 37 1 45 7 37 1 45 Ephemeroptera Siphlonuridae 0 0 0 0 0 0 0 9 0 9 0 1 0 1 9 1 0 10 Ephemeroptera UNKNOWN 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 Gastropoda Lymnaedae 4 2 6 0 0 0 0 0 0 0 0 0 0 0 4 2 0 6 Gastropoda Physidae 10 2 12 0 0 0 0 0 0 0 0 0 0 0 10 2 0 12 Gastropoda Planorbidae 5 0 5 0 0 1 1 0 0 0 16 4 1 21 21 4 2 27 Gastropoda Pomatiopsidae 3 0 3 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 Gastropoda Viviparidae 17 4 21 0 0 0 0 0 0 0 11 4 0 15 28 8 0 36 Hemiptera Corixidae 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 Hemiptera Delphacidae 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 Hemiptera Gerridae 0 1 1 0 0 0 0 0 0 0 3 1 0 4 3 2 0 5 Hemiptera Hebridae 0 0 0 0 0 0 0 1 0 1 2 0 0 2 3 0 0 3 Hemiptera Hydrometridae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Hemiptera Mesoveliidae 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Hemiptera Notonectidae 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 Hemiptera Veliidae 0 0 0 0 0 1 1 1 0 1 8 29 0 37 9 29 1 39 Isopoda Asellidae 25 1 26 0 0 0 0 15 0 15 74 0 0 74 114 1 0 115Neuroptera Sisuridae 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 Odanata Coenagrionidae 3 0 3 1 0 0 1 0 0 0 11 8 0 19 15 8 0 23 Odanata Cordulegastridae 0 0 0 0 0 0 0 0 0 0 2 0 0 2 2 0 0 2


376

Altona Marsh Elder Swamp Meadowville Muddlety TOTAL Order Family E O total E O SS total E O total E O SS total E O SS totalOdanata Corduliidae 0 0 0 0 1 0 1 0 0 0 0 12 0 12 0 13 0 13 Odanata Libellulidae 0 0 0 1 0 0 1 0 0 0 3 2 0 5 4 2 0 6 Odanata Protoneuridae 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 Oligochaeta Oligochaeta 0 0 0 3 0 0 3 3 0 3 0 0 0 0 6 0 0 6 Ostracoda Podocopa 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 Pelecypoda Sphaeriidae 39 2 41 1 0 0 1 2 0 2 16 0 1 17 58 2 1 61 Plecoptera Nemouridae 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 Plecoptera Perlodidae 0 0 0 0 0 0 0 2 0 2 0 0 0 0 2 0 0 2 Trichoptera Hydrophilidae 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 UNKNOWN UNKNOWN 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1

TOTALS 126 52 178 52 8 23 83 53 0 53 232 116 11 359 463 176 34 673


377

Appendix 37. Species list of all birds sampled inside and outside 50 m radius plots

(number of birds per point count) in 11 mitigation and 4 natural wetlands in West


Mitigation Natural Common Name Scientific Name x SE x SE Great Blue Heron Ardea herodias 1.7 0.7 0.3 0.0 Green Heron Butorides virescens 2.1 0.3 1.0 0.0 Turkey Vulture Cathartes aura 2.0 4.3 3.0 1.1 Canada Goose Branta canadensis 20.3 14.8 10.8 10.3 Muscovy Duck Cairina moschata 0.3 0.0 0 0 Green-winged Teal Anas crecca 0.1 0.0 0 0 Black Duck Anas rubripes 0.1 0.0 0 0 Wood Duck Aix sponsa 9.0 4.9 0 0 Mallard Anas platyrhynchos 7.7 3.2 1 0.3 Red-shouldered Hawk Buteo lineatus 0.0 0.0 0.25 0 Red-tailed Hawk Buteo jamaicensis 0.1 0.0 0 0 Ruffed Grouse Bonasa umbellus 0.1 0.0 0 0 Wild Turkey Meleagris gallopavo 0.3 0.2 0.5 0 Northern Bobwhite Colinus virginianus 0.0 0.0 0.25 0 Virginia Rail Rallus limicola 0.1 0.0 0 0 Sora Porzana carolina 0.5 0.0 0 0 Killdeer Charadrius vociferus 1.5 0.8 0.75 0.4 Spotted Sandpiper Actitis macularia 0.5 0.3 0.25 0 American Woodcock Scolopax minor 0.0 0.0 0.5 0 Mourning Dove Zenaida macroura 2.4 1.7 4.5 0 Yellow-billed Cuckoo Coccyzus americanus 1.8 0.5 0.75 0 Chimney Swift Chaetura pelagica 0.5 0.2 2.25 1 Ruby-throated Hummingbird Archilochus colubris 0.3 0.0 0 0 Belted Kingfisher Ceryle alcyon 1.4 0.3 0.25 0 Red-bellied Woodpecker Melanerpes carolinus 1.3 0.5 3 3.5 Red-headed Woodpecker Melanerpes erythrocephalus 0.0 0.0 0.25 0 Downy Woodpecker Picoides pubescens 1.5 0.6 0 0 Northern Flicker Colaptes auratus 2.1 0.7 1.25 0.4 Pileated Woodpecker Dryocopus pileatus 1.9 0.7 1 0.3 Eastern Wood-Pewee Contopus virens 1.5 0.7 1 0.3 Acadian Flycatcher Empidonax virescens 1.6 1.4 1.5 1.4 Alder Flycatcher Empidonax alnorum 0.8 0.3 3.75 1.7

378

Mitigation Natural Common Name Scientific Name x SE x SE Willow Flycatcher Empidonax traillii 4.3 1.8 10.5 2.9 Least Flycatcher Empidonax minimus 0.3 0.0 0 0 Eastern Phoebe Sayornis phoebe 0.4 0.0 0 0 Great Crested Flycatcher Myiarchus crinitus 1.2 1.5 0.5 0 Olive-sided Flycatcher Contopus borealis 0.0 0.0 0.25 0 Eastern Kingbird Tyrannus tyrannus 1.5 0.6 1.75 0.4 White-eyed Vireo Vireo griseus 0.5 0.3 2 0.0 Yellow-throated Vireo Vireo flavifrons 0.6 0.1 0.5 0.0 Warbling Vireo Vireo gilvus 0.3 0.0 0.25 0.0 Red-eyed Vireo Vireo olivaceus 7.3 2.7 4 1.6 Blue Jay Cyanocitta cristata 2.5 0.9 3 1.2 American Crow Corvus brachyrhynchos 7.1 1.0 8 1.8 Common Raven Corvus corax 0.0 0.0 1.25 0.0 Tree Swallow Tachycineta bicolor 11.4 2.3 4.5 2.3 Northern Rough-winged Swallow Stelgidopteryx serripennis 1.5 0.7 0 0 Barn Swallow Hirundo rustica 5.7 3.7 3.5 1.3 Black-capped Chickadee Poecile atricapillus 0.8 0.6 0.25 0 Carolina Chhickadee Parus carolinensis 0.3 0.0 0 0 Tufted Titmouse Baeolophus bicolor 3.4 1.0 2 1.0 Brown Creeper Certhia americana 0.1 0.0 0.25 0.0 Red-breasted Nuthatch Sitta canadensis 0.1 0.0 0 0 White-breasted Nuthatch Sitta carolinensis 0.8 0.4 0.25 0 Carolina Wren Thryothorus ludovicianus 0.9 0.4 0.75 0.4 House Wren Troglodytes aedon 0.3 0.2 1.5 0.0 Blue-gray Gnatcatcher Polioptila caerulea 1.7 0.9 2.25 1.8 Eastern Bluebird Sialia sialis 0.4 0.0 0 0 Veery Catharus fuscescens 0.1 0.0 0 0 Hermit Thrush Catharus guttatus 0.0 0.0 0.25 0 Swainson's Thrush Catharus ustulatus 0.0 0.0 0.5 0 Wood Thrush Hylocichla mustelina 3.5 1.6 1.25 1.1 American Robin Turdus migratorius 5.8 1.7 3.25 1.9 Gray Catbird Dumetella carolinensis 4.3 1.1 8.5 2.5 Northern Mockingbird Mimus polyglottos 1.2 0.6 2.5 1.4 Brown Thrasher Toxostoma rufum 0.7 0.2 0.75 0.4 European Starling Sturnus vulgaris 18.3 9.9 25.75 35.0Cedar Waxwing Bombycilla cedrorum 11.0 3.1 2 1.0 Blue-winged Warbler Vermivora pinus 1.0 0.7 1.5 0.0


379

Mitigation Natural Common Name Scientific Name x SE x SE Golden-winged Warbler Vermivora chrysoptera 0.1 0.0 0.75 0.0 Northern Parula Parula americana 0.2 0.0 0 0 Yellow Warbler Dendroica petechia 4.2 1.0 9.25 3.1 Magnolia Warbler Dendroica magnolia 1.2 1.2 0.25 0.0 Black-throated Green Warbler Dendroica virens 0.1 0.0 0.25 0.0 Yellow-throated Warbler Dendroica dominica 1.1 1.3 0 0.0 Black-and-white Warbler Mniotilta varia 0.3 0.2 0.75 0.0 Prairie Warbler Dendroica discolor 0.2 0.0 0 0 Cerulean Warbler Dendroica cerulea 0.5 0.0 0 0 Prothonotary Warbler Protonotaria citrea 0.1 0.0 0 0 American Redstart Setophaga ruticilla 0.5 0.6 0 0 Worm-eating Warbler Helmitheros vermivorus 1.6 1.3 0.25 0 Ovenbird Seiurus aurocapillus 0.7 0.6 1.25 0.4 Kentucky Warbler Oporornis formosus 0.1 0.0 0 0.0 Common Yellowthroat Geothlypis trichas 10.0 2.3 13.5 2.9 Scarlet Tanager Piranga olivacea 2.3 1.2 1 0.7 Eastern Towhee Pipilo erythrophthalmus 4.7 1.4 3.75 1.3 Chipping Sparrow Spizella passerina 2.2 2.1 1 0.0 Field Sparrow Spizella pusilla 3.4 1.0 1.75 1.8 Grasshopper Sparrow Ammodramus bairdii 0.1 0.0 0 0 Song Sparrow Melospiza melodia 17.3 4.2 24.75 3.7 Savannah Sparrow Passerculus sandwichensis 0.5 0.3 1.25 0.0 Swamp Sparrow Melospiza georgiana 1.7 2.3 7.5 9.9 Vesper Sparrow Pooecetes gramineus 0.1 0.0 0 0 Dark-eyed Junco Junco hyemalis 0.5 0.3 0 0 Northern Cardinal Cardinalis cardinalis 5.1 1.8 6 4.8 Rose-breasted Grosbeak Pheucticus ludovicianus 0.1 0.0 0.25 0 Indigo Bunting Passerina cyanea 7.7 2.7 5.75 3.5 Red-winged Blackbird Agelaius phoeniceus 52.4 12.1 73 27.9Boat-tailed Grackle Quiscalus major 0.0 0.0 0.25 0.0 Common Grackle Quiscalus quiscula 2.3 0.9 0 0 Brown-headed Cowbird Molothrus ater 0.2 0.0 0 0 Baltimore Oriole Icterus galbula 0.9 0.2 0.75 0 Orchard Oriole Icterus spurius 0.1 0.0 0 0 American Goldfinch Carduelis tristis 7.0 1.3 6 3.7 House Sparrow Passer domesticus 0.3 0.0 0 0


380

Appendix 38. Number of birds sampled inside 50 m radius plots (I), outside plots (O) and totals for 11 mitigation wetlands in West


Walnut Bottom Vepco


Leading Creek



Enoch Branch Bear Run TOTAL

Common Name Scientific Name I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total Great Blue Heron Ardea herodias 5 0 5 0 0 0 0 1 1 0 1 1 6 1 7 0 0 0 0 1 1 0 0 0 3 0 3 0 1 1 0 0 0 14 5 19 Green Heron Butorides virescens 0 2 2 0 0 0 1 1 2 2 0 2 2 1 3 0 0 0 0 0 0 1 3 4 0 3 3 4 1 5 2 0 2 10 11 21 Turkey Vulture Cathartes aura 0 21 21 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 22 22 Canada Goose Branta canadensis 89 0 89 0 0 0 57 61 118 10 0 10 2 0 2 7 0 7 3 0 3 0 0 0 0 0 0 0 0 0 0 1 1 0 62 230 Muscovy Duck Cairina moschata 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 Green-winged Teal Anas crecca 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 Black Duck Anas rubripes 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Wood Duck Aix sponsa 38 1 39 0 0 0 1 0 1 0 0 0 37 0 37 1 0 1 0 0 0 6 0 6 10 0 10 3 1 4 8 1 1 95 3 98 Mallard Anas platyrhynchos 20 8 28 4 1 5 10 7 17 0 0 0 24 0 24 0 2 2 0 0 0 3 1 4 3 1 4 0 0 0 1 0 1 65 20 85 Red-tailed Hawk Buteo jamaicensis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Ruffed Grouse Bonasa umbellus 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 Wild Turkey Meleagris gallopavo 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 Virginia Rail Rallus limicola 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Sora Porzana carolina 0 0 0 0 0 0 4 2 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 2 6 Killdeer Charadrius vociferus 1 0 1 1 0 1 2 2 4 0 0 0 2 1 3 0 0 0 0 0 0 0 0 0 3 4 7 0 0 0 0 0 0 9 7 16 Spotted Sandpiper Actitis macularia 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 1 0 1 7 0 7 Mourning Dove Zenaida macroura 1 1 2 0 0 0 0 1 1 0 0 0 0 6 6 0 0 0 0 0 0 1 0 1 7 8 15 0 0 0 0 1 1 9 17 26 Yellow-billed Cuckoo Coccyzus americanus 0 4 4 0 0 0 0 0 0 0 2 2 0 0 0 0 3 3 0 0 0 0 0 0 1 1 2 0 3 3 0 6 6 1 19 20 Chimney Swift Chaetura pelagica 0 0 0 0 0 0 2 0 2 0 0 0 1 0 1 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 3 2 5 Ruby-throated Hummingbird Archilochus colubris 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 3 0 3 Belted Kingfisher Ceryle alcyon 4 0 4 0 2 2 0 0 0 1 0 1 0 0 0 0 1 1 0 0 0 1 0 1 2 0 2 2 0 2 2 0 2 12 3 15 Red-bellied Woodpecker Melanerpes carolinus 1 0 1 0 1 1 0 0 0 0 0 0 0 2 2 0 1 1 0 1 1 0 0 0 0 0 0 1 2 3 0 5 5 2 12 14 Downy Woodpecker Picoides pubescens 0 0 0 0 0 0 0 0 0 4 0 4 0 1 1 2 4 6 0 0 0 0 0 0 0 0 0 2 0 2 2 1 3 10 6 16 Northern Flicker Colaptes auratus 0 1 1 1 2 2 0 0 0 2 1 3 0 0 0 3 5 8 2 0 2 3 0 3 1 0 1 0 2 2 1 0 1 13 10 23 Pileated Woodpecker Dryocopus pileatus 0 1 1 0 0 0 0 0 0 0 3 3 0 1 1 1 4 5 0 0 0 0 0 0 0 0 0 1 4 5 1 5 6 3 18 21 Eastern Wood-Pewee Contopus virens 0 0 0 0 0 0 0 0 0 0 2 2 0 1 1 0 4 4 0 0 0 0 0 0 0 0 0 0 2 2 2 5 7 2 14 16 Acadian Flycatcher Empidonax virescens 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 0 2 2 2 4 0 0 0 0 0 0 0 0 0 5 6 11 10 8 18

381

Walnut Bottom Vepco


Leading Creek




Common Name Scientific Name I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total Alder Flycatcher Empidonax alnorum 0 0 0 1 1 2 0 3 3 4 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 4 9 Willow Flycatcher Empidonax traillii 0 0 0 0 1 1 7 1 8 0 1 1 11 5 16 5 3 8 0 0 0 0 0 0 11 2 13 0 0 0 0 0 0 34 13 47 Least Flycatcher Empidonax minimus 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 Eastern Phoebe Sayornis phoebe 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 2 0 2 4 0 4 Great Crested Flycatcher Myiarchus crinitus 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 1 0 1 7 3 10 10 3 13 Eastern Kingbird Tyrannus tyrannus 1 1 2 0 0 0 0 0 0 6 0 6 0 1 1 0 1 1 1 1 2 1 0 1 4 0 4 0 0 0 0 0 0 13 4 17 White-eyed Vireo Vireo griseus 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 0 0 0 0 0 2 1 3 1 0 1 4 2 6 Yellow-throated Vireo Vireo flavifrons 0 0 0 0 1 1 0 0 0 0 1 1 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 1 1 2 0 2 4 3 7 Warbling Vireo Vireo gilvus 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 3 0 3 Red-eyed Vireo Vireo olivaceus 1 0 1 3 6 9 1 0 1 0 1 1 13 1 14 7 5 12 4 1 5 1 2 3 1 1 2 2 0 2 21 9 30 54 26 80 Blue Jay Cyanocitta cristata 0 0 0 0 1 1 0 0 0 0 0 0 0 2 2 1 5 6 0 1 1 1 1 2 0 1 1 1 5 6 2 6 8 5 22 27 American Crow Corvus brachyrhynchos 0 9 9 0 5 5 1 6 7 0 3 3 0 12 12 0 8 8 0 4 4 0 5 5 0 5 5 0 7 7 1 12 13 2 76 78 Tree Swallow Tachycineta bicolor 15 2 17 5 1 6 17 4 21 23 0 23 4 4 8 13 0 13 21 0 21 2 0 2 9 2 11 0 0 0 3 0 3 112 13 125 Northern Rough-winged Swallow Stelgidopteryx serripennis 6 1 7 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 1 0 1 2 0 2 2 0 2 0 0 0 2 0 2 15 1 16 Barn Swallow Hirundo rustica 35 0 35 0 0 0 7 0 7 0 0 0 9 0 9 0 0 0 2 0 2 0 0 0 4 0 4 6 0 6 0 0 0 63 0 63 Black-capped Chickadee Poecile atricapillus 0 0 0 0 0 0 0 0 0 0 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 2 3 5 0 2 2 3 6 9 Carolina Chhickadee Parus carolinensis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 3 2 1 3 Tufted Titmouse Baeolophus bicolor 0 1 1 0 0 0 0 1 1 0 1 1 1 5 6 1 5 6 0 1 1 0 2 2 0 1 1 2 6 8 7 3 10 11 26 37 Brown Creeper Certhia americana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Red-breasted Nuthatch Sitta canadensis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 White-breasted Nuthatch Sitta carolinensis 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 4 4 0 0 0 0 0 0 1 0 1 0 0 0 2 0 2 4 5 9 Carolina Wren Thryothorus ludovicianus 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 1 1 2 1 0 1 3 1 4 8 2 10 House Wren Troglodytes aedon 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 3 0 3 Blue-gray Gnatcatcher Polioptila caerulea 0 0 0 0 0 0 0 0 0 0 0 0 4 1 5 0 1 1 1 0 1 1 0 1 0 0 0 2 1 3 7 1 8 15 4 19 Eastern Bluebird Sialia sialis 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 4 0 4 Veery Catharus fuscescens 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Wood Thrush Hylocichla mustelina 0 0 0 0 2 2 0 0 0 0 1 1 0 0 0 1 7 8 1 0 1 0 2 2 2 0 2 1 5 6 5 11 16 10 28 38 American Robin Turdus migratorius 0 0 0 3 2 5 0 1 1 8 7 15 8 8 16 1 0 1 0 1 1 8 1 9 7 3 10 1 2 3 0 3 3 36 28 64 Gray Catbird Dumetella carolinensis 0 0 0 0 0 0 1 0 1 3 1 4 11 2 13 0 4 4 0 0 0 4 0 4 7 0 7 5 2 7 4 3 7 35 12 47 Northern Mockingbird Mimus polyglottos 1 2 3 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 2 5 1 6 0 0 0 1 0 1 9 4 13 Brown Thrasher Toxostoma rufum 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 1 1 3 0 3 0 1 1 5 3 8 European Starling Sturnus vulgaris 2 1 3 1 2 3 5 0 5 1 1 2 0 21 21 0 3 3 3 0 3 28 37 65 43 52 95 0 1 1 0 0 0 83 118 201 Cedar Waxwing Bombycilla cedrorum 0 0 0 2 0 2 6 0 6 5 0 5 20 10 30 4 3 7 3 19 22 5 16 21 3 0 3 0 4 4 3 18 21 51 70 121 Blue-winged Warbler Vermivora pinus 0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 3 3 6 0 0 0 0 0 0 0 0 0 1 0 1 2 0 2 6 5 11


382

Walnut Bottom Vepco


Leading Creek




Common Name Scientific Name I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total I O total Golden-winged Warbler Vermivora chrysoptera 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Northern Parula Parula americana 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 0 0 1 1 2 Yellow Warbler Dendroica petechia 3 2 5 0 0 0 2 1 3 7 0 7 10 0 10 6 2 8 3 1 4 0 1 1 5 1 6 1 0 1 1 0 1 38 8 46 Magnolia Warbler Dendroica magnolia 0 0 0 2 7 9 0 0 0 1 1 2 0 0 0 0 0 0 1 0 1 0 1 1 0 0 0 0 0 0 0 0 0 4 9 13 Black-throated Green Warbler Dendroica virens 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Yellow-throated Warbler Dendroica dominica 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 0 0 7 2 9 8 4 12 Prairie Warbler Dendroica discolor 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 1 2 Cerulean Warbler Dendroica cerulea 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 6 3 3 6 Prothonotary Warbler Protonotaria citrea 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Black-and-white Warbler Mniotilta varia 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 1 0 1 3 0 3 American Redstart Setophaga ruticilla 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 3 1 4 4 1 5 Worm-eating Warbler Helmitheros vermivorus 0 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 6 4 6 10 4 14 18 Ovenbird Seiurus aurocapillus 0 0 0 1 4 5 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 1 7 8 Kentucky Warbler Oporornis formosus 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Common Yellowthroat Geothlypis trichas 0 1 1 4 5 9 3 2 5 6 2 8 20 8 28 15 2 17 0 0 0 9 0 9 8 0 8 4 6 10 12 3 15 81 29 110 Scarlet Tanager Piranga olivacea 0 0 0 0 1 1 0 0 0 0 0 0 1 2 3 2 2 4 1 0 1 0 0 0 0 0 0 1 3 4 5 7 12 10 15 25 Eastern Towhee Pipilo erythrophthalmus 0 1 1 0 3 3 0 0 0 0 1 1 4 2 6 4 2 6 0 2 2 1 2 3 2 2 4 9 2 11 9 6 15 29 23 52 Chipping Sparrow Spizella passerina 0 0 0 1 0 1 1 0 1 2 1 3 0 0 0 0 0 0 0 0 0 1 1 2 0 0 0 0 0 0 5 12 17 10 14 24 Field Sparrow Spizella pusilla 1 4 5 0 5 5 2 7 9 0 0 0 0 5 5 1 9 10 0 0 0 0 1 1 0 0 0 1 1 2 0 0 0 5 32 37 Grasshopper Sparrow Ammodramus bairdii 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Song Sparrow Melospiza melodia 8 3 11 12 3 15 11 1 12 2 3 5 34 16 50 22 8 30 2 1 3 9 0 9 14 0 14 10 1 11 24 6 30 148 42 190 Savannah Sparrow Passerculus sandwichensis 0 0 0 3 0 3 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 5 Swamp Sparrow Melospiza georgiana 0 0 0 4 0 4 10 5 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 14 5 19 Vesper Sparrow Pooecetes gramineus 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 Dark-eyed Junco Junco hyemalis 1 0 1 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 6 0 6 Northern Cardinal Cardinalis cardinalis 0 1 1 0 0 0 0 0 0 0 0 0 6 6 12 3 5 8 1 1 2 3 3 6 4 1 5 0 3 3 7 12 19 24 32 56 Rose-breasted Grosbeak Pheucticus ludovicianus 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Indigo Bunting Passerina cyanea 1 1 2 0 1 1 0 0 0 3 1 4 7 2 9 15 1 16 1 1 2 2 2 4 2 0 2 11 8 19 19 7 26 61 24 85 Red-winged Blackbird Agelaius phoeniceus 54 14 68 7 1 8 64 74 138 14 1 15 63 20 83 22 4 26 26 8 34 76 13 89 60 4 64 10 2 12 38 1 39 434 142 576 Common Grackle Quiscalus quiscula 10 0 10 0 0 0 0 0 0 2 2 4 0 5 5 0 0 0 0 0 0 0 0 0 3 0 3 1 2 3 0 0 0 16 9 25 Brown-headed Cowbird Molothrus ater 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 2 0 2 Baltimore Oriole Icterus galbula 0 0 0 0 0 0 0 0 0 1 0 1 3 0 3 1 0 1 2 0 2 2 0 2 0 0 0 0 0 0 1 0 1 10 0 10 Orchard Oriole Icterus spurius 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 American Goldfinch Carduelis tristis 12 0 12 1 2 3 0 4 4 2 0 2 12 3 15 6 2 8 1 0 1 5 2 7 3 4 7 7 0 7 11 0 11 60 17 77 House Sparrow Passer domesticus 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 3


383

Appendix 39. Number of birds sampled inside 50 m radius plots (I), outside plots (O) and totals for 4 natural wetlands in West


Altona Marsh

Elder Swamp Meadowville Muddlety TOTAL

Common Name Scientific Name I O total I O total I O total I O total I O totalGreat Blue Heron Ardea herodias 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Green Heron Butorides virescens 0 0 0 0 0 0 0 2 2 2 0 2 2 2 4 Turkey Vulture Cathartes aura 0 2 2 0 6 6 0 1 1 0 3 3 0 12 12Canada Goose Branta canadensis 5 31 36 0 0 0 0 7 7 0 0 0 5 38 43Wood Duck Aix sponsa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mallard Anas platyrhynchos 0 1 1 1 1 2 0 0 0 0 1 1 1 3 4 Red-shouldered Hawk Buteo lineatus 0 0 0 0 0 0 0 0 0 1 0 1 1 0 1 Wild Turkey Meleagris gallopavo 0 0 0 0 0 0 0 2 2 0 0 0 0 2 2 Northern Bobwhite Colinus virginianus 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 Killdeer Charadrius vociferus 0 1 1 0 2 2 0 0 0 0 0 0 0 3 3 Spotted Sandpiper Actitis macularia 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 American Woodcock Scolopax minor 0 0 0 0 0 0 2 0 2 0 0 0 2 0 2 Mourning Dove Zenaida macroura 3 15 18 0 0 0 0 0 0 0 0 0 3 15 18Yellow-billed Cuckoo Coccyzus americanus 0 1 1 0 0 0 0 1 1 0 1 1 0 3 3 Chimney Swift Chaetura pelagica 0 6 6 0 0 0 3 0 3 0 0 0 3 6 9 Belted Kingfisher Ceryle alcyon 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 Red-bellied Woodpecker Melanerpes carolinus 6 5 11 0 0 0 0 1 1 0 0 0 6 6 12Red-headed Woodpecker Melanerpes erythrocephalus 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1

384

Altona Marsh


Common Name Scientific Name I O total I O total I O total I O total I O totalDowny Woodpecker Picoides pubescens 1 0 1 0 0 0 0 0 0 1 0 1 2 0 2 Northern Flicker Colaptes auratus 1 2 3 0 0 0 0 2 2 0 0 0 1 4 5 Pileated Woodpecker Dryocopus pileatus 1 0 1 0 2 2 0 1 1 0 0 0 1 3 4 Eastern Wood-Pewee Contopus virens 0 2 2 0 0 0 0 1 1 0 1 1 0 4 4 Acadian Flycatcher Empidonax virescens 1 0 1 0 0 0 3 2 5 0 0 0 4 2 6 Alder Flycatcher Empidonax alnorum 0 1 1 1 6 7 0 0 0 6 1 7 7 8 15Willow Flycatcher Empidonax traillii 15 2 17 1 2 3 10 1 11 10 1 11 36 6 42Great Crested Flycatcher Myiarchus crinitus 1 0 1 0 0 0 1 0 1 0 0 0 2 0 2 Olive-sided Flycatcher Contopus borealis 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Eastern Kingbird Tyrannus tyrannus 3 0 3 0 0 0 0 0 0 1 3 4 4 3 7 White-eyed Vireo Vireo griseus 0 0 0 0 0 0 3 1 4 3 1 4 6 2 8 Yellow-throated Vireo Vireo flavifrons 0 0 0 0 0 0 2 0 2 0 0 0 2 0 2 Warbling Vireo Vireo gilvus 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Red-eyed Vireo Vireo olivaceus 1 1 2 3 2 5 5 3 8 0 1 1 9 7 16Blue Jay Cyanocitta cristata 0 5 5 0 1 1 1 0 1 3 2 5 4 8 12American Crow Corvus brachyrhynchos 0 6 6 0 4 4 2 8 10 3 9 12 5 27 32Common Raven Corvus corax 0 0 0 0 5 5 0 0 0 0 0 0 0 5 5 Tree Swallow Tachycineta bicolor 10 1 11 2 0 2 1 0 1 4 0 4 17 1 18Barn Swallow Hirundo rustica 0 2 2 0 0 0 0 7 7 3 2 5 3 11 14Black-capped Chickadee Poecile atricapillus 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 Tufted Titmouse Baeolophus bicolor 2 0 2 0 0 0 0 1 1 1 4 5 3 5 8


385

Altona Marsh


Common Name Scientific Name I O total I O total I O total I O total I O totalBrown Creeper Certhia americana 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 White-breasted Nuthatch Sitta carolinensis 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 Carolina Wren Thryothorus ludovicianus 1 1 2 0 0 0 0 0 0 0 1 1 1 2 3 House Wren Troglodytes aedon 4 2 6 0 0 0 0 0 0 0 0 0 4 2 6 Blue-gray Gnatcatcher Polioptila caerulea 0 0 0 0 0 0 7 0 7 1 1 2 8 1 9 Hermit Thrush Catharus guttatus 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Swainson's Thrush Catharus ustulatus 0 0 0 0 2 2 0 0 0 0 0 0 0 2 2 Wood Thrush Hylocichla mustelina 0 0 0 0 0 0 1 3 4 0 1 1 1 4 5 American Robin Turdus migratorius 8 1 9 0 2 2 1 0 1 0 1 1 9 4 13Gray Catbird Dumetella carolinensis 10 2 12 0 1 1 9 2 11 9 1 10 28 6 34Northern Mockingbird Mimus polyglottos 2 5 7 0 0 0 2 1 3 0 0 0 4 6 10Brown Thrasher Toxostoma rufum 0 0 0 0 0 0 1 0 1 1 1 2 2 1 3 European Starling Sturnus vulgaris 0 2 2 0 0 0 0 0 0 101 0 101 101 2 103Cedar Waxwing Bombycilla cedrorum 0 5 5 1 0 1 1 0 1 0 1 1 2 6 8 Blue-winged Warbler Vermivora pinus 0 0 0 0 0 0 3 0 3 2 1 3 5 1 6 Golden-winged Warbler Vermivora chrysoptera 0 0 0 0 0 0 3 0 3 0 0 0 3 0 3 Yellow Warbler Dendroica petechia 9 1 10 1 1 2 8 0 8 15 2 17 33 4 37Magnolia Warbler Dendroica magnolia 0 0 0 0 0 0 1 0 1 0 0 0 1 0 1 Black-throated Green Warbler Dendroica virens 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 Yellow-throated Warbler Dendroica dominica 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Black-and-white Warbler Mniotilta varia 0 0 0 0 0 0 0 0 0 1 2 3 1 2 3


386

Altona Marsh


Common Name Scientific Name I O total I O total I O total I O total I O totalWorm-eating Warbler Helmitheros vermivorus 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 Ovenbird Seiurus aurocapillus 0 0 0 0 0 0 1 2 3 0 2 2 1 4 5 Common Yellowthroat Geothlypis trichas 18 3 21 4 9 13 13 0 13 4 3 7 39 15 54Scarlet Tanager Piranga olivacea 0 0 0 0 0 0 1 0 1 3 0 3 4 0 4 Eastern Towhee Pipilo erythrophthalmus 1 0 1 0 2 2 3 3 6 1 5 6 5 10 15Chipping Sparrow Spizella passerina 0 0 0 3 1 4 0 0 0 0 0 0 3 1 4 Field Sparrow Spizella pusilla 0 0 0 1 5 6 0 0 0 0 1 1 1 6 7 Song Sparrow Melospiza melodia 27 3 30 12 3 15 19 4 23 27 4 31 85 14 99Savannah Sparrow Passerculus sandwichensis 0 0 0 5 0 5 0 0 0 0 0 0 5 0 5 Swamp Sparrow Melospiza georgiana 1 0 1 19 10 29 0 0 0 0 0 0 20 10 30Northern Cardinal Cardinalis cardinalis 10 9 19 0 0 0 3 1 4 0 1 1 13 11 24Rose-breasted Grosbeak Pheucticus ludovicianus 1 0 1 0 0 0 0 0 0 0 0 0 1 0 1 Indigo Bunting Passerina cyanea 1 0 1 0 0 0 15 0 15 6 1 7 22 1 23Red-winged Blackbird Agelaius phoeniceus 101 44 145 23 8 31 21 6 27 74 15 89 219 73 292Boat-tailed Grackle Quiscalus major 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 Common Grackle Quiscalus quiscula 0 2 2 0 0 0 0 2 2 1 18 19 1 22 23Baltimore Oriole Icterus galbula 1 0 1 0 0 0 1 0 1 0 1 1 2 1 3 American Goldfinch Carduelis tristis 9 8 17 0 1 1 2 1 3 2 1 3 13 11 24


387

Appendix 40. Species lista of all frogs sampled by survey period in 11 mitigation wetlands in West Virginia (WB = Walnut Bottom,

VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus

Joist MacMillan, EB = Enoch Branch, and BR = Bear Run), 2001-2002.

a * represents the observation of a particular species

Year 1 WB VO BC ER LC SC SR T TJM EB BR Common Name Scientific Name 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3Spring Peeper Psuedacris c. crucifer * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *Gray Treefrog Hyla chrysoscelis * * * * * * * *American Bullfrog Rana catesbeiana * * * * * * * * * * *Wood Frog Rana sylvatica * * * *Green Frog Rana clamitans melanota * * * * * * * * * * * * * * * * * * * * *American Toad Bufo a. americanus * * * * * * * * *Pickerel Frog Rana palustris * * * * * * * * * * * * * * * * Year 2 WB VO BC ER LC SC SR T TJM EB BR Common Name Scientific Name 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3Spring Peeper Psuedacris c. crucifer * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *Gray Treefrog Hyla chrysoscelis * * * * * * * * *American Bullfrog Rana catesbeiana * * * * *Wood Frog Rana sylvatica * * * * * * * *Green Frog Rana clamitans melanota * * * * * * * * * * * * * * *American Toad Bufo a. americanus * * * * * * * * *Pickerel Frog Rana palustris * * * * * * * * * * * *

388

Appendix 41. Species lista of all frogs sampled by survey period in 4 natural

wetlands in West Virginia (AM = Altona Marsh, ES = Elder Swamp, MV =

Meadowville, and MY = Muddlety), 2001-2002.

a * represents the observation of a particular species

Year 1 AM ES MV MY Common Name Scientific Name 1 2 3 1 2 3 1 2 3 1 2 3Spring Peeper Psuedacris c. crucifer * * * * * * * * * * * *Gray Treefrog Hyla chrysoscelis * *Bull Frog Rana catesbeiana * *Wood Frog Rana sylvatica * Green Frog Rana clamitans melanota * * * * * * *American Toad Bufo a. americanus * Pickerel Frog Rana palustris * * Year 2 AM ES MV MY Common Name Scientific Name 1 2 3 1 2 3 1 2 3 1 2 3Spring Peeper Psuedacris c. crucifer * * * * * * * * * * *Gray Treefrog Hyla chrysoscelis * * * *Bull Frog Rana catesbeiana *Wood Frog Rana sylvatica * * Green Frog Rana clamitans melanota * * * * *American Toad Bufo a. americanus * * Pickerel Frog Rana palustris * * *

389

Appendix 42. A comparison of actual mean values of all variables measured within the beaver,

muskrat, mink, great blue heron, red-winged blackbird, wood duck, snapping turtle, and red-

spotted newt Habitat Suitability Index models between mitigation (n = 11) and natural (n = 4)


Mitigationa Naturala

HSI model variables x SE x SE F1,13 P Beaver V1: percent tree cover a. within wetland basin 0.07 0.1 2.3 1.1 4.97 0.044b. within 100 m 39.9 6.8 20.4 9.7 0.00 0.986c. within 200 m 45.1 8.0 43.2 7.3 0.02 0.904V2: percent trees 2.5-15.2 cm dbh a. within wetland basin 0.0 0.0 0.0 0.0 N/A N/A b. within 100 m 3.4 2.9 36.7 9.4 9.05 0.010c. within 200 m 11.5 4.7 21.7 7.9 0.88 0.367V3: percent shrub cover a. within wetland basin 7.5 2.0 27.8 6.3 9.06 0.010b. within 100 m 11.6 3.0 28.8 8.1 3.54 0.082c. within 200 m 12.6 2.8 22.7 6.2 1.80 0.203V4: shrub canopy height (m) a. within wetland basin 1.5 0.2 1.6 0.1 0.12 0.921b. within 100 m 2.1 0.1 1.4 0.1 8.49 0.012c. within 200 m 2.0 0.1 1.5 0.1 8.52 0.012V5: woody vegetation species compositionb a. within wetland basin A: 4; B: 7 N/A All Bs N/A N/A N/A b. within 100 m All Bs N/A All Bs N/A N/A N/A c. within 200 m All Bs N/A All Bs N/A N/A N/A V6: mean annual water fluctuationc All As N/A All As N/A N/A N/A Muskrat V1: percent emergent vegetation 48.0 6.2 59.4 10.2 0.90 0.361V2: percent year with water 100 0.0 100 0.0 N/A N/A V3: percent Scirpus validus, S. americanus 13.6 3.9 42.8 14.1 8.10 0.014Typha latifolia Mink V1: percent year with water 100 0.0 100 0.0 N/A N/A V2: percent persistent emergent vegetation 46.9 6.0 59 10.1 1.11 0.310

390

Mitigation Natural HSI model variables x SE x SE F1,13 P V3: percent tree/shrub cover <100 m 48.2 6.0 62.1 11.8 1.40 0.258Great blue heron V1: distance between forage area 36.8 21.8 37.5 23.9 0.00 0.986 and potential nest site V2: presence of shallow, clear water with fish yes: 9; no; 2 N/A yes: 3; no: 1 N/A N/A N/A V3: 100 m foraging disturbance free zone all yes N/A all yes N/A N/A N/A V4: presence of forest within 250 m all yes N/A all yes N/A N/A N/A V5: 150, 250 m nesting disturbance free zone yes: 8; no: 3 N/A yes: 2; no: 2 N/A N/A N/A V6: distance (km) between potential 50.8 4.2 82.4 28.5 3.26 0.094 and actual/previous nest site Red-winged blackbird V1: percent broad-leaf monocots 17.2 4.4 39.9 9.9 6.02 0.029V2: percent year with water 100 0.0 100 0.0 N/A N/A V3: presence of carp 10 of 11 N/A 0 of 4 N/A N/A N/A V4: presence of Odonates yes N/A yes N/A N/A N/A V5: percent emergent vegetaion 48.0 6.2 59.4 10.2 0.90 0.361Wood duck V1: number of potential nesting cavities/0.4 ha 6.4 1.3 10 3.4 1.53 0.237V2: number of nest boxes/0.4 ha 0.1 0.1 0.0 0.0 1.41 0.257V3: density of potential nest sites (no./0.4 ha) 1.3 0.3 1.8 0.6 1.08 0.318V4: percent potential brood cover 58.5 0.8 83.2 6.4 4.64 0.051V5: percent potential winter cover 47.5 0.8 86.8 7.8 7.00 0.020V6: distance b/w cover types 0.0 0.0 0.0 0.0 N/A N/A V7: percent area optimum nesting habitat 25.0 0.8 36.3 12.5 1.14 0.315V8: percent area optimum brood habitat 82.7 0.8 61.5 20.8 1.51 0.240Snapping turtle V1: water temperature (°C) during summer 27.7 0.9 23.8 2.5 3.52 0.083V2: water velocity (cm/s) during summer 0.003 0.0 0.0 0.0 0.99 0.339V3: percent vegetation in littoral zone 72.9 4.5 62.8 11.0 1.06 0.323V4: water depth vs. ice depth all yes N/A all yes N/A N/A N/A V5: percent silt in substrate 24.3 2.1 18.9 3.3 1.79 0.204V6: distance (m) to small stream 12.3 4.9 0.0 0.0 2.19 0.162V7: distance (m) to permanent water 0.0 0.0 0.0 0.0 N/A N/A Red-spotted newt V1: percent water < 2m deep 100 0.0 100 0.0 N/A N/A V2: percent vegetation in littoral zone 72.9 4.5 62.8 11.0 1.06 0.323V3: distance (m) to forest 14.5 6.8 0.0 0.0 1.59 0.229


391

Appendix 42. Continued. a The same letter following means indicates no difference between wetland types (P > 0.05). bA = woody vegetation dominated by aspen (Populus spp.), willow (Salix spp.), cottonwood (Populus spp.), or alder (Alnus spp.) B = woody vegetation dominated by other deciduous species C = woody vegetation dominated by coniferous species cA = small fluctuations with no effect on burrow/lodge entrances B = moderate fluctuations with some effect on burrow/lodge entrances C = extreme fluctuations or water absent for part of year

392

Appendix 43. Actual and Suitability index (SI) mean values for variables measured within the beaver, muskrat, mink, great blue

heron, red-winged blackbird, wood duck, snapping turtle, and red-spotted newt Habitat Suitability Index models between mitigation (n

= 11) and natural (n = 4) wetlands in West Virginia, 2001-2002.

Mitigationa Naturala HSI model variables Actual x SE SI SE Actual x SE SI SETotal SI value: all species combined 0.56a 0.02 0.60a 0.03Beaver Total SI value 0.74a 0.1 1.0b 0.0V1: percent tree cover a. within wetland basin 0.07 0.1 0.01 0.0 2.3 1.1 0.05 0.0b. within 100 m 39.9 6.8 0.75 0.1 20.4 9.7 0.63 0.1c. within 200 m 45.1 8.0 0.72 0.1 43.2 7.3 0.78 0.1V2: percent trees 2.5-15.2 cm dbh a. within wetland basin 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0b. within 100 m 3.4 2.9 0.15 0.1 36.7 9.4 0.49 0.1c. within 200 m 11.5 4.7 0.22 0.1 21.7 7.9 0.27 0.1V3: percent shrub cover a. within wetland basin 7.5 2.0 0.16 0.0 27.8 6.3 0.55 0.1b. within 100 m 11.6 3.0 0.29 0.1 28.8 8.1 0.56 0.1c. within 200 m 12.6 2.8 0.30 0.1 22.7 6.2 0.51 0.1V4: shrub canopy height (m) a. within wetland basin 1.5 0.2 0.69 0.1 1.6 0.1 0.81 0.1

393

Mitigationa Naturala HSI model variables Actual x SE SI SE Actual x SE SI SEb. within 100 m 2.1 0.1 0.95 0.0 1.4 0.1 0.73 0.1c. within 200 m 2.0 0.1 0.95 0.0 1.5 0.1 0.74 0.0V5: woody vegetation species compositionb a. within wetland basin A: 4; B: 7 N/A 0.75 0.1 All Bs N/A 0.60 0.0b. within 100 m All Bs N/A 0.60 0.0 All Bs N/A 0.60 0.0c. within 200 m All Bs N/A 0.60 0.0 All Bs N/A 0.60 0.0V6: mean annual water fluctuationc All As N/A 1.0 0.0 All As N/A 1.0 0.0Muskrat Total SI value 0.35a 0.04 0.55a 0.1V1: percent emergent vegetation 48.0 6.2 0.81 0.1 59.4 10.2 0.92 0.03V2: percent year with water 100.0 0.0 1.0 0.0 100.0 0.0 1.0 0.0V3: percent Scirpus validus, S. americanus, Typha latifolia 13.6 3.9 0.18 0.04 42.8 14.1 0.38 0.2Mink Total SI value 0.79a 0.1 0.89a 0.04V1: percent year with water 100.0 0.0 1.0 0.0 100.0 0.0 1.0 0.0V2: percent persistent emergent vegetation 46.9 6.0 0.82 0.1 59.0 10.1 0.91 0.03V3: percent tree/shrub cover <100 m 48.2 6.0 0.66 0.1 62.1 11.8 0.82 0.1Great blue heron Total SI value 0.26a 0.02 0.23a 0.1V1: distance between forage area 36.8 21.8 1.0 0.0 37.5 23.9 1.0 and potential nest site V2: presence of shallow, clear water with fish yes: 9; no; 2 N/A 0.91 0.1 yes: 3; no: 1 N/A 0.88 0.0


394

Mitigationa Naturala Habitat model variables Actual x SE SI SE Actual x SE SI SEV3: 100 m foraging disturbance free zone all yes N/A 1.0 0.0 all yes N/A 1.0 0.1V4: presence of forest within 250 m all yes N/A 1.0 0.0 all yes N/A 1.0 0.0V5: 150, 250 m nesting disturbance free zone yes: 8; no: 3 N/A 0.80 0.2 yes: 2; no: 2 N/A 0.63 0.0V6: distance (km) between potential 50.8 4.2 0.10 1.3 82.4 28.5 0.10 0.2 and actual/previous nest site Red-winged blackbird Total SI value 0.03a 0.01 0.15b 0.1V1: percent broad-leaf monocots 17.2 4.4 0.10 0.0 39.9 9.9 0.55 0.3V2: percent year with water 100.0 0.0 1.0 0.0 100.0 0.0 1.0 0.0V3: presence of carp 10 of 11 N/A 0.92 0.1 0 of 4 N/A 1.0 0.0V4: presence of Odonates yes N/A 1.0 0.0 yes N/A 1.0 0.0V5: percent emergent vegetaion 48.0 6.2 0.42 0.1 59.4 10.2 0.60 0.2Wood duck Total SI value 0.82a 0.1 0.68a 0.1V1: number of potential nesting cavities/0.4 ha 6.4 1.3 N/A N/A 10.0 3.4 N/A N/AV2: number of nest boxes/0.4 ha 0.1 0.1 N/A N/A 0.0 0.0 N/A N/AV3: density of potential nest sites (no./0.4 ha) 1.3 0.3 0.25 0.1 1.8 0.6 0.36 0.1V4: percent potential brood cover 58.5 0.8 0.80 0.1 83.2 6.4 0.62 0.2V5: percent potential winter cover 47.5 0.8 0.80 0.1 86.8 7.8 0.47 0.3V6: distance b/w cover types 0.0 0.0 N/A N/A 0.0 0.0 N/A N/AV7: percent area optimum nesting habitat 25.0 0.8 0.81 0.1 36.3 12.5 0.98 0.03V8: percent area optimum brood habitat 82.7 0.8 0.83 0.1 61.5 20.8 0.71 0.1


395

Mitigationa Naturala Habitat model variables Actual x SE SI SE Actual x SE SI SESnapping turtle Total SI value 0.60a 0.01 0.53a 0.04V1: water temperature (°C) during summer 27.7 0.9 0.98 0.02 23.8 2.5 0.80 0.1V2: water velocity (cm/s) during summer 0.003 0.0 1.0 0.0 0.0 0.0 1.0 0.0V3: percent vegetation in littoral zone 72.9 4.5 0.73 0.1 62.8 11.0 0.63 0.1V4: water depth vs. ice depth all yes N/A 1.0 0.0 all yes N/A 1.0 0.0V5: percent silt in substrate 24.3 2.1 0.24 0.02 18.9 3.3 0.19 0.04V6: distance (m) to small stream 12.3 4.9 1.0 0.0 0.0 0.0 1.0 0.0V7: distance (m) to permanent water 0.0 0.0 1.0 0.0 0.0 0.0 1.0 0.0Red-spotted newt Total SI value 0.90a 0.1 0.80a 0.11V1: percent water < 2m deep 100.0 0.0 1.0 0.0 100.0 0.0 1.0 0.0V2: percent vegetation in littoral zone 72.9 4.5 0.92 0.1 62.8 11.0 0.80 0.1V3: distance (m) to forest 14.5 6.8 0.98 0.04 0.0 0.0 1.00 0.0a The same letter following means indicates no difference between wetland types (P > 0.05). bA = woody vegetation dominated by aspen (Populus spp.), willow (Salix spp.), cottonwood (Populus spp.), or alder (Alnus spp.) B = woody vegetation dominated by other deciduous species C = woody vegetation dominated by coniferous species cA = small fluctuations with no effect on burrow/lodge entrances B = moderate fluctuations with some effect on burrow/lodge entrances C = extreme fluctuations or water absent for part of year


396

Appendix 44. Variable measurements and Suitability Index (SI) values for the red-

winged blackbird Habitat Suitability Index model for mitigation (n = 11) and natural

(n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO =

Vepco, BC = Buffalo Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek,

SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and

BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV =

Meadowville, and MY = Muddlety), 2001-2002.

V1 V2 V3 V4 V5 HSI formula % of year carp % emergent % broad- with surface absent vegetation leaved water from Odanates (persistent and (V1*V2*V3 Mitigation monocots present wetland? present? nonpersistent) *V4*V5) WB Actual 12.7 100.0 yes yes 44.6 SI 0.10 1.0 1.0 1.0 1.0 0.10 VO Actual 3.8 100.0 yes yes 66.9 SI 0.10 1.0 1.0 1.0 0.30 0.03 BC Actual 2.8 100.0 yes yes 41.5 SI 0.10 1.0 1.0 1.0 1.0 0.10 ER Actual 14.8 100.0 yes yes 22.3 SI 0.10 1.0 1.0 1.0 0.10 0.01 LC Actual 3.6 100.0 yes yes 68.8 SI 0.10 1.0 1.0 1.0 0.30 0.03 SC Actual 10.8 100.0 yes yes 81.0 SI 0.10 1.0 1.0 1.0 0.30 0.03 SR Actual 17.1 100.0 yes yes 22.4 SI 0.10 1.0 1.0 1.0 0.10 0.01 T Actual 37.6 100.0 yes yes 68.0 SI 0.10 1.0 1.0 1.0 0.30 0.03 TJM Actual 10.4 100.0 no yes 47.2 SI 0.10 1.0 0.1 1.0 1.0 0.01 EB Actual 30.4 100.0 yes yes 38.9 SI 0.10 1.0 1.0 1.0 0.1 0.01

397

V1 V2 V3 V4 V5 HSI formula % of year carp % emergent % broad- with surface absent vegetation leaved water from Odanates (persistent and (V1*V2*V3 Mitigation cont. monocots present wetland? present? nonpersistent) *V4*V5) BR Actual 45.6 100.0 yes yes 26.7 SI 0.10 1.0 1.0 1.0 0.1 0.01 Mean actual 17.2 100.0 n/a n/a 48.0 Mean SI 0.10 1.0 0.92 1.0 0.42 0.03 Natural AM Actual 59.6 100.0 yes yes 87.3 SI 1.0 1.0 1.0 1.0 0.30 0.30 ES Actual 34.6 100.0 yes yes 44.3 SI 0.1 1.0 1.0 1.0 1.0 0.10 MV Actual 14.6 100.0 yes yes 43.8 SI 0.1 1.0 1.0 1.0 1.0 0.10 MY Actual 50.9 100.0 yes yes 62.0 SI 1.0 1.0 1.0 1.0 0.1 0.10 Mean Actual 39.9 100.0 n/a n/a 59.4 Mean SI 0.55 1.0 1.0 1.0 0.60 0.15


398

Appendix 45. Variable measurements and Suitability Index (SI) values for the beaver Habitat Suitability Index model for mitigation

(n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER

= Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch,

and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002.

V5 HSI formulac

V1 V2 V3 V4 Species composition V6 a/b = [(V1*V2)1/2 * V5]1/2 +

% tree cover % trees 2.5 to 15.2 cm dbh % shrub cover shrub canopy height (m) of woody vegetation a mean [(V3*V4)1/2 *V5]1/2

w/in w/in w/in w/in w/in annual c = .5[(V1*V2)1/2 * V5]1/2 +

wetland wetland wetland wetland wetland water [(V3*V4)1/2 *V5]1/2

Mitigation basin < 100 m < 200 m basin < 100 m < 200 m basin < 100 < 200 basin < 100 m < 200 m basin < 100 m < 200 m Fluctuationb a+b+c/2.5 WB Actual 0.0 26.7 22.5 0.0 26.7 53.3 0.0 0.0 0.0 n/a 2.0 1.6 B B B A SI 0.0 0.73 0.61 0.0 0.42 0.62 0.0 0.0 0.0 0.0 1.0 0.80 0.60 0.60 0.60 1 0.58 VO Actual 0.0 66.7 72.7 0.0 20.0 13.3 4.5 3.3 10.8 0.60 1.8 1.6 B B B A SI 0.0 0.92 0.85 0.0 0.4 0.30 0.01 0.08 0.26 0.30 0.92 0.80 0.60 0.60 0.60 1 1.0 BC Actual 0.0 0.0 0.0 0.0 6.7 20.0 22.1 18.3 19.2 0.60 1.4 1.7 B B B A SI 0.0 0.0 0.0 0.0 0.25 0.4 0.50 0.47 0.51 0.30 0.65 0.90 0.60 0.60 0.60 1 0.69 ER Actual 0.0 53.3 50.8 0.0 0.0 13.3 10.7 3.3 2.5 1.8 1.9 2.0 B B B A SI 0.0 1.0 1.0 0.0 0.0 0.3 0.23 0.08 0.02 0.92 0.98 1.0 0.60 0.60 0.60 1 0.49 LC Actual 0.0 25.0 30.5 0.0 13.6 6.7 2.8 20.0 22.5 1.1 1.9 1.8 A B B A SI 0.0 0.66 0.71 0.0 0.31 0.25 0.02 0.50 0.55 0.60 0.98 0.92 1.0 0.60 0.60 1 1.0 SC Actual 0.0 60.0 65.5 0.0 0.0 6.7 11.0 8.0 11.0 1.9 1.9 2.0 B B B A SI 0.0 1.0 0.91 0.0 0.0 0.25 0.25 0.22 0.26 0.98 0.98 1.0 0.60 0.60 0.60 1 0.63 SR Actual 0.50 32.5 59.4 0.0 0.0 0.0 4.9 3.8 3.8 1.8 2.4 2.3 B B B A SI 0.0 0.85 1.0 0.0 0.0 0.0 0.1 0.09 0.04 0.92 1.0 1.0 0.60 0.60 0.60 1 0.51 T Actual 0.0 33.8 27.5 0.0 0.0 0.0 8.0 20 15 1.9 1.9 1.9 B B B A SI 0.0 0.83 0.78 0.0 0.0 0.0 0.20 0.50 0.38 0.98 0.98 0.98 0.60 0.60 0.60 1 0.78 TJM Actual 0.0 18.8 17.5 0.0 6.7 13.3 14.1 10.0 13.8 1.7 2.5 2.4 A B B A SI 0.0 0.51 0.43 0.0 0.25 0.30 0.30 0.25 0.33 0.90 1.0 1.0 1.0 0.60 0.60 1 1.0

399

Appendix V5 HSI formulac

V1 V2 V3 V4 Species composition V6 a/b = [(V1*V2)1/2 * V5]1/2 +

% tree cover % trees 2.5 to 15.2 cm dbh % shrub cover shrub canopy height (m) of woody vegetation a mean [(V3*V4)1/2 *V5]1/2

w/in w/in w/in w/in w/in annual c = .5[(V1*V2)1/2 * V5]1/2 +

wetland wetland wetland wetland wetland water [(V3*V4)1/2 *V5]1/2 Mitigation cont. basin < 100 m < 200 m basin < 100 m < 200 m basin < 100 < 200 basin < 100 m < 200 m basin < 100 m < 200 m fluctuationb a+b+c/2.5 EB Actual 0 48.8 69.8 0 0 0 3.8 32.5 31.7 1.7 2.6 2.3 A B B A SI 0 1.0 0.88 0 0 0 0.06 0.77 0.80 0.90 1.0 1.0 1.0 0.60 0.60 1.0 0.87 BR Actual 0.30 73.8 79.8 0 0 0 0.70 8.8 8.8 1.5 2.4 2.5 A B B A SI 0 0.8 0.77 0 0 0 0.01 0.20 0.20 0.75 1.0 1.0 1.0 0.60 0.60 1.0 0.62 Mean actual 0.07 39.9 45.1 0 3.4 11.5 7.5 11.6 12.6 1.5 2.1 2.0 n/a n/a n/a n/a Mean SI 0.01 0.75 0.72 0 0.15 0.22 0.16 0.29 0.3 0.69 0.95 0.95 0.75 0.60 0.60 1.0 0.74 Natural AM Actual 7.4 25.0 23.3 0 60.0 33.3 12.3 5.0 2.5 1.9 1.7 1.6 B B B A SI 0.16 0.66 0.62 0 0.67 0.46 0.28 0.1 0.02 0.98 0.9 0.8 0.60 0.60 0.60 1.0 1.0 ES Actual 1.7 3.3 22.5 0 66.7 53.3 23 63.3 48.3 1.2 0.9 1.2 B B B A SI 0.05 0.03 0.61 0 0.75 0.62 0.52 1.0 1.0 0.6 0.48 0.6 0.60 0.60 0.60 1.0 1.0 MV Actual 0 57.5 56.3 0 13.3 0 58.4 10.0 10.6 1.4 1.8 1.8 B B B A SI 0 1.0 1.0 0 0.3 0 1.0 0.25 0.26 0.65 0.92 0.92 0.60 0.60 0.60 1.0 1.0 MY Actual 0 75.0 70.8 0 6.7 0 17.6 36.7 29.2 2.0 1.3 1.3 B B B A SI 0 0.83 0.87 0 0.25 0 0.41 0.9 0.75 1.0 0.62 0.62 0.60 0.60 0.60 1.0 1.0 Mean Actual 2.3 20.4 43.2 0 36.7 21.7 27.8 28.8 22.7 1.6 1.4 1.5 n/a B B A Mean SI 0.05 0.63 0.78 0 0.49 0.27 0.55 0.56 0.51 0.81 0.73 0.74 0.60 0.60 0.60 1.0 1.0

a A = woody vegetation dominated (>50%) by aspen, willow, cottonwood, or alder B = woody vegetation dominated by other deciduous species C = woody vegetation dominated by confiers b A = small fluctuations B = moderate fluctuations C = extreme fluctuations c Total HSI score is equal to the lesser value of V6 and a+b+c/2.5


400

Appendix 46. Variable measurements and Suitability Index (SI) values for the muskrat Habitat Suitability Index model for mitigation

(n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER

= Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch,

and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002.

Food/Cover Cover Component Component Food Component

V3 V1 V2 % of emergent % emergent vegetation consisting vegetation % of year of Olney bulrush, HSI formula a (persistent and with surface common threesquare, SI Cover = SI Food = Mitigation nonpersistent) water present or cattail (V1 * V2)1/2 (V1 * V3)1/2 WB Actual 44.6 100 12.7 SI 0.89 1.0 0.11 0.94 0.31 VO Actual 66.9 100 2.9 SI 1.0 1.0 0.10 1.00 0.32 BC Actual 41.5 100 2.8 SI 0.84 1.0 0.10 0.92 0.29 ER Actual 22.3 100 14.8 SI 0.48 1.0 0.15 0.69 0.27 LC Actual 68.8 100 3.1 SI 1.0 1.0 0.10 1.0 0.32

401

Food/Cover Cover Component Component Food Component V1 V2 V3 % of emergent % emergent vegetation consisting vegetation % of year of Olney bulrush, HSI formula a (persistent and with surface common threesquare, SI Cover = SI Food = Mitigation cont. nonpersistent) water present or cattail (V1 * V2)1/2 (V1 * V3)1/2 SC Actual 81.0 100 10.3 SI 1.0 1.0 0.10 1.0 0.32 SR Actual 22.4 100 19.5 SI 0.49 1.0 0.19 0.70 0.31 T Actual 68 100 37.6 SI 1.0 1.0 0.45 1.0 0.67 TJM Actual 47.2 100 10.4 SI 0.91 1.0 0.10 0.95 0.30 EB Actual 38.9 100 0.0 SI 0.82 1.0 0.10 0.91 0.29 BR Actual 26.7 100 35.4 SI 0.53 1.0 0.44 0.73 0.48 Mean actual 48.0 100 13.6 Mean SI 0.81 1.0 0.18 0.89 0.35


402

Food/Cover Cover Component Component Food Component V1 V2 V3 % of emergent % emergent vegetation consisting vegetation % of year of Olney bulrush, HSI formula a (persistent and with surface common threesquare, SI Cover = SI Food = Natural nonpersistent) water present or cattail (V1 * V2)1/2 (V1 * V3)1/2 MY Actual 87.3 100 62.9 SI 0.95 1.0 0.8 0.97 0.87 ES Actual 44.3 100 35.6 SI 0.87 1.0 0.44 0.93 0.62 MV Actual 43.8 100 66.7 SI 0.86 1.0 0.18 0.93 0.39 MY Actual 62.0 100 6.0 SI 1.0 1.0 0.1 1.0 0.32 Mean Actual 59.4 100 42.8 Mean SI 0.92 1.0 0.38 0.96 0.55 a Total HSI score is equal to the lesser value of SI Cover and SI Food


403

Appendix 47. Variable measurements and Suitability Index (SI) values for the mink Habitat

Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in West Virginia

(mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run,

LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist

MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh,

ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002.

V1 V2 V3 HSI formula % tree and/or % of year % persistent shrub cover with surface emergent w/in 100 m Mitigation water present vegetation of water's edge V1((4V2 + V3)/5)WB Actual 100 42.4 36.3 SI 1.0 0.83 0.43 0.75 VO Actual 100 61.8 68.4 SI 1.0 1.0 0.91 0.98 BC Actual 100 40.3 18.3 SI 1.0 0.82 0.30 0.72 ER Actual 100 22.3 55.0 SI 1.0 0.50 0.73 0.55 LC Actual 100 63.8 41.3 SI 1.0 1.0 0.60 0.92 SC Actual 100 81.0 64.0 SI 1.0 0.98 0.88 0.96 SR Actual 100 22.4 36.3 SI 1.0 0.50 0.52 0.50 T Actual 100 68.0 41.3 SI 1.0 1.0 0.61 0.92 TJM Actual 100 47.2 26.3 SI 1.0 0.98 0.43 0.87 EB Actual 100 38.9 65.0 SI 1.0 0.78 0.89 0.80 BR Actual 100 26.7 77.6 SI 1.0 0.60 1.0 0.68

404

V1 V2 V3 HSI formula % tree and/or % of year % persistent shrub cover with surface emergent w/in 100 m Mitigation cont. water present vegetation of water's edge V1((4V2 + V3)/5)Mean actual 100 46.9 48.2 Mean SI 1.0 0.82 0.66 0.79 Natural AM Actual 100 86.3 30.0 SI 1.0 0.90 0.48 0.82 ES Actual 100 43.8 66.6 SI 1.0 0.85 0.90 0.86 MV Actual 100 43.8 65.0 SI 1.0 0.90 0.89 0.89 MY Actual 100 62.0 86.7 SI 1.0 1.0 1.0 1.0 Mean Actual 100 59 62.1 Mean SI 1.0 0.91 0.82 0.89


405

Appendix 48. Variable measurements and Suitability Index (SI) values for the great-blue heron Habitat Suitability Index model for

mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo

Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB =

Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY =

Muddlety), 2001-2002.

Foraging Component Reproduction Component V1 V2 V3 V4 V5 V6 HSI formula distance (m) disturbance free distance (km) of b/w foraging presence of disturbance presence of (250 m for land and potential nest area and shallow, clear free up to forest w/in 150 m for water) site to actual (V1*V2* potential water with 100 m around 250 m of around potential or previous V3*V4*

Mitigation nest site fish (<25 cm) foraging area? wetland? nesting sites? nest site V5*V6)1/2 WB Actual 10.0 yes/yes yes yes yes 83.4 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 VO Actual 20.0 yes/no yes yes yes 55.8 SI 1.0 0.50 1.0 1.0 1.0 0.10 0.22 BC Actual 250.0 yes/no yes yes yes 52.3 SI 1.0 0.50 1.0 1.0 1.0 0.10 0.22 ER Actual 0.0 yes/yes yes yes yes 49.6 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 LC Actual 50.0 yes/yes yes yes yes 37.9 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32

406


Mitigation cont. nest site fish (<25 cm) foraging area? wetland? nesting sites? nest site V5*V6)1/2 SC Actual 20.0 yes/yes yes yes yes 42.4 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 SR Actual 0.0 yes/yes yes yes no 43.2 SI 1.0 1.0 1.0 1.0 0.25 0.10 0.16 T Actual 20.0 yes/yes yes yes no 47.6 SI 1.0 1.0 1.0 1.0 0.25 0.10 0.16 TJM Actual 25.0 yes/yes yes yes no 48.1 SI 1.0 1.0 1.0 1.0 0.25 0.10 0.16 EB Actual 5.0 yes/yes yes yes yes 65.4 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 BR Actual 5.0 yes/yes yes yes yes 32.9 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 Mean actual 36.8 n/a n/a n/a n/a 50.8 Mean SI 1.0 0.91 1.0 1.0 0.8 0.10 0.26


407


Natural nest site fish (<25 cm) foraging area? wetland? nesting sites? nest site V5*V6)1/2 AM Actual 50.0 yes/yes yes yes yes 166.4 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 ES Actual 100.0 yes/yes yes yes yes 56.2 SI 1.0 1.0 1.0 1.0 1.0 0.10 0.32 MV Actual 0.0 yes/no yes yes no 40.6 SI 1.0 0.5 1.0 1.0 0.25 0.10 0.11 MY Actual 0.0 yes/yes yes yes no 66.4 SI 1.0 1.0 1.0 1.0 0.25 0.10 0.16 Mean Actual 37.5 n/a n/a n/a n/a 82.4 Mean SI 1.0 0.88 1.0 1.0 0.63 0.10 0.23


408

Appendix 49. Variable measurements and Suitability Index (SI) values for the wood duck Habitat Suitability Index model for

mitigation (n = 11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo

Coal, ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB =

Enoch Branch, and BR = Bear Run; natural sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY =

Muddlety), 2001-2002.

Breeding Model Winter model Total HSI V1 V2 V3 V4 V7 V8 SI formula V5 # of tree density of % area % area % potential equals higher cavities/0.4 ha potential nest w/ optimum w/ optimum Total breeding winter cover SI between with 7.6 X 10 cm # of nest # of nest sites/0.4ha: % potential nesting brood-rearing SI = lower value (equals breeding SI Mitigation entrance boxes boxes/0.4 ha (.18*V1) + (.95*V2) brood cover habitat (= nesting SI) habitat (= brood SI) of V7 and V8 total winter SI) and winter SI WB Actual 4.0 0.0 0.0 .72 49.1 14.0 98.0 46.9 SI .14 0.98 .70 0.98 0.70 0.92 0.92 VO Actual 1.3 2.0 0.11 0.34 71.4 7.0 100 66.3 SI 0.07 1.0 0.28 1.0 0.28 1.0 1.0 BC Actual 0.0 1.0 0.04 0.04 63.6 1.0 100 62.4 SI 0.01 1.0 0.02 1.0 0.02 1.0 1.0 ER Actual 8.0 0.0 0.0 1.4 33 28.0 65.0 33.0 SI 0.28 0.65 1.0 0.65 0.65 0.62 0.65 LC Actual 9.3 0.0 0.0 1.4 71.6 34.0 100 66.6 SI 0.34 1.0 1.0 1.0 1.0 1.0 1.0 SC Actual 6.7 10.0 0.59 1.7 92 34.0 30.0 92.0 SI 0.34 0.3 1.0 0.3 0.30 0.29 0.30 SR Actual 8.0 3.0 0.4 1.8 28.9 32.0 60.0 28.9 SI 0.32 0.6 1.0 0.6 0.60 0.57 0.60 T Actual 5.3 5.0 0.65 1.6 76 24.0 98.0 76.0 SI 0.24 0.98 1.0 0.98 0.98 0.98 0.98

409

Breeding Model Winter model Total HSI V1 V2 V3 V4 V7 V8 SI formula V5 # of tree density of % area % area % potential equals higher cavities/0.4 ha potential nest w/ optimum w/ optimum Total breeding winter cover SI between with 7.6 X 10 cm # of nest # of nest sites/0.4ha: % potential nesting brood-rearing SI = lower value (equals breeding SI Mitigation cont. entrance boxes boxes/0.4 ha (.18*V1) + (.95*V2) brood cover habitat (= nesting SI) habitat (= brood SI) of V7 and V8 total winter SI) and winter SI TJM Actual 6.7 0.0 0.0 1.2 70.5 24.0 100 70.5 SI 0.24 1.0 1.0 1.0 1.0 1.0 1.0 EB Actual 5.3 0.0 0.0 0.95 60 19.0 100 45.8 SI 0.19 1.0 0.94 1.0 0.94 0.90 0.94 BR Actual 16.0 0.0 0.0 2.9 27.7 58.0 59.0 27.4 SI 0.58 0.59 1.0 0.59 0.59 0.56 0.59 Mean actual 6.4 0.20 1.3 58.5 26 82.7 47.5 Mean SI 0.25 0.80 0.81 0.83 0.64 0.82 0.82 Natural AM Actual 18.7 0.0 0.0 3.4 99.6 68.0 4.0 99.5 SI 0.68 0.04 1.0 0.4 0.40 0.01 0.40 ES Actual 4 0.0 0.0 0.72 68.6 14.0 100 68.1 SI 0.14 1.0 0.9 1.0 0.90 1.0 0.90 MV Actual 12 0.0 0.0 2.2 85 44 60.0 100 SI 0.44 0.6 1.0 0.6 0.60 0.0 0.60 MY Actual 5.3 0.0 0.0 0.95 79.6 19.0 82.0 79.6 SI 0.19 0.82 1.0 0.82 0.80 0.86 0.80 Mean Actual 10 0.0 0.0 1.8 83.2 36.3 61.5 86.8 Mean SI 0.36 0.62 0.98 0.71 0.68 0.47 0.68


410

Appendix 50. Variable measurements and Suitability Index (SI) values for the snapping turtle Habitat Suitability Index model for mitigation (n =

11) and natural (n = 4) wetlands in West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal, ER = Elk Run, LC =

Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle, TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural

sites: AM = Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-2002.

Winter Cover Reproduction Interspersion Food Component (SIF) Component (SIWC) Component (SIR) Component (SII) V1 V2 V3 V4 V5 V6 V7 HSI formula mean water mean water temp (°C) at mid velocity (cm/s) % aquatic winter water distance (m)

depth during at mid depth vegetation in depth > max. % silt in distance (m) to permanent (SIF*SIWC*SIR)1/3 Site summer during summer littoral zone ice depth? substrate to small stream water * SII WB Actual 26.2 0.0 84.7 yes 18.5 0.0 0.0 SI 1.0 1.0 0.84 1.0 0.19 1.0 1.0 0.56 VO Actual 22.2 0.014 66.9 yes 25.1 50.0 0.0 SI 0.82 1.0 0.67 1.0 0.25 1.0 1.0 0.59 BC Actual 27.4 0.0 52.4 yes 29.1 35.0 0.0 SI 1.0 1.0 0.52 1.0 0.29 1.0 1.0 0.61 ER Actual 26.6 0.0 87.6 yes 23.4 0.0 0.0 SI 1.0 1.0 0.88 1.0 0.23 1.0 1.0 0.6 LC Actual 26.4 0.0 75.2 yes 39.3 10.0 0.0 SI 1.0 1.0 0.75 1.0 0.39 1.0 1.0 0.71 SC Actual 30.9 0.0 87.8 yes 29.1 0.0 0.0 SI 1.0 1.0 0.88 1.0 0.29 1.0 1.0 0.65 SR Actual 26.4 0.0 63.4 yes 18.4 10.0 0.0

411


depth during at mid depth vegetation in depth > max. % silt in distance (m) to permanent (SIF*SIWC*SIR)1/3 Site summer during summer littoral zone ice depth? substrate to small stream water * SII SI 1.0 1.0 0.63 1.0 0.18 1.0 1.0 0.54 T Actual 28.8 0.002 89.6 yes 21.5 15.0 0.0 SI 1.0 1.0 0.90 1.0 0.22 1.0 1.0 0.60 TJM Actual 27.0 0.011 47.9 yes 28.8 10.0 0.0 SI 1.0 1.0 0.48 1.0 0.29 1.0 1.0 0.61 EB Actual 29.2 0.001 82.9 yes 13.6 5.0 0.0 SI 1.0 1.0 0.83 1.0 0.14 1.0 1.0 0.51 BR Actual 33.9 0.0 63.2 yes 20.8 0.0 0.0 SI 1.0 1.0 0.63 1.0 0.21 1.0 1.0 0.57 Mean actual 27.7 0.003 72.9 n/a 24.3 12.3 0.0 Mean SI 0.98 1.0 0.73 1.0 0.24 1.0 1.0 0.60 Natural AM Actual 20.1 0.0 87.8 yes 11.0 0.0 0.0 SI 0.65 1.0 0.88 1.0 0.11 1.0 1.0 0.45 ES Actual 23.4 0.0 44.7 yes 19.5 0.0 0.0 SI 0.90 1.0 0.45 1.0 0.20 1.0 1.0 0.53 MV Actual 20.6 0.0 43.8 yes 17.9 0.0 0.0 SI 0.64 1.0 0.44 1.0 0.18 1.0 1.0 0.49 MY Actual 31.1 0.0 74.8 yes 27.2 0.0 0.0 SI 1.0 1.0 0.75 1.0 0.28 1.0 1.0 0.63


412


depth during at mid depth vegetation in depth > max. % silt in distance (m) to permanent (SIF*SIWC*SIR)1/3 Site summer during summer littoral zone ice depth? substrate to small stream water * SII Mean Actual 23.8 0.0 62.8 n/a 18.9 0.0 0.0 Mean SI 0.80 1.0 0.63 1.0 0.19 1.0 1.0 0.53


413

Appendix 51. Variable measurements and Suitability Index (SI) values for the red-spotted

newt Habitat Suitability Index model for mitigation (n = 11) and natural (n = 4) wetlands in

West Virginia (mitigation sites: WB = Walnut Bottom, VO = Vepco, BC = Buffalo Coal,

ER = Elk Run, LC = Leading Creek, SC = Sugar Creek, SR = Sand Run, T = Triangle,

TJM = Trus Joist MacMillan, EB = Enoch Branch, and BR = Bear Run; natural sites: AM

= Altona Marsh, ES = Elder Swamp, MV = Meadowville, and MY = Muddlety), 2001-

2002.

V1 V2 V3 HSI formula % aquatic vegetation distance (m) % water in littoral to forested Mitigation < 2 m deep zone cover type V1 * V2 * V3 WB Actual 100 84.7 10.0 SI 1.0 1.0 1.0 1.0 VO Actual 100 66.9 25.0 SI 1.0 0.93 1.0 0.93 BC Actual 100 52.4 75.0 SI 1.0 0.72 0.75 0.54 ER Actual 100 87.6 0.0 SI 1.0 1.0 1.0 1.0 LC Actual 100 75.2 0.0 SI 1.0 1.0 1.0 1.0 SC Actual 100 87.8 20.0 SI 1.0 1.0 1.0 1.0 SR Actual 100 63.4 0.0 SI 1.0 0.89 1.0 0.89 T Actual 100 89.6 0.0 SI 1.0 1.0 1.0 1.0 TJM Actual 100 47.9 25.0 SI 1.0 0.69 1.0 0.69 EB Actual 100 82.9 5.0 SI 1.0 1.0 1.0 1.0 BR Actual 100 63.2 0.0 SI 1.0 0.87 1.0 0.87

414

V1 V2 V3 HSI formula % aquatic vegetation distance (m) % water in littoral to forested Mitigation cont. < 2 m deep zone cover type V1 * V2 * V3 Mean actual 100 72.9 14.5 Mean SI 1.0 0.92 0.98 0.90 Natural AM Actual 100 87.8 0.0 SI 1.0 1.0 1.0 1.0 ES Actual 100 44.7 0.0 SI 1.0 0.62 1.0 0.62 MV Actual 100 43.8 0.0 SI 1.0 0.58 1.0 0.58 MY Actual 100 74.8 0.0 SI 1.0 0.98 1.0 0.98 Mean Actual 100 62.8 0.0 Mean SI 1.0 0.80 1.0 0.80


415

Appendix 52. Common and scientific names of all birds included in Analysis of

Variance models used to calculate metrics for wetland rankings and in Canonical

Correspondence Analyses (CCA) on 11 mitigation and 4 reference wetlands, West


Common Name Scientific Name Great Blue Heron Ardea herodias Green Heron Butorides virescens Turkey Vulture Cathartes aura Canada Goose Branta canadensis Muscovy Duck Cairina moschata Green-winged Teal Anas crecca Black Duck Anas rubripes Wood Duck Aix sponsa Mallard Anas platyrhynchos Red-shouldered Hawk Buteo lineatus Red-tailed Hawk Buteo jamaicensis Ruffed Grouse Bonasa umbellus Wild Turkey Meleagris gallopavo Northern Bobwhite Colinus virginianus Virginia Rail Rallus limicola Sora Porzana carolina Killdeer Charadrius vociferus Spotted Sandpiper Actitis macularia American Woodcock Scolopax minor Mourning Dove Zenaida macroura Yellow-billed Cuckoo Coccyzus americanus Chimney Swift Chaetura pelagica Ruby-throated Hummingbird Archilochus colubris Belted Kingfisher Ceryle alcyon Red-bellied Woodpecker Melanerpes carolinus Red-headed Woodpecker Melanerpes erythrocephalus Downy Woodpecker Picoides pubescens Northern Flicker Colaptes auratus Pileated Woodpecker Dryocopus pileatus Eastern Wood-Pewee Contopus virens Acadian Flycatcher Empidonax virescens

416

Common Name Scientific Name Alder Flycatcher Empidonax alnorum Willow Flycatcher Empidonax traillii Least Flycatcher Empidonax minimus Eastern Phoebe Sayornis phoebe Great Crested Flycatcher Myiarchus crinitus Olive-sided Flycatcher Contopus borealis Eastern Kingbird Tyrannus tyrannus White-eyed Vireo Vireo griseus Yellow-throated Vireo Vireo flavifrons Warbling Vireo Vireo gilvus Red-eyed Vireo Vireo olivaceus Blue Jay Cyanocitta cristata American Crow Corvus brachyrhynchos Common Raven Corvus corax Tree Swallow Tachycineta bicolor Northern Rough-winged Swallow Stelgidopteryx serripennis Barn Swallow Hirundo rustica Black-capped Chickadee Poecile atricapillus Carolina Chhickadee Parus carolinensis Tufted Titmouse Baeolophus bicolor Brown Creeper Certhia americana Red-breasted Nuthatch Sitta canadensis White-breasted Nuthatch Sitta carolinensis Carolina Wren Thryothorus ludovicianus House Wren Troglodytes aedon Blue-gray Gnatcatcher Polioptila caerulea Eastern Bluebird Sialia sialis Veery Catharus fuscescens Hermit Thrush Catharus guttatus Swainson's Thrush Catharus ustulatus Wood Thrush Hylocichla mustelina American Robin Turdus migratorius Gray Catbird Dumetella carolinensis Northern Mockingbird Mimus polyglottos Brown Thrasher Toxostoma rufum European Starling Sturnus vulgaris Cedar Waxwing Bombycilla cedrorum

Appendix 52. Continued

417

Common Name Scientific Name Blue-winged Warbler Vermivora pinus Golden-winged Warbler Vermivora chrysoptera Northern Parula Parula americana Yellow Warbler Dendroica petechia Magnolia Warbler Dendroica magnolia Black-throated Green Warbler Dendroica virens Yellow-throated Warbler Dendroica dominica Black-and-white Warbler Mniotilta varia Prairie Warbler Dendroica discolor Cerulean Warbler Dendroica cerulea Prothonotary Warbler Protonotaria citrea American Redstart Setophaga ruticilla Worm-eating Warbler Helmitheros vermivorus Ovenbird Seiurus aurocapillus Kentucky Warbler Oporornis formosus Common Yellowthroat Geothlypis trichas Scarlet Tanager Piranga olivacea Eastern Towhee Pipilo erythrophthalmus Chipping Sparrow Spizella passerina Field Sparrow Spizella pusilla Grasshopper Sparrow Ammodramus bairdii Song Sparrow Melospiza melodia Savannah Sparrow Passerculus sandwichensis Swamp Sparrow Melospiza georgiana Vesper Sparrow Pooecetes gramineus Dark-eyed Junco Junco hyemalis Northern Cardinal Cardinalis cardinalis Rose-breasted Grosbeak Pheucticus ludovicianus Indigo Bunting Passerina cyanea Red-winged Blackbird Agelaius phoeniceus Boat-tailed Grackle Quiscalus major Common Grackle Quiscalus quiscula Brown-headed Cowbird Molothrus ater Baltimore Oriole Icterus galbula Orchard Oriole Icterus spurius American Goldfinch Carduelis tristis House Sparrow Passer domesticus


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