Establishing Restoration Objectives for Eelgrass in Long Island Sound

Part I: Review of the Seagrass Literature Relevant to Long Island Sound

Final Grant Report to the Connecticut Department of Environmental Protection, Bureau of Water Protection and Land Reuse and the U.S. Environmental Protection Agency

Funded by a Cooperative Agreement: LI-97107201, CDFA#66-437

(UCONN FRS#542190 )

April 2008

By

Jamie M. P. Vaudrey, Ph.D. Department of Marine Sciences

University of Connecticut 1080 Shennecossett Road

Groton, CT 06340 jamie.vaudrey@alum.wellesley.edu

Contents Acronyms ........................................................................................................................................ ii

List of Tables.................................................................................................................................. iii

List of Figures ................................................................................................................................ iii

Technical Advisory Committee...................................................................................................... iv

Technical Advisory Committee...................................................................................................... iv

Acknowledgements ......................................................................................................................... v

Executive Summary ........................................................................................................................ 1

Subject Summaries and Overviews ................................................................................................. 4

Historical Distribution and Long-Term Decline ............................................................................. 8

Specific Factors Affecting Zostera marina ..................................................................................... 9

Light ........................................................................................................................................... 9

Depth................................................................................................................................... 13

Maximum Depth Limit .................................................................................................. 13

Secchi Depth............................................................................................................. 14

Light Extinction Coefficient ..................................................................................... 15

Minimum Depth Limit................................................................................................... 15

Total Suspended Solids (turbidity) ..................................................................................... 17

Epiphytes............................................................................................................................. 18

Temperature ............................................................................................................................. 19

Nutrient Availability ................................................................................................................ 20

Example 1 – Nitrogen Loads ......................................................................................... 20

Example 2 – Light and Nitrogen Loads......................................................................... 20

Example 3 – Temperature and Nitrogen Loads ............................................................. 21

Example 4 – Nutrient Interactions ................................................................................. 21

Carbohydrates ..................................................................................................................... 21

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Nitrogen .............................................................................................................................. 22

Future Considerations ......................................................................................................... 24

Sediment Characteristics .......................................................................................................... 24

Sediment Organic Content .................................................................................................. 25

Sulfides and Anoxia ............................................................................................................ 25

Wave Action and Current Speed.............................................................................................. 26

Competition with Other Primary Producers .................................................................................. 27

Indicators ....................................................................................................................................... 29

Putting It All Together - Interactions Between Factors................................................................. 30

Setting Goals for Water Quality in Long Island Sound................................................................. 32

Future Research............................................................................................................................. 35

Recovery of Seagrass - a few success stories ................................................................................ 36

Case Studies .................................................................................................................................. 42

Appendix I – Summary of Data Verification and Validation Results ........................................... 43

References ..................................................................................................................................... 47

Acronyms

CT DA - Connecticut Department of Agriculture

CT DEP – Connecticut Department of Environmental Protection

DA - Connecticut Department of Agriculture

DEP - Connecticut Department of Environmental Protection

EPA – Environmental Protection Agency

LIS – Long Island Sound

SAV - submerged aquatic vegetation

TAC – Technical Advisory Committee

USFWS – United States Fish and Wildlife Service

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List of Tables

Table 1: Comparison of recommended habitat requirements for the growth and survival of eelgrass. .............................................................................................................. 2

Table 2: Descriptions of Habitat Requirements for Zostera marina. ............................... 10

Table 3: Recommended habitat requirements for the growth and survival of eelgrass... 34

Table 4: Review of the current literature documenting the natural recovery of seagrass.37

Table 5: Data Quality Indicators (DQI) and their application. ......................................... 43

Table 6: Summary of unpublished data types and category for the Case Study report (A= acceptable, Q = acceptable with qualifications, U = unacceptable). .................... 45

Table 7: Summary of historical data and nitrogen load data types and category for the Case Study report (A= acceptable, Q = acceptable with qualifications, U = unacceptable). ....................................................................................................... 46

List of Figures

Figure 1: Identifying critical levels of photon flux densities............................................ 11

Figure 2: N loading rate per hectare of estuarine surface area versus percent primary production by the three dominant communities.................................................... 12

Figure 3: Patterns in seagrass bed characteristics with depth. ......................................... 14

Figure 4: Vertical distribution of eelgrass in Long Island Sound based on the tidal range and light attenuation coefficients (Kd). ................................................................. 16

Figure 5: Change in spatial location and patch size of Z. marina distribution in Waquoit Bay in response to nutrient enrichment. ............................................................... 20

Figure 6: Comparison of rates and stocks for three groups of primary producers. .......... 28

Figure 7: Conceptual model of the effect of increased nutrient loading on seagrasses, stressing the self-accelerating nature of the process. ............................................ 30

Figure 8: Schematic representation of the main factors determining the occurrence of seagrass (copied from Boer 2007). ....................................................................... 31

Figure 9: Conceptual model of factors affecting seagrass distribution............................. 33

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Technical Advisory Committee

The following group of people were invited to attend annual meetings pertaining to eelgrass in Long Island Sound. This project was proposed and developed based on those discussions. Since the start of the project in the fall of 2006, the TAC has been invited to annual meetings to review progress and have been invited to review the drafts of this report and the accompanying website.

Alan Banister, Stonington Shellfish Commission Alison Branco, Department of Marine Sciences, University of Connecticut Betty Buckley, Graduate School of Oceanography, University of Rhode Island Lisa Cavallaro, National Marine Fisheries Service Karen Chytalo, New York State Department of Environmental Conservation Chris Deucutis, Narragansett Bay Estuary Program Robinson Fulweiler, Graduate School of Oceanography, University of Rhode Island Corey Garza, National Marine Fisheries Service Stephen Granger, Graduate School of Oceanography, University of Rhode Island Tom Halavik, U.S. Fish and Wildlife Service Sally Harold, The Nature Conservancy, Connecticut Branch Louise Harrison, U.S. Fish and Wildlife Service liaison to the EPA Johanna Hunter, U.S. EPA New England Mark Johnson, Connecticut Department of Environmental Protection Milan Keser, Dominion Environmental Lab, Dominion Nuclear Connecticut Jim Kremer (UConn Project Manager), Department of Marine Sciences, University of Connecticut Jim Latimer, U.S. EPA, National Health and Environmental Effects Research Laboratory Jane MacLellan, previously the U.S. Fish and Wildlife Service liaison to the EPA John Mullaney, USGS Connecticut Water Science Center Scott Nixon, Graduate School of Oceanography, University of Rhode Island Katie O’Brien-Clayton, Connecticut Department of Environmental Protection Chris Pickerell, Cornell Cooperative Extension Ron Rozsa, Connecticut Department of Environmental Protection Paul Stacey (CT DEP Project Manager), Connecticut Department of Environmental Protection Laura Stephenson, New York State Department of Environmental Conservation Kelly Streich, Connecticut Department of Environmental Protection Mark Tedesco, U.S. EPA Long Island Sound Office Jamie Vaudrey (Principal Investigator), Department of Marine Sciences, University of Connecticut Lisa Wahle, Connecticut Department of Environmental Protection Adam Whelchel, The Nature Conservancy, Connecticut Branch Harry Yamalis, Connecticut Department of Environmental Protection Charlie Yarish, Department of Marine Sciences, University of Connecticut Heather Young, New York State Department of Environmental Conservation

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Acknowledgements

J. Vaudrey would like to thank the many people who contributed data for the development of the case studies and databases: J. Kremer, UCONN; A. Banister, Pine Point School; J. Mullaney, USGS; M. Keser, J. Swenarton, et al., Millstone Environmental Lab; J. Latimer, U.S. EPA NHEERL; C. Yarish, UCONN; M. DiGiacomo-Cohen, CTDEP LISRC; R. Rozsa, CT DEP; A. Branco, UCONN; A. Desbonnet, RI Sea Grant; S. Nixon and R. Fulweiler, URI; F. Grimsey, “Save the River, Save the Hills.”

Advisory support was provided by all members of the technical advisory committee. However, additional thanks are due to Jim Kremer, Paul Stacey, Jim Latimer, Ron Rozsa, Mark Johnson, Charlie Yarish, John Mullaney, Mary DiGiacomo-Cohen, Milan Keser, Alan Desbonnet, Scott Nixon, and Stephen Granger for the ongoing conversations, insights and editorial reviews. Beth Doran, CT DEP LISRC, has provided technical assistance with the design of the website and was responsible for programming the on-line searchable database of articles.

Executive Summary

Eelgrass (Zostera marina) was once prevalent throughout the shallow coastal areas of Long Island Sound (LIS). The Atlantic-wide die off of the species in the 1930s resulted in the loss of eelgrass from much of the local area, but healthy populations were reestablished in the eastern portion of LIS by the 1950s. The recovery of eelgrass in the western Sound was less successful and today those populations have vanished. Since the 1950s, eelgrass populations along the Connecticut coast have suffered additional losses believed to be linked to the effect of nitrogen loading on the coastal ecosystem. The aim of this report was to summarize the literature regarding the factors affecting the growth and distribution of Z. marina relevant to Long Island Sound and identify levels for water quality standards and habitat guidelines that would be protective of Z. marina. Part II of this report presents the application of the water quality recommendations to three case study sites (Niantic River, Mumford Cove, Pawcatuck River / Little Narragansett Bay), including verification of the recommended habitat guidelines and a comparison of the nitrogen loads to various Connecticut estuaries.

The most important factor governing both the distribution and growth of Z. marina is the availability of light. The maximum depth of distribution is governed by the minimum amount of light required by Z. marina, which is about 22% of the surface light if measured as light in the water column. In addition to being attenuated by the water, light is also attenuated by particles in the water (phytoplankton, total suspended solids) and by epiphytes on the leaves. Measuring the light in the water column via Secchi depth or a light meter (light attenuation coefficient) accounts for the particles in the water. To account for the light attenuated by the epiphytes, direct measurements of the epiphytes are required or a model may be employed which relates water column characteristics to an estimate of epiphyte biomass. If the light attenuated by epiphytes is taken into account, the minimum light required by Z. marina should be around 15% of the surface light. Free-floating macroalgae may also shade Z. marina if it becomes abundant. In some New England estuaries, macroalgae has completely overgrown Z. marina to become the dominant primary producer.

The minimum depth is governed by the tidal range and the degree of wave action experienced in the area. Z. marina, in general, requires a depth greater than ½ the tidal amplitude in order to avoid exposure during low tide. For Long Island Sound, it appears an areal distribution including a vertical change of more than 1m is needed for a bed to flourish, if the shallow edge of the bed is at the minimum depth limit.

Temperature and nutrients may affect Z. marina indirectly or directly. Temperature and nutrients can affect light availability by stimulating or suppressing the growth rate of epiphytes, phytoplankton, or macroalgae. Nitrogen can directly affect Z. marina by stimulating productivity, if nitrogen is limiting. However, light is usually the limiting factor in LIS. When nitrogen availability is high, the N can cause the over utilization of carbon which should instead be stored for later use by the plant. Z. marina exhibits optimal temperature ranges for growth and photosynthesis. The water temperature affects the distribution, and the annual and seasonal variability within beds.

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While light is the main factor controlling eelgrass distribution and growth, with nutrients and temperature secondarily affecting the autoecology of Z. marina, other features of the habitat also determine whether eelgrass will successfully colonize a particular location. These features include physical aspects of the sites (tide, waves, current speed), sediment characteristics (percent organics, sediment sulfides), and water column characteristics (oxygen, salinity). Eelgrass exhibits a range of tolerance for each of these factors. For the physical factors, exceeding the range of tolerance results in a physical disturbance to the plant such as burial or uprooting. For the sediment and water column characteristics, exceeding the zone of tolerance typically results in a physiological response, such as a translocation of internal resources. The plant can deal with short term excursions outside the zone of tolerance, but extended periods of exposure to unfavorable conditions typically results in a degradation of plant tissue.

Restoration guidelines for submerged aquatic vegetation based on water quality and habitat-based requirements have been developed for the Chesapeake Bay region by evaluating decades of monitoring data, experimental evidence, statistical analyses of the data, and modeling efforts (Batiuk et al. 2000; Batiuk et al. 1992). These guidelines have been developed to include marine and freshwater submerged aquatic vegetation (SAV). For this report, the Chesapeake Bay guidelines for Z. marina were examined relative to a recent study looking at habitat requirements for Z. marina in Long Island Sound (Yarish et al. 2006) and data from the three case study sites presented in Part II of this report.

Table 1: Comparison of recommended habitat requirements for the growth and survival of eelgrass. Chesapeake Bay

GuidelinesGuidelines for LIS

(Yarish et al. 2006)Guidelines for LIS (Case Study Sites) Guideline Type

Minimum Light Requirement at the leaf surface (%) > 15 > 15 primary requirement

(must estimate epiphyte biomass)Water Column Light

Re < 22 < 22 subtitute for Min. Light Requirement (%) quirement at the Leaf Surface

Kd (1/m) < 1.5 < 0.7 < 0.7 provided for reference, use minimum light as the standard

Chlorophyll-a (µg / L) < 15 < 5.5 < 5.5 secondary requirement (diagnostic tool)

Dissolved Inorganic Nitrogen (mg/L) < 0.15 < 0.03 < 0.03 secondary requirement (diagnostic

tool)Dissolved Inorganic Phosphorus (mg/L) < 0.02 < 0.02 < 0.02 secondary requirement (diagnostic

tool)

Total Suspended Solids (mg/L) < 15 < 30 no data secondary requirement (diagnostic tool)

Sediment Organics (%) 0.4 to 12 3 to 5 0.4 to 10 habitat constraint

Vertical Distribution (m) Zmax = 0.5m + Zmin Zmax = 1m + Zmin Zmax = 1m + Zmin habitat constraint

Sediment Grain Size 0.4 - 30 % fines < 20% silt and clay no data habitat constraint

Sediment Sulfide Concentration (µM) < 1000 < 400 no data habitat constraint

Current Velocity (cm/s) 5 < X < 180 5 < X < 100 no data habitat constraint

Light in the water column was designated as the primary requirement, meaning it was the primary factor determining whether a particular location was suitable for Z. marina. The restoration guidelines were presented in terms of the percent light

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received by the plant, either at the leaf surface (which includes attenuation by the epiphytes) or through the water column (= traditional light attenuation coefficient of water). The secondary requirements (nutrients, chlorophyll-a, total suspended solids) affected the availability of light and may have directly affected the physiology of the plants. Both the primary and secondary requirements are water quality based metrics with the potential for change under management.

The factors listed as “habitat constraints” were related to the physical and sediment characteristics of the habitat. The physical factors (current velocity, minimum depth of distribution) helped to identify whether a certain area was suitable for eelgrass, but these factors were not likely to be changed due to mitigation efforts. The maximum depth of distribution, and thus the vertical distribution, could change as a result of changing water quality. The sediment characteristics should also change as a result of changes in the water quality or primary producer community. But these habitat constraints were used primarily as a means of explaining why Z. marina was not present in a location where the water quality appeared suitable.

Suggestions for future research included:

• Additional testing of the habitat requirements as they pertain to Long Island Sound

• Greater efforts at monitoring in sites with and without eelgrass, especially the small enclosed embayments most likely to experience the effects of eutrophication

• Collect additional historical datasets from other sites in LIS or other areas of New England with which to check the recommended guidelines.

• Test the algorithm used to estimate percent light received by the leaf surface which uses a model relating epiphyte biomass to Kd, DIN, DIP and TSS (Batiuk et al. 2000) for LIS.

• Develop habitat maps of coastal areas identifying suitable eelgrass habitat.

• Work with the USDA-NRCS to develop maps of sediment sulfides in nearshore regions.

• Use the tissue nutrient content of eelgrass and some macroalgae to characterize the nutrient status of estuaries.

• Deploy light meters to investigate the variability in the light environment.

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Subject Summaries and Overviews

A number of review papers addressing the issue of seagrass loss due to natural and human induced causes have been produced in the last few years (Duarte 2002; Orth et al. 2006a; Short and Neckles 1999; Short and Wyllie-Escheverria 1996). Four books relevant to seagrass have also been published: 2 literature compilations (Hemminga and Duarte 2000; Larkum et al. 2005), a methods book (Short et al. 2001), and a seagrass atlas (Green and Short 2003). The Connecticut Department of Environmental Protection (DEP) and Department of Agriculture (DA) produced a report assessing the impacts of commercial and recreational fishing activities on eelgrass in Connecticut’s waters, including recommendations for the management of the industry that would be protective of the eelgrass habitat (Johnson et al. 2007). The point of this review is not to duplicate those comprehensive works, but to highlight the information previously presented and supplement the cosmopolitan reviews with additional information from the literature, specific to Long Island Sound. A short summary of three of the most relevant reviews is provided in this section with the intent of leading readers to additional sources of information.

Orth et al. (2006a) and Duarte (2002) have both written comprehensive reviews which include an overview of what makes seagrass unique, the value of seagrass ecosystems, the threats to seagrass, and suggestions for future research and management to sustain and improve seagrass ecosystems. While both of these reviews pull information from a broad base of primary and grey literature and are presented to a scientific audience, they are written in such a manner as to be accessible to the informed non-scientist. These reviews provide an excellent overview of the key topics of concern to coastal scientists and managers with regards to seagrass. Short and Neckles (1999) reviewed the literature for physiological and distributional seagrass studies pertinent to factors likely to change as a result of global warming. While few of these studies were conducted to look at the effect of global warming on seagrass, this literature review extrapolates how seagrass productivity and distribution might change in response to a changing global climate.

In “A Global Crisis for Seagrass Ecosystems,” Orth et al. (2006a) start by briefly reviewing the evolutionary history of seagrasses, taxonomic diversity, and unique characteristics which allow seagrasses to exist as vascular plants living fully submerged in water. The authors note that while seagrass distribution has shifted over evolutionary time scales, the rapid changes currently occurring as a result of human induced pressures far outweighs historical changes. Orth et al. (2006a) liken seagrass to “coastal canaries”, with the implication that loss of seagrass signals important loss of ecosystem services. These services include: carbon sequestration, reducing current speed thus trapping and storing sediment and nutrients, greater biodiversity, nursery grounds, facilitating trophic transfers, and cross-habitat utilization by fauna. A key point for managing seagrass population and nutrient input from the watershed is that seagrasses integrate impacts “over measurable and definable timescales.” A number of examples are cited where the response of seagrasses were used to assess the management actions undertaken in the watersheds.

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Orth et al. (2006a) identify multiple stressors involved with the decline of seagrass (change in global climate, shifts in water quality, increases in sediment and nutrient loads, and direct influence of other organisms) but point out that little has been done to look at the interaction of multiple stressors on seagrass decline. They also identify two emerging threats to seagrass: invasive species and the proliferation of fish farming and other aquaculture activities. The authors conclude the paper by addressing the issues of monitoring, management, restoration, conservation, and increasing public awareness.

“Seagrass loss is usually the symptom of a larger problem. To effectively reverse the decline of seagrasses, conservation plans must first identify and resolve the problems at a scale that includes the interconnectivity of coastal systems and the mechanisms affecting the declines and gains (e.g., water quality, land use practices). Once this is done, restoration efforts should be balanced against the capacity of seagrasses to recover naturally.”

In “The Future of Seagrass Meadows,” Duarte (2002) provides a review of the literature with the goal of forecasting the status of seagrass ecosystems over the period of 2002 to 2025. The review focuses not only on the effect of climate change, but also on the responses of seagrass ecosystems to the pressures of an increasing human population. An overview of seagrass evolution and diversity is provided, including basic environmental requirements (light level, salinity range, sediment type, organic content, redox potential, etc.). A summary of productivity and organic matter storage capacity is provided, an area of expertise for Dr. Duarte. The environmental forcing factors that lead to disturbances and interannual or long-term variability in biomass and areal coverage are highlighted, with an emphasis on the effect of human impacts on seagrass ecosystems. Physical impacts are an “unambiguous” human impact, ranging in the size of effect from small boat moorings to changing flow patterns from the installation of port infrastructure or sand-retaining beach groynes.

Another major pressure on seagrass reviewed by Duarte (2002) was the cultural eutrophication of coastal waters. Increasing nutrients in the water column do very little to stimulate seagrass productivity, but macroalgae and phytoplankton were well-suited to take advantage of the increased nutrient supply. The increased productivity by these other primary producers reduces the light received by the seagrass, reducing the productivity of seagrass. Other factors covered include: light environment, sediment environment, siltation, circulation, pollution, and biodiversity and invasive species. Duarte (2002) states that,

“Direct or indirect human intervention locally causes most impacts. However, at the regional or global scale, human activity also exerts an important impact on seagrass ecosystems. These effects are remarkably difficult to separate from responses to background natural changes in the highly dynamic coastal ecosystem. These impacts involve the effects of the realized and predicted climate change, and result from changes in sea level, water temperature, UV irradiance, and CO2 concentration”

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Duarte (2002) details future threats to seagrass, all of which are related to an increasing human population: increases in nutrient loads to coastal waters, even with improving wastewater treatment; increased physical disturbance to seagrass meadows due to increased use of coastal waters; increases in coastal aquaculture; and changes in seagrass productivity and coverage due to human induced global climate changes. Loss of seagrass from an ecosystem has resulted in sediment resuspension, decrease in biodiversity, and modification of foodwebs which can result in the loss of harvestable organisms. The recent decadal trend for seagrasses has been one of steady loss of seagrass areal coverage. The partial recovery of seagrass in the North Atlantic following the wasting disease related die-off in the 1930s indicates that re-establishment of seagrass populations is possible if environmental conditions are suitable, however the causes for the present seagrass decline are only predicted to worsen.

To manage and respond to threats to current seagrass ecosystems effectively, more knowledge of these ecosystems is required. One aspect highlighted by Duarte (2002) is the need for increased monitoring and an early indicator of decline. Management of the pressures on seagrass are also critical. Mechanical disturbance is the most easily managed as it is a direct effect and the source is easily identifiable. Management of the indirect effects, such as nutrient input from the watershed, are harder to implement and must be coupled with an increase in public awareness of the nature and value of seagrass ecosystems and the effect of land-use practices on coastal waters.

In “The effects of global climate change on seagrasses,” Short and Neckles (1999) apply the current knowledge of seagrass biology and how various taxa respond to the environment to the question of how global warming will affect seagrass distribution and productivity in the next century. For Z. marina, the environmental forcing factors affecting distribution and productivity are likely to be: increasing temperature, rising sea level, and increasing CO2 concentrations in the water. Each of these forcing factors have multiple affects on Z. marina and may act in a variety of ways, depending on the location of the interaction and the status of the ecosystem (eutrophic vs. less-impacted systems).

In Z. marina, as temperature increases, the respiration rate of the leaves increases faster than the photosynthetic rate, causing a decrease in the photosynthesis-to-respiration ratio (P:R). Thus, Z. marina has a seasonal growth optimum and exhibits decreased productivity above this optimum. Increasing temperatures also stimulate the growth of epiphytes on the leaves, reducing the light received by the plants. The overall effect of increasing temperature on Z. marina is predicted to be detrimental.

Rising sea level will change the amount of light received by Z. marina, as the light will be traveling through more water and light is attenuated at an exponential rate through the water column. This may limit the amount of photosynthesis in the existing beds. In this way, the change in water depth has the potential to cause a shift in the habitat location for Z. marina. Plants currently living at their maximum depth distribution (generally determined by the light they received), will die. Plants prohibited from moving shoreward by the minimum depth requirement may be able to colonize into previously shallower areas, though this may be hampered by human modification of the shoreline and use of shallow areas. The tidal range and current speeds may also change

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in response to rising sea level. The tidal range (= mean high water – mean low water) determines the minimum depth to which eelgrass can colonize, as the plant is usually restricted to areas where it is protected from exposure at low tide (see section on “Minimum Depth Limit,” page 15, for a discussion of this topic). Increased tidal range will prohibit the movement of plants into previously shallower areas, negating the possible benefit of opening of new habitat areas at the shallower limit of seagrass distribution. The effects of increasing current speed will depend on the local system. In some areas, beds may be eroded while in other depositional areas, new habitat for Z. marina may be created. Greater circulation and high current velocities may re-suspend sediments, increasing turbidity, and reducing light available to the plants. Alternatively, increased circulation may flush seagrass beds overgrown with macroalgae, improving the status of the beds. The effects of rising sea level essentially relates back to changes in available light to the seagrass, thus any of these negative effects will be exacerbated in environments with higher turbidity levels.

The last effect of increasing sea level rise is unrelated to light, but does open up new habitat for Z. marina: the intrusion of saline water into previously brackish or freshwater areas. This could cause a shift in the community in freshwater areas to an estuarine environment. The negative to this point is that wasting disease, Labyrinthula zosterae Porter et Muehlstein, is suppressed by low salinity water. An elevation of salinity in the estuarine environment removes a low salinity haven for Z. marina when recovering from the effects of the wasting disease.

At the time the report was released, no longer-term studies of the affect of CO2 increases on seagrass productivity were available, but a short-term lab experiment (45d) showed CO2 enrichment resulted in a positive photosynthetic response, and the plants required only half the light of plants grown in unenriched water. Thus, an increase in CO2 may offset a reduction in available light brought about by rising sea level. However, if epiphytic algae also respond positively to increase in CO2, then a more rapid decline of Z. marina may be expected.

Applying Short and Neckles’ (1999) predictions to Z. marina in Long Island Sound, the overall effect of global warming is likely to cause a reduction of the Z. marina areal distribution and photosynthetic productivity. Increasing temperature and CO2 are both likely to stimulate epiphyte production. Coupled with increasing water depth, light available to the plants will be reduced and the maximum distribution depth will be reduced. Increasing CO2 in the water might help offset reduced photosynthetic productivity caused by reduced available light. Salinity intrusions into riverine areas may open new habitat for eelgrass, assuming nutrient levels in those areas are low enough to favor Z. marina over macroalgae or phytoplankton.

Lee et al. (2007) have written a review paper on the effects of light, temperature, and nutrients on seagrass growth covering a broad range of seagrass species. Their review covers similar topics presented in this report, with more emphasis on the physiological side of the seagrass response and many examples beyond Z. marina, providing an additional resource for information on these topics. In the same volume of the Journal of Experimental Marine Biology and Ecology (a special issue on the biology

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and ecology of seagrasses), Burkholder et al. (2007) presented an excellent overview on the effect of eutrophication on seagrass populations. Many of the topics presented in this report are addressed in that review, with worldwide coverage of seagrass species.

Historical Distribution and Long-Term Decline

Three reports have extensively documented the historic distribution of eelgrass in Long Island Sound using published literature, reports, herbarium voucher specimens, unpublished data, and anecdotal comments (Johnson et al. 2007; Rozsa 1994; Yarish et al. 2006). The two reports published in recent years also included information from the 2002 CT DEP / USFWS aerial surveys of the current eelgrass coverage (Johnson et al. 2007; Tiner et al. 2003; Tiner et al. 2007; Yarish et al. 2006). The CT DEP / USFWS conducted a second aerial survey of eelgrass in 2006, with the plan of continuing the aerial surveys every 2 years as a long-term monitoring effort (Tiner et al. 2007). All five of these reports are available on the website (http://www.lisrc.uconn.edu/ eelgrass/index.htm). A database of historical and current eelgrass locations is also available in GIS format and as an excel database.

For a detailed description of the historical distribution of Zostera marina in Long Island Sound, refer to the reports available on the website. Z. marina was common throughout the sound, within appropriate habitats, prior to 1930. By the summer of 1931, most of the Z. marina ranging from North Carolina to New England and in much of the Atlantic had been wiped out by the wasting disease. Only an estimated 1% of the population remained, mostly found in the low salinity waters of upper estuarine areas (Cottam 1933). The eastern portion of Long Island Sound experienced a recovery by the 1950s, while the western Long Island Sound recovery was spotty and eventually failed (see references cited in: Johnson et al. 2007; Rozsa 1994; Yarish et al. 2006). In the 1980s, Clinton Harbor was the western-most location with Z. marina. As of 2006, a small patch of eelgrass still existed in the bight between Clinton Harbor and Westbrook Harbor associated with the Duck Island breakwater (Tiner et al. 2007). Beyond that small patch, eelgrass beds are mostly found from Rocky Neck State Park east to the Rhode Island border (Tiner et al. 2007). Since the 1980s, Z. marina has been disappearing from the embayments of Long Island Sound (Johnson et al. 2007). However, some moderate increases have been seen between the 2002 and 2006 aerial surveys southwest of Quiambog Cove, around Mason Island and Ram Island, in upper Stonington Harbor, and especially in Niantic River (Tiner et al. 2007).

In the late 1980s, Z. marina was still abundant in Little Narragansett Bay (Dillingham et al. 1992) and generally absent from Mumford Cove (Vaudrey et al. 2007). By the 2006 aerial survey, the opposite trend was seen, with eelgrass flourishing in Mumford Cove and absent from Little Narragansett Bay (Tiner et al. 2007; Vaudrey et al. 2007). Niantic River eelgrass was flourishing in the 1970s, declined significantly in the 1980s, was nearly absent in 1988 (Short 1988), and has fluctuated since that time period without attaining a truly lush population similar to the 1970s for multiple years (Keser et al. 2003).

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Specific Factors Affecting Zostera marina

While many factors affect the productivity and success of Z. marina, the three factors exhibiting the greatest control are light, temperature, and nutrients (Dennison et al. 1993; Lee et al. 2007). These three factors interact to create the environment experienced by the seagrass, determining the overall productivity.

Light is generally limiting, as Z. marina requires high light levels. This requirement limits the depth distribution of Z. marina (Depth, page 13). Phytoplankton and suspended solids in the water column attenuate the light, further reducing the amount available to Z. marina (Total Suspended Solids, page 17). Epiphytes on eelgrass leaves and shading by macroalgae can also intercept light before it is received by the plants (Epiphytes, page 17). In areas with consistent water quality problems, these interactions will limit the habitat area suitable for the growth of Z. marina.

Z. marina exhibits an optimal temperature range for growth with a worldwide average of 15.3ºC ± 1.6ºC and 23.3ºC ± 2.5ºC for photosynthesis, respectively (Lee et al. 2007). The actual range varies by location and the environment experienced by the population. High summer temperatures may inhibit growth and possibly photosynthesis. In the shallow sub-embayments of Long Island Sound, summer temperatures may be detrimental to the success of eelgrass (Temperature, page 19).

Nutrients, nitrogen (N) and phosphorous (P), as well as inorganic carbon (C), are required for growth of Z. marina. Nitrogen is generally considered the limiting nutrient in temperate estuaries, but with access to the sediment nutrient pool, nutrients are not often considered to be a limiting factor for seagrass growth. Research in this area shows there are times when C, N, or P may be limiting to Z. marina in temperate estuaries, under certain situations (Lee et al. 2007). However, the concern with nutrients usually centers around what happens when Z. marina is in an enriched environment. Under these circumstances, macroalgae, epiphytes, and phytoplankton growth are stimulated; increasing competition with seagrass for light. One theory suggest that at extremely high NO3

- levels, Z. marina populations may also decline due to direct physiological effects unrelated to a decrease in available light (Burkholder et al. 1992; Touchette and Burkholder 2007).

LIGHT

Light is generally recognized as the most important factor limiting Z. marina productivity. Z. marina has a high light requirement relative to macroalgae and phytoplankton (Dennison et al. 1993; Duarte 1995; Hauxwell et al. 2003; Lee et al. 2007; Longstaff and Dennison 1999; Moore and Wetzel 2000). Z. marina is typically cited as requiring a minimum of around 11% surface irradiance (Duarte 1991; Short et al. 1993). Macroalgae requires much less light to thrive, ranging from 0.12% of surface irradiance for thicker species to <0.003% for thin macroalgae (Markager and Sand-Jensen 1992). While the 11% light limit for seagrass growth is used as a guideline for seagrasses, it has also been recognized that this value will vary with location, species, and population of

9

seagrass. For Z. marina, a cosmopolitan literature review of minimum light requirements shows values ranging from 4% to 44% of surface irradiance (table 2). Values from the east coast of the United States range between 15% and 35% of surface irradiance, with studies specific to Long Island Sound and Massachusetts also falling in this same range (Dennison and Alberte 1985; Koch and Beer 1996; Moore 1991).

Table 2: Descriptions of Habitat Requirements for Zostera marina.

The success of Z. marina is related not only to the percent of light it receives from the surface at any given instant, but also the cumulative amount over a day (figure 1). Dennison and Alberte (1985) performed an in situ experiment in Great Harbor, Woods Hole, MA where they manipulated the light intensity and the photoperiod of light reaching beds of Z. marina. They concluded that growth and biomass in the eelgrass growing at the deeper end of its range was primarily controlled by the total light reaching the plot, versus other environmental conditions. They state that it is the daily light period for light at saturating levels (Hsat) which is most important in determining the

10

productivity of plants growing at the edge of their distribution rather than the absolute light intensity. They suggested a minimum Hsat of 6 hours for eelgrass survival, with 10 hours used as an indicator for sufficient light for successful eelgrass growth. This estimate of 10 hours is consistent with the Hsat determined for Long Island Sound of 12.5 hours (Koch and Beer 1996) and 10.5 hours for San Francisco Bay (Zimmerman et al. 1995).

Figure 1: Identifying critical levels of photon flux densities. Hcomp is the period of time where PAR is great enough to allow photosynthesis to balance or exceed respiration. Hsat is the period of time where light is at saturating levels and photosynthesis is maximized, causing net carbon assimilation in the primary producer (from Dennison 1987).

In New England as in most estuaries, phytoplankton and macroalgae are typically nitrogen limited. However, N limitation of eelgrass is probably rare in nature. Values of N needed to saturate eelgrass growth based on a computer model were well below what was typically found in situ (Zimmerman et al. 1987). Both phytoplankton and macroalgae have higher uptake rates of dissolved inorganic nitrogen and faster growth rates than seagrass. Thus the requirement of high light for seagrass also necessitates low nutrients in the water, or phytoplankton and macroalgae are able to thrive and shade the seagrass (Duarte 1995; Harlin and Thorne-Miller 1981; Moore and Wetzel 2000; Short and Burdick 1996; Taylor et al. 1999; Zimmerman et al. 1987) . As one example, nitrogen loading to Waquoit Bay contributed to the decline of eelgrass by promoting the growth of macroalgae, epiphytes, and phytoplankton which had a combined shading effect on new and established shoots of eelgrass (Hauxwell et al. 2003). Similar results were seen in a 3-year mesocosm study conducted at the Jackson Estuarine Laboratory in New Hampshire (Short et al. 1995). These observations on the physiology of different groups of primary producers coupled with empirical evidence from seagrass ecosystems has led to a model relating the nitrogen loading rate from the watershed to the percent contribution to primary production by the three main groups of primary producers found in shallow estuaries: seagrass, macroalgae, and phytoplankton (figure 2).

11

Figure 2: N loading rate per hectare of estuarine surface area versus percent primary production by the three dominant communities. According to one theory, seagrass will dominate at low nutrient loads from the watershed. As nutrient loading increases, macroalgae will receive enough nitrogen to grow at optimal rates and begin to shade seagrass. At the highest loads, phytoplankton, with a faster nitrogen uptake rate than macroalgae, will outcompete the macroalgae for nitrogen and shade the macroalgae. The S (Sage Lot Pond), Q (Quashnet River), and C (Child’s River) at the top of the figure indicate the N loading rate and primary producer status in three estuaries in Waquoit Bay, MA. (figure 3 from Valiela et al. 1997)

While this simple model relating nitrogen loading rate to the primary producers present in the system has a plausible physiological basis and fits some real world cases, it has not been widely tested or confirmed, and the critical value of nitrogen loading, the point where a system is likely to switch from seagrass to macroalgae dominated, is still uncertain. The residence time of the ecosystem also changes the relative importance of the contributions of these groups of primary producers. For example, when residence time is long, phytoplankton may be more likely to dominate the system at an earlier point and the macroalgae curve will follow the shape of the seagrass curve. This is because phytoplankton are less likely to be washed out of the estuary, allowing them time build up a larger population in the estuary (Valiela et al. 1997).

The model presented in figure 2 assumes a bottom-up control of community structure, where the light and nutrient availability control which group of primary producers are present. In mesocosm experiments of nutrient enrichment, replicates of nutrient enriched seagrass system were eventually dominated by phytoplankton, macroalgae, or epiphytes (Short et al. 1995; Taylor et al. 1999). The presence of animals in these mesocosms reflected a real world situation where top-down control of trophic levels may have influenced which group of primary producers dominated the community once the light quantity had been reduced to a point where eelgrass was no longer competitive. In fact, the presence of certain fish, herbivores, or filter-feeding bivalves in the environment may sustain eelgrass populations in a nutrient rich environment by grazing on macroalgae, phytoplankton, and epiphytes (Heck Jr and Valentine 2007; Moore and Wetzel 2000).

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Z. marina exhibits responses to light similar to the response of some terrestrial plants exposed to sun versus shade: plants in higher light environments exhibit higher photosynthetic and respiratory rates, higher chl a : chl b ratios, and less chlorophyll / leaf area relative to deeper populations (Dennison and Alberte 1982; Lee et al. 2007). The ratio of chl a : chl b might decrease in plants from the deeper edge of the bed or in reduced light conditions as wavelengths absorbed by chl a are attenuated more rapidly in the water column than those absorbed by chl b. Shoot density and total biomass also tend to decrease, possibly an acclimation response to prevent self-shading. Under reduced light, eelgrass may improve photosynthetic performance by increasing pigment content in the leaves and increasing leaf area per unit leaf biomass. (Lee et al. 2007). Leaf turnover times and leaf production rates were greater under higher light environments and these characteristics proved to be more responsive to the light environment than other photosynthetic characteristics (Dennison and Alberte 1982).

Depth

The distribution of biomass, shoot density and shoot weight are typically related to increasing depth (Duarte 1991), as illustrated by Krause-Jensen et al. (2000) who analyzed a data set of 1200 samples of eelgrass using boundary functions (figure 3). In this approach, instead of modeling the relationship between the average value of a set of data and a forcing factor, the boundary (max values, 90th percentiles, etc.) is modeled. This approach can only be applied to large data sets, but has the benefit of the ability of describing the major limiting resource and revealing structure in the data that may be masked when evaluating the average values. The biomass and percent coverage followed the expected bell-shaped curve with depth, with greater values found at intermediate depths and lower values found at the extremes of the distribution. The shoot density declined with depth in an exponential fashion, as would be expected if light were the controlling factor. This reduces self-shading among plants. The light climate at depth was further enhanced by the plants by increasing the length and width of leaves, as evidenced by the average shoot weight with depth (Duarte 1991; Krause-Jensen et al. 2000).

Maximum Depth Limit As mentioned previously, the maximum depth limit of seagrass beds is related to

the minimum light requirement over an average 24 hour cycle. Seagrasses are capable of storing carbohydrates in leaves and rhizomes, and rely on these internal reserves to supplement the metabolic demand on days when the light received by the plant is not adequate to support photosynthesis equal to respiratory demands (Burke et al. 1996; Cabello-Pasini et al. 2002; Zimmerman et al. 1987) . The Hcomp value or minimum requirement for % of surface irradiance has been used to predict the maximum depth of eelgrass distribution. Methods for estimating the maximum depth of an eelgrass bed from light in the water column have not changed greatly in recent years. The maximum depth is estimated from an assumed minimum light requirement plus an estimate of water

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Figure 3: Patterns in seagrass bed characteristics with depth. Shoot density (Aa), biomass (Bb), shoot weight (Cc) and cover (Dd) of eelgrass as functions of water depth in Øresund, Denmark. Left panels: all individual observations (open circles) and 90th percentiles of the grouped observations (filled circles). Right panels: Modeled fits of maxima (solid line), 90th percentiles (broken line) and all data (dotted line). (figure 3 from Krause-Jensen et al. 2000)

clarity, using either a Secchi disc depth or a light extinction coefficient (Kd) from light profiles. Attempts have been made to further refine these estimates by adding in other predictors such as nutrient concentrations, but success with these models has been limited (Greve and Krause-Jensen 2005). A few of the standard options for estimating the maximum depth limit for eelgrass are explained below.

SECCHI DEPTH The maximum depth limit for eelgrass in the Woods Hole area was roughly

equivalent to the annual average secchi depth (secchi depth is typically equal to the depth where light intensity is ~10% of surface irradiance) (Dennison 1987).

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LIGHT EXTINCTION COEFFICIENT Duarte (1991) developed a model of seagrass depth limits applicable to a variety

of species based on a search of the literature. This relationship described the maximum depth of the bed (Zc) in terms of the light extinction coefficient (Kd) of the water:

log Zc (m) = 0.26 – 1.07 log Kd (m-1) (equation 1)

which was simplified to (Duarte 1991):

Zc = 1.86 / Kd. (equation 2)

Duarte et al. (2007) recently evaluated the predictive power of the 1991 equation for seagrass depth limits, as well as a number of other predictive equations, using seagrass depth distribution data from the literature. They found that the 1991 equation overestimated the actual depth of colonization in shallow turbid waters. Two new equations were developed, one for turbid waters and one for clear waters, with the division between the two groups set at a Kd of 0.27 m-1. For Long Island Sound, the appropriate equation would be:

log Zc (m) = 0.10 – 1.02 log Kd (m-1) (equation 3)

Chesapeake Bay guidelines (Batiuk et al. 2000) use the Lambert-Beer equation for light extinction in water and apply a minimum water column light requirement of >22% for eelgrass areas:

d

0

Z

max KIIln

Z⎟⎟⎠

⎞⎜⎜⎝

⎛−

=( ) →

dmax K

0.22ln−= → Zmax = 1.514 / Kd Z

A model similar to Duarte’s statistically derived results (equation 3) is obtained from the Chesapeake Bay formulation if a 28% minimum water column light requirement is used for eelgrass.

Minimum Depth Limit While much focus has centered on the maximum depth limit for eelgrass, a

minimum depth limit is also imposed in many locations by the tides. In Long Island Sound, all eelgrass is subtidal. Intertidal populations do appear in Massachusetts (www.buzzardsbay.org/eelgrass-gis-data.htm 2008), New Hampshire, and Maine (Rivers and Short 2007), but these are areas where eelgrass plants are protected in some way from dessication. The minimum depth of distribution based on the tides can be defined as equal to one half the tidal amplitude (Koch 2001). In Long Island Sound, an area with semi-diurnal tides, this is calculated as

Zmin = (mean higher high water - mean lower low water) / 2.

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The western end of Long Island Sound has a higher tidal amplitude (2-3.5m) than the eastern end (0-1m), which directly affects the possible minimum depth distribution of eelgrass, regardless of water quality and light availability (Koch and Beer 1996).

Koch and Beer (1996) conducted a study in Long Island Sound modeling potential distribution of eelgrass based on measurements of light extinction coefficients and photosynthetic measurements of eelgrass from LIS. Their work revealed that for beds occurring at the minimum depth limit, a successful bed needed to extend to a depth at least 1m greater than the shallow edge of the bed (figure 4). This provides a buffer for the shallower edge of the bed against the damaging effect of winter storms and exposure during extreme tides. This suggestion was based on the observation that just west of Clinton Harbor, the western-most location with eelgrass present at the time of their study, the area of bottom available for colonization increased to a potential vertical range of 1.5 to 2m. Their suggestion was that eelgrass requires a vertical range encompassing a change of more than 1m in depth in order to colonize the area (Zmax ≥ 1m + Zmin). In Chesapeake Bay, where a mix of submerged aquatic vegetation species are included in the management plan, this relationship has been included but the vertical depth of possible distribution is smaller, Zmax ≥ 0.5m + Zmin (Batiuk et al. 2000).

While light is typically considered to be the factor determining the depth limit of seagrasses, Zieman and Wetzel (1980) mention another constraint on depth distributions. Historically, it has been noted that seagrasses are not usually found past 10m in depth. This depth distribution has been attributed to the high light requirements of seagrass. A review of a number of studies lead Zieman and Wetzel to suggest that this limitation may be due to hydrostatic pressure, in addition to the limiting effects of low light levels (Zieman and Wetzel 1980).

Figure 4: Vertical distribution of eelgrass in Long Island Sound based on the tidal range and light attenuation coefficients (Kd). Solid circles (SLW) indicate the spring low water level representing the shallowest depths of Z. marina. Triangles (Zg) indicate the depth at which the minimum light required for growth of eelgrass in LIS is available at solar noon (assuming mean tide coincides with solar noon). Squares represent the present limit of eelgrass distribution. Dashed line indicates depth to which eelgrass could occur if Kd was 0.5 m-1 throughout Long Island Sound (tidal range not taken into account). (figure 3 from Koch and Beer 1996)

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Total Suspended Solids (turbidity)

Sustained reductions in light availability due to increases in turbidity can be detrimental to eelgrass populations. As turbidity increases, less light is available to the eelgrass plants, eelgrass plants die thus reducing the colonized area, sediments become less stable and resuspension of sediments are more likely without the presence of the root-rhizome system, and turbidity increases in a positive feedback loop. During periods of increased turbidity (e.g. storm events, anthropogenically caused turbidity pulses), the plants rely on internal carbohydrate stores to carry them through periods of light limitation, first accessing carbohydrates stored in the leaves then accessing the stock stored in the rhizomes (Burke et al. 1996; Cabello-Pasini et al. 2002; Moore et al. 1997; Ralph et al. 2007). Periods of light limitation longer than 3 weeks have led to elimination of eelgrass from areas (Cabello-Pasini et al. 2002; Moore et al. 1997). As the carbohydrates stored in the plant are exhausted and translocation of stock from neighboring plants is no longer an option, the leaves begin to disintegrate and are eventually broken off through the physical movement of the water. Recolonization of these areas via seedlings is likely to be an important mechanism as vegetative reproduction is slow and the rhizome complex has been damaged by the demand placed on the carbohydrate reserves (Cabello-Pasini et al. 2002).

While the length of a turbidity event is important, the timing is also key to whether eelgrass is able to survive. Reductions in light availability during the spring time may have the greatest effect on the survival of the plants (Burke et al. 1996; Moore et al. 1997; Ralph et al. 2007). Moore et al. (1996) saw a large drop in shoot growth of Z. marina in the York River, U.S.A. in April, when plant growth rates were at their annual maximum. This drop coincided with a period of high suspended load and reduced light. Reduction in total daily light availability in June has been observed to lead to complete loss of Z. marina plants by the end of the summer (Moore et al. 1996). While other stressors may play a role in this decline, light is believed to play a key role in the success of Z. marina. It appears that single events can have a great impact on the success of seagrasses, if these events occur during critical growth periods.

Moore and Wetzel (2000) followed up earlier observations in the York River by conducting mesocosm experiments. A major benefit in the mesocosm versus in situ experiments was the ability to control and define the variables which may impact seagrass growth (light levels, temperature, current velocity, sediment types, etc.) Moore and Wetzel (2000) investigated the response of Z. marina to different levels of nutrients and light availability. They found that light was the principal limiting factor to growth of seagrasses in moderately nutrient enriched regions of the bay. This was a direct result of the fact that nutrient enrichment can promote phytoplankton growth, which in turn increased the turbidity of the water, thus cutting down on the available light for seagrasses. In addition, the runoff of sediments and dissolved substances commonly associated with increased nutrient supply to an estuary also increased the turbidity levels.

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Epiphytes

Interactions between epiphytes (microalgae and macroalgae colonizing seagrass), eelgrass, and epiphyte grazers are complex and not easily predicted. Epiphyte biomass is controlled by light, nutrient availability, grazers, and hydrodynamic conditions. The epiphytes interact with the seagrasses by competing for light and nutrients from the water column, but can also provide benefits in the form of increased nutrient regeneration as the epiphytes are grazed and feces from the grazers are deposited to the sediments (Borowitzka et al. 2005; Van Montfrans et al. 1984). Epiphytes can account for 1 to 36% of the above-ground biomass in a Z. marina bed (Borowitzka et al. 2005) and equal 17-18% of the total primary production of the bed (Van Montfrans et al. 1984).

Significant losses of aquatic vascular plants from nearshore sites have often been attributed to anthropogenic inputs of suspended particulate matter, dissolved nutrients, or both (Moore et al. 1996). The eutrophication of coastal systems limits the potential for growth in seagrasses by promoting algal blooms which shade the plants and by promoting excessive epiphytic and filamentous algal overgrowths which limit the light and carbon available to the plant for photosynthesis (Moore et al. 1996; Stevenson et al. 1993). However, Moore et al. (1996) observed that epiphytic biomass was not higher in the fall, when nutrient inputs to the York River were at their highest. This indicates that factors other than nutrient supply limited epiphyte net accumulation in the fall. Possible culprits were invertebrate grazers or temperature.

While epiphytes do have the potential to grow and shade seagrass in response to increasing nutrient loads, the presence of epiphyte grazers could moderate this effect or in some cases reduce the level of epiphytes present (Moore and Wetzel 2000; Neckles et al. 1993). This moderating effect by epiphyte grazers has been observed in a number of mesocosm studies (Borowitzka et al. 2005; Short et al. 1995; Taylor et al. 1995). In the mesocosms, increased nutrient loading led to increased epiphyte load on seagrass leaves. In some cases, the epiphytes shaded the seagrass and became the dominant primary producers. In other cases, grazers kept the epiphyte population under control and other primary producers dominated (Short et al. 1995).

In an example from the Waquoit Bay system, epiphytes were found in greater abundance on Z. marina leaves from the estuaries experiencing the greatest nutrient loads. The epiphyte biomass was greatest during the late summer, fall, and winter when plastochrone intervals (the length of time between the production of a new leaf) were longest, as the epiphytes had a greater amount of time to colonize the leaf and grow (Hauxwell et al. 2003). From March to June, epiphyte biomass, and its effect on light attenuation, was relatively low with <30% of light received at the leaf attenuated by epiphytes (see figure in Hauxwell et al. 2003). From August to December, light levels were often below saturating levels for photosynthesis, but only in one site did they fall below the compensation irradiance for photosynthesis (see figure in Hauxwell et al. 2003). In these sites, epiphyte grazers were not successful at keeping the epiphytes completely in check, but the epiphyte biomass did not overwhelm the eelgrass populations.

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The revised Chesapeake Bay guidelines for habitat based requirements now include an algorithm for determining the amount of light attenuated by epiphytes on the seagrass leaves (Batiuk et al. 2000). Clearly, the role this group of organisms plays in the seagrass system is large. The questions arising now are determining and/or predicting the relative importance of epiphyte grazers.

TEMPERATURE

Z. marina exhibits optimal growth at an intermediate temperature in its range of tolerance. This leads to a bimodal growth pattern during the growing season, with optimal growth in the spring and fall and inhibition in the warm summer months (Bintz et al. 2003; Moore et al. 1996; Olesen and Sand-Jensen 1993). In northern latitudes, a unimodal pattern may be observed, if the warmest summer temperatures remain in the optimal region for growth, usually 15ºC to 20ºC (Lee et al. 2007). During the winter, production is almost nonexistent for Zostera marina. The extent to which the plants go dormant depends on their location. Warmer zones will have a shorter period of dormancy, and in some cases a period of dormancy may be absent. Moore and Wetzel’s (2000) mesocosm experiments documented this seasonal variability in production. Shoot growth decreased over time both during the summer, when ambient temperatures rose above the optimal range of 15-17ºC for this area, and towards the end of the fall season, when ambient temperatures dropped below the optimal temperature range.

The optimum temperature for photosynthesis varies with light availability (16ºC to 30ºC) (Lee et al. 2007). Above the optimal range, eelgrass exhibits decreased productivity (typically in mid-summer) (Moore et al. 1996; Short and Neckles 1999). As light levels decrease, the optimal range of temperature for photosynthesis also decreases. This implies that low light levels during the warm summer months are especially stressful to the plants. Respiration and photosynthesis both increase as temperature increases, but respiration increases more for a given increase in temperature, potentially adding to the summertime stress on the plant (Dennison 1987; Lee et al. 2007).

While the optimal temperature range is affected by the light availability, the metabolic rate of the plant should be similar under varying temperatures, once the plants have acclimated (Zimmerman et al. 1989). Seasonal temperature changes alone are unlikely to effect the light saturation coefficient (Hsat) for photosynthesis. The mid-summer mortality experienced by some populations were likely due to a thermally induced disruption of metabolism, a critical thermal level was exceeded.

The optimal temperature range can also vary between populations of the same species. For example, Zostera marina from Alaska was able to tolerate being frozen in ice at –6ºC for 12 hours. Plants from Washington and California were unable to tolerate this stress. On the high end, Zostera marina in Florida showed an optimum temperature for photosynthesis at 29ºC, with a lethal limit of 33-34ºC, if maintained for a period of time. (McRoy and McMillan, 1977) In comparison, Thalassia testudinum can tolerate temperatures of 20ºC to 36ºC, with an optimum range of 28ºC to 30ºC. (Zieman and Wetzel, 1980) Zostera marina shows a wider tolerance for temperatures than Thalassia

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testudinum, but is more competitive in cooler temperatures, as evidenced by their respective distributions.

NUTRIENT AVAILABILITY

Excess nitrogen introduced to a system can affect eelgrass by stimulating production of competitors for light or it can act synergistically with other factors to exacerbate the effect (temperature, light, type of nutrient available, etc.). This section will present a few examples of these interacting effects, then focus on carbohydrate and nitrogen separately.

Example 1 – Nitrogen Loads Nitrogen loading to Waquoit Bay contributed to the decline of eelgrass (figure 5)

by promoting the growth of macroalgae, epiphytes, and phytoplankton which had a combined shading effect on new and established shoots of eelgrass (Hauxwell et al. 2003). Nutrient loads which appear to be protective of eelgrass in Waquoit Bay are in the range of <28 to 63 kg N ha-1 y-1 (Hauxwell et al. 2003).

Figure 5: Change in spatial location and patch size of Z. marina distribution in Waquoit Bay in response to nutrient enrichment. Black areas are eelgrass coverage of near 100%. Diagonal lines are patchy coverage. Dotted areas were unknown. (figure 12 from Valiela et al. 1992)

Example 2 – Light and Nitrogen Loads The direct effect of nutrient loading to eelgrass mesocosms was a stimulation of

macroalgae, phytoplankton, and epiphytes. These various forms of algae competed with the eelgrass for light and eelgrass growth was seen to decrease in a linear fashion with reduced light. When plants were simply shaded, leaf length increased. When nutrient levels were increased, leaf lengths were shorter, suggesting nutrient loading has a negative impact on leaf morphology separate from the effect of shading (Short et al. 1995)

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Example 3 – Temperature and Nitrogen Loads Nutrient enrichment experiments in seagrass mesocosms demonstrated that

increased nutrient loads lead to phytoplankton and macroalgae blooms. The detrimental effects of nutrient enrichment were compounded in treatments where temperature was increased by 4ºC relative to the control, indicating the effects of increasing nutrient loads will be exacerbated when temperatures also increases (Bintz et al. 2003).

Example 4 – Nutrient Interactions Harlin and Thorne-Miller (1981) treated the water column of a Rhode Island

Coastal lagoon with low levels of ammonium, nitrate, and phosphate to examine the effects of nutrient addition to the growth of Zostera marina, Ruppia maritima, and a few macroalgae. Ammonium additions resulted in the production of dense mats of Ulva lactuca and Enteromorpha plumosa, free-floating green algae. It also stimulated growth in leaf and root-rhizome fractions of Zostera marina, showing a greater positive response in areas with a stronger current. The growth of Ruppia maritima was inversely correlated with the growth of the green algae. Nitrate additions enhanced the growth of the macroalgae, but did not significantly effect the growth of Zostera marina or Ruppia maritima. Phosphate additions enhanced the growth of Zostera marina and Ruppia maritima in areas with a slow current. The phosphate additions did not affect the growth rates of the macroalgae. The most responsive indicator of nutrient additions was leaf length of Zostera marina. Based on these results, it appears that ammonium addition had the greatest effect on growth, suggesting that nitrogen is the limiting nutrient.

Carbohydrates

Seagrasses use reserve stores of carbon to drive metabolism during periods when metabolic demands cannot be met by photosynthesis, including over-wintering (Alcoverro et al. 2001; Olesen and Sand-Jensen 1993; Zimmerman et al. 1997; Zimmerman et al. 1989). Depletion of these stores can occur due to responses of the plant to reduced light (p. 9) and/or increases in temperature (p. 19), turbidity (p. 17), sediment sulfide (p. 24), and excess nitrogen (p. 22) (Burke et al. 1996; Cabello-Pasini et al. 2002; Moore et al. 1997; Olesen and Sand-Jensen 1993; Pedersen and Borum 1993; Ralph et al. 2007; Risgaard-Petersen and Ottosen 2001).

In Chincoteague Bay, shading of eelgrass for only 3 weeks during the spring growing season was sufficient to reduce non-structural carbohydrates in the plant by 40 to 51% (Burke et al. 1996). Turbidity during this time period “could reduce the amount of potentially accumulated [non-structural carbohydrate] reserves by 66% during that time period, increasing the risk for exhaustion during subsequent periods of stress, and thus jeopardize overwintering and perhaps even summer survival.” These plants, growing at the southern limit of their range, illustrate over an annual cycle that almost all carbohydrates stored in the plant are utilized at some point in the year leaving the reserves at a low point at the end of winter. Burke et al. (1996) suggest that this population has a small margin of safety with regards to carbohydrate reserves and are thus likely to be adversely effected by any negative perturbations to the system such as decreases in grazers of epiphytes; or increases in nutrients, turbidity, or temperature.

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Nitrogen

Carbon is not often limiting to seagrass growth, as evidenced by the low variability of C levels in tissue relative to N or P (Short 1987). The sediment pool of nutrients is far more concentrated (typically <20µM to 1000 µM for NH4

+ and 20 µM for PO4

3-) than the water column (typically <3µM for NO3- and NH4

+ and <2 µM for PO43-).

Assimilation of NO3- is less favored over the reduced form of N, as the process is

energetically costly, requiring stored carbon and/or the availability of photosynthate (see review paper by Lee et al. 2007). While the sediment pool contains a considerably richer concentration of nutrients, the assimilation of nutrients by leaves and roots has been observed in a number of studies as being nearly equal, with slightly more nutrients being assimilated by the roots (Lee et al. 2007). This apparent disparity may be explained by a few studies(with Amphibolis antarctica and Thalassia testudinum) which have shown that leaves have a higher affinity for nutrients than roots (Lee and Dunton 1999; Pedersen et al. 1997). Zimmerman et al. (1987) developed a model of the growth dynamic of Z. marina which indicated long-term nitrogen limitation was unlikely to occur at levels typically found in situ. At the time of the study, little was known about nitrate processing in the plant, so some assumptions were made about the rate kinetics for this process. The model suggests, as Lee et al.’s (2007) review stated, that leaves and roots play a roughly equivalent role in nutrient acquisition for the plant, with roots being slightly dominant in nitrogen uptake. Under low light conditions, the importance of nitrogen uptake and assimilation by leaves increases because the activity of the root/rhizome uptake system is dependent on photosynthesis. However, the model predicts leaf uptake and assimilation should account for no more than 60% of the total nitrogen supplied to the plant under the shortest periods of irradiance-saturated photosynthesis (Hsat) of about 6 hours (Zimmerman et al. 1987).

Over the course of a year, Z. marina may experience nitrogen limitation. The plant has developed a system of quick response to nutrient availability in the environment, assimilating available nitrate and ammonium and storing the nitrogen for future use. Results from Zimmerman et al.’s (1987) model indicated that Z. marina may grow at maximum rates for up to 30 days without external nitrogen supplies due to internal reserves, buffering the plant against short term nitrogen limitation in the environment. Z. marina also reclaims nitrogen from older leaves and is effective at internal recycling, which accounts for as much as 27% of its annual nitrogen needs (Pedersen and Borum 1993; Risgaard-Petersen and Ottosen 2001).

Z. marina beds act as a nitrogen sink in spring and early summer and release nutrients to the environment when leaves senesce, primarily in the fall and winter periods. In the nitrogen cycle in seagrass beds, nitrogen assimilation by the plants is a far more important process than denitrification for the removal of nitrogen from the water column. N in the decaying plant material was likely to be remineralized on the order of months, making the eelgrass beds a source of N to unvegetated areas in the local region and recycling some of the N locally by supplying an estimated 23% of the annual nitrogen budget for the seagrass bed (Pedersen and Borum 1993; Risgaard-Petersen and Ottosen 2001).

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In Waquoit Bay, the source of nitrogen in Sage Lot Pond (low nutrient load, eelgrass present) was compared to Childs River (high nutrient load, no eelgrass) (Hauxwell et al. 2003). Recycling of nitrogen accounted for an estimated 99% of the N-demand by all primary producers in the eelgrass site and 64% of the N-demand by primary producers in the non-eelgrass site. These estimates reflect the higher nitrogen load to Childs River and the greater efficiency with which eelgrass traps and recycles nutrients relative to other types of primary producers. The water residence time of Sage Lot Pond is 1.5d versus 2.3d for Childs River, roughly comparable between the two sites and slightly more likely to wash the nutrients out of Sage Lot Pond at a faster rate.

Eelgrass evolved under nutrient limited conditions, so appears to have optimized the nitrate uptake processes (Burkholder et al. 1994; Touchette 2007). Under low nutrient loads, the plants would be able to take advantage of nutrient pulses and store N for later use. Some researchers have theorized that in a systematically nitrogen enriched environment, eelgrass appears to be “poisoned” by the uptake of N, as it has no feedback mechanism to stop the uptake process (Burkholder et al. 1992; Van Katwijk et al. 1997). They suggest the result of continuing nitrogen uptake is the reallocation of all available carbohydrate from storage reserves to the production of energy and carbon skeletons needed to reduce nitrate and form amino acids (Touchette and Burkholder 2000). As N becomes available, eelgrass will reallocate resources to uptake and assimilate the nitrogen at the expense of carbon reserves. Under high nitrogen loads, seagrass may become carbon-limited; a condition which can eventually lead to the demise of the plant, typified by a loss of structural integrity (Burkholder et al. 1992; Touchette 2007). In one mesocosm experiment in North Carolina, warm temperatures combined with low-level water column nitrate enrichment induced a loss of eelgrass and plants crumbled when sampled (Burkholder et al. 1992). This type of failure was attributed to a physiological response to nitrogen over-enrichment. In a similar experiment conducted in Rhode Island by a different group of researchers, the “nitrogen toxicity” effect on plant integrity was not observed at any nitrogen loading levels (Kopp 1999).

In the Grevlingen, Netherlands, a study examining the effects of light and nutrients on two natural populations of eelgrass indicated that nitrogen limitation was thought to be one of the causes for the decline of the population in the area (van Lent et al. 1995). While this is unlikely to be a problem in the small embayments of Long Island Sound, tissue nutrient data from a population of eelgrass near Ram Island, Mystic River indicated N limitation (Vaudrey 2008). Areas of Narragansett Bay have also shown evidence of nitrogen fixation, another indication of N limitation in a system that is still considered nutrient impaired (Fulweiler et al. 2007).

In addition to the effects already mentioned, increased nitrogen loads to a system also have the potential to promote increases in the occurrence of wasting disease, which is an infection by the slime mold Labyrinthula zosteroides. The theory is that this occurs because nitrogen and carbon are utilized for the production of amino acids rather than in the production of alkaloids and other anti-microbial compounds (Burkholder et al. 2007; Short and Wyllie-Escheverria 1996).

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Future Considerations

Carbon dioxide levels in the water were increased in a mesocosm experiment to determine the possible effects of globally increasing CO2 in the world’s oceans on seagrass populations. Photosynthetic rate increased without a corresponding increase in respiration, allowing the plants to thrive at a light level that was detrimental to the unenriched treatment. These results indicated that rising CO2 level may be beneficial to seagrass in eutrophic coastal areas (Zimmerman et al. 1997).

SEDIMENT CHARACTERISTICS

Koch (2001) has presented a review and analysis of data which summarized the effect of sediment characteristics and physical characteristics on eelgrass distribution. This review is widely referenced as a comprehensive paper pulling together many of the factors which explain why eelgrass may be absent from a site when light and water quality appear to be suitable. The reader is referred to this paper for a more in depth treatment of the subject. A more recent review (Boer 2007) touches on many of the same topics, with the addition of new data and additional references, but relies heavily on Koch’s (2001) paper for the foundation information on sediment interactions.

Z. marina colonizes sediments with percent fines ranging from 2.3% to 56.3% (Koch 2001). As reviewed by Koch (2001), at the lower spectrum of grain size, the exchange of porewater with the overlying water column is reduced. This situation may lead to increased concentrations of nutrients and sulfides in the sediments. As grain size increases, the porosity of the sediments correspondingly increases and the sediments are likely to be better flushed. This reduces porewater concentrations of nutrients and may lead to nutrient limitation.

A recent study in Ninigret Pond, RI combined the subaqueous soil survey classification employed by the USDA-NRCS to relate eelgrass presence to sediment characteristics (Bradley and Stolt 2006). One benefit of using the USDA classification was the multiple levels of description already defined by the Soil Survey Standard Methods. In the area surveyed, light was plentiful for eelgrass growth. The absence of eelgrass from certain areas of the bay was instead correlated with sediment characteristics. The areas with eelgrass tended to be sediments with finer grain sizes and higher organic matter (very fine sandy loam, silt loam, fine sand). Eelgrass coverage was positively correlated with acid volatile sulfide in the sediments (Bradley and Stolt 2006). This is consistent with the observation that eelgrass beds will trap sediment and deposit leaves as detritus, increasing organic matter in the area, which in turn increases the chance of anoxia and hence the development of sulfide in the sediment. A positive correlation was also seen with sediment salinity concentration (34 to 44 ppt), which were in turn correlated with total nitrogen concentrations in the sediment pore water. The USDA-NRCS are considering extending their survey of subaqueous soils to Connecticut embayments beyond the survey already conducted in Little Narragansett Bay. Such surveys could provide information for possible restoration efforts or inform expectations of eelgrass expansion in CT embayments.

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Sediment Organic Content

A review of the sediment organic matter in healthy Z. marina beds indicated values ranged from 0.41% to 16.4% organic matter (see table in Koch 2001). The higher levels of organic matter were associated with higher levels of phytotoxins, especially sulfide. Koch (2001) reported that higher sediment organic content was seen for species with larger leaves, species more likely to transport oxygen from the leaves to the roots, thus creating an oxygenated zone around the roots and rhizomes. This oxygenated buffer zone in the rhizosphere helps to limit the effect of phytotoxins in the sediment on plant growth and photosynthesis.

Sulfides and Anoxia

Eelgrass metabolism is involved with its sediment chemistry in a sequence of reactions. As photosynthesis proceeds, carbohydrates are released from the plant’s root system. The mineralization of this organic matter takes place under aerobic conditions near the sediment surface where the oxic zone is typically a few millimeters thick, but as oxygen is depleted with depth in the sediment, alternate electron acceptors are used. Due to the high availability of sulfate in the marine environment, sulfate reduction becomes an important anaerobic process, resulting in the production of sulfide in the sediments. The products of primary production in a seagrass bed, in the form of detrital matter and carbohydrates released from the roots, are likely to stimulate microbial anaerobic metabolism in sediments (Vichkovitten and Holmer 2005). So, ironically, increased production by seagrass fuels production of sediment sulfide, a phytotoxin.

Even modest increases in porewater sulfide levels can reduce growth and productivity. Eelgrass is able to grow in anoxic sediment by translocating oxygen from leaves to the root/rhizome system. As incident light is reduced as a result of attenuation in the water column, PAmax (the maximum attainable rate of photosynthesis, based on current conditions as well as physiology) is also reduced. Additionally, PAmax is reduced ~0.075 µmol O2 min-1 mg Chl-1 for every increase of 100 µmol of sulfide in the sediment. Under eutrophic conditions, light attenuation in the water column increases and more organic matter settles to the bottom, fueling the anaerobic community. PAmax is decreased by the decrease in available light and by the increase in sediment porewater sulfide concentrations. Reduced photosynthesis in the plant means that less oxygen is sent to the root/rhizome complex and less oxygen escapes out of the roots into the surrounding sediments, thus decreasing sulfide oxidation. Under unfavorable conditions, this coupling can lead to the loss of eelgrass in an area (Goodman et al. 1995)

One hypothesis as to why seagrasses are sensitive to reductions in light is because of their high light requirements, typically cited as averaging 11% of surface irradiance (Io), with empirical values ranging from 5 to 25% of Io. An alternate (or perhaps additive) hypothesis explaining the sensitivity to low light is the fact that plants are often found in anoxic sediments. Sulfide in the sediment porewater leads to reduced photosynthesis, increased respiration, and may lead to decreases in production and growth. The plants must see enough light to generate enough oxygen through photosynthesis to overcome the respiratory demands of its’ heterotrophic biomass and

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maintain a positive carbon balance to continue to grow. Under low-light conditions, seagrasses fix less carbon. To maintain a positive carbon balance, carbon is translocated from rhizomes to maintain metabolic functions, respiratory demands are reduced, and patterns of carbon storage are changed. (Ralph et al. 2007)

Terrados et al. (1999) conducted an experimental manipulation of sediment anoxia levels to examine the effect of sediment sulfide levels on seagrass growth, one of the study sites being a temperate Z. marina bed. While there was large variability between species, they concluded that increased sediment anoxia and accompanying increases in sulfide concentrations resulted in reduced leaf growth for Z. marina. No effects on shoot density were observed for Z. marina.

Koch (2001) reviewed a number of studies to examine the effect of porewater sulfide concentration on eelgrass health and found indications that concentrations above 1mM may be toxic. While the 1mM threshold was suggested, the final conclusion was that data in this area were scant and it was a topic needing further research.

WAVE ACTION AND CURRENT SPEED

The reader is referred to Koch (2001) for a full review of the interactions of seagrass and current velocity. Koch highlights the positive and negative effects of the physical structure of seagrass beds reducing the current velocity. This has a few benefits for the seagrass: reduced self-shading as the plants maintain a more vertical position in the water column, increased settling of suspended solids and organic particles which leads to increased water clarity, and increased sediment nutrient availability, higher water residence time allowing greater access to water column nutrients which in turn lowers water column nutrient availability to epiphytes as the eelgrass assimilates the nutrients, increased settlement of larval organisms which increase species diversity and these organisms may graze on epiphytes. Negative effects of slower currents include: increased sediment sulfides due to increased organic matter and a thicker diffusive boundary layer on the leaves. The literature review for Z. marina targets current velocities of 3 to 180 cm s-1 for Z. marina (Koch 2001) as a suitable habitat.

In a number of studies, the current speed has been linked to growth, which is in turn linked to the transport of required nutrients. The diffusion of CO2 into the tissues of seagrasses is slow compared to diffusion into terrestrial plants, as a result of the low diffusion coefficient of gases in water. The diffusion path into the seagrasses is also long (up to 50μm). Added to these two factors is the presence of a stagnant zone of water at the cellular surfaces of the leaf (the diffusive boundary layer). In a review of a number of studies, Zieman and Wetzel (1980) found evidence that a low velocity current could disrupt the stagnant zone at the leaf’s surface and increase diffusion rates. This increase in diffusion was considered to be a primary causative factor for the observed increase in photosynthetic rates. Both Zostera marina and Thalassia testudinum showed maximum standing crops in areas where the velocity averaged 1 knot (0.5 cm s-1). (Zieman and Wetzel, 1980) Additional studies were cited to support Zieman and Wetzel’s results.

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Fonseca, et al (1983) examined the effect of current on the growth of Z. marina in North Carolina and found that growth was positively correlated with the tidal current velocity. Z. marina was able to tolerate current flows up to 120-150 cm s-1. Their data suggested that meadows in low flow areas are sinks for fine sediments and that meadows in high flow areas are sources for fine sediments.

The growth response of Z. marina leaf and root-rhizome fractions to additions of ammonium to the water column in a temperate coastal lagoon was greater in areas where the current reached 12 cm s-1 than in areas with little or no current. Concentrations of N in tissue did not change. In areas with no current, growth increase was small, but the concentration of N in the tissue doubled as compared to the control plots. (Harlin and Miller, 1981)

In Ninigret Pond, an annual population of Z. marina was present on a tidal plain delta with current speeds between 8 and 29 cm s-1, depending on location (Harlin et al. 1982). This population grew from seeds each year. In low energy areas, loss in the fall was in part due to increased wind stress. In stronger current areas, the plant’s ability to decrease current speed and accumulate sediments caused burial of the plants leading to their loss in the fall. In this case, eelgrass exists in a marginally suitable habitat by taking on the characteristics of an annual plant.

The wave orbital velocity, tide, and wave energy are expected to determine the minimum depth of seagrass (Boer 2007; Koch 2001). However, in shallow areas where the waves are being dissipated essentially as they are generated (where the depth > wavelength / 2), such as the seagrass environment of LIS, equations for estimating the minimum depth of seagrass beds from these variables have not had good success (Koch 2001). A better indicator has been based on tides alone, where minimum depth is defined as half the tidal amplitude. For a semi-diurnal tide, this is:

Zmin = (Mean High High Water – Mean Low Low Water) / 2

See the section “Minimum Depth Limit” for more information.

Competition with Other Primary Producers

With increasing nutrients in a system, macroalgae is able to grow to a point where it shades seagrass, effectively outcompeting the seagrass for the available light (Bintz et al. 2003; Short et al. 1995; Taylor et al. 1999; Valiela et al. 1997). This ability of macroalgae to compete as nutrients increase is related to the rates shown in figure 6. At low nitrogen levels, seagrass has the advantage, due to the higher C : N requirements. At higher N levels, the nitrogen needs of the macroalgae are more readily met, and it can grow considerably faster than seagrass. As macroalgae biomass starts to increase, it is an effective competitor for N (see the faster N uptake rate) and is tolerant of lower light levels due to self-shading or reduced water quality.

While the macroalgae do directly shade the seagrass, other perturbations to the environment are introduced by macroalgal blooms. Thick stands of macroalgae promote

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hypoxia and/or anoxia due to high respiration rates during the night or in warm temperatures. As mentioned previously, low oxygen levels often require seagrass to access non-structural carbohydrate reserves to fuel the energy demanding process of translocating oxygen from photosynthetic tissue down to the rhizomes (Burkholder et al. 2007; Hauxwell et al. 2001). Dense canopies of macroalgae reduce advective flow, further compounding low oxygen problems in the water column as well as potentially leading to the build up of ammonium formed through nitrogen regeneration by the macroalgae and underlying sediments. Ammonium concentrations in the macroalgal canopy can reach values as high as 260µM (vs. <2 µM in overlying water column) (Burkholder et al. 2007; Van Katwijk et al. 1997) and newly recruited eelgrass shoots have been observed in toxic concentrations of ammonium (>100 µM) generated by macroalgae (Hauxwell et al. 2001).

Cultural eutrophication promotes bottom-water and sediment anoxia in the ecosystem (Burkholder et al. 2007). Low or no oxygen in the water column or sediments increases the need for eelgrass to translocate oxygen from photosynthetic tissue to the roots, and inhibits ammonium uptake by the roots which in turn leads to lower photosynthetic rates. Increased sediment sulfide levels during periods of anoxia negatively affect seagrass growth and photosynthesis (Burkholder et al. 2007; Goodman et al. 1995; Holmer and Bondgaard 2001)

Figure 6: Comparison of rates and stocks for three groups of primary producers. The line within the boxes is the median; the boxes span the 25th to the 75th quartiles; the horizontal lines extend to the 95% confidence limits, and the dots show outliers (figure 4 from Valiela et al. 1997, adapted from Duarte 1995).

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Indicators

Eelgrass tissue nutrient content can be used as an indicator of nutrient enrichment when referenced to “typical” concentrations for the species. Carbon content in the tissue was typically steady while the nitrogen and phosphorous content vary with availability of the nutrients. The typical value of the C : N for marine planktonic organisms was assumed to be around 6.6, according to the Redfield Ratio of 106C : 16N : 1P. However, a literature search for C : N of macrophytes indicates a value closer to 19C : 1N for seagrass (Atkinson and Smith 1983; Duarte 1992; Fourqurean et al. 1997; Short 1987; Short 1990) and closer to 14C : 1N for macroalgae (Atkinson and Smith 1983). Nutrient ratios in tissue will change throughout the season, reflecting changes in the environment. But care must be taken to account for changes due to the age of the leaf (tissue N decreases with leaf age) and under certain growing conditions (C:N is also a function of light, where high photosynthetic rates under high light conditions lead to a depletion of tissue nutrients) (Burkholder et al. 2007).

While the tissue nutrient content reflects the recent nutrient environment experienced by the macrophytes, Lee et al. (2004) developed an early assessment of nutrient enrichment which is more sensitive than tissue nutrients alone. This indicator (NPI: nutrient pollution indicator) also includes a measure of the plant morphology. The index has been effective at identifying nutrient gradients within estuaries and a method has been developed for “testing” water quality at various locations with eelgrass harvested from a common source and mounted on racks in the sites of interest (Short and Burdick 2003).

The wide range in C:N:P ratios is due to differences in the nutrients and light. Plants from low nutrient waters show significantly higher C:N and C:P ratios than those from high nutrient waters. (Atkinson and Smith, 1983) Ratios will also differ within a species when it is grown on nutrient poor versus nutrient rich substrates. For example, Short (1987) found that Zostera marina leaves had a ratio of 189:11:1 when grown on nutrient rich mud substrates. When Zostera marina was grown on a relatively nutrient poor sand substrate, the ratio increased to 235:9:1. When seagrasses are grown in nutrient poor water, it appears that they are able to modify the C:N:P ratio so that less nutrient / biomass are required to build tissue. The ratio of elemental constituents also shows a seasonal variability, which has been linked to changes in nutrient availability on a seasonal basis. (Fourqurean, et al; 1992a)

Moore and Wetzel (2000) examined the effects of different nutrient levels on the growth of eelgrass in mesocosms situated on the banks of the York River in Virginia. They found that eelgrass shoots demonstrated decreased levels of nutrients with increasing light levels during the spring, summer and fall. As light increased, the rate of production increased. The elemental composition changed to reflect the faster rate of production in relation to the rate of nutrient uptake. Tissue nitrogen was greatest during the fall. At this time, the amount of N in the leaves found in enriched versus non-enriched treatments was not significantly different. The root-rhizome elemental composition demonstrated no significant response to nutrient levels or light during the

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summer. However, the nitrogen content in the root-rhizome was higher in the enriched treatments at all three tested light levels during the spring, and the two highest light levels during the fall. Highest levels of nitrogen in the seagrass tissues occurred during the fall (3.5-3.8%), suggesting that N is less limiting in the fall than during the spring (2.0-3.2%) and summer (2.0-3.0%). (Moore and Wetzel, 2000) Shoot tissue levels of phosphorous followed the same trend as nitrogen for the nutrient enriched treatments, however, Moore and Wetzel (2000) did not observe a response to the various light regimes.

Putting It All Together - Interactions Between Factors

The components of seagrass ecosystems, including the physical, biological, and geological aspects, engage in a complex web of interactions. Seemingly beneficial events (like increased production in seagrass beds) can have negative consequences (increased sulfide production in the sediments). Determining the net outcome of any single action is difficult, as the system is self-regulating, subject to perturbations, and there is much we still don’t understand about the interactions involved.

Obviously, light is of primary importance to the success of seagrass. Low nutrients in the water column help reduce competition with other primary producers for light. Figure 7 illustrates the effect of increased nutrient loading as a self-accelerating process on the loss of seagrass. Grazing on epiphytes and macroalgae can slow this effect, represented in the figure by the “spring”. But as seagrass is lost from the ecosystem, sediment is resuspended and light quality is degraded. The low light level stimulates the growth of algae and further reduces the biomass of seagrass.

Figure 7: Conceptual model of the effect of increased nutrient loading on seagrasses, stressing the self-accelerating nature of the process. Grazing can act as a buffer to the effect of nutrient loading on seagrass loss (figure 5 from Duarte 1995).

Olesen (1996) conducted a study which exemplified the complex interactions encountered in these systems. The project compared secchi depth, water column nutrients, chlorophyll a, turbidity, and eelgrass distribution in 10 basins of a Danish embayment with the purpose of determining which of these factors had the greatest effect on the light available to seagrass and predicting the likely effect of a reduction in nutrient loads to the system. The results showed that suspended solids contributed a large portion

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to light attenuation in the system. So while a reduction in nutrients would cause a reduction in chlorophyll, the effect would not be as great as anticipated due to the remaining influence of the suspended solids. However, if eelgrass was able to colonize the area, the baffling effect of the leaves on current speed would reduce the sediment load in the water and the root-rhizome system of the plants would stabilize the sediments, preventing further resuspension.

As part of a review of sediment-seagrass interactions, Boer (2007) developed a schematic representation of the interactions of the main factors in seagrass beds (figure 8). The figure graphically illustrates how seagrass is controlled by its environment and in turn modifies the environment. What is missing from the schematic is a clearer representation of the physiological parameters of the eelgrass (non-structural carbohydrates, nitrogen, oxygen status; effect of sulfides, etc.).

Figure 8: Schematic representation of the main factors determining the occurrence of seagrass (copied from Boer 2007).

While the interactions are complex, statistical analyses of available data across numerous eelgrass inhabited areas have allowed for the development of management criteria in the Chesapeake Bay region which seem to be applicable across many sites in that region as well as in LIS (Batiuk et al. 2000).

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Setting Goals for Water Quality in Long Island Sound

Much of the research defining habitat requirements for Zostera marina was conducted in the Chesapeake Bay area. The original guidelines for habitat suitability identified adequate light availability as the most important requirement for seagrass (Batiuk et al. 1992; Dennison et al. 1993). The light reaching the leaf surface is influenced by the water column light attenuation coefficient, which results from absorption and scattering of light by particles in the water, and by absorption of light by the water itself (figure 9). The particles in the water responsible for absorption and scattering are primarily phytoplankton, measured as chlorophyll-a, and total organic and inorganic particles, measured as total suspended solids. The epiphytes on the leaf surface also contribute to the light absorption. The original guidelines identified minimum habitat requirements by statistically analyzing those components of the environment that interact to control eelgrass distribution. Nutrients were included as they stimulate the production of both phytoplankton and epiphytes.

The original Chesapeake Bay guidelines defined water column light in terms of the light extinction coefficient (Kd) (Batiuk et al. 1992). However, there was no way to adjust the management Kd for varying desired restoration depths (Batiuk et al. 2000). The Kd also did not take into account the effect of varying tidal ranges, which changed the maximum depth of bed distribution. To account for these shortcomings, the requirements have been redefined in terms of minimum light required by seagrass, either as percent of light received by the leaf (PLL) or percent of light received through the water (PLW) (figure 9, table 3). PLW takes into account the attenuation of light through the water column. PLL also includes the light attenuated by the epiphytes. On average, for eelgrass the epiphytes account for 30% additional light absorption at the leaf surface (Batiuk et al. 2000).

The PLW can be measured from light readings in the water column or calculated from Secchi depth using the Lambert-Beer equation. An algorithm has been developed to estimate the epiphytic contribution to PLL from the Kd, total suspended solids, dissolved inorganic nitrogen (or dissolved inorganic phosphorous, if P is the limiting nutrient) (Batiuk et al. 2000). This algorithm has been tested in the Chesapeake Bay region by deploying artificial substrates in the environment to evaluate the epiphyte biomass versus DIN concentration and in mesocosm experiments. This algorithm should be tested in LIS using similar verification techniques.

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Figure 9: Conceptual model of factors affecting seagrass distribution. From the Chesapeake Bay Submerged Aquatic Vegetation Water Quality and Habitat-Based Requirements and Restoration Targets second technical synthesis (Batiuk et al. 2000).

In the mid-1990s, Yarish et al. (2006) conducted a two year study in part to examine the habitat requirements for Z. marina in LIS. They developed suggested guidelines for LIS based on the Chesapeake Bay guidelines for habitat requirements by examining 3 Connecticut sites (table 3). For this report, the suggested guidelines from these earlier reports were again applied to three case study sites in Connecticut, further verifying the work conducted by Yarish et al. (table 3, see section on Case Studies for

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more information on the derivation of the suggested guidelines). The primary requirement important for managing eelgrass is the light received by the plant. The secondary requirements listed are used as diagnostics tools for determining why eelgrass is not present in a site if the primary requirement appears sufficient for the growth and success of eelgrass. The habitat constraints provide information for determining whether a site is unsuitable for eelgrass growth, due to sediment characteristics or physical restraints of the system (flow, space). These factors taken together allow for the mapping of potential eelgrass habitat in the area and identification of systems in need of increased oversight.

Table 3: Recommended habitat requirements for the growth and survival of eelgrass. Values are from Chesapeake Bay (Batiuk et al. 2000), Yarish et al.’s (2006) evaluation of habitat criteria for LIS, and the recommendations developed from the case studies presented as part of this report.

Chesapeake Bay Guidelines

Guidelines for LIS (Yarish et al. 2006)

Guidelines for LIS (Case Study Sites) Guideline Type

Minimum Light Requirement at the leaf surface (%) > 15 > 15 primary requirement

(must estimate epiphyte biomass)Water Column Light

Requirement (%) < 22 < 22 subtitute for Min. Light Requirement at the Leaf Surface

Kd (1/m) < 1.5 < 0.7 < 0.7 provided for reference, use minimum light as the standard

Chlorophyll-a (µg / L) < 15 < 5.5 < 5.5 secondary requirement (diagnostic tool)

Dissolved Inorganic Nitrogen (mg/L) < 0.15 < 0.03 < 0.03 secondary requirement (diagnostic

tool)Dissolved Inorganic Phosphorus (mg/L) < 0.02 < 0.02 < 0.02 secondary requirement (diagnostic

tool)

Total Suspended Solids (mg/L) < 15 < 30 no data secondary requirement (diagnostic tool)

Sediment Organics (%) 0.4 to 12 3 to 5 0.4 to 10 habitat constraint

Vertical Distribution (m) Zmax = 0.5m + Zmin Zmax = 1m + Zmin Zmax = 1m + Zmin habitat constraint

Sediment Grain Size 0.4 - 30 % fines < 20% silt and clay no data habitat constraint

Sediment Sulfide Concentration (µM) < 1000 < 400 no data habitat constraint

Current Velocity (cm/s) 5 < X < 180 5 < X < 100 no data habitat constraint

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Future Research

Additional testing of the habitat requirements as they pertain to Long Island Sound could aid in defining the limits for the secondary criteria and habitat constraints, including the total suspended solids, sediment grain size, sediment sulfide, sediment organics, and current velocity. Greater efforts at monitoring in sites with and without eelgrass, especially the small enclosed embayments most likely to experience the effects of eutrophication, would allow for further verification of the criteria for Long Island Sound. Chesapeake Bay has applied decades worth of monitoring data to the development of the criteria. Results from this data analysis and the Yarish et al. (2006) case studies provides evidence that LIS secondary guidelines should be more conservative than those of Chesapeake Bay. Efforts could be made to collect additional historical datasets from other sites in LIS or other areas of New England with which to check the recommended guidelines. The primary minimum light requirement of eelgrass appears similar between the two sites (LIS and Cheseapeake Bay), now that it is framed in terms of the percent light received versus the Kd.

In addition to simply needing more data to verify the guidelines, there are aspects of the Chesapeake Bay management plan that need to be tested before applying to Long Island Sound. Most importantly, the algorithm used to estimate PLL by using a model relating epiphyte biomass to Kd, DIN, DIP and TSS (Batiuk et al. 2000). The relationship between epiphytes, nutrients, and light received by the water column in LIS should be critically examined.

The following suggestions for additional information and research needs were developed from the case studies:

• Very little is known about the sediment sulfide conditions in Long Island Sound embayments and about the effect of sediment sulfide on eelgrass growth. Collaborating with the USDA NRCS as they continue to expand their subaqueous soil mapping in Connecticut could provide a source of samples. As mentioned previously, the core section sampled would need to be appropriate to the root/rhizome zone of eelgrass, vs. the larger sections sampled in the LNB survey (Surabian 2007).

• The tissue nutrient content of eelgrass and some macroalgae provided a good indication of the nutrient exposure of eelgrass plants (Vaudrey 2007). A survey of eelgrass beds, coupled with the U.S.F.W.S. aerial survey would provide an indication of the status of the eelgrass beds, beyond an estimate of coverage. The samples are relatively easy to collect and process. By examining the same portion of each plant collected (e.g. the first 10 cm of the third leaf, erupted from the sheath), various locations can be compared. A seasonal effect does alter the nitrogen availability, so ideally multiple samples would be taken over the growing season. The range of nitrogen availability seems high, with limiting values near a site sampled at Ram Island and excess nitrogen experienced by the seagrass in Niantic River and Mumford Cove. The NPI (nutrient pollution indicator) could

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also be employed to look at site differences, using the technique of harvesting eelgrass from a common site and suspending it on racks in multiple sites for comparison of the nitrogen available from the water column (Short and Burdick 2003). At low light levels, leaf tagging methods as an indicator of growth will not capture the limitation imposed on the plant as the eelgrass reallocates internal non-structrual carbohydrate reserves (NCS) to sustain growth. Olesen and Sand-Jensen (1993) state that the energy status of the plants are more appropriately evaluated by examining the carbon content or organic dry weight.

• Deployable light meters are now available which allow for continuous monitoring of underwater light conditions. Cheaper versions require maintenance every few days to clean the optics, while pricier versions come equipped with a wiper (e.g. HOBO PAR Sensor, Dataflow Odyssey PAR Recorder, Compact-LW). These instruments could provide information on the light environment in the sites missed by sporadic sampling. Including the potential issue of increased turbidity on the weekends due to recreational boat traffic (Short 1988). Citizen action groups undertaking monitoring projects should be encouraged to continue recording Secchi depth.

Recovery of Seagrass - a few success stories

During the 1990s, approximately 12,000 km2 of seagrass were lost (Duarte 2002; Short and Wyllie-Escheverria 1996), 2% of the worldwide estimated original area of 600,000 km2 (Duarte 2002). This estimate was derived from documented cases at about 40 sites with enough data to verify the loss of seagrass, with the actual lost area assumed to be much greater (Short and Wyllie-Escheverria 1996). The general overall trend for seagrass coverage is certainly one of decline (Hemminga and Duarte 2000; Orth et al. 2006a). However, there are a few documented cases of recovery of seagrass from various types of disturbances (table 4).

Each case of seagrass recovery occurs under a unique set of conditions. With so few cases of documented recovery, a summary of the various instances can be conducted with the purpose of looking for commonalities and providing evidence for the positive effects of planned improvements to watershed management strategies. This collection of case studies also allows for the formulation and may help in answering such questions as: What is the time frame of recovery? How stable are these systems over time? Are additional restoration efforts needed and are they likely to be successful? Each paper in table 4 is summarized independently, even if multiple papers refer to the same system. Papers are organized by the type of disturbance, with papers from the same geographical system listed consecutively.

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Table 4: Review of the current literature documenting the natural recovery of seagrass. While some of these cases show large scale growth of seagrass (e.g. 40km2 in Chincoteague Bay in 10 years), many are documenting recovery on a much smaller scale (e.g. <4m2 in Bouches-du-Rhône, 3km2 in St Croix).

Disturbance Location Species Reference

nutrient loading Tampa Bay, Florida, USA Halodule wrightii

(Johansson and Lewis III 1992; Lewis III et al. 1999; Tomasko et al. 2005)

nutrient loading Sarasota Bay, Florida, USA “seagrass” (Tomasko et al. 2005)

nutrient loading Mondego Estuary, Portugal Zostera noltii (Cardoso et al. 2004; Lillebø et

al. 2005)

nutrient loading Gulf St. Vincent, South Australia

Posidonia sinuosa, Amphibolis antarctica, Zostera tasmanica, Halophila ovalis

(Bryars and Neverauskas 2004)

nutrient loading & sediment loading

Bouches-du-Rhône, Southern France, Mediterranean Sea

Zostera marina (Bernard et al. 2005)

nutrient loading Mumford Cove, Connecticut, USA Zostera marina (Vaudrey et al. 2007)

nutrient loading* Chincoteague Bay, Delmarva Peninsula, USA

Zostera marina (Koch and Orth 2003; Orth et al. 2006b)

propeller scars* Tampa Bay, Florida, USA Thalassia testudinum (Dawes et al. 1997)

boating scars* Florida Keys, USA Thalassia testudinum (Whitfield et al. 2004)

boat moorings* Rottnest Island, Western Australia

Posidonia sinuosa, Posidonia australis, Amphibolis antarctica, Amphibolis griffithii

(Hastings et al. 1995)

anoxic event Odense Fjord, Denmark Zostera marina (Greve et al. 2005)

anoxic event Thau lagoon, French Mediterranean Sea Zostera marina (Plus et al. 2003)

2 floods and 1 hurricane

Hervey Bay, Eastern Australia

Halophila decipiens, Halophila spinulosa, Halophila ovalis

(Preen et al. 1995)

hurricane* St. Croix, US Virgin Islands Syringodium filiforme (Kendall et al. 2004)

1930s wasting disease

many locations in North Atlantic coastal areas Zostera marina (Cottam 1933; Frederiksen et

al. 2004; Rasmussen 1977)

none identified Success Bank, Western Australia

Posidonia coriacea, Amphibolis griffithii (Kendrick et al. 1999)

none identified Assawoman Bay, Delmarva Peninsula, USA

Zostera marina (Orth et al. 2006b)

none identified Sinepuxent Bay, Delmarva Peninsula, USA Zostera marina (Orth et al. 2006b)

none identified Southern coastal bays, Delmarva Peninsula, USA

Zostera marina (Orth et al. 2006b)

natural cycle of loss and recovery

Turnbull Bay, Indian River Lagoon, FL, USA

Halodule wrightii, Ruppia maritima (Morris and Virnstein 2004)

* Unlike all other cases presented, seagrass was present in the local ecosystem following the disturbance.

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NUTRIENT REDUCTION - Hillsborough Bay, a sub-estuary of Tampa Bay, FL, was recolonized by the seagrass Halodule wrightii 5 years after the wastewater treatment facility discharging into the bay was upgraded from a primary treatment facility to provide advanced wastewater treatment (AWT). The bay was determined to be nitrogen limited. The pre- and post-upgrade water column TIN concentration dropped from ~1mg/L in 1976-1984 to ~0.8mg/L in 1985-1989, with a spike up to 1.2mg/L in 1987. The recolonization was attributed to greater water clarity associated with lower chlorophyll concentration in the water, specifically, with large biomass reduction of a blue-green alga. (Johansson and Lewis III 1992)

NUTRIENT REDUCTION - The Tampa Bay estuary provides an example for the course to take towards successfully managing a large estuary like Long Island Sound. In the last 30 years, a grass-roots effort to clean up Tampa Bay has evolved into a coordinated “multi-layered network involving three counties, a dozen cities, a variety of regional and federal agencies and numerous citizens and special interest groups.” The results of these efforts have been improved water quality in the estuary and increasing seagrass coverage since 1982. Regulatory criteria for water quality targets were initially technology based, shifted to being water quality based, and are currently resource based. The resource which serves as the standard is the distribution of seagrass, but the integrated coastal management plan includes a list goals for other habitat criteria, water quality standard, fish and wildlife criteria, spill prevention and response, dredging and dredged material management, and public education and involvement. A key point is the time course of recovery, the reduction in algae and increase in water transparency showed a 5 year time lag following the reduction in the nutrient input. While seagrass showed an expansion in areal coverage, recolonization is a slow process. (Lewis III et al. 1999)

NUTRIENT REDUCTION – The total nitrogen load to Tampa Bay and Sarasota Bay, FL, USA have been reduced in the last 20 years as point sources have come under stricter regulations. In both estuaries, point sources of nitrogen now contribute less than 15% of the total nitrogen load. Increases in seagrass coverage in the estuaries have been linked to the improvement in water quality, which in turn were attributed to the reduced anthropogenic nitrogen loads. While seagrass coverage expanded >1200ha between 1988 and 2002, and >4200ha of “patchy” meadow were transformed into “continuous” meadow, the seagrass coverage has not changed a great deal since 1996. A link between freshwater flow, rainfall, and/or seagrass recovery have not been found, indicating the increases in seagrass coverage were due to the improvement in water quality brought about by the reduction in nutrient loads. (Tomasko et al. 2005)

NUTRIENT REDUCTION – On the west coast of Portugal, the seagrass beds of the Mondego estuary have expanded in response to mitigation efforts to improve water quality. The estuary has experienced increasing nutrient loads since the 1930s from agricultural runoff and has seen changes in hydrographic flow due to expanding harbor facilities. These conditions have resulted in increased turbidity, increased nutrient concentration in the water and a corresponding increase in macroalgae and decline in seagrass. In 1998, mitigation measures were undertaken to change the flow regime, effectively redirecting a large amount of high nutrient / low salinity water away from the lower fork of the estuary. The water column ammonia concentrations dropped

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significantly, the N:P was reduced, macroalgae biomass decreased, and seagrass (Zostera noltii) biomass increased. (Lillebø et al. 2005). Prior to the mitigation efforts in Mondego estuary, it was predicted that changes in the sediment of the area due to shifts in the dominant primary producer community would make natural recolinization by seagrass difficult (Cardoso et al. 2004). Lillebø et al. (2005) observed that 5 years after the mitigation, seagrass biomass was still lower than historically recorded levels and cited the possible hysteresis effect of changes in the sediment regime.

NUTRIENT REDUCTION - In 1978, a pipeline for digested sludge from the Port Adelaide sewage treatment works (PASTW) was sited in the Gulf St. Vincent, South Australia. The outfall was in 12m of water, located in a dense seagrass meadow comprised primarily of Posidonia sinuosa and Amphibolis antarctica with low densities of Zostera tasmanica and Halophila ovalis. By 1981, seagrass was absent from the 365ha area surrounding the outfall, with discernable effects extending a further 1535ha around the outfall. In 1993, the sludge outfall was decommissioned and a casual examination around the outfall in 1998 documented the return of seagrass to the area. A more complete study of the are in 2001 and 2002 revealed that a mixed community of seagrass had returned to the site, dominated by the fast-growing, early-colonizer Halophila australis. Posidonia sp. were present at less than 1% coverage and were expected to expand in coverage, eventually forming the climax community. Given the slow growth and spread of Posidonia sp., this process was expected to take decades. (Bryars and Neverauskas 2004)

NUTRIENT and SEDIMENT REDUCTION – Until the late 1960s, Zostera marina was found throughout the Berre and Vaïne brackish lagoons, Bouches-du-Rhône, Southern France, Mediterranean Sea. In 1966, the hydrological flow in the area was changed to accommodate a hydroelectrical power plant, reducing the salinity and increasing turbidity and nutrient levels in the formerly saline lagoons. By 1973, the eelgrass had disappeared from the area. In the 1980s nutrient input from sewage treatment plants was significantly reduced to the local waters. By 1994, the fresh water flow into the lagoon had experienced a substantial and steady decline, extending back a number of years. This decline in freshwater flow was accompanied with a significant reduction in the silt load (1.6Mt/a in 1977 to 0.1Mt/a in 1994). In 2001 and 2002, small sparse beds (< 4m2 total area for all beds) of eelgrass had recolonized the area. Bernard et al. (2005) were uncertain of the future success of eelgrass in the area, given the sparse and patchy nature of the first few colonizers. (Bernard et al. 2005)

NUTRIENT REDUCTION - Following the diversion of a sewage treatment facility wastewater outflow from Mumford Cove, CT in the fall of 1987, water column nutrient levels were greatly reduced. The middle section of the small cove was transformed from an algal dominated community (< 300 g D.W. m-2 Ulva lactuca) to a Zostera marina dominated community within 10 years. The deeper (2 to 3m) upper arm of the cove is still relatively bare sediment, with some macroalgae present. (Vaudrey et al. 2007)

39

NUTRIENT REDUCTION - In four of the northern bays of the Delmarva Peninsula, expansion of Zostera marina has occurred at an average rate of about 305 ha y-1 for a total growth of 7319ha between 1986 and 2003. The expansion is though to be due to recruitment via seedlings. A lack of success in neighboring bays was attributed to higher anthropogenic nutrient loads to those areas. Transplant tests in embayments in the southern end of the Delmarva Peninsula indicated the habitat was suitable for eelgrass, but the lack of seeds was keeping eelgrass from establishing a presence in the area. (Koch and Orth 2003; Orth et al. 2006b)

PROPELLER SCARS - Thalassia testudinum was slow to re-grow into propeller scars due to the nature of proliferation of the rhizome. If the rhizome apex which contains the active meristem is severed, production of short shoots, either terminal or branching, are impossible, until a new apex is generated. The process of generating a new apex can take up to 10 months for T. testudinum. Thus, full re-growth into propeller scars can take 3.5 to 4 years and up to 7 years. Halodule wrightii is able to convert a short shoot apical meristem into a rhizome apical meristem, allowing for a much quicker recovery in the event of a severing of the rhizome. (Dawes et al. 1997)

BOAT “INJURIES” TO SEAGRASS BEDS - Thalassia testudinum seedlings may be an important mechanism for “jump starting” recovery process following an injury to a seagrass bed. Cohorts of seedlings were followed for 4 years. Survivorship was relatively low at the end of the 4 years, but the authors suggested the presence of the seedlings may have helped with the restablishment of beds. It was also noted that other species of seagrass, especially Z. marina, typically produce much greater numbers of seeds per area than T. testudinum. (Whitfield et al. 2004)

SCOUR FROM BOAT MOORINGS - Examined damage to seagrass beds at Rottnest Island, Western Australia due to boat mooring using aerial photographs from 1941-1992. In general, boat moorings created a bare patch in the seagrass bed which under the right hydrodynamic conditions, increased in size over time. The bare patches in some cases coalesced with neighboring mooring-induced bare patches to create larger bare areas or areas of heavily fragmented seagrass beds. Some recovery of seagrass in smaller bare patches around moorings was observed, especially in bays with a depositional environment. Larger disturbances did not show recolonization. Hastings et al. (1995) conclude that natural recovery is possible at relatively fast rates of around 10 years, with a range of 10 to 50 years. However, the scale of the human-induced damage is important to the success of recolonization, with mooring holes <20m being recolonized while larger patches show little change even after 50 years. (Hastings et al. 1995)

ANOXIC EVENT - The recolonization of Odense Fjord, a Danish estuary, by Zostera marina following an anoxic event in the fall of 2000 was primarily due to germination of seeds from the local seed bank. While seedlings accounted for the bulk of the recovery, only 1% of the germinated seedlings survived past the first growing season. Some plants which survived the anoxic event, accounting for 4% of the shoots present, also played a role in recolonizing via rapid vegetative expansion in all directions. (Greve et al. 2005)

40

ANOXIC EVENT - An anoxic crisis during August 1997 in the Thau lagoon of the French Mediterranean Sea eliminated Zostera marina from the lagoon. Recolonization occurred within 9 months, with biomass levels returning to pre-disturbance levels. Recovery occurred through a combination of high seedling survival for the seeds already present in the seed bank of the lagoon, likely due to reduced macroalgae and fauna, and increased production of reproductive shoots during the second growing season. No reproductive shoots were produced the first season, so a second anoxic event during that growing season would have left the seed bank with very few viable seeds and the recovery process would have been considerably longer. (Plus et al. 2003)

FLOOD (2) AND HURRICANE - Approximately 1000 km2 of seagrass were lost from Hervey Bay on the eastern shore of Australia in 1992 following 2 major floods and a hurricane occurring within a 3 week period. Seagrass in deep water (> 10m) were light deprived due to a plume of very turbid water. Seagrass in shallow water (< 10m) were uprooted by wave action. By 1993, seagrass in the deep water showed signs of recovery, with seagrass germinating from seeds. The shallow water sites showed little seed germination, indicating the seed bank in the sediment had been scoured away or the seeds had been damaged by the storm action. In other areas, recovery of shallow water seagrass have taken 10 or more years in areas affected by hurricanes. (Preen et al. 1995)

HURRICANE - From 1971 to 1999, deepwater (10-20m) beds of Syringodium filiforme in Buck Island Channel, St. Croix, US Virgin Islands increased from 1.33km2 to 4.34km2. This increase in coverage could not be correlated with improvements in water quality or declines in seagrass grazers. Kendall et al. (2004) suggest the greater frequency of hurricane experienced in the last 20 years has stimulated growth by aiding dispersal of seeds and reproductive fragments. While hurricanes are detrimental to shallower seagrass beds, the deeper location of these beds protects them from the devastating effects of hurricanes by dampening the wave energy. (Kendall et al. 2004)

WASTING DISEASE - A comparison of aerial photographs of five shallow-water eelgrass populations in Denmark over the period of 1940s-1990s revealed that populations of eelgrass decimated by the wasting disease in the 1930s showed a time lag of approximately 10 years before substantial recolonization was seen. After the slow start, recolonization progressed at a faster pace, proving to be a “self-accelerating process.” All study sites showed large fluctuations in areal distribution, with the largest fluctuations seen in the more protected embayments, likely due to the increased pressures of eutrophication and temperature fluctuations with the reduced water flow encountered in these areas. (Frederiksen et al. 2004)

UNKNOWN - Over the last 20 years, seagrass areal coverage has been increasing on Success Bank in Western Australia. The two primary species found in the beds are Posidonia coriacea and Amphibolis griffithii, both species endemic to western Australia. These patches of seagrass are located in temperate Australia on sand habitats. Modeling efforts indicate that understanding of the recolonization process is lacking. The spread of the patches can be accounted for by horizontal elongation of the rhizomes in some cases, but not all, suggesting that colonization by seedlings also plays a role in the spread of the

41

patches. Reasons why seagrass is increasing in this site and not others were not examined. (Kendrick et al. 1999)

UNKNOWN - There has been a natural recovery of Zostera marina in four of the northern coastal bays of the Delmarva Peninsula in the last 20 years. This spread is not associated with a decrease in nutrient loading to the system and there is no indication that water quality indices relevant to seagrass survival have changed significantly in the last 30 years. Orth et al. (2006b) suggest that the expansion occurred due to seed dispersal from recovering beds in the area. They suggest that beds may have survived the wasting disease epidemic of the 1930s in more brackish waters, providing a seed stock for the recovery of beds in the area. These beds are no longer present, likely due to increased nutrient loading from the rising population along the coast and the indirect pressures that places on seagrass. The southern bays appeared suitable for Z. marina, but no beds were present due to a lack of a seed source. Transplanting in these sites has been successful. “Seeds and seed dispersal play an important role in the recovery and expansion of these beds.” (Orth et al. 2006b)

NATURAL CYCLE OF LOSS & RECOVERY - In 1995, a poorly-flushed, restricted sub-estuary (Turnbull Bay) in the northern Indian River Lagoon, FL experienced a shift in seagrass species from Halodule wrightii to Ruppia maritima, coincident with increasing macroalgae biomass. Over 100ha of seagrass disappeared from 1996 to 1997. By 2000, seagrass had returned to its pre-perturbation levels. This decline in seagrass was not linked to water quality issues or to a natural or anthropogenic catastrophic event. Morris and Virnstein (2004) proposed that the loss of seagrass was part of a natural cycle, where decaying seagrass and macroalgae accumulate in beds, creating an organic ooze which stresses the seagrass by raising sulfide levels in the sediments. Anoxia in the sediments and the accompanying high sulfide levels cause the seagrass to become loosely attached and eventually to fail. Without the seagrass and associated rhizome mat to hold the ooze in place, the decaying organic matter can be flushed out of the embayment under storm conditions. Removal of the organic matter leaves behind an embayment with a primarily mineral sediment, ready for recolonization by seagrass. (Morris and Virnstein 2004)

Case Studies

Three case study sites from Connecticut were examined to determine the suitability of the Chesapeake Bay habitat guidelines to Long Island Sound. These are presented in a separate report (Part II: Case Studies).

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Appendix I – Summary of Data Verification and Validation Results The following statements relevant to data verification and validation are from

section A7 of the QAPP (available on the project website):

“All data acquired for the project must be evaluated for conformance to QA/QC procedures required under EPA quality assurance guidance for acceptable data quality. Since much of the data may not have been produced under an approved EPA QAPP, the PI will be responsible for this evaluation and determination of data acceptability. For peer-reviewed publications, the methodologies may adequately support good QA/QC protocols and be quantitatively acceptable, but gray literature and unpublished data files will likely require contact with the authors and, by interview or from recorded files, a determination of QA/QC procedural acceptability will be made. This determination will rely on availability of specific data quality indicators (DQI) recommended by EPA (EPA 2002) that assess precision, bias, accuracy, representativeness, comparability, completeness and sensitivity (table 5). When available, these values will be reported as metadata in the final database (see Section B10, Data Management, [in QAPP]). If there are inadequate data available to assess one or more DQIs, the metadata file will indicate that inadequacy, thus flagging the data, which will limit its utility.”

Table 5: Data Quality Indicators (DQI) and their application. DQI Review Criteria Precision Verify if measures of precision were completed and reported. Consider:

• Analytical instrument consistency • Methodology • Field splits/duplicate performance • Laboratory splits and spikes

Bias Check for bias in data distribution • Reference samples • Spikes

Accuracy Be sure data accurately reflect matrix condition • Reference samples • Percent recovery or bias

Representativeness Verify that data reflect the prevailing environmental condition • Consider precision, bias and accuracy • Check sampling design for spatial and temporal acuity • Consider professional (TAC) and peer review commentaries

Comparability Compare and contrast results from similar studies • Use all DQIs to explain differences and their potential resolution • Check all QA metadata and protocols for error

Completeness Review data reporting adequacy • All data should be reported • Validity and qualification of observations

Sensitivity Check cause and effect relationships and variable discrimination • Method detection limits • Instrument detection limits • Quantification limits

43

For the literature survey (Establishing Restoration Objectives for Eelgrass in Long Island Sound, Part I: Review of the Seagrass Literature Relevant to Long Island Sound), the majority of results presented were from the primary literature. As the papers were reviewed, the methods were critically evaluated to be certain the protocols were within EPA standards and would provide quantitatively acceptable data. Details on acceptance criteria are provided in the QAPP. Most of the paper reviewed did not identify that a QAPP had been completed as part of the project, however, standard methods were used for all studies included in the literature review.

For the case study report (Establishing Restoration Objectives for Eelgrass in Long Island Sound, Part II Case Studies), a more rigorous evaluation of the data was applied and documented in the databases and metadata accompanying the databases. The data presented in the case study reports came from a small group of researchers. The bulk of the data presented was unpublished and in some cases in draft form. In all cases of unpublished data, the PI interviewed the scientists in charge of collecting and managing the data to discuss the criteria listed in table 5. For the historical data from Mumford Cove, the PI was not able to contact many of the scientists. However, the methods were well-detailed in their reports. The metadata provided with the databases at the project website includes more information on the quality of the data. Table 6 provides a summary of the data types and the data categories assigned to each type used in the case study report, for the unpublished data. For this level of data use, all data were acceptable or the data would not have been used as part of the case study analysis. Table 7 includes the data categories for historical data and the nitrogen loads from the case study report. Many more of these data rate a “Q” - they were essential data, but the methods used were not consistent with the rigorous modern standard, reporting was not adequate to determine the methods actually used, or in many cases (especially with the nitrogen loads), the data were still in draft form.

44

Table 6: Summary of unpublished data types and category for the Case Study report (A= acceptable, Q = acceptable with qualifications, U = unacceptable).

45

Table 7: Summary of historical data and nitrogen load data types and category for the Case Study report (A= acceptable, Q = acceptable with qualifications, U = unacceptable). References in parentheses are reports or primary literature, see the Reference list for the full citation. The Q* indicates the data was probably A, but the report or paper was not detailed enough to be able to determine if the methods were adequate and the researcher was not available.

(Benoit 1975; Buck 1971; Buck and Feng 1983; Curtis and Dunbar 1985; French et al. 1989a; French et al. 1989b; Fulweiler and Nixon 2005; Kleinschmidt.Associates 2006; Mullaney et al. 2002; Process Research Inc. 1975)

46

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