John Tirpak, Todd Jones-Farrand, Frank Thompson, Dan Twedt, and Bill
UihleinUniversity of Missouri, USFS Northcentral Research Station, USGS Patuxent Wildlife Research Center, Lower Mississippi Valley
Joint Venture
IT Demands to Ecoregional IT Demands to Ecoregional Scale Landbird Planning in the Scale Landbird Planning in the
WGCPWGCP
Background
• North American – Landscapes capable
of sustaining bird populations at prescribed levels
• North American Landbird Conservation Plan
Background
• Process– Develop range-wide population
objectives– Allocate population objectives to
specific regions– Translate target population numbers to
habitat objectives within each region• Requires a link between habitats and
populations– PIF Conservation Design Workshop
Planning in the MAV
• Assumption: Forest patch size is dominant factor affecting habitat suitability in agricultural landscape
• Need: Identify forest patches of suitable size
• IT demands:– Remote sensing– GIS (Patch delineation)
Planning in the WGCP
• Assumption: Forest patch size is dominant factor affecting habitat suitability in agricultural landscape
Planning in the WGCP
• Assumption: Forest patch size is dominant factor affecting habitat suitability in agricultural landscape
Planning in the WGCP
• Assumption: Forest structure is dominant factor affecting habitat suitability in forested landscape
• Need: Assess forest structure
Forest Inventory and Analysis (FIA)
• US Forest Service• Database estimates:
– Volume, growth, and removal of forest resources
– Forest health and condition
• National standards– Sampling design– Data collection– Sampling intervals
ObjectivesObjectives
• Develop a methodology that uses Develop a methodology that uses FIA data to define avifaunal habitat FIA data to define avifaunal habitat structure across an ecoregional structure across an ecoregional scalescale
• Use this data to assess sustainability Use this data to assess sustainability of priority bird species in these of priority bird species in these landscapeslandscapes
Characterization with NLCD and Characterization with NLCD and FIAFIA
• Map forest structure attributes across BCR
NLCD FIA Basal Area
Characterization with NLCD and Characterization with NLCD and FIAFIA
• Required IT capabilities
NLCD FIA Basal AreaRemote Sensing Database GIS
Habitat Suitability Index Approach
• Bird-habitat models– HSI
• A priori models based on best biology
• Peer-review
– Density• First suitability function
– Productivity• Second suitability function
– Viability• Combine density and
productivity
Example
• Acadian flycatcher– Neotropical migrant– Habitats
• Water– Bottomland hardwoods– Deciduous forest ravines
• Mature forest– Sawtimber> pole >
sapling
• Closed canopies
– Occupies small (~15 ha) forest fragments but has lower productivity there
Acadian Flycatcher © Greg Lasley
Acadian Flycatcher HSI
• Density SI– SI1: Landform, forest type, timber size class– SI2: Distance (m) to water – SI3: Canopy cover (%)– SI4: Forest patch size (ha)– SI5: % forest in 1-km window
• Productivity SI– SI6: % forest in 10-km window– SI7: % forest in 100-m window (edge effect)
• Calculation– Density SI = (((SI1 * SI3)0.500) * ((Max(SI4 and
SI3) * SI2)0.500)) 0.500
– Productivity SI = ((SI6 * 2/3) + (SI7 * 1/3))0.500
Data Sources
IT capability
Variable Remote Sensing
Database GIS
Landform DEM ArcGIS
Landcover NLCD ArcGIS
Timber size class
FIA ArcGIS
Distance to water
NHD NHD ArcGIS
Canopy cover FIA ArcGIS
Forest patch size
NLCD ArcGIS
Percent forest NLCD ArcGIS
NLCDFIA
Data Quality Issues
• NLCD– Currentness– Rare habitats and mixed
forest
• NHD– Differences in digitizing
detail
• FIA– Limited data – Fuzzy locations
Worst Case Scenario
• Processing time– Model development
• 6 months
– Mapping habitat variables• Landscape = ~1.5 months• Site = ~1 month
– Running models• 1 day/species = ~1.5 months
– Total = 10 months
Table 3. Relationship between canopy cover (%) and suitability index scores for Acadian flycatcher habitat.
Canopy cover (%) Suitability index
0 a 0.000
31 b 0.000
73 b 0.333
91 b 1.000
100 a 1.000
a Assumed values
b Prather and Smith (2003)
Canopy cover (%)
Rel
ativ
e de
nsity
0 20 40 60 80 100
Worst Case Scenario
• Storage– Mapping habitat
• Landscape – 25 maps x 1.35 GB /map = 33.75 GB
• Site – 13 variables x 29 subsections x 125 MB/map = 47.125
GB– 13 variables x 700 MB mosiacs = 9.1 GB
– Running models• Individual SIs
– 3.5 maps /species x 1 GB/map = 3.5 GB/species = 140 GB
• Density, productivity, viability – 3 maps/species x 1.35 GB /map = 4.05 GB / species =
162 GB
– Total = ~400 GB
Worst Case Scenario
• Updates– Processing time
• NLCD updated every 10 years– 1.5 months
• FIA updated every year (5-year rotation)– 1 month
• Rerunning models– 1 species/day
– Storage• 400 GB
– Personnel• Who?
Product DeliveryArcGIS Server, SQL Server, Web Server
Projected Products
Target AudienceModel
sModel Inputs
Current D-P-V
Predicted D-P-V
Model Validatio
n
Land managers X X X X
Wildlife biologists X X X X
JV board members X X
JV coordinators X X
Partners in Flight X X X X X
JVs / BCRs that want to do the same thing X X X
Acknowledgements
• Bill Dijak, Hong He, Steve Shifley – University of Missouri
• Jane Fitzgerald – American Bird Conservancy and Central Hardwoods Joint Venture
• Charles Baxter, Craig Conzelmann, Amy Keister, and Helen Whiffen – Lower Mississippi Valley Joint Venture
• Mark Hatfield, Ron McRoberts, and Mark Nelson – USFS FIA program