1. John Tirpak, Todd Jones-Farrand, Frank Thompson, Dan Twedt, and Bill Uihlein University of Missouri, USFS Northcentral Research Station, USGS Patuxent Wildlife Research Center, Lower Mississippi Valley Joint Venture IT Demands to Ecoregional Scale Landbird Planning in the WGCP

2. Background North American –Landscapes capable of sustaining bird populations at prescribed levels North American Landbird Conservation Plan

3. 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

4. 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)

5. Planning in the WGCP Assumption: Forest patch size is dominant factor affecting habitat suitability in agricultural landscape

6. Planning in the WGCP Assumption: Forest patch size is dominant factor affecting habitat suitability in agricultural landscape

7. Planning in the WGCP Assumption: Forest structure is dominant factor affecting habitat suitability in forested landscape Need: Assess forest structure

8. 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

9. Objectives Develop a methodology that uses FIA data to define avifaunal habitat structure across an ecoregional scaleDevelop a methodology that uses FIA data to define avifaunal habitat structure across an ecoregional scale Use this data to assess sustainability of priority bird species in these landscapesUse this data to assess sustainability of priority bird species in these landscapes

10. Characterization with NLCD and FIA Map forest structure attributes across BCR NLCDFIABasal Area

11. Characterization with NLCD and FIA Required IT capabilities NLCDFIABasal Area Remote SensingDatabaseGIS

12. 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

13. 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

14. 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

15. Data Sources IT capability VariableRemote SensingDatabaseGIS LandformDEMArcGIS LandcoverNLCDArcGIS Timber size classFIAArcGIS Distance to waterNHD ArcGIS Canopy coverFIAArcGIS Forest patch sizeNLCDArcGIS Percent forestNLCDArcGIS

16. NLCDFIA Data Quality Issues NLCD –Currentness –Rare habitats and mixed forest NHD –Differences in digitizing detail FIA –Limited data –Fuzzy locations

17. 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)

18. 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

19. 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?

20. Product Delivery ArcGIS Server, SQL Server, Web Server Projected Products Target AudienceModels Model Inputs Current D-P-V Predicted D-P-V Model Validation Land managersXXXX Wildlife biologistsXXXX JV board membersXX JV coordinatorsXX Partners in FlightXXXXX JVs / BCRs that want to do the same thingXXX

21. 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