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