a landscape scale framework for cooperative grassland bird conservation
DESCRIPTION
A Landscape Scale Framework for Cooperative Grassland Bird Conservation. “A formal application of common sense for situations too complex for the informal use of common sense.” R. Keeney. STRUCTURED DECISION MAKING (SDM). SDM core elements - PrOACT. Pr oblem – Solve the right problem - PowerPoint PPT PresentationTRANSCRIPT
A Landscape Scale Framework for Cooperative Grassland Bird
Conservation
“A formal application of common sense for situations too complex for the informal use of common sense.”
R. Keeney
STRUCTURED DECISION MAKING (SDM)
SDM core elements - PrOACT
• Problem – Solve the right problem• Objectives – Describe the desired
outcomes• Alternatives – Consider any
reasonable approach• Consequences – Describe how well
alternatives meet objectives• Tradeoffs – Incorporate values,
optimal solutions– Core of structured decision making (Hammond et al., 1999).
Why SDM works• Breaks a problem into key
components–Makes decision-making transparent
• Helps identify where the difficulty in making a decision lies
• Helps identify where effort ($$) should be focused
• Provides a wide array of tools for making ‘smart’ decisions
WHAT IS THE PROBLEM?
OBJECTIVE
To sustain viable grassland bird populations East of the Rocky
Mountains.
1. Status quo2. Conservation Design3. Outreach/Marketing 4. Regulatory/Enforcement
(Int’l)5. Regulatory/Enforcement (US) 6. Public Land Acquisition7. Best Management Practices
(BMP)8. Policies: Ecosystem Services9. Economic Incentives
ALTERNATIVES AND ACTIONS
ADOPT A PRAIRIE
Connecting birds to landowner decisions
Δ birds Δ grass Δ birds
× = Δ grass Δ landowners Δ landowners
CONSEQUENCES (of alternatives, via landowner’s behavior)
LAND (Agricultural/Grass/Forest)
Knowledge/RiskRegulatory (ESA, legislation, spp. of concern)
$$ Return(hunting, agriculture, grazing, bird watching, energy development, conservation easement, potential future opportunities)
Quality of Life(cultural, land ethic, hunting, wildness)
Ecosystem Integrity (water quality, biodiversity, nativeness, carbon, erosion)
We did this for each of three landowner types, through the nine alternatives, incorporating five objectives.
Landowner values,
motivations
Problem: What will a land owner decide for a given parcel of land? (Land can be grass, agriculture, or forest)
Five Objectives:• Bird Conservation (B)• Carbon Sequestration (C) • Water Quality (W)• Economic Return ($)• Biodiversity (BIO)
Three types of landowners:• a profit-maximizing producer• a conservation-minded small farmer• a conservationist
CONSEQUENCES
Profit-maximizing Producer
Conservation Design
Outreach/ Marketing
Regulatory/ Enforcement
Public Land
BMP Ecosystem Services
Economic Incentive
Status Quo
Birds 0 0.5 0 0 0 0.05 0 0Carbon 0 0.7 0.1 0 0 0.1 0.2 0
Water Quality 0 0.7 0.1 0 0 0.1 0.1 0Revenue 1 1 1 1 1 1 1 1
Biodiversity 0 0.4 0 0 0 0.1 0.05 0
Small Farmer
Birds 0.25 0.7 0.4 0.5 0.7 0.7 0.7 0.5Carbon 0 0.2 0 0 0.2 0 0 0
Water Quality 0.5 0.3 0.2 0.5 0.5 0.5 0.4 0.2Revenue 1 1 1 1 1 1 1 1
Biodiversity 0.1 0.8 0.4 0.5 0.7 0.7 0.6 0.5
Conservationist
Birds 1 1 1 1 1 1 1 1Carbon 0 0.7 0.4 0.4 0.6 0.4 0.4 0.4
Water Quality 0.5 0.7 0.4 0.4 0.7 0.7 0.6 0.4Revenue 0.8 0.8 0.8 0.8 0.8 0.9 0.9 0.8
Biodiversity 0.7 1 0.9 0.8 0.9 0.9 0.8 0.7
INFLUENCE DIAGRAMΔ birds Δ grass Δ birds
× = Δ grass Δ landowners Δ landowners
CONCEPTUAL MODEL
Habitat 1
Habitat 3
Habitat 5
Habitat 2
Habitat 4
Species 1
Breeding
Migration
Migration
Migration
Wintering
Species 2
Breeding
Migration
Wintering
Δ birds Δ grass Δ birds × =
Δ grass Δ landowners Δ landowners
Example LandscapesConservation Design
Profit-maximizing Producer
Landscape
ConservationistLandscape
1 2 1 1 3 1 3 1 3 1 2 3 2 1 1 1 1 2 3 3 2 1 1 1 2 3 1 1 3 1 1 1 1 1 1 3 1 3 1 1
3 2 1 1 1 1 3 2 1 1 1 2 1 3 3 1 1 1 1 1 1 3 2 2 1 2 3 1 1 3 3 1 1 3 1 3 1 1 1 1
3 3 3 1 3 2 2 1 2 1 1 2 3 3 1 2 1 1 1 1 1 3 1 3 1 3 1 3 1 1 3 1 3 3 1 2 1 1 1 3
1 1 2 3 1 1 3 1 3 3 1 3 1 3 1 1 1 1 1 1 1 1 3 1 3 3 1 3 1 1 2 1 1 1 1 2 3 3 3 1
1 1 1 3 1 1 3 3 3 3 3 1 3 3 2 3 2 2 3 3 1 1 1 2 1 1 1 1 3 1 1 2 1 1 3 3 1 1 3 1
3 1 1 3 1 1 1 1 1 1 1 1 1 1 2 1 3 3 2 1 2 1 2 1 1 2 1 1 1 3 1 1 1 1 3 2 1 1 2 1
1 3 1 1 1 3 1 3 1 3 2 1 1 2 3 1 1 1 2 2 1 3 1 3 2 2 1 1 1 2 3 2 3 1 1 1 1 3 1 1
3 2 3 1 2 3 1 3 2 3 1 3 3 1 1 3 3 3 1 2 1 2 3 1 3 1 1 1 1 1 1 1 1 2 3 1 2 3 1 1
1 1 3 1 1 1 3 1 3 1 3 1 1 1 1 3 3 1 1 3 1 1 1 3 1 3 2 1 3 3 3 1 1 2 1 3 3 2 1 1
2 1 1 3 3 2 1 3 3 1 1 3 1 3 1 3 3 3 1 3 3 3 3 2 3 1 1 3 2 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 3 1 1 3 1 2 3 3 3 1 3 3 3 3 3 1 1 3 1 3 2 1 1 3 3 1 1 1 1 3 1 3 2 3 3
1 3 3 3 3 1 2 1 2 2 3 1 1 1 3 1 1 3 3 3 1 1 1 3 1 1 3 1 1 1 1 1 1 1 3 1 3 3 1 1
3 2 3 1 1 1 1 3 3 3 3 3 1 1 3 1 1 3 1 1 1 1 3 1 1 1 1 1 3 1 1 1 1 3 1 2 2 3 1 1
1 1 2 3 1 1 2 3 3 1 3 3 3 1 3 3 1 1 1 3 3 2 1 1 1 2 3 2 3 3 3 1 1 1 1 1 3 2 3 1
1 1 3 3 3 1 1 1 3 1 3 2 2 1 1 1 3 3 3 3 3 1 3 2 2 3 1 1 1 1 3 1 3 2 1 1 3 3 1 1
2 3 1 3 1 3 3 3 1 2 1 1 1 2 3 3 1 3 3 1 1 1 1 1 1 1 1 2 2 1 3 3 2 1 1 1 3 1 1 3
1 1 1 1 1 2 3 1 2 1 1 2 3 2 3 1 1 2 2 1 3 1 3 1 1 1 3 1 3 3 1 1 1 1 1 2 1 1 3 3
3 1 1 1 1 2 1 3 3 3 2 3 2 2 1 3 1 3 3 1 3 1 1 3 1 1 3 3 3 1 2 1 1 3 1 1 3 3 3 3
1 1 1 3 1 1 1 3 3 1 3 1 2 1 1 1 3 3 1 1 2 2 3 1 1 1 1 1 2 3 1 3 3 2 1 2 3 1 3 3
1 1 3 2 1 3 2 2 3 1 1 1 1 3 1 1 1 3 1 1 1 1 3 1 2 3 1 1 1 2 1 1 2 3 3 3 1 3 3 1
1 1 2 2 1 3 3 3 3 3 3 2 1 1 1 2 3 3 3 1 3 1 1 1 1 2 3 2 3 1 3 2 2 1 3 1 2 3 1 2
2 3 1 1 1 2 1 1 2 1 1 2 3 3 3 3 3 2 1 1 3 3 3 3 3 1 1 3 1 2 3 3 1 2 1 3 1 1 3 1
1 3 3 1 2 1 1 3 3 3 2 1 3 2 3 3 1 1 3 1 1 1 3 1 1 1 3 1 2 1 2 1 3 3 1 2 3 1 1 1
2 3 2 3 3 1 3 1 1 1 1 3 1 1 3 1 1 1 3 1 3 3 1 1 1 1 3 1 1 1 1 3 3 3 3 3 3 1 1 3
2 1 1 1 1 1 3 1 2 1 3 3 1 1 1 3 3 1 1 3 3 3 1 3 3 2 1 3 1 1 1 3 3 2 1 1 1 1 1 3
1 3 1 1 1 1 3 3 3 3 3 2 2 3 3 1 3 3 1 3 3 3 1 3 2 1 1 3 1 1 3 1 3 1 1 2 1 1 1 2
3 1 3 3 3 3 1 3 3 3 1 1 2 1 1 1 1 1 1 3 2 3 3 3 1 3 3 1 1 2 1 1 3 1 3 3 1 1 3 2
1 1 1 1 1 1 3 1 1 2 2 1 2 1 1 1 3 1 3 3 1 1 3 1 3 1 3 1 3 1 3 3 1 1 3 3 1 1 1 3
1 1 2 2 3 1 1 1 1 3 1 1 1 1 2 1 1 1 1 3 1 3 1 3 1 1 3 2 3 1 3 1 3 3 1 1 1 1 1 3
3 2 1 3 3 3 1 2 3 1 1 1 1 2 1 3 2 3 3 2 1 3 3 1 3 1 3 1 3 1 1 2 3 3 1 1 3 2 1 3
1 1 3 3 2 2 1 1 1 1 3 2 3 2 3 1 1 1 1 3 3 1 1 3 1 1 1 2 2 1 1 1 3 1 1 2 3 1 3 3
3 1 3 3 3 1 1 1 1 1 1 1 1 3 3 1 1 1 1 1 3 1 3 1 3 3 3 1 1 1 1 1 3 2 3 3 1 1 1 3
1 1 2 3 3 3 1 1 1 3 3 1 1 1 1 2 1 1 1 1 1 1 3 1 1 2 3 2 3 1 3 3 1 3 3 1 3 3 1 3
3 2 3 1 3 1 3 1 3 3 1 3 3 3 3 3 3 1 3 1 2 3 2 3 1 3 3 3 1 2 3 1 3 3 3 1 3 1 2 1
1 3 1 1 3 3 3 1 1 1 3 2 1 1 1 3 1 2 1 1 2 1 1 1 1 2 1 1 3 1 3 1 2 3 3 1 1 1 1 2
1 3 1 1 2 2 1 1 3 3 1 1 3 2 3 1 3 3 1 3 3 1 1 1 3 1 2 1 1 2 1 3 3 3 2 2 3 3 1 3
3 3 1 2 2 3 1 3 1 2 1 1 1 1 1 3 3 2 3 1 1 3 3 1 1 3 1 1 1 2 1 1 3 1 1 3 2 3 2 3
2 1 2 3 2 1 1 3 3 2 1 1 3 1 1 2 3 1 1 3 1 1 1 1 3 1 2 1 1 1 3 3 3 1 1 3 3 1 1 3
2 1 1 1 3 3 1 1 1 1 1 2 1 1 3 1 3 3 3 1 3 1 1 1 3 1 3 3 3 1 1 3 3 2 2 1 1 3 1 3
3 3 3 1 1 3 3 1 2 2 3 3 3 1 3 3 1 2 1 2 3 1 1 1 1 1 3 1 3 3 1 3 2 1 2 1 2 3 1 3
2 2 2 2 3 2 2 3 2 3 2 3 3 3 3 1 2 3 1 1 3 3 2 1 2 3 2 2 1 1 3 1 2 2 3 2 3 3 2 2
3 1 2 2 3 3 1 3 2 3 3 2 1 1 2 1 1 2 2 2 3 2 3 1 2 3 2 2 1 1 2 2 3 3 2 1 3 3 3 3
1 2 2 1 2 2 2 1 3 1 1 2 1 1 1 1 3 2 3 3 2 3 3 2 1 1 3 3 1 2 1 2 2 2 1 3 1 2 2 1
2 2 1 2 1 2 1 1 1 1 3 2 2 1 2 2 2 2 3 3 3 3 3 3 2 1 2 2 2 2 3 2 3 1 3 3 2 2 3 1
2 2 1 3 2 3 2 3 2 3 2 2 3 2 2 3 2 2 2 2 2 2 3 2 2 3 1 3 2 2 2 1 2 2 2 2 1 2 2 2
1 3 2 1 3 2 2 3 2 2 2 3 3 3 3 1 2 3 2 3 3 2 2 3 2 1 3 1 3 1 2 3 3 3 3 2 2 2 2 2
2 3 1 3 3 1 3 2 2 1 2 3 2 2 2 3 2 3 2 2 2 2 2 3 1 1 1 3 3 3 1 1 3 1 2 1 2 2 2 1
3 2 2 2 2 2 2 3 2 2 1 1 1 1 3 1 2 1 3 3 2 3 2 3 1 1 1 1 2 1 3 1 3 1 1 2 2 2 3 3
2 3 2 2 2 2 2 2 2 3 2 2 2 3 2 1 3 2 2 2 2 2 2 1 3 2 2 2 2 1 3 2 1 2 3 1 3 1 2 1
2 2 3 2 2 2 3 1 1 3 3 3 2 1 2 3 2 3 3 2 2 2 3 3 3 1 1 3 2 3 2 3 3 1 3 1 3 1 3 3
2 2 2 3 3 1 3 2 3 2 2 1 1 2 2 1 3 3 1 2 2 3 3 2 1 2 3 3 3 2 2 1 1 2 3 1 3 2 3 3
2 3 2 2 3 3 1 3 2 1 3 3 3 1 3 2 3 1 2 1 2 3 2 1 1 2 1 3 3 2 3 3 2 2 2 3 2 1 3 3
2 2 2 2 2 3 3 1 1 1 3 1 3 3 2 2 2 1 1 2 1 2 2 3 2 2 1 1 2 2 1 2 2 3 2 2 1 3 3 2
3 3 3 2 2 3 3 2 2 3 2 3 2 2 3 1 1 1 3 2 2 3 2 3 3 1 2 2 3 2 1 2 2 3 3 2 1 3 2 2
3 2 1 2 3 3 2 2 1 2 3 2 2 3 2 3 3 3 1 3 2 2 3 2 3 1 3 1 3 1 2 3 2 3 1 2 2 3 2 2
3 3 3 3 2 3 2 3 3 2 2 3 1 1 3 2 2 2 2 1 2 1 1 1 3 3 2 2 3 2 1 2 3 2 2 2 2 3 1 1
3 3 2 2 2 2 3 2 2 2 3 2 3 3 2 1 3 2 1 3 3 2 1 2 3 2 2 1 3 1 2 3 3 1 3 2 2 2 1 3
2 2 3 1 3 2 2 1 1 3 3 2 2 3 3 3 1 3 2 2 2 3 2 3 3 1 2 3 1 2 3 2 2 2 3 2 2 3 3 3
2 1 2 3 2 2 3 3 3 2 2 2 2 2 3 1 3 3 2 1 1 3 3 2 3 2 2 1 3 3 3 3 3 3 2 1 2 2 3 3
3 3 3 3 1 1 2 3 2 2 3 2 3 3 2 3 3 1 3 1 2 3 2 1 2 3 1 3 2 2 3 1 2 2 3 1 3 3 3 2
2 3 2 3 1 2 2 3 1 2 1 1 3 1 2 1 2 3 3 1 2 2 2 1 3 3 2 2 2 2 2 3 1 2 1 2 1 2 2 1
3 2 2 2 2 2 1 3 3 3 3 2 2 1 1 2 3 2 2 1 1 2 2 3 2 3 2 3 3 1 2 2 2 2 2 2 2 2 3 2
2 3 2 2 3 1 2 1 3 3 2 3 3 2 1 2 2 1 2 2 2 2 3 2 3 3 3 2 3 2 2 3 1 3 2 2 3 2 3 3
3 3 2 3 3 2 2 2 2 3 2 3 1 3 3 3 1 2 1 2 1 2 3 2 3 2 1 1 1 3 3 1 1 2 3 2 1 1 2 2
2 3 2 2 2 2 2 2 3 2 2 3 3 1 3 3 2 2 3 1 2 1 3 1 2 3 2 2 1 1 3 2 2 3 1 3 3 2 2 3
2 3 2 2 2 2 2 2 1 2 2 2 2 1 2 2 2 3 2 2 2 3 3 2 2 3 3 1 3 3 2 2 2 3 3 3 3 1 2 1
3 3 3 2 2 2 2 2 1 3 2 1 2 1 2 1 1 3 3 2 2 3 2 2 3 3 3 2 1 3 1 1 3 2 3 2 3 3 1 1
1 1 2 2 2 3 3 3 1 2 3 3 2 2 1 3 2 2 3 2 2 2 3 2 3 2 1 2 3 1 1 1 2 3 3 1 3 2 2 2
1 2 3 1 3 2 2 2 2 3 2 1 3 2 3 2 2 2 2 2 2 1 3 3 1 2 2 1 2 2 3 2 2 2 1 2 2 3 1 3
1 2 3 1 1 3 3 3 2 3 3 3 3 1 1 2 2 1 2 1 3 2 2 3 3 3 3 3 2 1 2 3 3 3 3 2 3 2 2 1
1 1 2 3 3 3 2 2 3 1 3 3 1 2 3 2 3 1 1 3 1 2 2 2 1 1 1 1 2 3 2 3 1 2 2 1 3 2 3 3
2 2 2 3 1 3 2 2 2 2 2 3 3 1 3 1 2 3 1 1 3 3 2 1 1 2 2 3 2 3 3 2 2 2 1 2 2 2 1 3
1 1 2 2 3 3 3 2 2 2 2 2 3 2 3 1 1 1 1 2 2 2 2 3 2 3 3 1 1 2 1 2 3 3 2 1 2 1 3 2
3 2 3 2 3 3 3 2 3 1 3 3 3 1 2 3 1 2 1 2 1 3 2 2 1 2 2 3 3 2 2 2 2 3 3 1 2 2 2 2
3 1 2 1 3 2 2 1 2 2 1 2 2 1 3 2 3 3 2 3 1 3 2 2 2 3 2 2 2 1 1 2 2 1 3 1 1 3 1 2
2 2 2 2 3 2 2 3 2 1 1 3 2 3 3 3 2 3 3 2 2 2 1 1 1 3 1 2 2 2 1 2 3 3 2 3 3 2 1 3
1 2 1 1 2 3 1 3 2 2 2 2 2 1 3 2 3 3 3 2 3 1 2 1 2 2 3 1 1 3 3 3 3 3 2 1 3 2 3 3
3 2 1 1 2 2 3 3 3 2 2 3 1 3 2 1 2 2 2 3 3 2 2 2 2 2 3 2 2 3 3 3 2 2 1 3 2 3 2 3
2 2 1 1 1 1 2 3 2 1 2 3 3 3 1 2 1 2 3 3 2 3 2 3 2 2 3 1 1 3 2 1 3 3 2 2 3 2 1 2
2 3 3 2 1 1 1 1 3 3 2 1 1 2 1 2 1 2 2 2 3 1 3 2 2 3 3 1 3 2 1 2 2 3 1 2 2 2 2 1
Δ birds Δ grass Δ birds × =
Δ grass Δ landowners Δ landowners
AgGrassland
Forest
MODELING APPROACH
Species
Breeding
Migration
Wintering
• Need to model how land changes affect birds within a landscape
• Use a spatially-explicit model to incorporate landscape-level effects (e.g., area, configuration, edge, etc.) on the biology of the species
• Make assumptions explicit
Δ birds Δ grass
Breeding Migration Wintering
Nest DensityAdult
Survival
Nest succes
s
Breeding populati
on
Juvenile
Survival
Edge Effect
Edge Effect
Patch SizeHig
h
?
Δ birds Δ grass
Landscape Model
Smallest pixel that can support a nest
Egg survival decreased because forest cover increased
Nest density in grassland pixel as a function of land cover.
Nest site
Breeding Migration Wintering
Δ birds Δ grass
AgGrassland
Forest
Biological ConsequencesConservation Design
Profit-maximizing Producer
Landscape
ConservationistLandscape
1 2 1 1 3 1 3 1 3 1 2 3 2 1 1 1 1 2 3 3 2 1 1 1 2 3 1 1 3 1 1 1 1 1 1 3 1 3 1 1
3 2 1 1 1 1 3 2 1 1 1 2 1 3 3 1 1 1 1 1 1 3 2 2 1 2 3 1 1 3 3 1 1 3 1 3 1 1 1 1
3 3 3 1 3 2 2 1 2 1 1 2 3 3 1 2 1 1 1 1 1 3 1 3 1 3 1 3 1 1 3 1 3 3 1 2 1 1 1 3
1 1 2 3 1 1 3 1 3 3 1 3 1 3 1 1 1 1 1 1 1 1 3 1 3 3 1 3 1 1 2 1 1 1 1 2 3 3 3 1
1 1 1 3 1 1 3 3 3 3 3 1 3 3 2 3 2 2 3 3 1 1 1 2 1 1 1 1 3 1 1 2 1 1 3 3 1 1 3 1
3 1 1 3 1 1 1 1 1 1 1 1 1 1 2 1 3 3 2 1 2 1 2 1 1 2 1 1 1 3 1 1 1 1 3 2 1 1 2 1
1 3 1 1 1 3 1 3 1 3 2 1 1 2 3 1 1 1 2 2 1 3 1 3 2 2 1 1 1 2 3 2 3 1 1 1 1 3 1 1
3 2 3 1 2 3 1 3 2 3 1 3 3 1 1 3 3 3 1 2 1 2 3 1 3 1 1 1 1 1 1 1 1 2 3 1 2 3 1 1
1 1 3 1 1 1 3 1 3 1 3 1 1 1 1 3 3 1 1 3 1 1 1 3 1 3 2 1 3 3 3 1 1 2 1 3 3 2 1 1
2 1 1 3 3 2 1 3 3 1 1 3 1 3 1 3 3 3 1 3 3 3 3 2 3 1 1 3 2 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 3 1 1 3 1 2 3 3 3 1 3 3 3 3 3 1 1 3 1 3 2 1 1 3 3 1 1 1 1 3 1 3 2 3 3
1 3 3 3 3 1 2 1 2 2 3 1 1 1 3 1 1 3 3 3 1 1 1 3 1 1 3 1 1 1 1 1 1 1 3 1 3 3 1 1
3 2 3 1 1 1 1 3 3 3 3 3 1 1 3 1 1 3 1 1 1 1 3 1 1 1 1 1 3 1 1 1 1 3 1 2 2 3 1 1
1 1 2 3 1 1 2 3 3 1 3 3 3 1 3 3 1 1 1 3 3 2 1 1 1 2 3 2 3 3 3 1 1 1 1 1 3 2 3 1
1 1 3 3 3 1 1 1 3 1 3 2 2 1 1 1 3 3 3 3 3 1 3 2 2 3 1 1 1 1 3 1 3 2 1 1 3 3 1 1
2 3 1 3 1 3 3 3 1 2 1 1 1 2 3 3 1 3 3 1 1 1 1 1 1 1 1 2 2 1 3 3 2 1 1 1 3 1 1 3
1 1 1 1 1 2 3 1 2 1 1 2 3 2 3 1 1 2 2 1 3 1 3 1 1 1 3 1 3 3 1 1 1 1 1 2 1 1 3 3
3 1 1 1 1 2 1 3 3 3 2 3 2 2 1 3 1 3 3 1 3 1 1 3 1 1 3 3 3 1 2 1 1 3 1 1 3 3 3 3
1 1 1 3 1 1 1 3 3 1 3 1 2 1 1 1 3 3 1 1 2 2 3 1 1 1 1 1 2 3 1 3 3 2 1 2 3 1 3 3
1 1 3 2 1 3 2 2 3 1 1 1 1 3 1 1 1 3 1 1 1 1 3 1 2 3 1 1 1 2 1 1 2 3 3 3 1 3 3 1
1 1 2 2 1 3 3 3 3 3 3 2 1 1 1 2 3 3 3 1 3 1 1 1 1 2 3 2 3 1 3 2 2 1 3 1 2 3 1 2
2 3 1 1 1 2 1 1 2 1 1 2 3 3 3 3 3 2 1 1 3 3 3 3 3 1 1 3 1 2 3 3 1 2 1 3 1 1 3 1
1 3 3 1 2 1 1 3 3 3 2 1 3 2 3 3 1 1 3 1 1 1 3 1 1 1 3 1 2 1 2 1 3 3 1 2 3 1 1 1
2 3 2 3 3 1 3 1 1 1 1 3 1 1 3 1 1 1 3 1 3 3 1 1 1 1 3 1 1 1 1 3 3 3 3 3 3 1 1 3
2 1 1 1 1 1 3 1 2 1 3 3 1 1 1 3 3 1 1 3 3 3 1 3 3 2 1 3 1 1 1 3 3 2 1 1 1 1 1 3
1 3 1 1 1 1 3 3 3 3 3 2 2 3 3 1 3 3 1 3 3 3 1 3 2 1 1 3 1 1 3 1 3 1 1 2 1 1 1 2
3 1 3 3 3 3 1 3 3 3 1 1 2 1 1 1 1 1 1 3 2 3 3 3 1 3 3 1 1 2 1 1 3 1 3 3 1 1 3 2
1 1 1 1 1 1 3 1 1 2 2 1 2 1 1 1 3 1 3 3 1 1 3 1 3 1 3 1 3 1 3 3 1 1 3 3 1 1 1 3
1 1 2 2 3 1 1 1 1 3 1 1 1 1 2 1 1 1 1 3 1 3 1 3 1 1 3 2 3 1 3 1 3 3 1 1 1 1 1 3
3 2 1 3 3 3 1 2 3 1 1 1 1 2 1 3 2 3 3 2 1 3 3 1 3 1 3 1 3 1 1 2 3 3 1 1 3 2 1 3
1 1 3 3 2 2 1 1 1 1 3 2 3 2 3 1 1 1 1 3 3 1 1 3 1 1 1 2 2 1 1 1 3 1 1 2 3 1 3 3
3 1 3 3 3 1 1 1 1 1 1 1 1 3 3 1 1 1 1 1 3 1 3 1 3 3 3 1 1 1 1 1 3 2 3 3 1 1 1 3
1 1 2 3 3 3 1 1 1 3 3 1 1 1 1 2 1 1 1 1 1 1 3 1 1 2 3 2 3 1 3 3 1 3 3 1 3 3 1 3
3 2 3 1 3 1 3 1 3 3 1 3 3 3 3 3 3 1 3 1 2 3 2 3 1 3 3 3 1 2 3 1 3 3 3 1 3 1 2 1
1 3 1 1 3 3 3 1 1 1 3 2 1 1 1 3 1 2 1 1 2 1 1 1 1 2 1 1 3 1 3 1 2 3 3 1 1 1 1 2
1 3 1 1 2 2 1 1 3 3 1 1 3 2 3 1 3 3 1 3 3 1 1 1 3 1 2 1 1 2 1 3 3 3 2 2 3 3 1 3
3 3 1 2 2 3 1 3 1 2 1 1 1 1 1 3 3 2 3 1 1 3 3 1 1 3 1 1 1 2 1 1 3 1 1 3 2 3 2 3
2 1 2 3 2 1 1 3 3 2 1 1 3 1 1 2 3 1 1 3 1 1 1 1 3 1 2 1 1 1 3 3 3 1 1 3 3 1 1 3
2 1 1 1 3 3 1 1 1 1 1 2 1 1 3 1 3 3 3 1 3 1 1 1 3 1 3 3 3 1 1 3 3 2 2 1 1 3 1 3
3 3 3 1 1 3 3 1 2 2 3 3 3 1 3 3 1 2 1 2 3 1 1 1 1 1 3 1 3 3 1 3 2 1 2 1 2 3 1 3
0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0
0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 0 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0
0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 1 0 0
1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0
0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0
0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0
0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0
0 0 0 0 0 1 0 0 1 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
0 0 0 0 0 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0
0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0
0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 1 0 0 0 1 0 0 1
1 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0
0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0 0
1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1
0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1
0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0
0 0 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0
0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1
0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 0 0 0 0
0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0
1 0 1 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0
0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0
Nest potentialNest potential
2 2 2 2 3 2 2 3 2 3 2 3 3 3 3 1 2 3 1 1 3 3 2 1 2 3 2 2 1 1 3 1 2 2 3 2 3 3 2 2
3 1 2 2 3 3 1 3 2 3 3 2 1 1 2 1 1 2 2 2 3 2 3 1 2 3 2 2 1 1 2 2 3 3 2 1 3 3 3 3
1 2 2 1 2 2 2 1 3 1 1 2 1 1 1 1 3 2 3 3 2 3 3 2 1 1 3 3 1 2 1 2 2 2 1 3 1 2 2 1
2 2 1 2 1 2 1 1 1 1 3 2 2 1 2 2 2 2 3 3 3 3 3 3 2 1 2 2 2 2 3 2 3 1 3 3 2 2 3 1
2 2 1 3 2 3 2 3 2 3 2 2 3 2 2 3 2 2 2 2 2 2 3 2 2 3 1 3 2 2 2 1 2 2 2 2 1 2 2 2
1 3 2 1 3 2 2 3 2 2 2 3 3 3 3 1 2 3 2 3 3 2 2 3 2 1 3 1 3 1 2 3 3 3 3 2 2 2 2 2
2 3 1 3 3 1 3 2 2 1 2 3 2 2 2 3 2 3 2 2 2 2 2 3 1 1 1 3 3 3 1 1 3 1 2 1 2 2 2 1
3 2 2 2 2 2 2 3 2 2 1 1 1 1 3 1 2 1 3 3 2 3 2 3 1 1 1 1 2 1 3 1 3 1 1 2 2 2 3 3
2 3 2 2 2 2 2 2 2 3 2 2 2 3 2 1 3 2 2 2 2 2 2 1 3 2 2 2 2 1 3 2 1 2 3 1 3 1 2 1
2 2 3 2 2 2 3 1 1 3 3 3 2 1 2 3 2 3 3 2 2 2 3 3 3 1 1 3 2 3 2 3 3 1 3 1 3 1 3 3
2 2 2 3 3 1 3 2 3 2 2 1 1 2 2 1 3 3 1 2 2 3 3 2 1 2 3 3 3 2 2 1 1 2 3 1 3 2 3 3
2 3 2 2 3 3 1 3 2 1 3 3 3 1 3 2 3 1 2 1 2 3 2 1 1 2 1 3 3 2 3 3 2 2 2 3 2 1 3 3
2 2 2 2 2 3 3 1 1 1 3 1 3 3 2 2 2 1 1 2 1 2 2 3 2 2 1 1 2 2 1 2 2 3 2 2 1 3 3 2
3 3 3 2 2 3 3 2 2 3 2 3 2 2 3 1 1 1 3 2 2 3 2 3 3 1 2 2 3 2 1 2 2 3 3 2 1 3 2 2
3 2 1 2 3 3 2 2 1 2 3 2 2 3 2 3 3 3 1 3 2 2 3 2 3 1 3 1 3 1 2 3 2 3 1 2 2 3 2 2
3 3 3 3 2 3 2 3 3 2 2 3 1 1 3 2 2 2 2 1 2 1 1 1 3 3 2 2 3 2 1 2 3 2 2 2 2 3 1 1
3 3 2 2 2 2 3 2 2 2 3 2 3 3 2 1 3 2 1 3 3 2 1 2 3 2 2 1 3 1 2 3 3 1 3 2 2 2 1 3
2 2 3 1 3 2 2 1 1 3 3 2 2 3 3 3 1 3 2 2 2 3 2 3 3 1 2 3 1 2 3 2 2 2 3 2 2 3 3 3
2 1 2 3 2 2 3 3 3 2 2 2 2 2 3 1 3 3 2 1 1 3 3 2 3 2 2 1 3 3 3 3 3 3 2 1 2 2 3 3
3 3 3 3 1 1 2 3 2 2 3 2 3 3 2 3 3 1 3 1 2 3 2 1 2 3 1 3 2 2 3 1 2 2 3 1 3 3 3 2
2 3 2 3 1 2 2 3 1 2 1 1 3 1 2 1 2 3 3 1 2 2 2 1 3 3 2 2 2 2 2 3 1 2 1 2 1 2 2 1
3 2 2 2 2 2 1 3 3 3 3 2 2 1 1 2 3 2 2 1 1 2 2 3 2 3 2 3 3 1 2 2 2 2 2 2 2 2 3 2
2 3 2 2 3 1 2 1 3 3 2 3 3 2 1 2 2 1 2 2 2 2 3 2 3 3 3 2 3 2 2 3 1 3 2 2 3 2 3 3
3 3 2 3 3 2 2 2 2 3 2 3 1 3 3 3 1 2 1 2 1 2 3 2 3 2 1 1 1 3 3 1 1 2 3 2 1 1 2 2
2 3 2 2 2 2 2 2 3 2 2 3 3 1 3 3 2 2 3 1 2 1 3 1 2 3 2 2 1 1 3 2 2 3 1 3 3 2 2 3
2 3 2 2 2 2 2 2 1 2 2 2 2 1 2 2 2 3 2 2 2 3 3 2 2 3 3 1 3 3 2 2 2 3 3 3 3 1 2 1
3 3 3 2 2 2 2 2 1 3 2 1 2 1 2 1 1 3 3 2 2 3 2 2 3 3 3 2 1 3 1 1 3 2 3 2 3 3 1 1
1 1 2 2 2 3 3 3 1 2 3 3 2 2 1 3 2 2 3 2 2 2 3 2 3 2 1 2 3 1 1 1 2 3 3 1 3 2 2 2
1 2 3 1 3 2 2 2 2 3 2 1 3 2 3 2 2 2 2 2 2 1 3 3 1 2 2 1 2 2 3 2 2 2 1 2 2 3 1 3
1 2 3 1 1 3 3 3 2 3 3 3 3 1 1 2 2 1 2 1 3 2 2 3 3 3 3 3 2 1 2 3 3 3 3 2 3 2 2 1
1 1 2 3 3 3 2 2 3 1 3 3 1 2 3 2 3 1 1 3 1 2 2 2 1 1 1 1 2 3 2 3 1 2 2 1 3 2 3 3
2 2 2 3 1 3 2 2 2 2 2 3 3 1 3 1 2 3 1 1 3 3 2 1 1 2 2 3 2 3 3 2 2 2 1 2 2 2 1 3
1 1 2 2 3 3 3 2 2 2 2 2 3 2 3 1 1 1 1 2 2 2 2 3 2 3 3 1 1 2 1 2 3 3 2 1 2 1 3 2
3 2 3 2 3 3 3 2 3 1 3 3 3 1 2 3 1 2 1 2 1 3 2 2 1 2 2 3 3 2 2 2 2 3 3 1 2 2 2 2
3 1 2 1 3 2 2 1 2 2 1 2 2 1 3 2 3 3 2 3 1 3 2 2 2 3 2 2 2 1 1 2 2 1 3 1 1 3 1 2
2 2 2 2 3 2 2 3 2 1 1 3 2 3 3 3 2 3 3 2 2 2 1 1 1 3 1 2 2 2 1 2 3 3 2 3 3 2 1 3
1 2 1 1 2 3 1 3 2 2 2 2 2 1 3 2 3 3 3 2 3 1 2 1 2 2 3 1 1 3 3 3 3 3 2 1 3 2 3 3
3 2 1 1 2 2 3 3 3 2 2 3 1 3 2 1 2 2 2 3 3 2 2 2 2 2 3 2 2 3 3 3 2 2 1 3 2 3 2 3
2 2 1 1 1 1 2 3 2 1 2 3 3 3 1 2 1 2 3 3 2 3 2 3 2 2 3 1 1 3 2 1 3 3 2 2 3 2 1 2
2 3 3 2 1 1 1 1 3 3 2 1 1 2 1 2 1 2 2 2 3 1 3 2 2 3 3 1 3 2 1 2 2 3 1 2 2 2 2 1
1 1 1 1 0 1 1 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 1 1 0 0 0 0 1 1 0 1 0 0 1 1
0 0 1 1 0 0 0 0 1 0 0 1 0 0 1 0 0 1 1 1 0 1 0 0 1 0 1 1 0 0 1 1 0 0 1 0 0 0 0 0
0 1 1 0 1 1 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0 1 0 1 1 1 0 0 0 1 1 0
1 1 0 1 0 1 0 0 0 0 0 1 1 0 1 1 1 1 0 0 0 0 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 1 0 0
1 1 0 0 1 0 1 0 1 0 1 1 0 1 1 0 1 1 1 1 1 1 0 1 1 0 0 0 1 1 1 0 1 1 1 1 0 1 1 1
0 0 1 0 0 1 1 0 1 1 1 0 0 0 0 0 1 0 1 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 1 1 1 1 1
1 0 0 0 0 0 0 1 1 0 1 0 1 1 1 0 1 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0
0 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 1 0 0
1 0 1 1 1 1 1 1 1 0 1 1 1 0 1 0 0 1 1 1 1 1 1 0 0 1 1 1 1 0 0 1 0 1 0 0 0 0 1 0
1 1 0 1 1 1 0 0 0 0 0 0 1 0 1 0 1 0 0 1 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0
1 1 1 0 0 0 0 1 0 1 1 0 0 1 1 0 0 0 0 1 1 0 0 1 0 1 0 0 0 1 1 0 0 1 0 0 0 1 0 0
1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 1 0 1 0 0 1 0 0 0 1 0 0 1 1 1 0 1 0 0 0
1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 0 0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1
0 0 0 1 1 0 0 1 1 0 1 0 1 1 0 0 0 0 0 1 1 0 1 0 0 0 1 1 0 1 0 1 1 0 0 1 0 0 1 1
0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 1 0 1 0 0 1 1 0 1 1
0 0 0 0 1 0 1 0 0 1 1 0 0 0 0 1 1 1 1 0 1 0 0 0 0 0 1 1 0 1 0 1 0 1 1 1 1 0 0 0
0 0 1 1 1 1 0 1 1 1 0 1 0 0 1 0 0 1 0 0 0 1 0 1 0 1 1 0 0 0 1 0 0 0 0 1 1 1 0 0
1 1 0 0 0 1 1 0 0 0 0 1 1 0 0 0 0 0 1 1 1 0 1 0 0 0 1 0 0 1 0 1 1 1 0 1 1 0 0 0
1 0 1 0 1 1 0 0 0 1 1 1 1 1 0 0 0 0 1 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 1 0 1 1 0 0
0 0 0 0 0 0 1 0 1 1 0 1 0 0 1 0 0 0 0 0 1 0 1 0 1 0 0 0 1 1 0 0 1 1 0 0 0 0 0 1
1 0 1 0 0 1 1 0 0 1 0 0 0 0 1 0 1 0 0 0 1 1 1 0 0 0 1 1 1 1 1 0 0 1 0 1 0 1 1 0
0 1 1 1 1 1 0 0 0 0 0 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 1 0 0 0 1 1 1 1 1 1 1 1 0 1
1 0 1 1 0 0 1 0 0 0 1 0 0 1 0 1 1 0 1 1 1 1 0 1 0 0 0 1 0 1 1 0 0 0 1 1 0 1 0 0
0 0 1 0 0 1 1 1 1 0 1 0 0 0 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 0 0 0 1 0 1 0 0 1 1
1 0 1 1 1 1 1 1 0 1 1 0 0 0 0 0 1 1 0 0 1 0 0 0 1 0 1 1 0 0 0 1 1 0 0 0 0 1 1 0
1 0 1 1 1 1 1 1 0 1 1 1 1 0 1 1 1 0 1 1 1 0 0 1 1 0 0 0 0 0 1 1 1 0 0 0 0 0 1 0
0 0 0 1 1 1 1 1 0 0 1 0 1 0 1 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0
0 0 1 1 1 0 0 0 0 1 0 0 1 1 0 0 1 1 0 1 1 1 0 1 0 1 0 1 0 0 0 0 1 0 0 0 0 1 1 1
0 1 0 0 0 1 1 1 1 0 1 0 0 1 0 1 1 1 1 1 1 0 0 0 0 1 1 0 1 1 0 1 1 1 0 1 1 0 0 0
0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 1 0 1 1 0
0 0 1 0 0 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 1 0 0 0 0 1 0 1 0 0 1 1 0 0 1 0 0
1 1 1 0 0 0 1 1 1 1 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 1 1 0 1 0 0 1 1 1 0 1 1 1 0 0
0 0 1 1 0 0 0 1 1 1 1 1 0 1 0 0 0 0 0 1 1 1 1 0 1 0 0 0 0 1 0 1 0 0 1 0 1 0 0 1
0 1 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 0 0 1 1 1 1
0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 1 0 0 1 0 0 0 1 1 1 0 1 1 1 0 0 1 1 0 0 0 0 0 0 1
1 1 1 1 0 1 1 0 1 0 0 0 1 0 0 0 1 0 0 1 1 1 0 0 0 0 0 1 1 1 0 1 0 0 1 0 0 1 0 0
0 1 0 0 1 0 0 0 1 1 1 1 1 0 0 1 0 0 0 1 0 0 1 0 1 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0
0 1 0 0 1 1 0 0 0 1 1 0 0 0 1 0 1 1 1 0 0 1 1 1 1 1 0 1 1 0 0 0 1 1 0 0 1 0 1 0
1 1 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 1 0 0 1 0 1 0 1 1 0 0 0 0 1 0 0 0 1 1 0 1 0 1
1 0 0 1 0 0 0 0 0 0 1 0 0 1 0 1 0 1 1 1 0 0 0 1 1 0 0 0 0 1 0 1 1 0 0 1 1 1 1 0
Δ birds Δ landowners
MigrationBreeding
Occupancy of grassland stopover habitat:
- Grassland and cropland suitable at the local scale (pixel)
- Negative effect of surrounding forest cover
Survivorship in grassland stopover habitat:
- Forage quality of surrounding landscape- Survival greater in grassland than in
cropland
Wintering
Wintering
MigrationBreeding
• We represented a grassland bird’s interaction with the landscape during winter in a similar way to the migration framework.
• However, it was simplified in that only the individual pixel-level determined survivorship.
• We assumed that grassland birds do not use forest sites during the winter and that grassland pixels had higher survivorship than agricultural pixels.
• We further assumed that the over-winter survivorship rate was simply the average survivorship value of all suitable pixels.
Integrating land cover choice and grassland models
• We generated five, 1.44 km2 landscapes that were each filled with 1600, 30-meter pixels.
• We assigned each pixel as grassland, agriculture or forest with the probability of each choice being determined by the alternative-generated results from the land cover choice model.
• We assigned one landscape to represent the breeding area, three to be migratory stopover areas, and one to be the wintering ground.
• Once the landscapes were generated, we applied the spatially-explicit model to them.
• Using this framework, we evaluated each of the 27 landowner by alternative combinations.
• We started each bird population with 100 birds and ran the model for 30 years.
The effect of each alternative policy and landowner on the expected growth of
grassland bird populations:Bird Population Growth Rate
LANDSCAPE TYPE
POLICYProfit-maximizing
Producer Small Farmer Conservationist
Conservation Design -0.12 0.03 0.09
Outreach/Marketing 0.06 0.07 0.09Regulatory/Enforcement -
International-0.11 0.03 0.05
Regulatory/Enforcement - US -0.06 0.03 0.06
Public Land Acquisition -0.2 0.04 0.08
Best Management Practices -0.16 0.07 0.1
Policy - Ecosystem Service 0.03 0.09 0.1
Policy – Economic Incentive 0.05 0.09 0.13
Status Quo -0.23 0.03 0.07
The effect of each alternative policy and landowner on the expected growth of
grassland bird populations:Bird Population Growth Rate
LANDSCAPE TYPE
POLICYProfit-maximizing
Producer Small Farmer Conservationist
Conservation Design -0.12 0.03 0.09
Outreach/Marketing 0.06 0.07 0.09Regulatory/Enforcement -
International-0.11 0.03 0.05
Regulatory/Enforcement - US -0.06 0.03 0.06
Public Land Acquisition -0.2 0.04 0.08
Best Management Practices -0.16 0.07 0.1
Policy - Ecosystem Service 0.03 0.09 0.1
Policy – Economic Incentive 0.05 0.09 0.13
Status Quo -0.23 0.03 0.07
Model Result – Identifying thresholds
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
0.2
0 0.1 0.2 0.3 0.4 0.5 0.6
Gras
slan
d Bird
Pop
ulati
on G
rowth
Rate
Percent Grass Expected from Policy
Progress Following the Workshop
• Allison Vogt connected us with the CEC and RMBO Grasslands efforts.
• Conference call with the CEC is leading to an expanded mapping effort to identify Grassland Priority Conservation Areas throughout eastern North America.
• Began communicating with Rocky Mountain Bird Observatory on developing full life cycle conservation and modeling approaches.
Progress Following the Workshop
• Finalized Outreach Materials (fact sheet, presentation, poster)
• Engaging Bird Habitat Joint Ventures and Landscape Conservation Cooperatives in annual cycle bird models and human dimensions research.
• Reaching out to regional working groups
NEEDS FOR ASSISTANCE• Expand participation in overall framework – Does this make sense? What doesn’t work?– Decision makers – who are they?– Look for and engage other stakeholder groups –
whom are we missing so far?
• Identify support and funding needs– Full-time coordinator!– Funds to obtain missing information (i.e.,
migration and wintering grounds, demographic studies)
• Begin gathering and compiling data to identify information gaps and validate/improve models
NEEDS FOR ASSISTANCE• Develop teams around full life cycle conservation
(breeding, migration, wintering)– We will need to engage partners in Canada ,
US, and Mexico – Specifically, we will ask partners to
communicate and stay in touch, collaborate on projects, and prioritize filling data gaps.
• Maintain and expand coordinated network– E.g., wintering grounds (Mexico and South
America)
WORKSHOP PARTICIPANTS• Coordinators:
– Katie Koch (USFWS, R3, Migratory Bird Program)– Soch Lor (USFWS, R6, Inventory and Monitoring Initiative)
• Coaches: – Eric Lonsdorf (Chicago Botanic Garden)– Evan Grant (USGS, Patuxent Wildlife Research Center)
• Agency representatives:– Marissa Ahlering (The Nature Conservancy)– Laurel Barnhill (USFWS, R4, Inventory and Monitoring Initiative,)– Tom Dailey (National Bobwhite Conservation Initiative)– Ryan Drum (USFWS, R3, HAPET office)– Connie Mueller (USFWS, R6, Lostwood NWR)– David Pavlacky (Rocky Mountain Bird Observatory)– Christine Ribic (USGS, Wisconsin Cooperative Wildlife Research Unit)– Catherine Rideout (USFWS, East Gulf Coastal Plain Joint Venture)– David Sample (Wisconsin Department of Natural Resources)
