Strategic Habitat Conservation: Modeling to support
cooperative, adaptive, science-based management USGS-USFWS Science
Support Partnership Ashton Drew
Slide 2
Outline SSP project context & objectives Building a tool to
meet SHC science and management objectives Species-habitat modeling
approach Future directions
Slide 3
SSP & SHC Challenge Move from static to dynamic thinking
regarding how you collect, summarize, utilize, and share data
Scaling: stepping-down & stepping-up Communicating: science
& management Modeling: general (what) & specific (where)
Management: acting & monitoring
Slide 4
SHC Highlights Biological Planning Delivery of Conservation
Actions Monitoring & Research Conservation Design Selecting
species suitable for modeling Maximizing benefits from existing
data & expertise Knowledge summary & communication tools
Hypotheses & sampling design based on ecological assumptions
and predicted management outcomes Regular maintenance of GIS and
biological data layers Temporal cautionary note Decision support
tools to evaluate alternative actions Integration of value systems
into ecological model Decisions based on available science with
documented assumptions and alternatives considered Multiple scales,
on and off refuge lands Must be documented in a GIS
Slide 5
Pilot Project Objective Aid with step-down of national
population & habitat objectives Partners in Flight 2004
National Goals Bachmans sparrow (250,000) Increase 100%
Brown-headed nuthatch (1.5 mil) Increase 50% Errol Taskin
www.birdsource.org Ecosystem? National Wildlife Refuges? Other
protected lands?
Slide 6
Management Context & Priorities State and refuge level
planning documents Reference national and international plans Set
management priorities in ecosystem context Partnership for
coordinated management in time and space Shift from few to many
species and habitats Quantitative goals & measures of
success
Slide 7
RTNCF Pilot Model Guidelines Bayesian Approach? Two spatial
scales Terrestrial & aquatic species Data-rich & data-poor
(expert opinion) scenarios Start with GAP products Design for
adaptive management use
Slide 8
Starting on the same page... Set population objectives for
species Set abundance goals for RTNCF natural communities Convert
population/abundance objectives into habitat objectives Map
potential conservation areas where deficits exist Step down
population/abundance objectives to individual refuges and partner
lands What do managers want? & What can a model provide? &
What are the objectives of SHC?
Slide 9
Starting on the same page... Set population objectives for
species Set abundance goals for RTNCF natural communities Convert
population/abundance objectives into habitat objectives Map
potential conservation areas where deficits exist Step down
population/abundance objectives to individual refuges and partner
lands Models dont set targets... People do!
Slide 10
Starting on the same page... Set population objectives for
species Set abundance goals for RTNCF natural communities Convert
population/abundance objectives into habitat objectives Map
potential conservation areas where deficits exist Step down
population/abundance objectives to individual refuges and partner
lands Managers starts with national goals... Modeling starts with
local knowledge
Slide 11
Starting on the same page... Set population objectives for
species Set abundance goals for RTNCF natural communities Convert
population/abundance objectives into habitat objectives Map
potential conservation areas where deficits exist Step down
population/abundance objectives to individual refuges and partner
lands Is habitat acquisition the only management action under
consideration?
Slide 12
Starting on the same page... Set population objectives for
species Set abundance goals for RTNCF natural communities Convert
population/abundance objectives into habitat objectives Map
potential conservation areas where deficits exist Step down
population/abundance objectives to individual refuges and partner
lands Single descriptive outcome = knowledge communication tool
Multiple predictive outcomes = predictive decision support
tool
Slide 13
Starting on the same page... Set population objectives for
species Set abundance goals for RTNCF natural communities Convert
population/abundance objectives into habitat objectives Map
potential conservation areas where deficits exist Step down
population/abundance objectives to individual refuges and partner
lands Quantify refuge contributions to populations and habitats
Identify where and how refuge-scale management actions may
contribute to regional objectives Identify where and what
additional research would be most beneficial Coordinate activities
with partner agencies managers to step-down objectives and track
regional progress STATIC vs. DYNAMIC OBJECTIVES
Slide 14
Ecological Step-down TIME SPACE Strategic Land Use Plans
RefugeManagementPlans Policy Guidelines
Slide 15
Ecological Step-down TIME SPACE Strategic Land Use Plans
RefugeManagementPlans BiogeographicRange PatchyResources within
Habitat Habitat Distribution in Regional Landscape Policy
Guidelines
Slide 16
Knowledge & Assumptions Vary with Scale TIME SPACE
Strategic Land Use Plans RefugeManagementPlans BiogeographicRange
PatchyResources within Habitat Habitat Distribution in Regional
Landscape Good GIS data sources, limited knowledge Policy
Guidelines
Slide 17
TIME SPACE Strategic Land Use Plans RefugeManagementPlans
BiogeographicRange PatchyResources within Habitat Habitat
Distribution in Regional Landscape Reasonable knowledge, limited
GIS Policy Guidelines Knowledge & Assumptions Vary with
Scale
Slide 18
Effective Knowledge Transfer (Perera et al. 2007) TIME SPACE
BiogeographicRange Habitat Distribution in Regional Landscape
Strategic Land Use Plans RefugeManagementPlans PatchyResources
within Habitat Policy Guidelines
Slide 19
Amount of habitat, Number of individuals (total, % protected,
spatially-explicit) Significant sources of uncertainty Model
habitat location and quality based on expert opinion and literature
review Field validation & model updating Validated and updated
habitat model Species-Habitat Model
Slide 20
Amount of habitat, Number of individuals (total, % protected,
spatially-explicit) Significant sources of uncertainty Model
habitat location and quality based on expert opinion and literature
review Field validation & model updating Validated and updated
habitat model Species-Habitat Model Science Scenarios Management
Scenarios Hypothesis Set A vs. B Action Set A vs. B Evaluate costs
& risks to compare value Model habitat & population under
alternate scenarios Decision-Support Extension Perform selected
management action or research
Slide 21
Species-Habitat Model King Rail Rallus elegans
Slide 22
Coarse Scale Habitat Models SE GAP provides Potential
Occurrence in SE region King Rail live in Fresh or Brackish Marsh
Habitat (red)
Slide 23
Refuge-level Habitat Variability King Rail Rallus elegans
Slide 24
Bayesian Modeling Approach Prior Probability (Model)
Likelihood(Data) Posterior Probability (Model given the Data) 400m
grid cells containing GAP potential King Rail habitat Prob ( )
Slide 25
Bayesian Belief Network Prob ( ) P (detect KIRA) varies within
GAP predicted habitat Variables from literature and experts
Slide 26
Bayesian Belief Network
ForagingCourtingBroodingWinteringOccurrence Occurrence patterns
depend on activity and time of year **Availability for detection
varies by activity and time of year Prob ( )
Slide 27
Bayesian Belief Network ForagingCourtingBroodingWintering
LandcoverWater Depth Distance to Open Water Occurrence Habitat
Hierarchical habitat selection: macro and microhabitat Limited GIS
data at relevant temporal & spatial scale Prob ( )
Slide 28
Bayesian Belief Network ForagingCourtingBroodingWintering
LandcoverWater Depth Distance to Open Water Occurrence Habitat Prob
( ) Relationships from literature and expert opinion
Slide 29
Bayesian Belief Network Burning Flooding Acquisition
Restoration Occurrence Habitat Management Choices Management
choices influence occurrence patterns via habitat Again, choices
occur at multiple scales ForagingCourtingBroodingWintering
LandcoverWater Depth Distance to Open Water Prob ( )
Slide 30
Bayesian Belief Network ForagingCourtingBroodingWintering
LandcoverWater Depth Distance to Open Water Occurence Habitat
Management Choices Prob ( ) Manager defines potential habitat
management actions Manager decides how to act in given situation
based on probability and uncertainty associated with probability
Decision Burning Flooding Acquisition Restoration
Slide 31
Model Validation & Monitoring 400m grid cells containing
GAP potential King Rail habitat Prob ( ) depends on: patch size,
cell context, distance from open water, salinity, water depth
Stratify survey on GIS relevant assumptions Checking for ommission
& commission Collect microhabitat to distinguish false
assumptions from inadequate data
Slide 32
Science Management Feedback All SEGAP Marsh Patches SEGAP Marsh
Patches >1 acre Experts all suspect a minimum patch size, but
disagree about how small is too small
Slide 33
Science Management Feedback All SEGAP Marsh Patches SEGAP Marsh
Patches >1 acre Source of uncertainty in population and habitat
estimates Uncertainty passes to management decisions
Slide 34
Science Management Feedback All SEGAP Marsh Patches SEGAP Marsh
Patches >1 acre Take management action based on knowledge Select
monitoring sites to test patch size hypothesis that underlies
action
Slide 35
Pilot Project Models vs. The Real Thing
Slide 36
Future Directions? Five things I cant deliver (by June 2009)
pretty GUI interface interactive decision support multi-year
predictions population viability assessment GIS to track management
actions but all are feasible additions to the framework I am
developing
Slide 37
Pilot Model Species King Rail USFWS Focal Species Fresh &
brackish wetlands Back Bay, Cedar Island, Currituck, MacKay Island,
Pea Island, & Swanquarter Swainsons Warbler PIF Priority
Species Bottomland & upland hardwood forest Alligator River,
Great Dismal Swamp, Pocosin Lakes, Roanoke River Blueback Herring
NOAA Species of Concern Anadromous fish Roanoke River, Alligator
River
Slide 38
Modeling Method to Support SHC Pilot project to establish
protocol for: Gathering, summarizing existing data Gathering,
summarizing expert opinion Communally constructing a belief network
Asking science and management what-ifs Designing a monitoring
protocol to reduce uncertainty Updating model with new information
Recommending adjustments to management and/or monitoring
Slide 39
Bayesian Belief Network ForagingCourtingBroodingWintering
LandcoverWater Depth Distance to Open Water Occurence Habitat
Management Choices Prob ( ) Manager defines potential habitat
management actions Manager decides how to act in given situation
based on probability and uncertainty associated with probability
Decision Burning Flooding Acquisition Restoration
Slide 40
Occurrence Habitat Management Choices Ecological relationships
from literature and experts Manager decides how to act in given
situation based on probability and uncertainty associated with
probability Prob ( ) Foraging Spawning Migrating Water Quality
Substrate Shading Pool/Riffle Fish Ladder Landcover Riparian Mgmt.
Dam Removal Bayesian Belief Network Decision
Slide 41
Occurrence Habitat Management Choices Ecological relationships
from literature and experts Manager decides how to act in given
situation based on probability and uncertainty associated with
probability Prob ( ) Eggs Tadpoles Breeding Water Quality Shading #
Dry Days Landcover Artificial Ponds Restoration Aqcuisition
Bayesian Belief Network Decision Hybernating
Slide 42
Many Thanks To GIS Data: SE-GAP & BaSIC Lit Review: E.
Laurent, Q. Mortell Expert Opinions: Anonymous (USFWS, TNC, Natural
Heritage Program, Wildlife Resources Commission, NC Museums)
KIRA-CAP: National cooperation on research, modeling, and funding
Model and Validation Funding: USGS & USFWS
Slide 43
RTNCF SSP Questions: Ashton Drew: [email protected] or
[email protected] Project Website:
www.basic.ncsu.edu/proj/SSP.htmlwww.basic.ncsu.edu/proj/SSP.html
Quantify refuge contributions to populations and habitats Identify
where and how refuge-scale management actions may contribute to
regional objectives Identify where and what additional research
would be most beneficial Coordinate activities with partner
agencies managers to step-down objectives and track regional
progress