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Range of Available Species Habitat Models and Next Steps in the Northeast Region. Steve Williams Biodiversity and Spatial Information Center NC State University / Gap Analysis Program. USFWS NE Region Biologist’ Conference Baltimore, MD February 15 th , 2011. Overview.

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range of available species habitat models and next steps in the northeast region

Range of Available Species Habitat Models and Next Steps in the Northeast Region

Steve Williams

Biodiversity and Spatial Information Center

NC State University / Gap Analysis Program

USFWS NE Region Biologist’ Conference

Baltimore, MD

February 15th, 2011

overview
Overview
  • Model types and tradeoffs
  • Some pertinent examples
  • Models being used in Designing Sustainable Landscape projects
habitat modeling approaches
Habitat Modeling Approaches
  • Knowledge Based
    • dB Matrix
    • HSI, LSI
    • Bayesian Belief Network
  • Statistical Theory
    • Logistic regression
    • Occupancy
    • General linear regression
    • Poisson Regression
    • Hierarchical Spatial Count
    • Time removal
    • Distance
  • Machine Learning
    • Classification & Regression Trees
    • Random Forests
    • Artificial Neural Networks
    • MaxEnt

T. Jones-Farrand

slide4

Demographic

Models

(SEPMs)

Bioenergetic

Models

(TRUEMET)

Quantitative

Models

(C&RT)

Qualitative

Models

(HSI)

Increasing Strength of Scientific Foundation/Inference

Natural History

Descriptions

Ecological Theory

Statistically-sampled

Observations

Extent of Explanation

Process

Pattern

Data Requirements

Large

None/Little

Cost

Large

Little

Taxon

Gamebirds,

Endangered Species

Waterfowl

Shorebirds

Landbirds

Landbirds

T. Jones-Farrand

population data sources
Population Data Sources
  • Breeding Bird Survey
    • Population Info
      • Index of Relative Abundance (Presence)
    • Advantages
      • Consistent protocol & broad spatial coverage
    • Caveats
      • Roadside bias
      • Does not account for detection probability
      • Poor dataset for some species (e.g. timing, rare habitat)
      • Testing site-scale relationships

T. Jones-Farrand

population data sources6
Population Data Sources
  • Point Count Surveys (PCD, R8Bird, collect own)
    • Population Info
      • Index of Relative Abundance (Presence or Density)
    • Advantages
      • Off road, site habitat data, methods to account for detection probability
      • Testing site-scale relationships
    • Caveats
      • Poor temporal & spatial coverage of region
      • Inconsistent protocols across studies

T. Jones-Farrand

dikw model

Wisdom

Knowledge

Information

Data

DIKW Model
  • Data
  • Information
  • Knowledge
  • Wisdom
  • Data
    • Raw observations
      • 1 black-necked stilt
      • 3-acre mudflat
      • MAV
  • Information
    • Relevant data given meaning through relational context
      • 1 black-necked stilt in a 3-acre mudflat in the MAV
  • Knowledge
    • A collection of information, whose intent is to be useful
      • A 3-acre mudflat in the MAV will equal a black-necked stilt
      • # Stilts = (acresMF)/3
  • Wisdom
    • Synthesis of knowledge and an assessment of its value
      • Black-necked stilts prefer open habitats with shallow water

“No data” means we lack raw observations to feed into statistical modeling techniques

It does not mean that we lack understanding or wisdom

J. Tirpak

limitations of modeling with no data
Limitations of Modeling With “No Data”
  • Expert opinion is subjective
  • Translation to meaningful population numbers
    • Rank values
      • Categorical: marginal, suitable, optimal
      • Continuous: HSI scores (0.333)
    • Probabilities
      • P(0.75)
  • Expert opinion is subjective
    • Lack of objectivity
      • Reflects perspective
    • Qualitative not quantitative
      • Relative vs. absolute differences
    • Communication challenge

P (Encounter Site)

J. Tirpak

examples in practice
Examples in Practice
  • HSI models (CHJV & LMVJV)
  • Bayesian Belief Network (ACJV)

J. Tirpak

hsi models chjv lmvjv

Overall

Habitat

Suitability

Score

Hardwood

Basal Area

Suitability

Score

Suitability

Score

NLCD

FIA

HSI models (CHJV & LMVJV)

J. Tirpak

bayesian belief network acjv
Bayesian Belief Network - ACJV

P (Encounter Site)

C.A. Drew

designing sustainable landscapes in the eastern us
Designing Sustainable Landscapes in the Eastern US
  • Initial Pilot Area: South Atlantic Migratory Bird Initiative
  • Future Expansion to Eastern US
  • SE-GAP data set serves as the base dataset
  • NE-GAP data set currently underway
slide13
Knowledge-Driven Models

Utilizing existing GAP models of habitat availability (606 species in SE)

Readily available surrogate for relative potential for species occurrence (which are not available)

Used in development of Conservation Priority models for each focal species within a habitat guild

  • SAMBI DSL Species Modeling
sambi dsl species modeling
SAMBI DSL Species Modeling

Data-Driven Models

BBS Occupancy probability and range dynamics

Test hypotheses about avian range dynamics as function of climate change and other relevant macroecological covariates (e.g., land use change, position within species range, neighborhood effects) – Much stronger inferences than from static habitat-occurrence patterns

Provide important response variable – persistence

Links alternatives (actions) to fundamental objectives

Applicable to limited set of species

Useful to validate knowledge-driven models

J.A. Collazo

na lcc species modeling
NA LCC Species Modeling
  • Pilot phase: ~20 species in 3 study areas
  • Habit@ modeling framework
    • Multiscale GIS implementation of HSI
  • Initial models developed by Scott Schwenk (UV)
    • Predictor variables to include habitat systems & modifiers from the NE Terrestrial Habitat Classification and other ecological settings variables
    • External peer review
  • Models implemented by Kevin McGarigal (UMass)
    • utilizing Settings Spatial dataset containing abiotic, anthropogenic and vegetative derived datalayers
na lcc species modeling17
NA LCC Species Modeling
  • Habit@ - Multi-scale GIS modeling
    • Local Resource Availability (LRA): the availability of resources important to the species’ life history, such as food, cover, or nesting, at the local, finest scale (a single cell or pixel);
    • Homerange Capability (HRC): the capability of an area corresponding to an individual’s homerange to support an individual, based on quantity and quality of local resources, configuration of those resources, and condition as determined by intrusions from roads and development;
    • Population Capability (PC): the capability of an area to not only support a homerange, but its setting in a neighborhood that supports nearby homeranges—that is, the ability of an area to support not only a single individual, but a local population.

K. McGarigal

slide18

Thanks to contributors:

    • Todd Jones-Farrand
    • John Tirpak
    • Ashton Drew
    • Barry Grand
    • Jaime Collazo
    • Kevin McGarigal
    • Scott Schwenk
habit@ example of breeding wood thrush draft
Habit@ Example of Breeding Wood Thrush (draft)

Local resource capability for wood thrush is determined separately for the breeding season and post-breeding (pre-migration) season, as follows:

S. Schwenk

habit@ example of breeding wood thrush draft20
Habit@ Example of Breeding Wood Thrush (draft)
  • LRC-B. Local Resource Capability for Breeding
    • LRB1: Cover [cover1] -- Categorical index; assign weights to each ecological system
    • LRB2: Canopy closure [closure] -- Continuous logistic function of canopy cover variable.
    • LRB3: Understory [under] -- Continuous Gaussian function of an index of understory openness.
    • LRB4: Development intensity 1 [devint1] -- Continuous kernel estimate of development intensity
    • LRB5: Development intensity 2 [devint2] -- Continuous kernel estimate as above but at a finer scale

S. Schwenk

habit@ example of breeding wood thrush draft21
Habit@ Example of Breeding Wood Thrush (draft)
  • LRC-B. Local Resource Capability for Breeding
  • LRC-P. Local Resource Capability for Post-Breeding
    • LRP1: Cover [cover2] -- Continuous linear or logistic function of an index of early successional stage or low vegetation cover.
    • LRP2: Edge [edge] -- Continuous function of the magnitude of difference in vegetation structure.

S. Schwenk

habit@ example of breeding wood thrush draft22
Habit@ Example of Breeding Wood Thrush (draft)
  • LRC-B. Local Resource Capability for Breeding
  • LRC-P. Local Resource Capability for Post-Breeding

Home range capability for wood thrush is determined separately for the breeding season and post-breeding (pre-migration) season, as follows;

S. Schwenk

habit@ example of breeding wood thrush draft23
Habit@ Example of Breeding Wood Thrush (draft)
  • LRC-B. Local Resource Capability for Breeding
  • LRC-P. Local Resource Capability for Post-Breeding
  • HRC-B. Home Range Capability for Breeding
    • HRB1: Kernel [bkernel] -- For each focal cell with LRC-B>0, build a resistant kernel scaled to home range size with resistance weights derived from a variable such as vegetation biomass or canopy height that effectively provides low resistance to increasingly mature forest and high resistance to non-forest and development, and then compute the kernel-weighted sum of the LRC-B values and return the value to the focal cell. Note, here we build resistant kernel home ranges only for cells that confer breeding habitat value.

S. Schwenk

habit@ example of breeding wood thrush draft24
Habit@ Example of Breeding Wood Thrush (draft)
  • LRC-B. Local Resource Capability for Breeding
  • LRC-P. Local Resource Capability for Post-Breeding
  • HRC-B. Home Range Capability for Breeding
  • HRC-P. Home Range Capability for Post-Breeding
    • HRP1: Kernel [pkernel] -- Computed to take into effect the distance moved from from breeding season range to post-breeding season range.

S. Schwenk

habit@ example of breeding wood thrush draft25
Habit@ Example of Breeding Wood Thrush (draft)
  • LRC-B. Local Resource Capability for Breeding
  • LRC-P. Local Resource Capability for Post-Breeding
  • HRC-B. Home Range Capability for Breeding
  • HRC-P. Home Range Capability for Post-Breeding

Home range capability is computed as the product of HRC-B and HRC-P.

S. Schwenk

gap national environmental spatial data
GAP National Environmental Spatial Data
  • GAP National Land Cover Data
    • Ecological systems
  • Elevation
  • Slope
  • Aspect
  • Forest/nonforest edge
  • Forest interior
  • Percent canopy cover
  • Hydrography
    • Proximity to water features
  • Stream velocity
  • Human impacts (road & urban density)
contributions from gap analysis program
Contributions from Gap Analysis Program
  • Continental extent
  • WHR dB based on Ecological Systems
  • Hierarchical approach to species modeling
      • Known Range – all species
      • Predicted Distribution – all species
      • Habitat Importance – subset of species
contributions from gap analysis program29
Contributions from Gap Analysis Program
  • Continental extent
  • WHR dB based on Ecological Systems
  • Hierarchical approach to species modeling
  • Bayesian framework for model development
    • Bayesian Belief Network via Elicitator
      • Integrated with ArcGIS and R to provide immediate feedback
      • Measures of uncertainty due to system variability and expert diversity and confidence

James et al (2009) Elicitator : an expert elicitation tool for regression in ecology. Environmental Modelling & Software, 25(1), pp. 129-145.

national gap wildlife habitat relationship whr database
National GAP Wildlife Habitat Relationship (WHR) Database
  • Built upon recent regional GAP databases
  • 2011 spp. of terrestrial vertebrates in lower 48

317 Complete / 1078 Partial / 616 Undone

    • 3,267 individual models either draft or final (by season, by region)
    • Prioritizing birds, NE SGCN species, reptiles
sambi dsl priority model
SAMBI DSL Priority model

Combine densities to map priority for each species

Limiting factors (*)

Suitable longleaf sites (S)

Potential to use fire (F)

Compensatory factors (+)

Putative source populations (P)1

Public lands (L)

Distance to potential habitat (H)11Species specific data

Priority = S*F*(P+L+H)

J.B. Grand

priority for brown headed nuthatch for t00
Priority for Brown-headednuthatch for t00

Priority = suitability * burnability * (potential habitat + conservation lands + source populations)

J.B. Grand