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Estimating landscape carrying capacity through maximum clique analysis.

Therese M Donovan1, Gregory S Warrington, W Scott Schwenk

  • 1U.S. Geological Survey, Vermont Cooperative Fish and Wildlife Research Unit, Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, Vermont 05405, USA. tdonovan@uvm.edu

Ecological Applications : a Publication of the Ecological Society of America
|February 8, 2013
PubMed
Summary
This summary is machine-generated.

A new maximum clique analysis method estimates wildlife carrying capacity (N(k)) using habitat suitability (HS) maps. This approach provides more accurate population estimates for territorial species than previous methods.

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Area of Science:

  • Wildlife ecology
  • Spatial analysis
  • Conservation biology

Background:

  • Habitat suitability (HS) maps are crucial for wildlife science, linking species presence to landscape patterns.
  • Current HS maps detail optimal resource distribution but lack population size (carrying capacity, N(k)) estimates.
  • Accurate N(k) data is vital for effective wildlife management and conservation decision-making.

Purpose of the Study:

  • To introduce and validate a novel "maximum clique analysis" method for estimating carrying capacity (N(k)) of territorial species using HS maps.
  • To compare N(k) estimates derived from maximum clique analysis with alternative methods for Ovenbirds and bobcats.
  • To assess the computational feasibility and limitations of maximum clique analysis for different species distributions and scales.

Main Methods:

  • Developed HS maps (30-m2 resolution) for Ovenbirds (occupancy modeling) and bobcats (resource utilization modeling) in Vermont.
  • Identified "pseudo-home range" locations on HS maps where territories could be established.
  • Constructed mathematical graphs linking pseudo-home ranges, then used "maximum clique analysis" (via Cliquer program) to find the largest non-overlapping set of territories, estimating N(k).

Main Results:

  • Estimated carrying capacity (N(k)) for Ovenbirds at 236 individuals and for female bobcats at 42 individuals.
  • Maximum clique analysis yielded N(k) estimates significantly lower (1.4 to >30 times) than alternative ad hoc methods, suggesting potential upward bias in the latter.
  • The method is computationally intensive but manageable for problems with <1500 pseudo-home ranges, particularly for species with clustered distributions or large home ranges relative to grid scale.

Conclusions:

  • Maximum clique analysis offers a robust, spatially explicit method for estimating carrying capacity (N(k)) of territorial species from HS maps.
  • This approach provides more conservative and potentially more accurate N(k) estimates compared to simpler methods.
  • Further development and application are recommended, considering computational constraints and species-specific distribution patterns.