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Experimental evaluation of spatial capture-recapture study design.

Jill Fleming1,2, Evan H Campbell Grant1, Sean C Sterrett3

  • 1USGS Eastern Ecological Science Center, SO Conte Anadromous Fish Laboratory, 1 Migratory Way, Turners Falls, Massachusetts, 01376, USA.

Ecological Applications : a Publication of the Ecological Society of America
|July 19, 2021
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Summary
This summary is machine-generated.

Spatial capture-recapture (SCR) methods improve wildlife population estimates. This study found SCR estimates of space use and detectability are sensitive to study design, but population density estimates remain robust.

Keywords:
red-backed salamandersspatial capture-recapturestandardizationstudy design

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Area of Science:

  • Wildlife ecology
  • Population biology
  • Conservation science

Background:

  • Robust, long-term data are crucial for wildlife population analysis.
  • Advancements in analytical tools enhance statistical power for population estimates.
  • Spatial capture-recapture (SCR) methods integrate diverse study designs.

Purpose of the Study:

  • To empirically evaluate the effects of spatial study design configuration on inference using SCR methods in a wild population.
  • To assess the sensitivity of SCR parameter estimates to variations in detector array arrangement.
  • To provide guidance on best practices for SCR study design in wildlife research.

Main Methods:

  • Conducted a field experiment manipulating artificial cover object (ACO) arrangements for red-backed salamanders (Plethodon cinereus).
  • Applied SCR methods to analyze data collected under different spatial design configurations.
  • Empirically evaluated the impact of design configuration on estimates of space use, detectability, and population density.

Main Results:

  • Estimates of space use and detectability derived from SCR are sensitive to study design configuration, specifically array spacing and extent.
  • Population density estimates using SCR are generally robust to design variations.
  • Caution is advised when interpreting space use and detectability parameters due to design sensitivity, except when designs severely violate recommendations.

Conclusions:

  • SCR methods offer powerful tools for wildlife population estimation, but careful consideration of study design is essential.
  • The spatial arrangement of sampling effort significantly influences SCR estimates of space use and detectability.
  • Population density estimates from SCR are reliable across a range of designs, offering a robust metric for wildlife management.