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A spatially explicit capture-recapture estimator for single-catch traps.

Greg Distiller1, David L Borchers2

  • 1Statistics in Ecology, Environment and Conservation (SEEC) Department of Statistical Sciences University of Cape Town Private Bag X3 Rondebosch 7701 South Africa.

Ecology and Evolution
|December 8, 2015
PubMed
Summary
This summary is machine-generated.

A new single-catch likelihood improves spatially explicit capture-recapture (SECR) analyses for small mammal live-trapping studies. This method offers unbiased estimates of density and detection functions, especially in areas with varying animal distribution.

Keywords:
Density estimationsingle‐catch trap likelihoodspatially explicit capture–recapturestatistical methods

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Area of Science:

  • Ecology
  • Wildlife Biology
  • Statistical Modeling

Background:

  • Single-catch traps are common in small mammal studies.
  • Existing spatially explicit capture-recapture (SECR) analyses often use multicatch likelihoods, which can be problematic.

Purpose of the Study:

  • To derive and evaluate a new likelihood function for single-catch traps in SECR.
  • To compare the performance of single-catch and multicatch estimators under various conditions.

Main Methods:

  • Developed a continuous-time SECR model to derive a single-catch likelihood.
  • Used simulation studies to compare single-catch and multicatch estimators.
  • Assessed performance across scenarios with varying density and trap saturation.

Main Results:

  • The single-catch estimator provides unbiased estimates of density, distribution, and detection function parameters.
  • The multicatch estimator's performance degrades with high trap saturation and density gradients.
  • The single-catch estimator has higher variance but is more accurate for detection function interpretation and spatially variable densities.

Conclusions:

  • The single-catch estimator is recommended for accurate SECR analysis when detection function interpretation is key or density varies spatially.
  • The multicatch estimator remains a robust option for average density estimation if density is uniform and detection function parameters are not of primary interest.
  • Future research should focus on single-catch likelihoods with unknown capture times, recommending timing devices for current studies.