Spatially explicit capture-recapture (SECR) models have emerged as one solution to the problem of estimating the population density of mobile and cryptic animals. Spatial models embody assumptions regarding the spatial… Click to show full abstract
Spatially explicit capture-recapture (SECR) models have emerged as one solution to the problem of estimating the population density of mobile and cryptic animals. Spatial models embody assumptions regarding the spatial distribution of individuals and the spatial detection process. The detection process is modeled in SECR as a radial decline in detection probability with distance from the activity center of each individual. This would seem to require that home ranges are circular. The robustness of SECR when home ranges are not circular has been the subject of conflicting statements. Ivan et al. previously compared the SECR density estimator to a telemetry-scaled non-spatial estimator. I suggest that the apparent non-robustness of SECR in their study was a simulation artefact. New simulations of elliptical home ranges establish that the SECR density estimator is largely robust to non-circularity when detectors are spread in two dimensions, but may be very biased if the detector array is linear and home ranges align with the array. Transformation to isotropy reduces bias from designs of intermediate dimension, such as hollow square arrays. Possible alignment of home ranges should be considered when designing detector arrays.
               
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