Bias from heterogeneous usage of space in spatially explicit capture–recapture analyses



  1. Royle et al. (Methods in Ecology and Evolution, 2013, 4, 520) proposed a spatially explicit capture–recapture (SECR) model in which an animal's usage of a site, and hence its probability of detection, depends on a function of site-specific covariates normalized using a weighted sum of such values across the animal's home range.
  2. From simulations supposedly based on the model, they drew the conclusion that existing methods will produce ‘extremely biased’ estimates of population size when animals use space selectively. This conclusion is faulty because they simulated data from a different model, omitting the normalization needed to represent selection of resources at the home-range level.
  3. New simulations show that the null SECR estimator of population size is nearly unbiased for low to moderate levels of selective space use when the generating model includes normalization. Including detector-level covariates of detection, as allowed in standard software, nearly eliminates bias due to strongly selective space use, whether or not the generating model includes normalization.