Ecol Appl. 2022 Apr 3:e2618. doi: 10.1002/eap.2618. Online ahead of print.
ABSTRACT
Spatial capture-recapture (SCR) models are powerful analytical tools that have become the standard for estimating abundance and density of wild animal populations. When sampling populations to implement SCR, the number of unique individuals detected, total recaptures, and unique spatial relocations can be highly variable. These sample sizes influence precision and accuracy of model parameter estimates. Testing the performance of SCR models with sparse empirical datasets typical of low-density, wide-ranging species can inform the threshold at which a more integrated modeling approach with additional data sources or additional years of monitoring may be required to achieve reliable, precise parameter estimates. Using a multi-site, multi-year Utah black bear (Ursus americanus) capture-recapture dataset, we evaluated factors influencing the uncertainty of SCR structural parameter estimates, specifically density, detection, and the spatial scale parameter, sigma. We also provided some of the first SCR density estimates for Utah black bear populations, which ranged from 3.85 – 74.33 bears/100 km2 . Increasing total detections decreased uncertainty of density estimates, while an increasing number of total recaptures and individuals with recaptures decreased uncertainty of detection and sigma estimates, respectively. In most cases, multiple years of data were required for precise density estimates (<0.2 CV). Across study areas there was an average decline in CV of 0.07 with the addition of another year of data. One sampled population with very high estimated bear density had an atypically low number of spatial recaptures relative to total recaptures, apparently inflating density estimates. A complementary simulation study used to assess estimate bias suggested that when < 30% of recaptured individuals were spatially recaptured, density estimates were unreliable and ranged widely, in some cases to >3 times the simulated density. Additional research could evaluate these requirements for other density scenarios. Large numbers of individuals detected, numbers of spatial recaptures, and precision alone may not be sufficient indicators of parameter estimate reliability. We provide an evaluation of simple summary statistics of capture-recapture datasets that can provide an early signal of a need to alter sampling design or collect auxiliary data before model implementation to improve estimate precision and accuracy.
PMID:35368131 | DOI:10.1002/eap.2618