Comparing resource selection and demographic models for predicting animal density

摘要: Habitat-based prediction of population density relies on relationships between landscape configuration (i.e., abundance land-cover types) and equilibrium density. This may be accomplished by estimating resource selection probability functions (RSPFs) based presence–absence data, or relating carrying capacity to covariates. We used RSPFs for moose (Alces alces) from 2 study sites capacities 34 wildlife management units across northern Ontario, Canada, create estimators compared the predictions both models in a novel site obtained via aerial census. also projected RSPF predicted estimated each unit. The densities that were statistically indistinguishable at site, but model generated uninformatively broad intervals. failed predict Ontario; however, differences estimates varied predictably with covariates related forage availability, suggesting habitat strength transferability vary quality. Estimating using consistent relationship animal density; thus, applicability space will depend heavily similarity original sites. Demographic projection benefits spatiotemporal datasets improve reliability are relatively rare subject error. Our findings suggest selection-based estimation is preferable demographically because increased precision estimates, immediacy available data (e.g., single survey radio-telemetry multiple vs. many generations time series space), fine-scale patterns distribution abundance. © 2016 Wildlife Society.