Abstract
Spatial capture-recapture models (SCRs) provide an integrative statistical tool for analyzing animal movement and population patterns. Although incorporating home range formation with a theoretical basis of animal movement into SCRs can improve the prediction of animal space use in a heterogeneous landscape, this approach is challenging owing to the sparseness of recapture events. In this study, we developed an advection-diffusion capture-recapture model (ADCR), which is an extension of SCRs incorporating home range formation with advection-diffusion formalism, providing a new framework to estimate population density and landscape permeability. we tested the unbiasedness of the estimator using simulated capture-recapture data generated by a step selection function. We also compared the accuracy of population density estimates and home range shapes with those from SCR incorporating the least-cost path and basic SCR. In addition, ADCR was applied to a real dataset of Asiatic black bear (Ursus thibetanus) in Japan to demonstrate the capacity of the ADCR to detect geographical barriers that constrain animal movements. Population density and permeability of ADCR were substantially unbiased for simulated datasets. ADCR could detect environmental signals on connectivity more sensitively and could estimate population density, home range shapes, and size variations better than the existing models. For the application to the bear dataset, ADCR could detect the effect of water bodies as a barrier to movement, which is consistent with previous studies, whereas estimates by SCR with the least-cost path were difficult to interpret. ADCR provides unique opportunities to elucidate both individual- and population-level ecological processes from capture-recapture data. By offering a formal link with step selection functions to estimate animal movement, it is suitable for simultaneously modeling capture-recapture data and animal movement data. This study provides a basis for studies of the interplay between animal movement processes and population patterns.