Integrating dead recoveries in open‐population spatial capture–recapture models

Abstract

Abstract Integrating dead recoveries into capture–recapture models can improve inference on demographic parameters. But dead‐recovery data do not only inform on individual fates; they also contain information about individual locations. Open‐population spatial capture–recapture (OPSCR) has the potential to fully exploit such data. Here, we present an open‐population spatial capture–recapture–recovery model integrating the spatial information associated with dead recoveries. Using simulations, we investigate the conditions under which this extension of the OPSCR model improves inference and illustrate the approach with the analysis of a wolverine (Gulo gulo) dataset from Norway. Simulation results showed that the integration of dead recoveries into OPSCR boosted the precision of all demographic parameters. In addition, the integration of dead‐recovery locations boosted the precision of the inter‐annual movement parameter, which is difficult to estimate in OPSCR, by up to 40% in case of sparse data. We also detected a 139–367% increase in the probability of models reaching convergence with increasing proportion of dead recoveries when dead‐recovery information was integrated spatially, compared with a 30–107% increase when integrating dead recoveries in a non‐spatial way. The analysis of the wolverine data showed the same general pattern of improved parameter precision. Overall, our results highlight how leveraging the demographic and spatial information contained in dead‐recovery data in a spatial capture–recapture framework can improve population parameter estimation.

Keywords

• capture–recapture–recovery
• integrated modeling
• known fate
• mortality
• population dynamics
• spatial capture–recapture