Jointly estimating survival and mortality: integrating recapture and recovery data from complex multiple predator systems

Abstract

Identifying where, when, and how many animals live and die over time is principal to understanding factors that influence population dynamics. Capture–recapture–recovery (CRR) models are widely used to estimate animal survival and, in many cases, quantify specific causes of mortality (e.g., harvest, predation, starvation). However, the restrictive CRR framework can inhibit the consideration and inclusion of some types of recovery data. We developed an extension to the CRR framework to allow for the incorporation of recoveries from indeterminate temporal or spatial origin. This model jointly estimates cause-specific mortality and survival probabilities across multiple spatial and temporal scales, while accounting for differences in mortality-specific reporting and recovery rates. We fitted the model to data on a group of juvenile steelhead trout (Oncorhynchus mykiss) marked with passive integrated transponder tags in the Columbia River basin, USA. Following tagging and release, fish were detected alive at up to six downstream locations and/or recovered dead on one of nine bird colonies during seaward migration. We estimated that, in aggregate, avian predators consumed 31% of juvenile steelhead during outmigration to the ocean (95% CRI: [27, 36]). Colony-specific predation rates ranged from 95% of all steelhead mortality within some reaches. This integrated modelling approach provides a flexible framework to integrate multiple recapture and recovery data sources, providing a more holistic understanding of animal life history, including direct comparisons of cause-specific mortality factors and the cumulative impact of multiple mortality factors across time or space.