Joint estimation of growth and survival from mark-recapture data to improve estimates of senescence in wild populations.

Understanding age-dependent patterns of survival is fundamental to predicting population dynamics, understanding selective pressures, and estimating rates of senescence. However, quantifying age-specific survival in wild populations poses significant logistical and statistical challenges. Recent work has helped to alleviate these constraints by demonstrating that age-specific survival can be estimated using mark-recapture data even when age is unknown for all or some individuals. However, previous approaches do not incorporate auxiliary information that can improve age estimates of individuals. We introduce a survival estimator that combines a von Bertalanffy growth model, age-specific hazard functions, and a Cormack-Jolly-Seber mark-recapture model into a single hierarchical framework. This approach allows us to obtain information about age and its uncertainty based on size and growth for individuals of unknown age when estimating age-specific survival. Using both simulated and real-world data for two painted turtle (Chrysemys picta) populations, we demonstrate that this additional information substantially reduces the bias of age-specific hazard rates, which allows for the testing of hypotheses related to aging. Estimating patterns of senescence is just one practical application of jointly estimating survival and growth; other applications include obtaining better estimates of the timing of recruitment and improved understanding of life-history trade-offs between growth and survival.