Establishing Bayesian priors for natural mortality rate in carnivore populations

Abstract

In managed carnivore populations, natural mortality rate (d) is difficult to estimate directly, and context-specific data are typically weakly informative about it. Nevertheless, natural mortality is potentially an important component of total mortality, particularly if additive to harvest or culling mortality. The natural mortality rate exhibits allometric or life-history relationships that are invariant across diverse taxonomic groups, and it is valuable to derive estimates on this basis to serve as priors in later Bayesian models, steering parameter uncertainty towards biologically plausible values, and leading to more reliable model predictions and improved management recommendations. We used Bayesian hierarchical modeling and data from the literature to establish informative priors for instantaneous d as predictions scaled from body mass or maximum age. Posterior mean estimates of the scaling parameters of these models were 0.27 (body mass) and -1.07 (maximum age), respectively, conforming to expected values of -0.25 and -1.00. Direct estimates of d from published studies of coyotes (Canis latrans) in southern Texas, fisher (Pekania pennanti) in Sierra Nevada, and slender mongoose (Galerella sanguinea) in the Kalahari Desert were within the credible intervals of predictions for d using both models. We also compared survivorship curves based on model predictions with observed survivorship of red fox (Vulpes vulpes) from a variety of studies in Britain, among which intensity of culling varied markedly. Across all species, there was better support for the d prediction from maximum age, than from body mass. We thus recommend use of maximum age data to establish informative priors for d where possible. Posterior median predictions of d from maximum age were within 0.01-0.14/year of the direct estimates, whereas the differences between direct estimates and predictions from body mass were 0.04-0.27/year. Sensitivity analysis showed trivial effects of between-sex differences in body mass, and age-specific mortality, on predictions of d. Differences between body mass and maximum age model predictions were attributed to the relative importance of intrinsic and extrinsic mortality factors in the 2 approaches (i.e., maximum age predictions allowed for extrinsic factors to affect predicted mortality).