TY - JOUR T1 - Dead or gone? Bayesian inference on mortality for the dispersing sex JF - bioRxiv DO - 10.1101/031161 SP - 031161 AU - Julia A. Barthold AU - Craig Packer AU - Andrew J. Loveridge AU - David W. Macdonald AU - Fernando Colchero Y1 - 2015/01/01 UR - http://biorxiv.org/content/early/2015/11/10/031161.abstract N2 - Estimates of age-specific mortality are regularly used in ecology, evolution, and conservation research. However, existing methods to estimate mortality from re-sighting records of marked individuals fail at estimating mortality of males for species with male natal dispersal due to the uncertainty surrounding disappearances of adult males from study populations.Here, we develop a mortality model that imputes dispersal state (i.e., died or left) for uncertain male records as a latent state jointly with the coefficients of a parametric mortality model in a Bayesian hierarchical framework. To check the performance of our model, we first conduct a simulation study. We then apply our model to a long-term data set for African lions. Using these data, we further scrutinise the mortality estimates derived from our model by incrementally reducing the level of uncertainty in the male records. We achieve this by taking advantage of an expert’s intuition on the likely fate of each uncertain male record.We find that our new model produces accurate mortality parameters for simulated data of varying sample sizes and proportions of uncertain male records. From the empirical study we learned that our model provides similar mortality estimates for different levels of uncertainty in male records. However, a sensitivity of the mortality estimates to varying uncertainty is, as can be expected, detectable.We conclude that our model provides a solution to the challenge of estimating male mortality in species with data-deficiency for males due to natal dispersal. Given the utility of sex-specific mortality estimates in biological and conservation research and the virtual ubiquity of sex-biased dispersal, our model will be useful to a wide variety of applications. ER -