Using social structure to improve mortality estimates: An example with sperm whales

Summary: Estimates of mortality are fundamental to studies of population ecology and assessments of conservation status. Mortality is frequently estimated using individual identifications by means of mark-recapture methods. These estimates become biased with heterogeneity in identification and especially if patterns of heterogeneity change with time. If animals are social, then survival may be inferred from the identifications of social partners. We produce a likelihood model for estimating mortality using such social data. We show using simulation that this method can produce less biased and more precise estimates of mortality than standard methods when individuals are almost always identified with associates, and when there are time-varying patterns of heterogeneity in identifiability. The method seems little affected by some change in social affiliations or by growth or decline in population size. SEs and confidence intervals of mortality estimates can be estimated using likelihood methods. We apply the method to data from a population of sperm whales (Physeter macrocephalus) in the eastern Caribbean, obtaining estimates that are more precise and probably less biased than those from other methods. The method should be useful in improving mortality estimates for social species.