Abstract
Predicting the impact of disease epidemics on wildlife populations is one of the twenty-first century’s main conservation challenges. The long-term demographic responses of wildlife populations to epidemics and the life history and social traits modulating these responses are generally unknown, particularly for K-selected social species. Here we develop a stage-structured matrix population model to provide a long-term projection of demographic responses by a keystone social predator, the spotted hyena, to a virulent epidemic of canine distemper virus (CDV) in the Serengeti ecosystem in 1993/1994 and predict the recovery time for the population following the epidemic. Using two decades of longitudinal data from 625 known hyenas, we demonstrate that although the reduction in population size was moderate, i.e., the population showed high ecological ‘resistance’ to the novel CDV genotype present, recovery was slow. Interestingly, high-ranking females accelerated the population’s recovery, thereby lessening the impact of the epidemic on the population.
Highlights
Predicting the impact of disease epidemics on wildlife populations is one of the twenty-first century’s main conservation challenges
We investigated the population consequences of a canine distemper virus (CDV) epidemic[10,18], caused by a novel genotype better adapted to non-canids such as hyenas and lions Panthera leo than to canids[19]
The projected hyena population was reduced by 16% and needed more than a decade to return to its pre-epidemic size
Summary
Predicting the impact of disease epidemics on wildlife populations is one of the twenty-first century’s main conservation challenges. We show that stage-structured matrix population models[12,13] are highly suitable for these purposes because they allow us to assess how demographic performance (in terms of fecundity, survival and reproductive value) is influenced by infection status, and how disease persistence and dynamics are influenced by host demography and social structure[14,15] Such models can make full use of field data as input, i.e., state-specific parameters estimated by capture-mark-recapture (CMR) approaches[16], and permit the calculation of the basic reproduction number (R0) of a pathogen[14,15]. High-ranking females increased the ecological resistance of the hyena population and helped to accelerate its recovery, thereby favouring the fadeout of the CDV epidemic To our knowledge, this is the first study in a wildlife host to demonstrate that the interaction of host demographic performance, social status and infection state drive both R0 and the population response to a major epidemic
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