R 0 is a measure of the number of individuals infected by introducing a single infected individual into a susceptible population (over the course of its infectious period) 17, i.e., a measure of maximum transmissibility, and describes whether an infectious disease will invade or fade out in a population.
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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 ( R 0) of a pathogen 14, 15. Here 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. There is a strong need for a robust predictive framework to assess the potential risk that epidemics pose to wildlife populations, to provide projections of the recovery of populations from epidemics and to identify factors modulating population responses, particularly for K-selected and social species. It is therefore unclear how social traits modulate the magnitude of the potential reduction in host population size during an epidemic, or the recovery time to pre-epidemic population size 11. In social host species, the relationships between social traits and disease outcomes can be complex 8, 9, 10. To characterise these demographic responses, we apply two terms from the field of ecology-ecological resistance: the impact of exogenous disturbance on the state of a system and recovery: the endogenous process that pulls the disturbed system back towards equilibrium 7. We know little about the long-term demographic responses to infectious viral disease epidemics in wildlife species, particularly those with high maternal investment in a low number of offspring during a long lifespan ( K-selected species), probably because longitudinal studies on such species are rare 6. Viruses are of particular concern as they evolve rapidly, yielding new strains and adaptations to novel hosts 3, 5.
Human activities rapidly expand the geographical range and host species spectrum of pathogens, and epidemics caused by exotic pathogens in unexpected hosts are increasing 5. Interestingly, high-ranking females accelerated the population’s recovery, thereby lessening the impact of the epidemic on the population.Įpidemics responsible for a decline in keystone species can alter ecosystem dynamics and diminish biodiversity by increasing the chance of extirpation of host populations, and possibly the extinction of species 1, 2, 3, 4. 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.
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. 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.
Predicting the impact of disease epidemics on wildlife populations is one of the twenty-first century’s main conservation challenges.
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