Publication detailsDevenish-Nelson, E.S., Stephens, P.A., Harris, S., Soulsbury, C. & Richards, S.A. (2013). Does litter size variation affect models of terrestrial carnivore extinction risk and management? PLoS ONE 8(2): e58060.
- Publication type: Journal Article
- ISSN/ISBN: 1932-6203 (electronic)
- DOI: 10.1371/journal.pone.0058060
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
Background: Individual variation in both survival and reproduction has the potential to influence extinction risk. Especially for rare or threatened species, reliable population models should adequately incorporate demographic uncertainty. Here, we focus on an important form of demographic stochasticity: variation in litter sizes. We use terrestrial carnivores as an example taxon, as they are frequently threatened or of economic importance. Since data on intraspecific litter size variation are often sparse, it is unclear what probability distribution should be used to describe the pattern of litter size variation for multiparous carnivores.
Methodology/Principal Findings: We used litter size data on 32 terrestrial carnivore species to test the fit of 12 probability distributions. The influence of these distributions on quasi-extinction probabilities and the probability of successful disease control was then examined for three canid species – the island fox Urocyon littoralis, the red fox Vulpes vulpes, and the African wild dog Lycaon pictus. Best fitting probability distributions differed among the carnivores examined. However, the discretised normal distribution provided the best fit for the majority of species, because variation among litter-sizes was often small. Importantly, however, the outcomes of demographic models were generally robust to the distribution used.
Conclusion/Significance: These results provide reassurance for those using demographic modelling for the management of less studied carnivores in which litter size variation is estimated using data from species with similar reproductive attributes.