Affiliation:
1. Institute of Zoology, Zoological Society of London London UK
2. Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, Division of Biosciences, University College London London UK
3. Department of Biology University of Oxford Oxford UK
Abstract
AbstractIt has been suggested that animals may have evolved cooperative breeding strategies in response to extreme climatic conditions. Climate change, however, may push species beyond their ability to cope with extreme climates, and reduce the group sizes in cooperatively breeding species to a point where populations are no longer viable. Predicting the impact of future climates on these species is challenging as modelling the impact of climate change on their population dynamics requires information on both group‐ and individual‐level responses to climatic conditions. Using a single‐sex individual‐based model incorporating demographic responses to ambient temperature in an endangered species, the African wild dog Lycaon pictus, we show that there is a threshold temperature above which populations of the species are predicted to collapse. For simulated populations with carrying capacities equivalent to the median size of real‐world populations (nine packs), extinction risk increases once temperatures exceed those predicted in the best‐case climate warming scenario (Representative Concentration Pathway [RCP] 2.6). The threshold is higher (between RCP 4.5 and RCP 6.0) for larger simulated populations (30 packs), but 84% of real‐world populations number <30 packs. Simulated populations collapsed because, at high ambient temperatures, juvenile survival was so low that packs were no longer recruiting enough individuals to persist, leading them to die out. This work highlights the importance of social dynamics in determining impacts of climatic variables on social species, and the critical role that recruitment can play in driving population‐level impacts of climate change. Population models parameterised on long‐term data are essential for predicting future population viability under climate change.
Funder
Natural Environment Research Council
Subject
General Environmental Science,Ecology,Environmental Chemistry,Global and Planetary Change
Cited by
2 articles.
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