Low demographic variability in wild primate populations: fitness impacts of variation, covariation, and serial correlation in vital rates.
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In a stochastic environment, long-term fitness can be influenced by variation, covariation, and serial correlation in vital rates (survival and fertility). Yet no study of an animal population has parsed the contributions of these three aspects of variability to long-term fitness. We do so using a unique database that includes complete life-history information for wild-living individuals of seven primate species that have been the subjects of long-term (22-45 years) behavioral studies. Overall, the estimated levels of vital rate variation had only minor effects on long-term fitness, and the effects of vital rate covariation and serial correlation were even weaker. To explore why, we compared estimated variances of adult survival in primates with values for other vertebrates in the literature and found that adult survival is significantly less variable in primates than it is in the other vertebrates. Finally, we tested the prediction that adult survival, because it more strongly influences fitness in a constant environment, will be less variable than newborn survival, and we found only mixed support for the prediction. Our results suggest that wild primates may be buffered against detrimental fitness effects of environmental stochasticity by their highly developed cognitive abilities, social networks, and broad, flexible diets.
Published Version (Please cite this version)
Morris, William F, Jeanne Altmann, Diane K Brockman, Marina Cords, Linda M Fedigan, Anne E Pusey, Tara S Stoinski, Anne M Bronikowski, et al. (2011). Low demographic variability in wild primate populations: fitness impacts of variation, covariation, and serial correlation in vital rates. Am Nat, 177(1). pp. E14–E28. 10.1086/657443 Retrieved from https://hdl.handle.net/10161/4163.
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Bill Morris studies the population ecology of plants and insects (both herbivores and pollinators). Current projects include: the population dynamic consequences of constitutive and inducible resistance in plants, the maintenance of mutualistic interactions between flowering plants and nectar-robbing pollinators, the use of population-level attributes to detect biotic responses to ongoing environmental changes, and the use of mathematical models to assess viability of threatened and endangered populations. The common thread uniting these projects is that they combine field experiments and mathematical models to study population dynamics in natural and managed systems.
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