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The diversity of population responses to environmental change

Citation

Colchero, F and Jones, OR and Conde, DA and Hodgson, D and Zajitschek, F and Schmidt, BR and Malo, AF and Alberts, SC and Becker, PH and Bouwhuis, S and Bronikowski, AM and De Vleeschouwer, KM and Delahay, RJ and Dummermuth, S and Fernandez-Duque, E and Frisenvaenge, J and Hesselsoe, M and Larson, S and Lemaitre, J-F and McDonald, J and Miller, DAW and O'Donnell, C and Packer, C and Raboy, BE and Reading, CJ and Wapstra, E and Weimerskirch, H and While, GM and Baudisch, A and Flatt, T and Coulson, T and Gaillard, J-M, The diversity of population responses to environmental change, Ecology Letters, 22, (2) pp. 342-353. ISSN 1461-0248 (2019) [Refereed Article]


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Copyright 2018 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

DOI: doi:10.1111/ele.13195

Abstract

The current extinction and climate change crises pressure us to predict population dynamics with ever‐greater accuracy. Although predictions rest on the well‐advanced theory of age‐structured populations, two key issues remain poorly explored. Specifically, how the age‐dependency in demographic rates and the year‐to‐year interactions between survival and fecundity affect stochastic population growth rates. We use inference, simulations and mathematical derivations to explore how environmental perturbations determine population growth rates for populations with different age‐specific demographic rates and when ages are reduced to stages. We find that stage‐ vs. age‐based models can produce markedly divergent stochastic population growth rates. The differences are most pronounced when there are survival‐fecundity‐trade‐offs, which reduce the variance in the population growth rate. Finally, the expected value and variance of the stochastic growth rates of populations with different age‐specific demographic rates can diverge to the extent that, while some populations may thrive, others will inevitably go extinct.

Item Details

Item Type:Refereed Article
Keywords:age-structured population models, Bayesian inference, fecundity, mortality, survival
Research Division:Biological Sciences
Research Group:Evolutionary Biology
Research Field:Life Histories
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Biological Sciences
UTAS Author:Wapstra, E (Associate Professor Erik Wapstra)
UTAS Author:While, GM (Dr Geoff While)
ID Code:129622
Year Published:2019 (online first 2018)
Web of Science® Times Cited:4
Deposited By:Zoology
Deposited On:2018-12-10
Last Modified:2019-03-05
Downloads:58 View Download Statistics

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