Cant, J, Capdevila, P, Beger, M orcid.org/0000-0003-1363-3571 et al. (1 more author) (2023) Recent exposure to environmental stochasticity does not determine the demographic resilience of natural populations. Ecology Letters, 26 (7). pp. 1186-1199. ISSN 1461-023X
Abstract
Escalating climatic and anthropogenic pressures expose ecosystems worldwide to increasingly stochastic environments. Yet, our ability to forecast the responses of natural populations to this increased environmental stochasticity is impeded by a limited understanding of how exposure to stochastic environments shapes demographic resilience. Here, we test the association between local environmental stochasticity and the resilience attributes (e.g. resistance, recovery) of 2242 natural populations across 369 animal and plant species. Contrary to the assumption that past exposure to frequent environmental shifts confers a greater ability to cope with current and future global change, we illustrate how recent environmental stochasticity regimes from the past 50 years do not predict the inherent resistance or recovery potential of natural populations. Instead, demographic resilience is strongly predicted by the phylogenetic relatedness among species, with survival and developmental investments shaping their responses to environmental stochasticity. Accordingly, our findings suggest that demographic resilience is a consequence of evolutionary processes and/or deep-time environmental regimes, rather than recent-past experiences.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. Ecology Letters published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | demographic compensation; matrix population model; partial least squares regression; phylogenetic signal recovery; resistance; transient demography |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 May 2023 14:41 |
Last Modified: | 20 Jul 2023 08:57 |
Published Version: | https://onlinelibrary.wiley.com/doi/10.1111/ele.14... |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1111/ele.14234 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:199491 |