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Recent exposure to environmental stochasticity does not determine the demographic resilience of natural populations.
Cant, James; Capdevila, Pol; Beger, Maria; Salguero-Gómez, Roberto.
Afiliação
  • Cant J; Centre for Biological Diversity, University of St Andrews, St Andrews, UK.
  • Capdevila P; School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK.
  • Beger M; School of Biological Sciences, University of Bristol, Bristol, UK.
  • Salguero-Gómez R; Department of Zoology, University of Oxford, Oxford, UK.
Ecol Lett ; 26(7): 1186-1199, 2023 Jul.
Article em En | MEDLINE | ID: mdl-37158011
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Plantas / Ecossistema Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Ecol Lett Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Plantas / Ecossistema Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Ecol Lett Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido
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