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A predictive timeline of wildlife population collapse

Nature Ecology & Evolution volume 7, pages 320–331 (2023)Cite this article

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Abstract

Contemporary rates of biodiversity decline emphasize the need for reliable ecological forecasting, but current methods vary in their ability to predict the declines of real-world populations. Acknowledging that stressor effects start at the individual level, and that it is the sum of these individual-level effects that drives populations to collapse, shifts the focus of predictive ecology away from using predominantly abundance data. Doing so opens new opportunities to develop predictive frameworks that utilize increasingly available multi-dimensional data, which have previously been overlooked for ecological forecasting. Here, we propose that stressed populations will exhibit a predictable sequence of observable changes through time: changes in individuals’ behaviour will occur as the first sign of increasing stress, followed by changes in fitness-related morphological traits, shifts in the dynamics (for example, birth rates) of populations and finally abundance declines. We discuss how monitoring the sequential appearance of these signals may allow us to discern whether a population is increasingly at risk of collapse, or is adapting in the face of environmental change, providing a conceptual framework to develop new forecasting methods that combine multi-dimensional (for example, behaviour, morphology, life history and abundance) data.

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Fig. 1: Theoretical example of a timeline to collapse.

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Data availability

No original data were used. Literature-based data are properly cited. F.C. can be contacted at francesco.cerini@bristol.ac.uk or francesco.cerini@uniroma3.it. Source data are provided with this paper.

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Acknowledgements

F.C., D.Z.C. and C.F.C. are supported by NERC grant NE/T006579/1. All the Experimental Ecology and Conservation Lab (Duncan, Pol, Marc, Ellie) are gratefully acknowledged for the help in writing this piece.

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Authors and Affiliations

  1. School of Biological Sciences, University of Bristol, Bristol, UK

    Francesco Cerini & Christopher F. Clements

  2. School of Biosciences, University of Sheffield, Sheffield, UK

    Dylan Z. Childs

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  1. Francesco Cerini
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Contributions

C.F.C. and D.Z.C. formulated the framework. F.C. developed the ideas, reviewed the literature and wrote the first draft of the manuscript. All authors contributed substantially to revisions.

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Correspondence to Francesco Cerini.

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Supplementary Table 1

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Source Data Fig. Box 1 and 2

Sheet Box1_figure(a): Comparison of mean values + standard errors of two behaviours at two different sea-ice extensions. Sheet Box1_figure(b): comparison of probabilities of intra and interspecific attack, average P values and 95% confidence intervals at two coral covers. Sheet Box2_figure(a): time series of average bear weight with standard deviations. Sheet Box2_figure(b): comparison of average asymmetry index with standard errors between lizards living in fields with treatment versus control.

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Cerini, F., Childs, D.Z. & Clements, C.F. A predictive timeline of wildlife population collapse. Nat Ecol Evol 7, 320–331 (2023). https://doi.org/10.1038/s41559-023-01985-2

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