Patterns of mammalian population decline inform conservation action

Authors

  • Martina M. I. Di Fonzo,

    Corresponding author
    1. Institute of Zoology, Zoological Society of London, London, UK
    2. Division of Ecology and Evolution, Imperial College London, Ascot, UK
    3. ARC Centre of Excellence for Environmental Decisions, the NERP Environmental Decisions Hub, Centre for Biodiversity and Conservation Science, School of Biological Sciences, The University of Queensland, Brisbane, Qld, Australia
    Current affiliation:
    1. United Nations Environment Programme World Conservation Monitoring Centre, Cambridge, UK
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  • Ben Collen,

    1. Department of Genetics, Evolution and Environment, Centre for Biodiversity & Environment Research, University College London, London, UK
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  • Aliénor L. M. Chauvenet,

    1. ARC Centre of Excellence for Environmental Decisions, the NERP Environmental Decisions Hub, Centre for Biodiversity and Conservation Science, School of Biological Sciences, The University of Queensland, Brisbane, Qld, Australia
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  • Georgina M. Mace

    1. Division of Ecology and Evolution, Imperial College London, Ascot, UK
    2. Department of Genetics, Evolution and Environment, Centre for Biodiversity & Environment Research, University College London, London, UK
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Summary

  1. Evaluations of wildlife population dynamics have the potential to convey valuable information on the type of pressure affecting a population and could help predict future changes in the population's trajectory. Greater understanding of different patterns of population declines could provide a useful mechanism for assessing decline severity in the wild and identifying those populations that are more likely to exhibit severe declines.
  2. We identified 93 incidences of decline within 75 populations of mammalian species using a time-series analysis method. These included linear, quadratic convex (accelerating) declines, exponential concave (decelerating) declines and quadratic concave declines (representing recovering populations). Excluding linear declines left a data set of 85 declines to model the relationship between each decline-curve type and a range of biological, anthropogenic and time-series descriptor explanatory variables.
  3. None of the decline-curve types were spatially or phylogenetically clustered. The only characteristic that could be consistently associated with any curve type was the time at which they were more likely to occur within a time series. Quadratic convex declines were more likely to occur at the start of the time series, while recovering curve shapes (quadratic concave declines) were more likely at the end of the time series.
  4. Synthesis and applications. The ability to link certain factors with specific decline dynamics across a number of mammalian populations is useful for management purposes as it provides decision-makers with potential triggers upon which to base their conservation actions. We propose that the identification of quadratic convex declines could be used as an early-warning signal of potentially severe decline dynamics. For such a population, increased population monitoring effort should be deployed to diagnose the cause of its decline and avert possible extinctions. Conversely, the presence of a quadratic concave decline suggests that the population has already undergone a period of serious decline but is now in the process of recovery. Such populations will require different types of conservation actions, focussing on enhancing their chances of recovery.

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