


This study builds on our previous analyses, in which we identified three principal decline-curve types of increasing severity: quadratic concave (i.e. recovering), exponential concave (i.e. decelerating), and quadratic convex (i.e. accelerating) decline-curves (Figure A).   In our new study, we investigate whether the presence of different decline-curve types within 85 mammalian population time-series is dependent on particular species-specific traits, levels of anthropogenic pressure, or based on particular attributes of the time series itself.  The aim of our work was to gain insight into the conditions contributing to different decline-curves, and then use this understanding to pre-empt the application of suitable conservation management strategies under similar demographic conditions.

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Figure A: Three principle decline-curve types of increasing severity

Our main finding from this analysis was to do with the timing of different types of declines: quadratic convex declines were more likely to be detected towards the start of the population time series, whereas quadratic concave declines were more likely at the end of time-series. This pattern is easily recognisable within two population time-series of Saiga antelope, which were heavily exploited during the period following the break-up of the Soviet Union (Figure B; white dots represent the raw time-series, black dots represent switch points within the time series, and the dashed line represents the smoothed time-series). We believe our results can be explained in the context of different threatening processes. When a new pressure appears, there are four possible responses of a population: it may a) decline and then recover, b) decline to extinction, c) decline and stabilize, or d) be unaffected.  Early in this process, quadratic convex declines will be more likely, especially under severe or increasing pressures (e.g. an accelerating rate of habitat conversion).  Over the course of time, as the pressure stabilizes or reduces, a population that has not declined to extinction must either recover or stabilize, resulting in a concave (or decelerating) curve.

Figure B: Saiga population declines in Betpak-dala (Kazakhstan) and the Ustyurt plateau (Kazakhstan and Uzbekistan)

The tendency for quadratic convex declines to occur in the beginning of population time series could act as a signal for a novel threat, following which increased monitoring in combination with rapid conservation effort focussing on threat abatement should be put in place.  Instead, if concave declines were detected, it could be inferred that the population has already undergone a period of severe decline, from which its rate of decline is slowing or even recovering.  The presence of this decline type suggests a different type of management strategy might be required, focussed on supporting recovery (e.g. through improving the species’ habitat).  The identification of different decline types within the same monitoring programme could therefore provide a signal to change management strategy, in order to obtain the best chances of reversing the population’s negative trajectory.

Although not a prioritization mechanism on its own, differences in decline-type could also be incorporated within Criterion A of the IUCN Red List, as a more continuous indicator of the urgency with which a species’ extinction risk need addressing.  For example, species with a greater number of severe declines could be allocated a higher risk of extinction within the same Red List category, despite not having met the criteria for moving up a category at the species-level.  Assessing differences in population decline-curve dynamics could also be useful for prioritizing Red List (re)assessments, where an elevated presence of quadratic convex population declines could instigate a closer evaluation of a species’ extinction risk.

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Mammal populations: African elephants in Kruger National Park (South Africa) and Chital (spotted deer) in Corbett National Park (India)