Frog population viability under present and future climate conditions: a Bayesian state-space approach


  • R. McCaffery,

    Corresponding author
    1. Ecosystem and Conservation Sciences, College of Forestry and Conservation, University of Montana, Missoula, MT, USA
      Correspondence author.
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  • A. Solonen,

    1. Department of Mathematics and Physics, Lappeenranta University of Technology, Lappeenranta, Finland
    2. Finnish Meteorological Institute, Helsinki, Finland
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  • E. Crone

    1. Ecosystem and Conservation Sciences, College of Forestry and Conservation, University of Montana, Missoula, MT, USA
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    • Present address: Harvard Forest, Harvard University, Petersham, USA.

Correspondence author.


1. World-wide extinctions of amphibians are at the forefront of the biodiversity crisis, with climate change figuring prominently as a potential driver of continued amphibian decline. As in other taxa, changes in both the mean and variability of climate conditions may affect amphibian populations in complex, unpredictable ways. In western North America, climate models predict a reduced duration and extent of mountain snowpack and increased variability in precipitation, which may have consequences for amphibians inhabiting montane ecosystems.

2. We used Bayesian capture–recapture methods to estimate survival and transition probabilities in a high-elevation population of the Columbia spotted frog (Rana luteiventris) over 10 years and related these rates to interannual variation in peak snowpack. Then, we forecasted frog population growth and viability under a range of scenarios with varying levels of change in mean and variance in snowpack.

3. Over a range of future scenarios, changes in mean snowpack had a greater effect on viability than changes in the variance of snowpack, with forecasts largely predicting an increase in population viability. Population models based on snowpack during our study period predicted a declining population.

4. Although mean conditions were more important for viability than variance, for a given mean snowpack depth, increases in variability could change a population from increasing to decreasing. Therefore, the influence of changing climate variability on populations should be accounted for in predictive models. The Bayesian modelling framework allows for the explicit characterization of uncertainty in parameter estimates and ecological forecasts, and thus provides a natural approach for examining relative contributions of mean and variability in climatic variables to population dynamics.

5. Longevity and heterogeneous habitat may contribute to the potential for this amphibian species to be resilient to increased climatic variation, and shorter-lived species inhabiting homogeneous ecosystems may be more susceptible to increased variability in climate conditions.