Climate change and habitat loss are two of the primary causes of global biodiversity loss. Habitats gradually become unsuitable as temperature, rainfall, and related climatic variables change. In addition to climate change, 75% of the land surface around the world has been converted by humans. As habitats shift, species must adapt to the new conditions, move to stay within their suitable habitat, or die. We examine the global distribution of species’ vulnerabilities to climate change and habitat loss. Using integrodifference equations with information on demography and dispersal, we can quantify a population’s spreading speed -- the ability of a population to shift its range -- and its critical patch size – the size of habitat where population growth due to reproduction balances population loss through dispersal. We analyze the distributions of spreading speeds and critical patch sizes across a defined set of species within a system (e.g., community or taxonomic group). We use a range of distributions for population growth rates and dispersal. We explore the effect of covariation in population growth rates and dispersal - either positive or negative - on the resulting distributions of species’ spreading speeds and critical patch sizes.
Results/Conclusions
We developed a method that uses the distribution and covariance of dispersal ability and demography across species to calculate the expected distributions of spreading speeds and critical patch sizes. We analyzed the distributions for spreading speeds and critical patch sizes when dispersal variance and the geometric growth rates are independent and either fixed or distributed according to an exponential, gamma, modified gamma, or log-normal. We also calculated the distribution when the dispersal variance and growth rate are correlated based on the bi-variate lognormal distribution and the bi-variate gamma distribution. We can use these distributions to estimate the proportion of species that can shift their ranges in response to climate change or persist based on a minimum critical patch size. This approach allows us to predict responses to environmental change across a broad range of species for which data may be lacking, and this is particularly important for developing indicators of biodiversity loss and planning of remedial actions.