Plant extinction risk under climate change: are forecast range shifts alone a good indicator of species vulnerability to global warming?

Abstract

Models that couple habitat suitability with demographic processes offer a potentially improved approach for estimating spatial distributional shifts and extinction risk under climate change. Applying such an approach to five species of Australian plants with contrasting demographic traits, we show that: (i) predicted climate‐driven changes in range area are sensitive to the underlying habitat model, regardless of whether demographic traits and their interaction with habitat patch configuration are modeled explicitly; and (ii) caution should be exercised when using predicted changes in total habitat suitability or geographic extent to infer extinction risk, because the relationship between these metrics is often weak. Measures of extinction risk, which quantify threats to population persistence, are particularly sensitive to life‐history traits, such as recruitment response to fire, which explained approximately 60% of the deviance in expected minimum abundance. Dispersal dynamics and habitat patch structure have the strongest influence on the amount of movement of the trailing and leading edge of the range margin, explaining roughly 40% of modeled structural deviance. These results underscore the need to consider direct measures of extinction risk (population declines and other measures of stochastic viability), as well as measures of change in habitat area, when assessing climate change impacts on biodiversity. Furthermore, direct estimation of extinction risk incorporates important demographic and ecosystem processes, which potentially influence species’ vulnerability to extinction due to climate change.

Disturbance and distributions: avoiding exclusion in a warming world

“…Whenever it has been studied, disturbance has been seen to influence plant distributions: for example, at local scales when facilitating the invasion of one species of Californian tarweed (Asteraceae) into the habitat of others or at larger scales when modeling plant distributions in dryland Australia (Fordham et al 2012). Disturbance histories are also recognized as key to understanding vegetation patterns worldwide (Johns 1986, Clark 1996, Chiarucci et al 2010, Gennaretti et al 2014).…”

Uses and misuses of bioclimatic envelope modeling

“…2). Dealing with dispersal and biotic interactions in such contexts is far from trivial and requires approaches that go beyond the analytical framework offered by bioclimatic envelope models (e.g., Keith et al 2008, Anderson et al 2009, Fordham et al 2012). …”

“…3). If the prediction concerns occupied distributional areas, estimates of colonization rates as well as climate suitability are required, and approaches that couple bioclimatic envelope models with metapopulation models can be useful (e.g., Keith et al 2008, Anderson et al 2009, Fordham et al 2012). Whether the modeler should weight errors of omission and commission equally in such cases, or down-weight errors of commission, is still a matter of debate.…”

The Climate Adaptation Frontier

“…Yet, understanding of such tipping points and thresholds remains poor. In ecosystem science, substantial questions remain regarding the significance, identification and interpretation of thresholds [86,87] Similarly, specifying species-and location-specific climate thresholds that represent limits to adaptation remains challenging, as does assessing the likelihood of exceeding such thresholds [88][89][90]. However, limits to adaptation are influenced not just by biophysical processes, such as climate change, but also by social processes and the values of individual actors [2,26,31,32].…”