Moving forward with extinction risk predictions from climate change

15 10 2008

A little belated, but I thought this was worth mentioning for the Potential list…

182kydeee9pyxjpgOne from Keith and colleagues in Biology Letters entitled Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models is a nice example of a way forward to predict the extremely complex array of ecological processes and patterns that may arise from rapid climate change.

One of the major problems with predicting how biodiversity might respond to climate change is the typical simplicity of single-species ‘envelope’ models – these models basically use tolerance limits (generally, physiological) or optimum conditions to predict how a species’ distribution might change. Unfortunately, this usually negates the complex dynamics of populations, the dispersal capacity of individuals, and interactions with other species that may all dominate possible responses. In other words, climatic envelope models may be way, way off (and probably vastly optimistic).

Keith and colleagues have brought us a step closer to better predictions of (and hopefully, better responses to) climate change effects on species. They linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations in South African fynbos, a global biodiversity hotspot. They discovered that complex interactions between life history, disturbance regimes and distribution patterns mediate species extinction risks under climate change.

Well done! Our next challenge is to incorporate multiple species’ interactions into such models (just to make them as mind-bogglingly complex as possible) to give us better approaches for managing our depauperate future.

CJA Bradshaw

Add to FacebookAdd to NewsvineAdd to DiggAdd to Del.icio.usAdd to StumbleuponAdd to RedditAdd to BlinklistAdd to Ma.gnoliaAdd to TechnoratiAdd to Furl