There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Abstract
Concern over implications of climate change for biodiversity has led to the use of
bioclimatic models to forecast the range shifts of species under future climate-change
scenarios. Recent studies have demonstrated that projections by alternative models
can be so variable as to compromise their usefulness for guiding policy decisions.
Here, we advocate the use of multiple models within an ensemble forecasting framework
and describe alternative approaches to the analysis of bioclimatic ensembles, including
bounding box, consensus and probabilistic techniques. We argue that, although improved
accuracy can be delivered through the traditional tasks of trying to build better
models with improved data, more robust forecasts can also be achieved if ensemble
forecasts are produced and analysed appropriately.