Effects of Alternative sets of Climate Predictors on Species Distribution Models and Estimates of Extinction Risk

by Kyle Jensen

As arid ecosystems have been recognized as being especially sensitive to climate change, they thus provide an appropriate system to assess the use of SDMs in estimating the threat of climate change to various species. Species distribution models (SDMs) can quantify relationships between species and environmental factors, and use this data to predict spatial distributions. SDMs are thus widely used to derive projections of species distribution under conditions of climate change. These models are correlative however, and as such are unable to identify causal species-environment relationships. They can only be used as supporting evidence for an existing hypothesis on factors affecting species distribution; as such the factors must be chosen as inputs for the SDM to function. Identifying the important climatic factors involved in determining the range of a given species is a key factor in assessing the potential effects of climate change on species distribution and extinction risk. Little research however has been done investigating the effects using alternative sets of climate predictor variables may have on the projections of SDMs. Pliscoff et al (2014) seek to examine this area of potential uncertainty, addressing the potential variability of SDM spatial projections and determination of extinction risks through the creation and analysis of several sets of environmental predictors. They found that by adjusting climate predictor variables they were able to significantly affect predictions of spatial distribution as well as, for the first time, extinction risk estimates. This implies greater variability in such studies than previously thought. Continue reading