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

Are species distribution models validated by field trials?

by Kyle Jensen

Invasive species, especially plant species, are one of the greatest current threats to the Earth’s biodiversity. It is feared that with the advent of global warming areas favorable to such species will increase, especially for those invasives from warmer climates that have naturalized near areas of marginal temperature. This could have negative impacts on the diversity of exposed populations, so species distribution models (SDMs) have been developed to estimate possible future distributions of organisms. These models make predictions by relating occurrence data to environmental conditions, giving a general idea of how the potential threat of an invasive species may change over time, and suggesting possible mitigation activities. Such models however have rarely been tested against experiments from the field. Sheppard et al. (2014) seek to validate SDMs through field trials at varying sites based on suitability as predicted by SDMs. If the predicted success of species in the models matches those of actual field trials, then we could be more confident in ability of models to assess the risk of invasive success. The experiment also addresses the validity of the enemy release hypothesis, which is often assumed to be the case in invasive studies. The hypothesis posits that invasive species leave behind any natural enemies when they are introduced to a new environment, which would contribute to their success. This experiment questions that assumption and its use in SDMs. Continue reading

Disequilibrium between Tree Species Distributions and Regional Temperatures

by Cortland Henderson

Correlations between geographic distributions of plant species and the current climate have been identified, suggesting that species ranges will shift upwards if global temperatures rise. These links, however, are based on models that do not establish whether or not plant species are at equilibrium with the current climate, and are incapable of differentiating between naturally occurring shifts and climate-induced shifts. García-Valdés et al. (2013) examine the ten most common tree distributions throughout the Iberian Peninsula by creating a new species distribution model that relaxes built-in assumptions that tree species and climate are currently at equilibrium. Their model successfully removed previous biases and found that tree species are not at equilibrium Continue reading