Effects of alternative sets of climatic predictors on species distributionmodels and associated estimates of extinction risk: A test with plantsin an arid environment

Abstract

tThe effects of using alternative sets of climatic predictor variables on the performance, spatial predictionsand future projections of species distribution models (SDMs) and its consequences on extinction riskestimates have remained insufficiently studied.Here, we modelled the present and future potential distributions of 13 species of Heliotropium sect.Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied asequential procedure, starting from climate monthly variables, to derive six alternative sets of climaticpredictor variables. We used them to fit models with eight modelling techniques within an ensembleforecasting framework, and derived climate change projections for each of them. We evaluated the effectsof using these alternative sets of predictor variables on performance, spatial predictions and projectionsof SDMs using Generalised Linear Mixed Models (GLMM). Our Results show that the use of different setsof climatic predictor variables did not have a significant effect on overall metrics of model performance,but had significant effects on present and future spatial predictions and extinction risk estimates. Thisform of uncertainty in model-based estimates of extinction risk may need to be better acknowledged andquantified in future SDM studies.