Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: A test with plants in an arid environment

The effects of using alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) and its consequences on extinction risk estimates 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 a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Our Results show that the use of different sets of 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. This form of uncertainty in model-based estimates of extinction risk may need to be better acknowledged and quantified in future SDM studies.