Data for comparison of climate envelope models developed using expert-selected variables versus statistical selection

Climate envelope models are increasingly used to characterize potential future distribution of species under climate change scenarios. It is acknowledged that the use of climate envelope models comes with both strengths and limitations, and that results are sensitive to modeling assumptions, inputs, and specific methods. The selection of predictor variables, an integral modeling step, is one factor that can affect the modeling outcome. The selection of climate predictors is frequently achieved using statistical methods that ascertain correlations between species occurrence and climate data; this approach has been critiqued because it depends on statistical properties of the data, and does not directly implement biological information about how species respond to temperature or precipitation. In this study, we compared models and prediction maps for 15 threatened or endangered species in Florida created using two variable selection techniques: expert opinion and a statistical method. We compared model performance for contemporary predictions, and also compared the spatial correlation, spatial overlap, and area predicted for contemporary and future climate predictions between these two approaches (Brandt et al. 2017).

The data we used for this study include species occurrence data (n=15 species), climate data and predictions, an expert opinion questionnaire, and species masks that represented the model domain for each species. The species occurrence data, climate data, and climate predictions are freely available online, and therefore not included in this data release. The species occurrence data were obtained primarily from the online database Global Biodiversity Information Facility (GBIF; http://www.gbif.org/), and from scientific literature (Watling et al. 2011). Climate data were obtained from the WorldClim database (Hijmans et al. 2005) and climate predictions were obtained from the Center for Ocean-Atmosphere Prediction Studies (COAPS) at Florida State University (https://floridaclimateinstitute.org/resources/data-sets/regional-downsc…).

For this data release, we include the results of the expert opinion questionnaire and the species model domains (or masks). We developed an expert opinion questionnaire to gather information regarding expert opinion regarding the importance of climate variables in determining a species geographic range. The species masks, or model domains, were defined separately for each species using a variation of the target-group approach (Phillips et al. 2009), where the domain was determine using convex polygons including occurrence data for at least three phylogenetically related and similar species (Watling et al. 2012).