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Comparing species distribution models constructed with different subsets of environmental predictors

October 7, 2014

Aim

To assess the usefulness of combining climate predictors with additional types of environmental predictors in species distribution models for range-restricted species, using common correlative species distribution modelling approaches.

 

Location

Florida, USA

 

Methods

We used five different algorithms to create distribution models for 14 vertebrate species, using seven different predictor sets: two with bioclimate predictors only, and five ‘combination’ models using bioclimate predictors plus ‘additional’ predictors from groups representing: human influence, land cover, extreme weather or noise (spatially random data).We use a linear mixed-model approach to analyse the effects of predictor set and algorithm on model accuracy, variable importance scores and spatial predictions.

 

Results

Regardless of modelling algorithm, no one predictor set produced significantly more accurate models than all others, though models including human influence predictors were the only ones with significantly higher accuracy than climate-only models. Climate predictors had consistently higher variable importance scores than additional predictors in combination models, though there was variation related to predictor type and algorithm. While spatial predictions varied moderately between predictor sets, discrepancies were significantly greater between modelling algorithms than between predictor sets. Furthermore, there were no differences in the level of agreement between binary ‘presence–absence’ maps and independent species range maps related to the predictor set used.

 

Main conclusions

Our results indicate that additional predictors have relatively minor effects on the accuracy of climate-based species distribution models and minor to moderate effects on spatial predictions. We suggest that implementing species distribution models with only climate predictors may provide an effective and efficient approach for initial assessments of environmental suitability.

Citation Information

Publication Year 2014
Title Comparing species distribution models constructed with different subsets of environmental predictors
DOI 10.1111/ddi.12247
Authors David N. Bucklin, Mathieu Basille, Allison M. Benscoter, Laura A. Brandt, Frank J. Mazzotti, Stephanie S. Romañach, Carolina Speroterra, James I. Watling
Publication Type Article
Publication Subtype Journal Article
Series Title Diversity and Distributions
Index ID 70100139
Record Source USGS Publications Warehouse
USGS Organization Southeast Ecological Science Center