Species distribution model transferability and model grain size – finer may not always be better
Syed Amir Manzoora b✉, Geoffrey Griffithsc, Martin Lukáčb d
- aSchool of Agriculture, Policy and Development, University of Reading, Reading, UK. s.a.manzoor@pgr.reading.ac.uk
- bSchool of Agriculture, Policy and Development, University of Reading, Reading, UK
- cDepartment of Geography and Environmental Science, University of Reading, Reading, UK
- dFaculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic
- ✉Corresponding author
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Abstract
Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.
TL;DRIt is found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. (Semantic Scholar)