A GIS framework for the refinement of species geographic ranges

The archives of species range polygons developed under comprehensive assessments of the conservation status of species, such as the IUCN's Global Assessments, are a significant resource in the analysis of biodiversity for conservation planning. Species range polygons obtained from these studies are known to exhibit omissions (because of knowledge gaps) and imprecision in their boundaries. In this work, we present a method to refine those species range polygons in order to create more realistic representations of species geographic ranges. Using range polygons of four species of mammals in South America and environmental variables at a 1 km resolution, combined with a set of GIS algorithms, a procedure was developed to map the confidence that sub-polygon elements belong to a logical species range. The confidence map is then used as a weight for a Mahalanobis typicality empirical modelling procedure to generate a map of species-weighted typicalities that is then thresholded to generate the refined species range map. Methods for variable selection and quality assessment of the refined range are also included in the procedure. Analysis using independent validation data shows the power of this methodology to redefine species ranges in a more biophysically reasonable way. The quality of the final-range map depends on the habitat suitability threshold used to define the species range. The report of quality assessment produced is useful for identifying not only the threshold that produces the highest match to the original expert range but also for flagging those ranges with higher discrepancies, facilitating the identification of ranges that need further revision. The archives of species range polygons developed under comprehensive assessments of the conservation status of species, such as the IUCN's Global Assessments, are a significant resource in the analysis of biodiversity for conservation planning. Species range polygons obtained from these studies are known to exhibit omissions (because of knowledge gaps) and imprecision in their boundaries. In this work, we present a method to refine those species range polygons in order to create more realistic representations of species geographic ranges. Using range polygons of four species of mammals in South America and environmental variables at a 1 km resolution, combined with a set of GIS algorithms, a procedure was developed to map the confidence that sub-polygon elements belong to a logical species range. The confidence map is then used as a weight for a Mahalanobis typicality empirical modelling procedure to generate a map of species-weighted typicalities that is then thresholded to generate the refined species range map. Methods for variable selection and quality assessment of the refined range are also included in the procedure. Analysis using independent validation data shows the power of this methodology to redefine species ranges in a more biophysically reasonable way. The quality of the final-range map depends on the habitat suitability threshold used to define the species range. The report of quality assessment produced is useful for identifying not only the threshold that produces the highest match to the original expert range but also for flagging those ranges with higher discrepancies, facilitating the identification of ranges that need further revision.