Temporal matching of occurrence localities and forest cover data helps improve range estimates and predict climate change vulnerabilities

Improved quantification of species’ ranges is needed to provide more accurate estimates extinction risks for conservation planning. Highland tropical biodiversity may be particularly vulnerable the anthropogenic changes in land cover and climate subject overestimation geographic range size IUCN assessments. Here, we demonstrate a novel practical approach quantifying inferred reductions based upon temporal matching recent species occurrence localities vegetation data. As an illustration pertinent montane forest-associated with limited distribution data, use Gymnuromys roberti, endemic Malagasy rodent Least Concern status. We estimated climatic suitability change vulnerability using modeling (SDM). then determined deforestation tolerance thresholds by temporally percent forest values from MODIS layers. Finally, applied these postprocessing SDM-based estimates. These that lack sufficient substantially reduces current compared map. Projections 2050 suggest there will loss over three quarters currently suitable habitat along increased fragmentation, highlighting need include assessments as integral part Broader application SDMs could assist practitioners at various stages planning, stressing improved accessibility methodologically complex SDM approaches.