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

Abstract

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

Keywords

• Climate change
• Deforestation
• Distribution
• Gymnuromys roberti
• IUCN criteria
• Montane species