Elusive species distribution modelling: The case of Natrix natrix cypriaca

Abstract

Improving knowledge on species distribution is a fundamental part of ecological research and imperative when it comes to species conservation and management. For rare, endemic, and elusive species the effort to obtain reliable ecological data is extremely challenging. Data sparsity, or the use of outdated data, for species that are in the greatest need of protection, hampers the ability to develop efficient conservation and management schemes.In the present research, we use SDMs to examine the predictive distribution of elusive species exemplified by the Cyprus grass snake (Natrix natrix cypriaca). We use two different methods (i.e. Maxent and Ensemble) and three different sets of environmental envelopes (i.e. bioclimatic, biophysical, combined) for predicting species distribution. We compare the results of each model with the Extent of Occurrence (EOO) and Area of Occupancy (AOO) of the species and map high potential occurrence areas for future survey efforts indicating areas of interest outside the species previously known distribution.This research is the first effort to predict and map the potential distribution of this elusive species. The results have significantly improved past estimations clearly indicating a geographic range larger and wider that what was previously thought, providing new perspectives on the species ecology and conservation. This study demonstrates that SDMs can be employed successfully for elusive species with limited current localities providing insights on their distribution guiding monitoring schemes and conservation actions.