Natural history collections and the conservation of poorly known taxa: Ecological niche modeling in central African rainforest genets (Genetta spp.)

Natural history collections are crucial resources for conservation biology, particularly given the development of the ecological niche modeling (ENM) approach. We combined ENM with taxonomic investigations to address ecological, geographic, and phenotypic variation in the poorly known central African rainforest genets (Genetta cristata, Genetta servalina, Genetta victoriae) to provide new insights into their conservation status. Taxonomic identification was based on four discrete morphological characters. ENMs were developed using the Genetic Algorithm for Rule-Set Prediction (GARP), 10 environmental data layers and 310 georeferenced localities extracted from 667 museum specimens and 22 literature sources. Re-assessed taxonomic identifications allowed us to expand significantly the known range and ecological limits of the three genets. We suggested limited hybridization between G. cristata and G. servalina, in a zone of sympatry likely to cover central Cameroon, northwestern Gabon and Congo. ENM showed that almost all known occurrences were connected geographically by suitable ecological conditions, suggesting continuous potential distributions between supposedly isolated populations of the three genets. Our investigations indicated that G. cristata is distinct from G. servalina in morphology, geographic ranges and ecological niches, indicating species status for G. cristata, which, as such, should be the subject of appropriate conservation attention. Areas of predicted connectivity and actual zones of occurrence falling outside current forest cover should be surveyed to re-assess the status of the rainforest genets. Our study shows that combining ENM and taxonomic investigations can substantially improve data utilization from natural history collections, especially in the case of poorly known species.