Applying resource selection functions at multiple scales to prioritize habitat use by the endangered Cross River gorilla
Correspondence: Sarah Sawyer, USDA Forest Service, Pacific Southwest Region, 1323 Club Drive, Vallejo, CA 94592, USA.
The critically endangered Cross River gorilla is a patchily distributed taxon for which habitat selection has been modelled only at coarse spatial scales, using remotely sensed landscape data and large-scale species distribution maps. These coarse-scale models fail to explain why Cross River gorillas (CRG) display a highly fragmented distribution within what appears to be a large, continuous area of suitable habitat. This study aimed to refine our understanding of CRG habitat use to inform conservation planning both for the subspecies and for other fragmented species of conservation concern.
Cross River gorillas occur only in a discontinuous distribution in the southern portion of the Cameroon-Nigeria border region, an area that represents one of Africa's biodiversity hotspots. This study was carried out in the Northern Mone-Mt. Oko region, part of the Mone/Mbulu forest system located in the Manyu division of the South-west Province of Cameroon.
We used resource selection functions to understand habitat use by CRG at multiple scales. Specifically, we employed generalized additive models at the scale of the annual subpopulation range and conditional logistic regression at the scale of individual movements.
Cross River gorillas habitat selection is highly scale dependent. Localized measures of habitat quality strongly influenced selection at the subpopulation or landscape scale, while human activity and food availability were the best predictors of selection at finer scales.
Understanding why CRG do not occur in seemingly suitable habitat is crucial for designating critical habitat both within and between CRG subpopulations. Our results indicate that conservation planning to maintain critical habitat and connectivity among CRG populations will require an integrative, multi-scale planning approach incorporating large-scale landscape characteristics, human use patterns and CRG food availability.