Predicting the habitat usage of African black rhinoceros (Diceros bicornis) using random forest models.

Species distribution models are often used in ecology to ascertain relationships between environmental variables and species presence. Modelling to understand this relationship can be used to aid conservation management strategies. In this paper, we applied the random forest classification method to predict habitat used by black rhino for browsing. The random forest model was created using detailed habitat data collected from Ol Pejeta Conservancy in Kenya. Variables from plots where rhino had been present were compared to those not used by rhino. Independent data were used to test the predictive accuracy of the rules generated. The model performed well with the independent test data, correctly classifying 69% of the sampling plots where black rhino were present. Important habitat features that affected rhino presence were browse availability and density of vegetation, with Vachellia drepanolobium (formerly Acacia) and Euclea divinorum being important components. The analysis also highlighted areas of potential high browse pressure, which should be the focus of continued monitoring and management. [ABSTRACT FROM AUTHOR]