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Predicting the habitat usage of A frican black rhinoceros ( D iceros bicornis ) using r andom f orest models
Author(s) -
Lush Lucy,
Mulama Martin,
Jones Martin
Publication year - 2015
Publication title -
african journal of ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.499
H-Index - 54
eISSN - 1365-2028
pISSN - 0141-6707
DOI - 10.1111/aje.12192
Subject(s) - forestry , geography , habitat , ecology , vegetation (pathology) , random forest , biology , computer science , machine learning , medicine , pathology
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 r andom f orest classification method to predict habitat used by black rhino for browsing. The r andom f orest model was created using detailed habitat data collected from O l P ejeta C onservancy in K enya. 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 V achellia drepanolobium (formerly Acacia ) and E uclea divinorum being important components. The analysis also highlighted areas of potential high browse pressure, which should be the focus of continued monitoring and management.