Ecosphere Publishes Study: Modelling tools can effectively assess wild cheetah populations even in the face of uncertainty
- July 30, 2013
- by S. Johnson, Marker L. L., K. Mengersen, C.H. Gordon, J. Melzheimer, A. Schmidt-Küntzel, Nghikembua M., Fabiano E. C., J. Henghali, B. Wachter
Conservation of free‐ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object‐oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free‐ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free‐ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free‐ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi‐expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free‐ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.