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There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. Modeling the viability of the free-ranging cheetah population in Namibia: an object-oriented Bayesian network approach. Integrating additional empirical data into this network, as it becomes available, will help identify clear opportunities for improvements in farming practices which should reduce the risk of crop failure into the future.Ģ013. By engaging the farmers in this process of model development, we were able to identify additional research questions for the broader research team and to identify simple steps the farmers could take to reduce the risk of crop failure.

Overall, farmers perceived they have a better chance to minimise risk of failure for shrimp rather than rice crops, and limited opportunities appear to exist for successful production of both. The network identified the challenges to minimise the risk of failure for both crops, and the steps farmers can take to mitigate some of them. While both farmers and extension officers contributed to the identification of the processes included in the network, the farmers alone provided estimates of the probability of the relationships among them. The resulting network represents the experts' perceptions of the key risk factors to production and the interactions among them. We applied the approach in the Southern Mekong Delta, Vietnam, in the context of a broader research program into the sustainability of the rice-shrimp farming system. We applied a staged, iterative process to develop a probabilistic Bayesian belief network based on expert knowledge that describes the relationships that contribute to the risk of failure of both crops in integrated rice-shrimp farming systems during the wet season. Consequently, different farming practices and environmental factors that may affect crop production need to be clarified to guide research efforts. Research has yet to identify the complete array of key risk factors, and their potential interactions, for integrated rice-shrimp farming. Climatic variability has resulted in considerable crop losses in this system across many regions. While these systems were developed as a form of crop-rotation – growing rice in the wet season and shrimp in the dry season – some farmers grow both rice and brackish-water shrimp simultaneously during the wet season. In recent years, across tropical regions of the world, there has been an expansion of integrated farming systems that combine rice and shrimp production.

Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.

They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa.

Network inspector report blank rapid fir tools