BayFish – Tonle Sap: A Bayesian Model of The Fish Production In The Tonle Sap Great Lake, Cambodia

Probabilistic Bayesian networks have been used as decision making tools mainly in medicine and economics, but recently they have also been utilized in natural resource management. In this study a Bayesian model is built as a decisionmaking tool for fisheries management in the Tonle Sap Lake in Cambodia. As the largest freshwater fishery in the world, the Tonle Sap has enormous importance to both Cambodia and the whole of Lower Mekong Basin. The Tonle Sap Lake is an extremely dynamic and unique system due to the annual reversal of its outlet, which inundates large areas of the floodplain. In this case Bayesian network was used as the modelling tool for fisheries production because it was readily available and easily adaptable for this system. No effort was taken to test other modelling options or compare this model to other models, which also could have been used for this study. As in many developing countries there is a serious lack of data and knowledge of the system. To compensate for this deficiency, extensive stakeholders consultation was undertaken. The model is designed as a tool for decision makers responsible for the management of the Tonle Sap Lake fisheries.