A predictive diagnostic model for wild sheep (Ovis orientalis) habitat suitability in Iran

Wild sheep (Ovis orientalis) as the true ancestor of domestic sheep (Ovis aries) is currently listed as vulnerable (VU) by IUCN. Effective conservation of this species requires collecting all available ecological knowledge into a single framework that could be used for management decision making. Use of Bayesian Belief Networks for such purposes have been advocated over recent decades as this approach can integrate different sources of knowledge and perform comprehensive analyses. We built a decision support tool using BBN to assist in habitat management of wild sheep populations throughout the species’ geographical range. The behaviour of the model was tested using scenario and sensitivity analysis. Habitat security, food and water suitability, and thermal cover were recognised as the main habitat variables determining wild sheep habitat suitability. Integrating the complex interactions between variables, the model can be applied for both diagnostic and predictive analyses answering “what if” and “how” questions. This approach can assist wildlife conservationists for building similar models for other poorly-studied threatened species.