Assessing translocation success of the endangered Persian fallow deer using a Bayesian Belief Network

Abstract

Abstract. For the past 50 years, the endangered Persian fallow deer (Dama mesopotamica) have been translocated to various sites throughout Iran. To better understand the varying degrees of success at the translocation sites, population growth rates were measured for all the sites, and factors believed to affect the growth rate, such as initial population structures of the translocated herds and habitat characteristics, were identified and modeled. The population growth rate was used as a proxy for translocation success. Quantitative ecological data for Persian fallow deer is scarce, but expert knowledge was readily available to inform and enhance fallow deer management options. We integrated the available quantitative data and qualitative information in a Bayesian Belief Network (BBN) model to predict Persian fallow deer translocation success. The BBN model was tested using scenarios based on previous translocations to 13 sites in Iran. It correctly predicted the success of translocated populations in 11 out of the 13 sites. This model may be used as a decision support tool for future translocations, and can assist in designing reintroduction programs of the Persian fallow deer. Moreover, it should be adapted to incorporate new knowledge as evidence of translocation successes and failures emerge. Although the BBN model was developed specifically for the translocation of Persian fallow deer, this approach can clearly be applied to design and assess the success of translocation programs of other endangered species, and may be extended to design and assess alternative conservation management strategies.