Habitat suitability modelling of wild goat using Maximum entropy (MaxEnt) model in Hormood protected area (Fars province, Iran)

Abstract

Introduction: In this study, the habitat suitability of wild goats has been modeled in Hermod protected area with 208,731 hectares extent. This area, located in southern Zagros Mountains between Fars and Hormozgan provinces with a hot and dry climate, suffered severe droughts and a gradual decrease of habitats quality as a result in recent years. wild goat is a large-sized species and play a key role in the middle of the mountainous ecosystem’s food chain in Iran. In addition to controlling the balance of herbaceous species, this species plays an important role in the diet of large predators such as leopards and wolves. Two main goals of the present study were to identify the habitat prefers of this species and to determine the importance and degree of influence of each of the influencing factors on the suitability of its habitat. Material & methods: Using global positioning system and field visits throughout the year (From the beginning of the spring to the end of the winter of 2023), 66 presence points of wild goats were recorded as dependent variables. Environmental variables (including 18 bioclimatic variables, three topographic variables and six human variables) was also assigned as independent variables and using the Maximum entropy (MaxEnt) software habitat suitability was modeled. To create 19 bioclimatic variables derived from temperature and precipitation (Bio1-Bio19), the Biovars function was used in the dismo package in the R software. 70% of the total presence points were used for modeling (training) and 30% for model validation (test). The validity of the model was measured based on the area under the ROC curve (AUC). Results: The results of habitat suitability modeling showed that a total of 19021.72 hectares (9.11%) of the Hermod protected area, is suitable for wild goats. In terms of the validity of the model results, in this study, the value of AUC was 0.939, which indicates the excellent predictive performance of the model. The results of examining the importance of the factors affecting habitat suitability showed that the most important variables are elevation and slope with 37.3% and 19.3% respectively. Conclusion: The results of the present study can help wildlife managers and policy makers to meet conservation and management goals and reduce the conflict between wildlife and humans.