Over recent years, the population of Caspian cobra Naja oxiana has declined in its distribution range in Iran due to habitat destruction and overhunting. Consequently, their small and isolated populations in fragmente...Over recent years, the population of Caspian cobra Naja oxiana has declined in its distribution range in Iran due to habitat destruction and overhunting. Consequently, their small and isolated populations in fragmented landscapes are facing genetic and demographic threats. Evaluating the spatial distribution pattern of Naja oxiana, identifying core habitat patches and improving landscape connectivity among the patches have a significant role in the long-term survival of the species. This study predicts the spatial distribution map of the Caspian cobra considering the factors affecting the predictive power of the distribution models, including sampling bias in presence points, correct selection of background locations, and input model parameters. The sampling bias in presence points was removed using spatial filtering. Several models were run using 19 environmental variables that eventually led to the selection of the effective habitat variables and best MaxEnt distribution model. We also used an ensemble model(EM) of habitat suitability methods to predict the potential habitats of the species. Topographical roughness, shrublands, average annual precipitation, and sparse rangeland with a density of ≤ 20% had the most effect on the spatial distribution of Caspian cobra. The evaluation of models confirmed that the EM has more predictive performance than MaxEnt in predicting the distribution of Naja oxiana.展开更多
文摘Over recent years, the population of Caspian cobra Naja oxiana has declined in its distribution range in Iran due to habitat destruction and overhunting. Consequently, their small and isolated populations in fragmented landscapes are facing genetic and demographic threats. Evaluating the spatial distribution pattern of Naja oxiana, identifying core habitat patches and improving landscape connectivity among the patches have a significant role in the long-term survival of the species. This study predicts the spatial distribution map of the Caspian cobra considering the factors affecting the predictive power of the distribution models, including sampling bias in presence points, correct selection of background locations, and input model parameters. The sampling bias in presence points was removed using spatial filtering. Several models were run using 19 environmental variables that eventually led to the selection of the effective habitat variables and best MaxEnt distribution model. We also used an ensemble model(EM) of habitat suitability methods to predict the potential habitats of the species. Topographical roughness, shrublands, average annual precipitation, and sparse rangeland with a density of ≤ 20% had the most effect on the spatial distribution of Caspian cobra. The evaluation of models confirmed that the EM has more predictive performance than MaxEnt in predicting the distribution of Naja oxiana.
