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摘要
Species distribution models are increasingly used in regional biodiversity assessments, pest management strate-gies, conservation biology, ecology and evolution. The Maximum Entropy model was applied to predict the potential dis-tribution of four egg parasitoids, e. g., Psix saccharicola, Trissolcus agriope, Trissolcus basalis and Trissolcus volgensis (all Hymenoptera: Scelionidae) in Kerman province, south of Iran. Presence records of the species sampled during 2012-2014 were used alongside with seven environmental predictors. Besides describing the climatic profile of the species, the contri-bution percentage of the bioclimatic variables was explored. The accuracy and performance of distribution models were also evaluated by the area under receiver operating characteristic curve (AUC) index. According to Jackknife, the mini-mum temperature of the coldest month was the most important predictor for the P. saccharicola distribution model. The temperature annual range and the minimum temperature of the coldest quarter were the most effective variables of species distribution for T. agriope and T. basalis, respectively. The mean diurnal range was the most important environmental factor for T. volgensis. The AUC values, based on training data, were 0.87 for P. saccharicola, 0.92 for T. agriope, 0.95 for T. basalis, and 0.89 for T. volgensis, confirming the high accuracy of MaxEnt in predicting the distribution model of these scelionid wasps.
- 出版日期2017-1
