مدل‌سازی نقش متغیرهای اقلیمی بر پراکنش کنه‌ تارتن دولکه‌ای در استان آذربایجان غربی

Recognizing the distribution of harmful mite species using climate data, geographical diversity, and optimal habitat determination from an animal geographic perspective can be of great help in better pest management. Species distribution modeling is one of the most common methods for determining the range and potential territory of geographical distribution of plant and animal species and usually determining this distribution in order to determine the appropriate environmental conditions as well as the action of species to this condition is used. There are several methods for modeling species distribution, one of the best and most widely used of which is the MaxEnt model. The MaxEnt software is based on the maximum- entropy approach for modeling species niches and distributions for presence- only species records. The MaxEnt model was used to potential distribution in several stations (orchards) of West Azerbaijan provinces in this study. Modeling the distribution of two-spotted spider mites using 6 environmental predictors and presence records including maximum temperature of the hottest month of the year, minimum temperature of the coldest month of the year, average temperature of the hottest season of the year, average temperature of the coldest season of the year, precipitation the warmest season of the year and the coldest rainy season of the year are among the 19 climatic variables. We used ROC curve analysis and the area below the AUC curve, which is a numerical indicator of the recognizing of the model's presence to evaluate the modeling result. AUC value equal to one means complete forecasting and without removing any of the presence points, above 0.9 indicates very good performance, above 0.8 indicates good performance, above 0.7 indicates acceptable performance. AUC value equal to 0.5 , is a random prediction for the expected model. The accuracy models were also evaluated by the area receiver operating characteristic curve (AUC) value in this study. According to the Jacknife test, variables of the temperature of the coldest season of the year, average temperature of the warmest season of the year and minimum temperature of the coldest month of the year were the most contributing in two-spotted spider mite distribution modeling in West Azerbaijan province that average temperature of the coldest season of the year was more important.