Maximum entropy modelling to predict the impact of abiotic variables on the potential distribution of Orthotomicus erosus (Wollaston) (Coleoptera, Curculionidae, Scolytinae) in Iran

Abstract

Risk assessment is utilized to prioritize preventive measures based on the probability of dispersal success of pests. A main part of the risk assessment procedure is to determine the effects of environmental variables on the current and potential geographical distributions. In the present study, the spatial distribution of the Mediterranean pine engraver, Orthotomicus erosus (Wollaston), was mapped and predicted using MaxEnt. Presence records of O. erosus (north, northeast, west and centre of Iran), environmental and topographic variables, with the lowest correlations among themselves and the highest effects on the pest distribution were used. A total of 76 presence records of O. erosus were collected. The results of the distribution prediction modelling revealed that the northern part of Iran and the areas along the Zagros are the most suitable habitats for this species. Examining environmental variable importance on the distribution of O. erosus showed that the variables related to temperature and precipitation had more contribution in the MaxEnt model, respectively than the altitude. Furthermore, the high accuracy of the model (0.928) indicated that the MaxEnt had an acceptable performance for the prediction of O. erosus distribution. These findings would provide primary and critical information about the potential distribution of O. erosus in Iran, which could be effective for the stable population regulation of this destructive pest.

Keywords

• climatic variables
• ecological niche
• jackknife
• maxent
• pine forests