Maxent model application for tree pest monitoring

Abstract

Tree pests can cause rapid and widespread damage, reducing the economic value of plants, production, in the case of fruit trees, and their role in mitigating climate change. There are several diseases that affect trees, including, for example, pine tree nematode (PWN), trunk fungal diseases, or Xylella fastidiosa (Xf).Mapping of diseased plants based on visual or automatic analysis of remote sensing data could be a useful support for in situ investigation planning. However, there is a clear need for better modeling methods to elaborate potential critical scenarios in order to early detect diseases (e.g. Xf) in host plants.Maxent (Maximum Entropy) has proved powerful when modeling species with available scarce presence-only occurrence data. The purpose is to predict potential distributions or explore expanding distributions. In this work we applied the Maxent model comparing local modeling results with worldwide cases towards a more comprehensive analysis of potential pest risk zones.Fil: Marzialetti, Pablo. Università degli Studi di Roma "La Sapienza"; ItaliaFil: Giovanni, Laneve. Università di Roma; ItaliaFil: Santilli, Giancarlo. Universidade do Brasília; BrasilFil: Huan, Wenjiang. Chinese Academy of Sciences; República de ChinaFil: Zappacosta, Diego Carlos. Universidad Nacional del Sur. Departamento de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaInternational Symposium on Geoscience and Remote SensingJapónInstitute of Electrical and Electronics EngineersThe Geoscience and Remote Sensing Societ