A proposed methodology for the predictive and cartographic modeling of an insect population: Semidalis kolbei in La Araucanía Region, Chile

Abstract

Semidalis kolbei occupies a significant area of south central Chile. However, it is necessary to determine and predict the occurrence of the insect at a given site. The aim of this research is to analyze the potential spatial distribution of S. kolbei in La Araucanía Region of Chile. The study compares ordinary kriging (OK) interpolation methods, geographically weighted regression (GWR) and global regression (GR). The following variables were used in the investigation: topography (altitude, aspect, and slope), distance from the littoral, climate, and geographical variables (latitude and longitude). Of the models evaluated, the GWR proved to be the most successful. This model revealed a marked east-west gradient in the distribution of S. kolbei and a relationship with altitude