Modelling potential distribution of a pine bark beetle in Mexican temperate forests using forecast data and spatial analysis tools

Abstract

Accurate and reliable predictions of pest species distributions in forest ecosystems are urgently needed by forest managers to develop management plans and monitor new areas of potential establishment. Presence-only species distribution models are commonly used in these evaluations. The maximum entropy algorithm (MaxEnt) has gained popularity for modelling species distribution. Here, MaxEnt was used to model the spatial distribution of the Mexican pine bark beetle (Dendroctonus mexicanus) in a daily fashion by using forecast data from the Weather Research and Forecasting model. This study aimed to exploit freely available geographic and environmental data and software and thus provide a pathway to overcome the lack of costly data and technical guidance that are a challenge to implementing national monitoring and management strategies in developing countries. Our results showed overall agreement values between 60 and 87%. The results of this research can be used for D. mexicanus monitoring and management and may aid as a model to monitor similar species.

Keywords

Spatial analysis / Dendroctonus mexicanus / Geodatabases / MaxEnt / Forest modelling

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