Understanding wildfire occurrence and size in Jalisco, Mexico: A spatio-temporal analysis

Abstract

In recent years, the growing frequency and severity of wildfires, influenced by both human activities and climate change, have posed significant challenges worldwide. Among the regions most affected by wildfires in Mexico is the state of Jalisco, which has the largest accumulated burned area in the last five decades. In this paper, we present an in-depth analysis of the spatio-temporal patterns of wildfire occurrence and size in the state of Jalisco, spanning the period from 2001 to 2020. Our approach included modeling the spatial distribution of the area burned by wildfires, employing Bayesian methodology with Integrated Nested Laplace Approximation (INLA) and Stochastic Partial Differential Equations (SPDE). Our findings highlight the critical roles of vegetation, temperature, and human activities in shaping wildfire behavior. Additionally, our model suggests four distinct wildfire-prone regions within the state. The insights gained from this study can serve as a foundation for future research and localized studies, aiding in the development of more targeted and effective wildfire management strategies in Jalisco.