Assessing the probability of wildfire occurrences in a neotropical dry forest

Abstract

ABSTRACT In tropical dry forests, wildfires are likely to become a major disturbance as a result of anthropogenic pressures and dryer conditions due to climate warming. Based on remote sensing techniques, this paper assesses the probability of fires occurring in the dry region of the Guanacaste Conservation Area (GCA), northwestern Costa Rica, testing the roles as fire determinants of topography, early successional forest stages, between-area susceptibility, and accessibility to human (roads and trails). Probability of fire occurrence and fire danger were determined based on a machine learning algorithm. Fire occurrence model was inferred from burned areas and fire line density; while fire danger was inferred from the probability of fire occurrence, the proportion of burned areas, and the number of fires per area. Results indicate that the presence of early successional vegetation on flat lowlands highly accessible by roads and trails are key components of fire occurrence. Three of the six investigated sectors show high probability of fire occurrence and fire danger, indicating the spatial heterogeneity of fire risk in the landscape. The results could be useful for the management of the conservation area.