Annual precipitation drives fire occurrence across sub-humid and semi-arid ecological gradients

Abstract

Fire is an integral part of semiarid to moderately humid ecosystem dynamics in North America. The biogeographical settings in which fires readily occur are affected by global processes like climate change, as well as local and regional characteristics such as terrain, proximity to human infrastructure, and vegetation structure. Increasing numbers and severity of fires today requires high-resolution and accurate predictions of fire probability. Species distribution models (SDM) allow researchers to identify environmental predictors of fire and depict the probability of fire occurrence. We applied a Maximum Entropy (Maxent) SDM to identify fire predictors and fire risk across a broad biogeographic humid to semi-arid climate gradient within the state of Texas. We used 15 years (2001-2016) of remotely sensed fire occurrence data, along with 13 biophysical variables representing climate, terrain, human activity, and landcover to generate multiple models. Annual precipitation was the primary predictor of fire occurrence, followed by elevation and landcover. After projecting fire probability onto three climate scenarios, we found moderate change in fire distribution. Humid and sub-humid areas had higher probabilities of fire occurrence while arid regions had lower probabilities under those scenarios. Overall, the linkage between fire occurrence and annual precipitation suggests that climate-driven fire probabilities will be variable under projected future climates.