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

Chase T Brooke,William E Rogers,A Michelle Lawing,Charles W Lafon

doi:10.21425/f5fbg49497

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.

Highlights

Global climate change is predicted to change fire activity across all terrestrial biomes, with fires generally increasing in number and severity (Dennison et al 2014)
We modeled the probability of fire occurrence using the Maximum Entropy (Maxent) model (Version 3.3.3k) (Phillips et al 2006)
Modeling fire occurrences with Species distribution models (SDM) showed that the comprehensive model had the highest area under the receiving operator curve (AUC), and predictability, followed by the climate, terrain, landcover, and human impacts models, respectively (Table 2)

Summary

Introduction

Global climate change is predicted to change fire activity across all terrestrial biomes, with fires generally increasing in number and severity (Dennison et al 2014). Fire activity in sub-humid and semi-arid drylands has increased alongside climate change and human activity over the past 50 years (Ortega et al 2012) These trends in fire activity vary based on historical climate, vegetation type, and topography, each influencing fire-environment interactions (Parisien et al 2012). Sub-humid and semi-arid drylands comprise 41% of all terrestrial land area, and 34% of the world’s population resides within these biomes (Maestre et al 2012, SCBD 2013). Vegetation productivity in these regions is frequently water-limited and subjected to regular drought and fire activity (Vallejo et al 2012). Climate warming is expected to alter climate controls on fire occurrence globally (Flannigan et al 2009), a regional understanding of climate controls and their future shifts is necessary to prepare for alternative fire-regime futures

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Results

Conclusion