Quantifying the human influence on fire ignition across the western USA

Area of Science:

• Ecology
• Environmental Science
• Remote Sensing

Background:

• Human activities are a primary driver of increased fire frequency globally.
• Existing fire models struggle to accurately incorporate ignition locations, leading to reliance on imprecise proxies.
• Understanding regional ignition patterns is crucial for effective fire management and ecological modeling.

Purpose of the Study:

• To create the first remotely sensed, regionally comprehensive fire ignition dataset for the western United States.
• To analyze the spatial relationships between anthropogenic land-use/disturbance features and fire ignitions.
• To determine how these relationships vary across different ecoregions.

Main Methods:

• Utilized Moderate Resolution Imaging Spectrometer (MODIS) Burned Area Product data from 2000-2012.
• Identified fire ignition points from satellite imagery.
• Employed hierarchical partitioning to assess the influence of various anthropogenic predictors on ignitions within distinct ecoregions.

Main Results:

• Developed a novel, consistently derived fire ignition dataset for the western US.
• Found significant variation in the predictive power of anthropogenic features across ecoregions.
• Identified railroad corridors and agricultural presence as strong predictors of ignition, outperforming population density and roads in many areas.

Conclusions:

• Anthropogenic land use, particularly agriculture and transportation corridors, are critical regional drivers of fire ignitions.
• The impact of human activities on fire regimes is heterogeneous and context-dependent across different ecoregions.
• Future fire modeling should incorporate specific land-use data for improved regional accuracy, moving beyond broad population proxies.