Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California

Park, Isaac W. and Mann, Michael L. and Flint, Lorraine E. and Flint, Alan L. and Moritz, Max and Pickell, Paul (2021) Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California. PLOS ONE, 16 (11). e0254723. ISSN 1932-6203

[thumbnail of journal.pone.0254723.pdf] Text
journal.pone.0254723.pdf - Published Version

Download (2MB)

Abstract

In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate–through limitations posed by fuel dryness (CWD) and availability (AET)–and human activity–through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modeling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.

Item Type: Article
Subjects: Eurolib Press > Geological Science
Depositing User: Managing Editor
Date Deposited: 21 Feb 2023 06:27
Last Modified: 02 Mar 2024 04:25
URI: http://info.submit4journal.com/id/eprint/581

Actions (login required)

View Item
View Item