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Wildfire occurrence varies among regions and through time due to the long-term impacts of climate on fuel structure and short-term impacts on fuel flammability. Identifying the climatic conditions that trigger extensive fire years at regional scales can enable development of area burned models that are both spatially and temporally robust, which is crucial for understanding the impacts of past and future climate change. We identified region-specific thresholds in fire-season aridity that distinguish years with limited, moderate, and extensive area burned for 11 extensively forested ecoregions in the western United States. We developed a new area burned model using these relationships and demonstrate its application...
Categories: Publication; Types: Citation
The effects of changing climate and disturbance on mountain forest carbon (C) stocks vary with tree species distributions and over elevational gradients. Warming can not only increase C uptake by stimulating productivity at high elevations but also enhance C release by increasing respiration and the frequency, intensity and size of wildfires. To understand the consequences of climate change for temperate mountain forests, we simulated interactions among climate, wildfire, tree species and their combined effects on regional C stocks in forests of the Greater Yellowstone Ecosystem, USA (GYE) with the LANDISā€II landscape change model. Simulations used historical climate and future potential climate represented by downscaled...
Categories: Publication; Types: Citation
Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1-km resolution and monthly intervals from 1990 through 2019 in the Southern Rocky Mountains ecoregion. We quantified risk by combining the predicted burn probabilities with decadal housing density. We then compared the predicted burn probabilities and risk across the study area with observed values and quantified trends. Finally,...
Categories: Publication; Types: Citation