Research Database
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Forest structural complexity and ignition pattern influence simulated prescribed fire effects
Year: 2024
Forest structural characteristics, the burning environment, and the choice of ignition pattern each influence prescribed fire behaviors and resulting fire effects; however, few studies examine the influences and interactions of these factors. Understanding how interactions among these drivers can influence prescribed fire behavior and effects is crucial for executing prescribed fires that can safely and effectively meet management objectives. To analyze the interactions between the fuels complex and ignition patterns, we used FIRETEC, a three-dimensional computational fluid dynamics fire…
Publication Type: Journal Article
Budworms, beetles and wildfire: Disturbance interactions influence the likelihood of insect-caused disturbances at a subcontinental scale
Year: 2024
Irruptive forest insects are a leading biotic disturbance across temperate and boreal forests. Outbreaks of forest insects are becoming more frequent and extensive due to anthropogenic drivers (e.g. climate and land-use), perhaps increasing the likelihood that forests will experience multiple insect-caused disturbances. Across the fire-prone Douglas-fir forests of western North America, recent outbreaks of the western spruce budworm and Douglas-fir beetle have impacted large expanses of forests, with a higher degree of overlap than expected in some ecoregions. Outbreaks of both insects are…
Publication Type: Journal Article
Disentangling drivers of annual grass invasion: Abiotic susceptibility vs. fire-induced conversion to cheatgrass dominance in the sagebrush biome
Year: 2024
Invasive annual grasses are often facilitated by fire, yet they can become ecologically dominant in susceptible locations even in the absence of fire. We used an extensive vegetation plot database to model susceptibility to the invasive annual grass cheatgrass (Bromus tectorum L.) in the sagebrush biome as a function of climate and soil water availability variables. We built random forest models predicting cheatgrass presence or dominance (>15 % relative cover) under unburned (37,219 plots) and burned conditions (6340 plots). We mapped predicted probability of cheatgrass…
Publication Type: Journal Article