GC33E-1338
Relative Influence of Top-Down ond Bottom-Up Controls on Mixed Severity Burn Patterns in Yosemite National Park, California, USA

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Van R Kane1, Nicholas Povak2, Matthew Brooks3, Brandon Collins4, Douglas Smith5 and Derek Churchill1, (1)University of Washington Seattle Campus, School of Environmental and Forest Sciences, Seattle, WA, United States, (2)US Forest Service Hilo, Pacific Southwest Research Station, Hilo, HI, United States, (3)U.S. Geological Survey,, Yosemite Field Station, El Portal, CA, United States, (4)US Forest Service Davis, Davis, CA, United States, (5)US Forest Service, Superior National Forest, Ely, MN, United States
Abstract:
In western North America, recent and projected increases in the frequency and severity of large wildfires have elevated the need to understand the key drivers of fire regimes across landscapes so that managers can predict where fires will have the greatest ecological impact, and anticipate changes under future climate change. Yosemite National Park offers a unique opportunity to study potential biophysical controls on fire severity patterns – fire management in this area has allowed many fires to burn since the 1970s, re-establishing a mixed severity fire regime. Previous studies within the park showed a high level of control from a variety of bottom-up (e.g., fire history, topography) and top-down (e.g., climate) variables on fire severity within a portion of the current study area, and found some evidence controls may break down for the largest fires. In the current study, we sought to identify (1) controls on fire severity across all fires that burned within Yosemite (1984-2013), (2) differences in controls across fire sizes, (3) the contributions of topographic, climatic, and fire history variables to total variance explained, and (4) the influence of spatial autocorrelation on model results. Our study includes 147 fires that burned over 78,500 ha within Yosemite. Modeling results suggested that fire size and shape, topography, and localized climate variables explained fire severity patterns. Fires responded to inter-annual climate variability (top-down) plus local variation in water balance, past fire history, and local topographic variability (bottom-up). Climate-only models lead to the highest level of pure variance explained followed by fire history, and topography models. Climate variables had distinctly non-linear relationships with fire severity, and key drivers were related to winter conditions. Fire severity was positively correlated with fire size, and severity increased towards fire interiors. Steeper and more complex topographies were associated with increased fire severity. The level of control among these factors varies across fire sizes indicating possible scale-wise shifts in dominance among controls. We will discuss differences in drivers across fire sizes to help identify where local climate conditions supersede bottom-up controls.