Half of the world’s ecoregions are fire-dependent – meaning that fire disturbances will in some way affect ecosystem services, including water resources and critical habitat, for threatened and endangered species. Additionally, anticipating fire behavior to estimate risks associated with fire containment, valued infrastructure, or land management goals is a vital component to any fire management action, including prescribed fire. Therefore, knowing how wildland fire behavior affects natural systems is necessary to understanding how these systems will evolve over time, as well as to quantify potential risks from fire disturbance, especially in light of climate change which is projected to cause an increase in wildland fire activity. Already novel fire conditions resulting from fire suppression and climate change are causing operational fire behavior models to fail, partly because these models are rooted on past observations and may not capture system behavior in novel conditions. Alternatively, mechanistic models based on the underlying physics of fire behavior and ecohydrologic response offer a possible path to understanding fire-dependent ecosystem response in novel conditions. I will present three examples where mechanistic models are used to understand complex physical links that connect fire behavior, hydrology, and ecosystem response.
Adam Lee Atchley completed a Bachelor's degree in plant ecology (2003) in the College of Forestry at Oregon State University and his Master's and Doctoral degrees in hydrological science and engineering (2009, 2013) at the Colorado School of Mines. Currently he is a research scientist and ecohydrologist with the Computational Earth Science Group at Los Alamos National Laboratory. His research centers on how physical hydrology connects wide-ranging earth systems. He is currently developing modeling strategies to account for surface and subsurface water balance changes in/at the hillslope to basin scale due to climate change. Large-scale disturbances and drought have induced dramatic vegetation change in the southwest, which has implications for water resources. Furthermore, basin wide shifts from snow- to rain-dominated regimes will also contribute to evolving hydrological systems. Predicting changes in an evolving system necessitates mechanistic modeling strategies that couple hydrology with dynamic vegetation. Atchley is particularly interested in employing these dynamically coupled models to tease out complex biological and hydrological cause and effect relationships as the hillslope and catchment scale.