The importance of plant water and carbon dynamics to fire behavior and effects and a framework to link remotely sensed estimates to fire models.
The condition of living woody plants can change fire behavior. Plants can have different levels of dryness throughout the seasons and in different parts of a landscape based water and nutrients in the soil. Lower levels of live fuel moisture in plants can be linked to faster fires and change the way fires burn and how likely plants are to die after a fire. Using live fuel moisture measurements from remote sensing tools, such as airborne systems, and linking these to models of fire behavior and effects we can improve our understanding of how fires may change in the future.
Fire behavior models have long used general fuels in broad groups. Now with new types of models and remote sensing measurements of fuels and fires, we can capture more realistic fuels and how they change in both their condition, such as live fuel moisture, and their structure. This information is critically important for fire management in conditions of drought and warming. Linking how living plants change through time and across a landscape to how fires might behave will give us information we need to better support communities in a world with more fire.
Wildfires have been recognized as a global crisis, but current fire models do not capture how living plants change in response to changing climate. With drought and warming temperatures increasing the importance of living plants as a factor in changing fire behavior, and new capabilities of models, we are able to capture these complex processes and interactions. We provide a renewed focus on capturing live woody plants in fire models. Living plant conditions and properties influence fire combustion and heat transfer and often dictate if a plant will survive. These interactions provide a mechanistic link between living plants and fire behavior and effects that can be included in new models. We include a conceptual framework linking remotely sensed estimates of plant condition to models of fire behavior and effects, which could be a crucial first step toward improving models used for global fire forecasting. This process-based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future.
Contact: L.T. Dickman, Los Alamos National Laboratory, firstname.lastname@example.org
LTD, AJ, RRL and SS were supported by the Los Alamos National Laboratory (LANL) through its Center for Space and Earth Science (CSES). Center for Space and Earth Science is funded by LANL’s Laboratory Directed Research and Development (LDRD) program under project no. 20210528CR. AJ and ZJR received additional funding from LANL LDRD under project no. 20210689ECR. RPF and STM were supported by SERDP project RC18-1346 and an NSERC Discovery Grant. AB acknowledges funding from the Austrian Science Fund (FWF, project P32203) and from the University of Innsbruck (Early-Stage Funding, grant W-171705). MY receives funding from the Australian Research Council, the Australian Research Data Commons, The SmartSat Cooperative Research Centre and Singtel Optus Pty Limited. JKS was supported by the National Center for Atmospheric Research, a major facility sponsored by the National Science Foundation (NSF) under Cooperative Agreement no. 1852977, with additional support from NASA Arctic Boreal Vulnerability Experiment Grant 80NSSC19M0107. JKS, SPS and CX were also supported as part of the Next-Generation Ecosystem Experiments – Tropics, funded by the US Department of Energy, Office of Science, Office of Biological and Environmental Research. SPS was also partially supported by the NASA Surface Biology and Geology Mission Study (NNG20OB24A) and through the United States Department of Energy contract no. DE-SC0012704 to Brookhaven National Laboratory. CMH acknowledges US Department of Defense (DoD) Strategic Environmental Research and Development Program (SERDP) Project RC19-1119. IA declares support from NSF WIFIRE Commons under grants 2040676 and 2134904. VRD acknowledges funding from MICINN projects RTI2018-094691-B-C31; EU H2020 (grant agreements 101003890). RAP acknowledges support from US Department of Defense Strategic Environmental Research and Development Program’s Closing Gaps Project RC20-1025. USDA Forest Service personnel were supported by annual Forest Service appropriations.