Use of the Wildland Fire Decision Support System (WFDSS) for full suppression and managed fires within the Southwestern Region of the US Forest Service

Self Cite

Background The decision making process undertaken during wildfire responses is complex and prone to uncertainty. In the US, decisions federal land managers make are influenced by numerous and often competing factors. Aims To assess and validate the presence of decision factors relevant to the wildfire decision making context that were previously known and to identify those that have emerged since the US federal wildfire policy was updated in 2009. Methods Interviews were conducted across the US while wildfires were actively burning to elucidate time-of-fire decision factors. Data were coded and thematically analysed. Key results Most previously known decision factors as well as numerous emergent factors were identified. Conclusions To contextualise decision factors within the decision making process, we offer a Wildfire Decision Framework that has value for policy makers seeking to improve decision making, managers improving their process and wildfire social science researchers. Implications Managers may gain a better understanding of their decision environment and use our framework as a tool to validate their deliberations. Researchers may use these data to help explain the various pressures and influences modern land and wildfire managers experience. Policy makers and agencies may take institutional steps to align the actions of their staff with desired wildfire outcomes.

Section: Research Backgroundmentioning

confidence: 99%

Factors influencing wildfire management decisions after the 2009 US federal policy update

Fillmore,

McCaffrey,

Bean

et al. 2024

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“…These studies found that successful coordination of response was driven by prefire planning that allowed the establishment of relationships and communication channels (Owen et al 2012;Nowell and Steelman 2015). The use of decision support systems (DSS) to navigate operational decision-making in the Southwest is increasingly documented by social scientists, revealing specific benefits for oversight of natural ignitions to achieve management objectives when using the Wildland Fire Decision Support System (WFDSS) (Fillmore and Paveglio 2023) and capacity for refocusing on long-term land management strategies when using Potential Operational Delineations (PODs) (Greiner et al 2021).…”

Section: Wildfire Responsementioning

confidence: 99%

Social science to advance wildfire adaptation in the southwestern United States: a review and future research directions

Edgeley

2023

Background Social science that seeks to advance wildfire adaptation in the southwestern US states of Arizona and New Mexico remains underdeveloped in comparison with other regions in the USA. Aim To identify key themes in the existing social science literature on wildfire in the Southwest and to determine future research needs that can inform more strategic adaptation across scales and contexts. Methods This article presents an in-depth literature review, organising findings using the Fire Adapted Communities Framework. Key results Research on social aspects of wildfire in the southwestern USA has continued to diversify and broaden in scope over time, but some foundational lines of inquiry (such as public support for prescribed fire) have become outdated while other areas of study (such as fire prevention) have not been explored at all. Conclusions Opportunities to advance wildfire social science efforts in the Southwest are abundant and well positioned to inform social understandings in other regions and countries. Implications Researchers wishing to conduct social science research related to wildfire in the Southwest should seek to update and diversify knowledge in this field both through strategic selection of study sites and populations and via intentional, rigorous research design that acknowledges and elevates the nuances of social interactions with wildfire.

Visibility-informed mapping of potential firefighter lookout locations using maximum entropy modelling

Mistick,

Campbell,

Dennison

2024

Background Situational awareness is an essential component of wildland firefighter safety. In the US, crew lookouts provide situational awareness by proxy from ground-level locations with visibility of both fire and crew members. Aims To use machine learning to predict potential lookout locations based on incident data, mapped visibility, topography, vegetation, and roads. Methods Lidar-derived topographic and fuel structural variables were used to generate maps of visibility across 30 study areas that possessed lookout location data. Visibility at multiple viewing distances, distance to roads, topographic position index, canopy height, and canopy cover served as predictors in presence-only maximum entropy modelling to predict lookout suitability based on 66 known lookout locations from recent fires. Key results and conclusions The model yielded a receiver-operating characteristic area under the curve of 0.929 with 67% of lookouts correctly identified by the model using a 0.5 probability threshold. Spatially explicit model prediction resulted in a map of the probability a location would be suitable for a lookout; when combined with a map of dominant view direction these tools could provide meaningful support to fire crews. Implications This approach could be applied to produce maps summarising potential lookout suitability and dominant view direction across wildland environments for use in pre-fire planning.