TY - JOUR
T1 - Navigating the evolving landscape of wildfire management
T2 - A systematic review of decision support tools
AU - O'Mara, Tristan
AU - Meador, Andrew Sánchez
AU - Colavito, Melanie
AU - Waltz, Amy
AU - Barton, Elvy
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/6
Y1 - 2024/6
N2 - Wildfires have become more frequent and intense in recent years, threatening terrestrial and aquatic ecosystems and neighboring urban communities. As a result, those responsible for managing wildland fires face increasing pressure to address this challenge strategically. Over the past 20 years, these managers have turned to decision support tools (DSTs) to help guide their actions. We conducted a systematic literature review to explore the landscape of decision support tools (DSTs) for wildfire management, focusing on their functionalities. We additionally examined potential gaps in their design and implementation. The systematic review led us to group decision support tools into categories for all DSTs, such as, Fire Behavior Models or Post Fire Models. These categories are not discrete and can be nested to address land management and fire response questions. Moreover, our findings highlighted a significant gap in tools that effectively integrate ease of use with collaborative capabilities, underscoring the urgency for developing more user-friendly and collaborative decision-making tools. Our research also revealed a disconnect between the academic literature's focus and the tools' actual field usage, emphasizing the need for more accurate documentation and a streamlined approach to wildfire management tool selection. We proposed further social science research to understand the real-world use and preferences of DSTs, aiming to bridge the gap between theoretical robustness and practical utility. This comprehensive analysis of DSTs addresses current wildfire management challenges and sets the stage for future advancements in developing more effective and user-oriented decision support systems.
AB - Wildfires have become more frequent and intense in recent years, threatening terrestrial and aquatic ecosystems and neighboring urban communities. As a result, those responsible for managing wildland fires face increasing pressure to address this challenge strategically. Over the past 20 years, these managers have turned to decision support tools (DSTs) to help guide their actions. We conducted a systematic literature review to explore the landscape of decision support tools (DSTs) for wildfire management, focusing on their functionalities. We additionally examined potential gaps in their design and implementation. The systematic review led us to group decision support tools into categories for all DSTs, such as, Fire Behavior Models or Post Fire Models. These categories are not discrete and can be nested to address land management and fire response questions. Moreover, our findings highlighted a significant gap in tools that effectively integrate ease of use with collaborative capabilities, underscoring the urgency for developing more user-friendly and collaborative decision-making tools. Our research also revealed a disconnect between the academic literature's focus and the tools' actual field usage, emphasizing the need for more accurate documentation and a streamlined approach to wildfire management tool selection. We proposed further social science research to understand the real-world use and preferences of DSTs, aiming to bridge the gap between theoretical robustness and practical utility. This comprehensive analysis of DSTs addresses current wildfire management challenges and sets the stage for future advancements in developing more effective and user-oriented decision support systems.
KW - Decision support
KW - Fire behavior
KW - Forest management
KW - Management frameworks
KW - Treatment prioritization
KW - Usability metrics
KW - Wildfire risk
UR - http://www.scopus.com/inward/record.url?scp=85193265049&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85193265049&partnerID=8YFLogxK
U2 - 10.1016/j.tfp.2024.100575
DO - 10.1016/j.tfp.2024.100575
M3 - Review article
AN - SCOPUS:85193265049
SN - 2666-7193
VL - 16
JO - Trees, Forests and People
JF - Trees, Forests and People
M1 - 100575
ER -