Research Program Areas
Advancing Wildfire Science through Multidisciplinary Analysis
The ReSHAPE program is supported by five integrated program areas that iteratively refine the TWIG viewer and advance the collective understanding of treatment effectiveness. By bridging the gap between rigorous academic research and on-the-ground management, we provide the evidence-based knowledge necessary to lower the risk of catastrophic wildfire. Our work enables the wildfire management community to assess interactions at scales previously unavailable, delivering actionable insights that support resilient forests.
Biophysical Effects
This program leverages extensive TWIG data and statistical techniques to understand when, why, and how forest treatments reduce fire severity and prevent fire spread.
During Colorado’s intense 2020 wildfire season, areas with prior forest treatments, like thinning, prescribed fire, or previous wildfire, burned less severely than in untreated areas. Even during extreme fire weather, treated areas generally experienced lower burn severity than untreated areas did during milder conditions. This pattern was especially pronounced in lower elevation forests, such as those dominated by ponderosa pine. These findings highlight the importance of strategically placed and ecologically appropriate treatments to shape wildfire outcomes within changing fire regimes.
Fact sheet for "Extreme Colorado 2020 fires: remotely sensed burn severity influenced by treatments, forest types and days of burning"
The influence of forest treatments on wildfire effects is challenging to interpret. Using a case study from the Cameron Peak Fire in Colorado, this paper discusses ecological metrics of forest treatment effects, fire behavior, important considerations and recommendations for evaluating treatments, and provides definitions for critical concepts to bring a common language and understanding to conversations about treatment effects.
Fact sheet for "Metrics and considerations for evaluating how forest treatments alter wildfire behavior and effects"
Economics
Conducted by our partner, the Conservation Economics Institute, this program researches the return on investment (ROI) and economic benefits of forest restoration efforts.
To help establish economic efficiency analysis of fuel treatments, the authors provided a methodological framework illustrating benefit-cost analysis and considerations for dealing with valuation complexity. Further analyses of the benefits and costs of fuels treatments would support a clearer understanding of the economic trade-offs involved. This information could highlight opportunities for long-term savings from proactive investments in wildfire resilience.
Summary sheet for " Economic Efficiency of Fuel Treatments in Western U.S. Forests: A Methodological Framework".
Restoration and fuel treatments have emerged as leading wildfire risk- reduction strategies in the American West, yet little is known about the cost-effectiveness of such programs. To evaluate forest restoration and fuel treatment benefits and costs, the authors conducted a meta-analysis of benefit-cost ratios for restoration benefit types documented in the literature for Western U.S. dry mixed conifer forests at risk of uncharacteristic wildfires.
Fact sheet for "Return on investment in restoration and fuel treatments in frequent-fire forests of the American west: A meta-analysis.
Data Science
This area focuses on clarifying federal systems of record and integrating diverse datasets to reduce uncertainty in wildfire models and identify high-risk areas for targeted fuel treatment.
In August 2025, we published an article in the journal Scientific Data that described the TWIG treatment index in detail. This paper also includes a link to a static version of the TWIG treatment index as it existed in August 2025.
As TWIG continues to evolve, the most up-to-date data and metadata are always available on this website under TWIG Data Resources. Still, the article contains some timeless background and history regarding the development and intended uses of TWIG.
We ask that all users of TWIG data cite this paper in their final publications.
Citation: Call, A., Tomczyk, N., Withnall, K.A., Dappen, P., Heusinkveld, D., Mueller, S.E., Holloway, B., Shennan, K., Herring, J.A., Franko, A., Colavito, M.M., Kimple, A.D., Sánchez Meador, A.J., Stevens-Rumann, C.S. A new geodatabase of fuel treatments across federal lands in the USA. Sci Data 12, 1485 (2025). https://doi.org/10.1038/s41597-025-05859-z
TWIG
Focused on the continual compilation and display of fuel treatment data, this program area manages the development and maintenance of the TWIG geodatabase.
The Treatment and Wildfire Interagency Geodatabase (TWIG) Viewer is a new public mapping tool developed by SWERI through the ReSHAPE program that makes it easier to find, view, and download federal fuel treatment and wildfire data. Early evaluation shows TWIG has strong potential to support planning, coordination, and communication among land managers, collaborators, and policymakers—though gaps in data and functionality remain. Ongoing user feedback is helping guide improvements as SWERI works to expand TWIG’s utility across jurisdictions.
Fact sheet for the full TWIG Evaluation Report, above.
Put Data Into Action
Start exploring our accessible, nationwide geodatabase for fuel treatments and wildfires today.
CONNECT (Social Science)
Our social science team evaluates the use and effectiveness of decision support tools to improve how geospatial data is applied in collaborative wildfire management.
Courtney et al. 2025. Mapping Community Capacity to Reduce Vulnerability to Wildfire in Colorado, USA
Researchers developed an index using publicly available data weighted by expert perceptions to map local capacity for wildfire management across Colorado, revealing significant geographic disparities between capacity and wildfire risk. The replicable methodology addresses a critical gap in wildfire planning, as substantial resources exist for modeling wildfire risk but complementary assessments of local capacity to respond have been largely absent.
Storymap: Mapping Community Capacity in Colorado
Storymap based on the research from the Courtney et al. 2025 paper "Mapping Community Capacity to Reduce Vulnerability to Wildfire in Colorado, USA"
OMara et al.2024., Systematic Review of Decision Support Tools
The authors of this paper conducted a systematic literature review to explore the landscape of decision support tools (DSTs) for wildfire management, focusing on their functionalities.
O'Mara et al. Fact Sheet
Fact sheet for "Navigating the Evolving Landscape of Wildfire Management: A Systematic Review of Decision Support Tools"