Changing wildfire complexity highlights the need for institutional adaptation
Data files
Jun 03, 2025 version files 257.45 MB
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incids_mtbs_final.gpkg
257.43 MB
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raw_pl_data_2020.csv
20.20 KB
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README.md
3.14 KB
Abstract
As wildfires grow increasingly complex, institutional adaptation- adjusting institutions to respond effectively to environmental changes- is crucial for enhancing wildfire management capabilities. However, institutional adaptation is a challenge as the connection between environmental changes and human institutions remains poorly understood. Here, by analyzing trends in five incident characteristics linked to institutional complexity at national and regional levels from 1999 to 2020 in the USA, we show national trends of increasing institutional complexity of wildfire indicators associated with wildfire governance, logistics, management, resource scarcity, and network coordination. Substantial regional variation was observed, with some cases exhibiting trends in opposite directions. For example, while jurisdictional complexity increased in the West, it decreased in the East. These results offer insight into the linkage between environmental change and demands for institutional adaptation, and provide an empirical basis for considering potential tradeoffs of different institutional adaptations in light of competing pressures.
https://doi.org/10.5061/dryad.9cnp5hqsk
Nowell, B., Jones, K., McGovern, S.M. 2025. Changing wildfire complexity highlights the need for institutional adaptation. Nature Climate Change.
Description of the data and file structure
Information about each input dataset available on Dryad and the attribute descriptions.
1) incids_mtbs_final.gpkg : MTBS geospatial wildfire boundaries and engaged jurisdictions
fid: unique record identifier
incident_id: unique fire identifier
fed_engag_cnt: count of federal jurisdictions within the wildfire boundary or 5-mile radius
trib_engag_cnt: count of tribal jurisdictions within the wildfire boundary or 5-mile radius
st_engag_cnt: count of states within the wildfire boundary or 5-mile radius
cnty_engag_cnt: count of counties within the wildfire boundary or 5-mile radius
cenpl_engag_cnt: count of census places within the wildfire boundary or 5-mile radius
START_YEAR: year wildfire ignition occurred
- Dataset is the final output from the Jurisdictional Complexity github repository. Review repository .README for additional data source and availability information.
- Citation for published manuscript:
Jones, K., Vukomanovic, J.V., Nowell, B., McGovern, S.M. 2024. Mapping Wildfire Jurisdictional Complexity Reveals Opportunities for Regional Co-Management. Global Environmental Change 84, 102084. https://doi.org/10.1016/j.gloenvcha.2024.102804
2) raw_pl_data_2020.csv : daily preparedness level (1-5)
month: month of the year
day_of_Month: day of the month
1999: preparedness level rating (1-5) for day/month/year
2000: preparedness level rating (1-5) for day/month/year
2001: preparedness level rating (1-5) for day/month/year
2002: preparedness level rating (1-5) for day/month/year
2003: preparedness level rating (1-5) for day/month/year
2004: preparedness level rating (1-5) for day/month/year
2005: preparedness level rating (1-5) for day/month/year
2006: preparedness level rating (1-5) for day/month/year
2007: preparedness level rating (1-5) for day/month/year
2008: preparedness level rating (1-5) for day/month/year
2009: preparedness level rating (1-5) for day/month/year
2010: preparedness level rating (1-5) for day/month/year
2011: preparedness level rating (1-5) for day/month/year
2012: preparedness level rating (1-5) for day/month/year
2013: preparedness level rating (1-5) for day/month/year
2014: preparedness level rating (1-5) for day/month/year
2015: preparedness level rating (1-5) for day/month/year
2016: preparedness level rating (1-5) for day/month/year
2017: preparedness level rating (1-5) for day/month/year
2018: preparedness level rating (1-5) for day/month/year
2019: preparedness level rating (1-5) for day/month/year
2020: preparedness level rating (1-5) for day/month/year
Data received March 2023 through personal communications with the National Interagency Fire Center.