Citation

Thompson MP, Carriger JF. Front. For. Glob. Change 2023; 6: 1-9.

Copyright

(Copyright © 2023, Frontiers Media)

DOI

10.3389/ffgc.2023.1266413

PMID

38482191

PMCID

PMC10936575

Abstract

Assessing the effectiveness and measuring the performance of fuel treatments and other wildfire risk mitigation efforts are challenging endeavors. Perhaps the most complicated is quantifying avoided impacts. In this study, we show how probabilistic counterfactual analysis can help with performance evaluation. We borrow insights from the disaster risk mitigation and climate event attribution literature to illustrate a counterfactual framework and provide examples using ensemble wildfire simulations. Specifically, we reanalyze previously published fire simulation data from fire-prone landscapes in New Mexico, USA, and show applications for post-event analysis as well as pre-event evaluation of fuel treatment scenarios. This approach found that treated landscapes likely would have reduced fire risk compared to the untreated scenarios. To conclude, we offer ideas for future expansions in theory and methods.

Language: en

Keywords

climate; effectiveness; event attribution; fuels management; mitigation; risk; simulation