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Article

Insights into Forest Composition Effects on Wildland–Urban Interface Wildfire Suppression Expenditures in British Columbia

Pacific Forestry Centre, Canadian Forest Service, Natural Resources Canada, 506 Burnside Road West, Victoria, BC V8Z 1M5, Canada
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Author to whom correspondence should be addressed.
Forests 2025, 16(11), 1626; https://doi.org/10.3390/f16111626 (registering DOI)
Submission received: 5 August 2025 / Revised: 16 September 2025 / Accepted: 20 October 2025 / Published: 24 October 2025
(This article belongs to the Section Forest Economics, Policy, and Social Science)

Abstract

Burned area, fire severity, and suppression expenditures have increased in British Columbia in recent decades with climate change. Approximately 80% of suppression expenditures are attributable to wildfires near the Wildland–Urban Interface (WUI). Evaluating the potential for fuel management to reduce suppression expenditures is essential to mitigating demands on fire response resources and reducing impacts on communities. One management approach is to increase the proportion of deciduous tree species, which have a lower propensity for crown fire. Using fire suppression expenditure data from 1981 to 2014, we applied the machine learning method causal forests (CFs) to estimate the effect of the proportion of conifer forest cover on suppression expenditures for WUI fires and how these effects varied with other influential factors (i.e., heterogenous treatment effects). Across all fires, the effect of conifer cover on suppression expenditures was stronger on private land compared to public land, under high fire danger measured by daily severity ratings (DSRs), which reflect wind speed and fuel moisture, and for fires igniting earlier in the calendar year, based on Julian day. These findings provide insights into prioritizing wildland fuel treatment when budgets are limited. The CFs approach demonstrates potential for broader applications in fire risk mitigation and analysis beyond the scope of the current data. CFs may also be valuable in other areas of forest research where heterogenous treatment effects are common.
Keywords: wildfire suppression expenditures or costs; forest composition; causal forest; machine learning; BC wildfire; wildfire management; wildland–urban interface; fuel treatment wildfire suppression expenditures or costs; forest composition; causal forest; machine learning; BC wildfire; wildfire management; wildland–urban interface; fuel treatment

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MDPI and ACS Style

Sun, L.; Chan, R.; Endo, K.; Taylor, S.W. Insights into Forest Composition Effects on Wildland–Urban Interface Wildfire Suppression Expenditures in British Columbia. Forests 2025, 16, 1626. https://doi.org/10.3390/f16111626

AMA Style

Sun L, Chan R, Endo K, Taylor SW. Insights into Forest Composition Effects on Wildland–Urban Interface Wildfire Suppression Expenditures in British Columbia. Forests. 2025; 16(11):1626. https://doi.org/10.3390/f16111626

Chicago/Turabian Style

Sun, Lili, Rico Chan, Kota Endo, and Stephen W. Taylor. 2025. "Insights into Forest Composition Effects on Wildland–Urban Interface Wildfire Suppression Expenditures in British Columbia" Forests 16, no. 11: 1626. https://doi.org/10.3390/f16111626

APA Style

Sun, L., Chan, R., Endo, K., & Taylor, S. W. (2025). Insights into Forest Composition Effects on Wildland–Urban Interface Wildfire Suppression Expenditures in British Columbia. Forests, 16(11), 1626. https://doi.org/10.3390/f16111626

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