Modeling fuel treatment impacts on fire suppression cost savings: A review
Author(s) -
Matthew P. Thompson,
Nathaniel Anderson
Publication year - 2015
Publication title -
california agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.472
H-Index - 25
eISSN - 2160-8091
pISSN - 0008-0845
DOI - 10.3733/ca.v069n03p164
Subject(s) - revenue , environmental science , natural resource economics , business , cost–benefit analysis , offset (computer science) , wildfire suppression , investment (military) , scale (ratio) , environmental economics , fire protection , environmental resource management , economics , computer science , finance , engineering , ecology , civil engineering , physics , quantum mechanics , politics , law , political science , biology , programming language
High up-front costs and uncertain return on investment make it difficult for land managers to economically justify large-scale fuel treatments, which remove trees and other vegetation to improve conditions for fire control, reduce the likelihood of ignition, or reduce potential damage from wildland fire if it occurs. In the short-term, revenue from harvested forest products can offset treatment costs and broaden opportunities for treatment implementation. Increasingly, financial analysis of fuel treatments is also incorporating long-term savings through reduced fire suppression costs, which can be difficult to quantify. This paper reviews the findings and lessons from recent modeling work evaluating the potential relationship between fuel treatments and avoided fire suppression costs. Across studies, treatments are generally predicted to reduce future fire suppression costs, although the magnitude of savings is unlikely to fully offset fuel treatment costs. This funding gap highlights the importance of forest product revenues in facilitating landscape-scale treatment. Factors influencing the effects of fuel treatment investments on fire suppression costs include the causal pathway linking treatment inputs to suppression cost outcomes; the spatiotemporal uncertainty of wildfire-treatment interactions; and the scale of fuel treatment programs.
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