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Details

Autor(en) / Beteiligte
Titel
Forest fire management to avoid unintended consequences: A case study of Portugal using system dynamics
Ist Teil von
  • Journal of environmental management, 2013-11, Vol.130, p.1-9
Ort / Verlag
Kidlington: Elsevier Ltd
Erscheinungsjahr
2013
Quelle
MEDLINE
Beschreibungen/Notizen
  • Forest fires are a serious management challenge in many regions, complicating the appropriate allocation to suppression and prevention efforts. Using a System Dynamics (SD) model, this paper explores how interactions between physical and political systems in forest fire management impact the effectiveness of different allocations. A core issue is that apparently sound management can have unintended consequences. An instinctive management response to periods of worsening fire severity is to increase fire suppression capacity, an approach with immediate appeal as it directly treats the symptom of devastating fires and appeases the public. However, the SD analysis indicates that a policy emphasizing suppression can degrade the long-run effectiveness of forest fire management. By crowding out efforts to preventative fuel removal, it exacerbates fuel loads and leads to greater fires, which further balloon suppression budgets. The business management literature refers to this problem as the firefighting trap, wherein focus on fixing problems diverts attention from preventing them, and thus leads to inferior outcomes. The paper illustrates these phenomena through a case study of Portugal, showing that a balanced approach to suppression and prevention efforts can mitigate the self-reinforcing consequences of this trap, and better manage long-term fire damages. These insights can help policymakers and fire managers better appreciate the interconnected systems in which their authorities reside and the dynamics that may undermine seemingly rational management decisions. •We use system dynamics to model a forest fire management system.•We explore how physical-political dynamics affect suppression/prevention policies.•Too much suppression self-reinforces further suppression and crowds out prevention.•A balanced approach minimizes this feedback cycle and long-term damages.•Model is adapted to Portugal but underlying dynamics are generalizable.

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