A landscape-scale optimisation model to break the hazardous fuel continuum while maintaining habitat quality

Javier León, Victor Maria Jacobus Johannes Reijnders, John W. Hearne (Corresponding Author), Melih Ozlen, Karin J. Reinke

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

Wildfires have demonstrated their destructive powers in several parts of the world in recent years. In an effort to mitigate the hazard of large catastrophic wildfires a common practice is to reduce fuel loads in the landscape. This can be achieved through prescribed burning or mechanically. Prioritising areas to treat is a challenge for landscape managers. To help deal with this problem we present a spatially explicit, multi-period mixed integer programming model. The model is solved to yield a plan to generate a dynamic landscape mosaic that optimally fragments the hazardous fuel continuum while meeting ecosystem considerations. We demonstrate that such a multi-period plan for fuel management is superior to a myopic strategy. We also show that a range of habitat quality values can be achieved without compromising the optimal fuel
reduction objective. This suggests that fuel management plans should also strive to optimise habitat quality. We illustrate how our model can be used to achieve this even in the special case where a faunal species requires mature habitat that is also hazardous from a wildfire perspective. The challenging computational effort required to solve the model can be overcome with either a rolling horizon approach or lexicographically. Typical Australian heathland landscapes are used
to illustrate the model but the approach can be implemented to priotitize treatments in any fire-prone landscape where preserving habitat conectivity is a critical constraint.
Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalEnvironmental modeling and assessment
DOIs
Publication statusPublished - 7 Nov 2018
Externally publishedYes

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habitat quality
wildfire
prescribed burning
heathland
habitat
hazard
ecosystem
plan

Keywords

  • UT-Hybrid-D
  • spatial optimization
  • fuel continuum
  • habitat quality
  • multiperiod landscape planning
  • Mixed integer programming
  • Wildfires

Cite this

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abstract = "Wildfires have demonstrated their destructive powers in several parts of the world in recent years. In an effort to mitigate the hazard of large catastrophic wildfires a common practice is to reduce fuel loads in the landscape. This can be achieved through prescribed burning or mechanically. Prioritising areas to treat is a challenge for landscape managers. To help deal with this problem we present a spatially explicit, multi-period mixed integer programming model. The model is solved to yield a plan to generate a dynamic landscape mosaic that optimally fragments the hazardous fuel continuum while meeting ecosystem considerations. We demonstrate that such a multi-period plan for fuel management is superior to a myopic strategy. We also show that a range of habitat quality values can be achieved without compromising the optimal fuelreduction objective. This suggests that fuel management plans should also strive to optimise habitat quality. We illustrate how our model can be used to achieve this even in the special case where a faunal species requires mature habitat that is also hazardous from a wildfire perspective. The challenging computational effort required to solve the model can be overcome with either a rolling horizon approach or lexicographically. Typical Australian heathland landscapes are usedto illustrate the model but the approach can be implemented to priotitize treatments in any fire-prone landscape where preserving habitat conectivity is a critical constraint.",
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A landscape-scale optimisation model to break the hazardous fuel continuum while maintaining habitat quality. / León, Javier; Reijnders, Victor Maria Jacobus Johannes; Hearne, John W. (Corresponding Author); Ozlen, Melih; Reinke, Karin J.

In: Environmental modeling and assessment, 07.11.2018, p. 1-11.

Research output: Contribution to journalArticleAcademicpeer-review

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