4.2 Article

A Landscape-Scale Optimisation Model to Break the Hazardous Fuel Continuum While Maintaining Habitat Quality

期刊

ENVIRONMENTAL MODELING & ASSESSMENT
卷 24, 期 4, 页码 369-379

出版社

SPRINGER
DOI: 10.1007/s10666-018-9642-2

关键词

Wildfires; Spatial optimisation; Fuel continuum; Habitat quality; Multiperiod landscape planning; Mixed integer programming

资金

  1. Marie Sklodowska-Curie RISE H2020 project GEO-SAFE [691161]
  2. Government of Spain [MTM2015-65803-R]
  3. Goverment of Madrid [S2013/ICE-2845 CASI-CAM-CM]
  4. UCM grant [CT27/16-CT28/16]

向作者/读者索取更多资源

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, multiperiod 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 multiperiod 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 prioritise treatments in any fire-prone landscape where preserving habitat connectivity is a critical constraint.

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