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Addressing Wildfire Risk in Forest Management Planning with Multiple Criteria Decision Making Methods

Author

Listed:
  • Susete Marques

    (Forest Research Center, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisboa, Portugal)

  • Marco Marto

    (Forest Research Center, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisboa, Portugal)

  • Vladimir Bushenkov

    (Research Centre for Mathematics and Applications, University of Évora, Colégio Luís Verney, Rua Romão Ramalho, 59, 7000-671 Évora, Portugal)

  • Marc McDill

    (Department of Ecosystems Science and Management, Pennsylvania State University, 310 Forest Resources Building University Park, State College, PA 16802-4301, USA)

  • JoséG. Borges

    (Forest Research Center, School of Agriculture, University of Lisbon, Tapada da Ajuda, 1349-017 Lisboa, Portugal)

Abstract

Wildfires impact the outcomes of forest management plans. Addressing that impact is thus critical for effective forest ecosystem management planning. This paper presents research on the use of multiple criteria decision making (MCDM) methods that integrate wildfire risk in planning contexts characterized by multiple objectives. Specifically, an a posteriori preference modeling approach is developed that adds wildfire criteria to a set of objectives representing ecosystem services supply values. Wildfire risk criteria are derived from stand-level wildfire occurrence and damage models as well as from the characteristics of neighboring stands that may impact wildfire probability and spread. A forested landscape classified into 1976 stands is used for testing purposes. The management planning criteria include the carbon stock, harvest volumes for three forest species, the volume of the ending inventory, and resistance to wildfire risk indicators. Results show the potential of multiple criteria decision making methods to provide information about trade-offs between wildfire risk and the supply of provisioning (timber) as well as regulatory (carbon) ecosystem services. This information may contribute to the effectiveness of forest ecosystem management planning.

Suggested Citation

  • Susete Marques & Marco Marto & Vladimir Bushenkov & Marc McDill & JoséG. Borges, 2017. "Addressing Wildfire Risk in Forest Management Planning with Multiple Criteria Decision Making Methods," Sustainability, MDPI, vol. 9(2), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:298-:d:90735
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    References listed on IDEAS

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    1. Nordström, Eva-Maria & Eriksson, Ljusk Ola & Öhman, Karin, 2010. "Integrating multiple criteria decision analysis in participatory forest planning: Experience from a case study in northern Sweden," Forest Policy and Economics, Elsevier, vol. 12(8), pages 562-574, October.
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    3. Rico, Margarita & González, Andrés, 2015. "Social participation into regional forest planning attending to multifunctional objectives," Forest Policy and Economics, Elsevier, vol. 59(C), pages 27-34.
    4. Aretano, Roberta & Semeraro, Teodoro & Petrosillo, Irene & De Marco, Antonella & Pasimeni, Maria Rita & Zurlini, Giovanni, 2015. "Mapping ecological vulnerability to fire for effective conservation management of natural protected areas," Ecological Modelling, Elsevier, vol. 295(C), pages 163-175.
    5. Keane, Robert E. & Drury, Stacy A. & Karau, Eva C. & Hessburg, Paul F. & Reynolds, Keith M., 2010. "A method for mapping fire hazard and risk across multiple scales and its application in fire management," Ecological Modelling, Elsevier, vol. 221(1), pages 2-18.
    6. J. Garcia-Gonzalo & T. Pukkala & J. Borges, 2014. "Integrating fire risk in stand management scheduling. An application to Maritime pine stands in Portugal," Annals of Operations Research, Springer, vol. 219(1), pages 379-395, August.
    7. Masashi Konoshima & Claire A. Montgomery & Heidi J. Albers & Jeffrey L. Arthur, 2008. "Spatial-Endogenous Fire Risk and Efficient Fuel Management and Timber Harvest," Land Economics, University of Wisconsin Press, vol. 84(3), pages 449-468.
    8. Yassemi, S. & Dragićević, S. & Schmidt, M., 2008. "Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour," Ecological Modelling, Elsevier, vol. 210(1), pages 71-84.
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    Cited by:

    1. Edgar Lorenzo-Sáez & Jose-Vicente Oliver-Villanueva & Victoria Lerma-Arce & Celia Yagüe-Hurtado & Lenin Guillermo Lemus-Zúñiga, 2021. "Potential Analysis of Mediterranean Forestry for Offsetting GHG Emissions at Regional Level: Evidence from Valencia, Spain," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    2. Marlene Marques & Keith M. Reynolds & Susete Marques & Marco Marto & Steve Paplanus & José G. Borges, 2021. "A Participatory and Spatial Multicriteria Decision Approach to Prioritize the Allocation of Ecosystem Services to Management Units," Land, MDPI, vol. 10(7), pages 1-22, July.
    3. C. Wade Ross & E. Louise Loudermilk & Steven A. Flanagan & Grant Snitker & J. Kevin Hiers & Joseph J. O’Brien, 2025. "Wildfire Severity Reduction Through Prescribed Burning in the Southeastern United States," Sustainability, MDPI, vol. 17(13), pages 1-16, July.
    4. Labarre, Clémence & Domec, Jean-Christophe & Andrés-Domenech, Pablo & Bödeker, Kai & Bingham, Logan & Loustau, Denis, 2025. "Improving forest decision-making through complex system representation: A viability theory perspective," Forest Policy and Economics, Elsevier, vol. 170(C).
    5. Schwaiger, Fabian & Poschenrieder, Werner & Biber, Peter & Pretzsch, Hans, 2019. "Ecosystem service trade-offs for adaptive forest management," Ecosystem Services, Elsevier, vol. 39(C).
    6. Semyung Kwon & Sanghyun Kim & Jeonghwan Kim & Wonseok Kang & Ki-Hyung Park & Chan-Beom Kim & Miguel M. Girona, 2021. "Predicting Post-Fire Tree Mortality in a Temperate Pine Forest, Korea," Sustainability, MDPI, vol. 13(2), pages 1-16, January.
    7. Brigite Botequim & Miguel N. Bugalho & Ana Raquel Rodrigues & Susete Marques & Marco Marto & José G. Borges, 2021. "Combining Tree Species Composition and Understory Coverage Indicators with Optimization Techniques to Address Concerns with Landscape-Level Biodiversity," Land, MDPI, vol. 10(2), pages 1-26, January.

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