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A stochastic approach to optimize Maritime pine (Pinus pinaster Ait.) stand management scheduling under fire risk. An application in Portugal

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  • L. Ferreira
  • M. Constantino
  • J. Borges

Abstract

The paper discusses research aiming at the development of a management scheduling model for even-aged stands that may take into consideration fuel treatments to address the risk of wildfires. A Stochastic dynamic programming (SDP) approach is proposed to determine the policy (e.g. the fuel treatment and thinning schedules and the rotation age) that produces the maximum expected discounted net revenue. Fuel treatment activities encompass shrub cleanings. Emphasis was on combining a deterministic stand-level growth and yield model with wildfire occurrence and damage models to design a SDP network. SDP stages are defined by age and state variables include both the stand basal area and the number of years since the last fuel treatment. Fire occurrence and damage scenarios are addressed at each stage. Results from an application to Maritime pine (Pinus pinaster Ait.) stand management scheduling in Leiria National Forest, Portugal, are presented. Results suggest that the modeling strategy may help assess the impact of wildfire risk on the optimal stand management schedule. They confirm that the maximum expected discounted net revenues decreases. Further, albeit some timber may be salvaged after the wildfire, rotation age also decreases when the risk of fire is considered. Finally, they provide interesting insights about the role of thinning and fuel treatment policies in mitigating risk. Copyright Springer Science+Business Media, LLC 2014

Suggested Citation

  • L. Ferreira & M. Constantino & J. Borges, 2014. "A stochastic approach to optimize Maritime pine (Pinus pinaster Ait.) stand management scheduling under fire risk. An application in Portugal," Annals of Operations Research, Springer, vol. 219(1), pages 359-377, August.
    • Handle: RePEc:spr:annopr:v:219:y:2014:i:1:p:359-377:10.1007/s10479-011-0845-z
    DOI: 10.1007/s10479-011-0845-z
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    References listed on IDEAS

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    1. Gregory S. Amacher & Markku Ollikainen & Erkki A. Koskela, 2009. "Economics of Forest Resources," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262012480, April.
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    Cited by:

    1. Miguel A. Lejeune & Janne Kettunen, 2017. "Managing Reliability and Stability Risks in Forest Harvesting," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 620-638, October.
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    3. Miguel A. Lejeune & Janne Kettunen, 2018. "A fractional stochastic integer programming problem for reliability-to-stability ratio in forest harvesting," Computational Management Science, Springer, vol. 15(3), pages 583-597, October.
    4. Matteo Jucker Riva & Hanspeter Liniger & Alejandro Valdecantos & Gudrun Schwilch, 2016. "Impacts of Land Management on the Resilience of Mediterranean Dry Forests to Fire," Sustainability, MDPI, vol. 8(10), pages 1-27, September.
    5. Labbé, Rodrigo & Niklitschek, Mario & Contreras, Marco, 2023. "Effect of climate change on the land rent of radiata pine plantations in Chile: Site productivity and forest fires," Forest Policy and Economics, Elsevier, vol. 156(C).
    6. Bhuiyan, Tanveer Hossain & Moseley, Maxwell C. & Medal, Hugh R. & Rashidi, Eghbal & Grala, Robert K., 2019. "A stochastic programming model with endogenous uncertainty for incentivizing fuel reduction treatment under uncertain landowner behavior," European Journal of Operational Research, Elsevier, vol. 277(2), pages 699-718.
    7. 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.

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