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Assessing the externalities of timber production

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  • Pukkala, Timo

Abstract

Responsible forest policy promotes management that does not impair the multiple uses of forests or decrease their regulative effects and biological diversity. The most important regulative effect of boreal forests is their ability to remove carbon dioxide from the atmosphere. High biological diversity improves the resilience of forest ecosystems and forest-based economies, enhancing the long-term sustainability of forest production. This study developed a method for assessing the performance of forest management in terms of its effects on multiple uses, biodiversity, and carbon sequestration. These externalities were described with 11 indicator variables, which can be calculated for any Finnish forest stand from the current forest inventory data with currently available models and algorithms. The indicator variables were normalized based on the ranges of the indicator variables in Finnish forests on different sites. The forest-level averages of the normalized indicator variables were used to calculate a multiplicative externality score for the forest. The developed method for calculating the forest-wide externality score was used in two forest holdings for alternative silvicultural systems. The case study results suggested that continuous cover management enhances the positive externalities of timber production, as compared to even-aged rotation forestry. Green-tree retention improved the externality score in both silvicultural systems. Maximizing the net present value of timber production in rotation forestry decreased the externality score by about 50% compared to a non-managed forest. The decrease was about 30% smaller in continuous cover forestry.

Suggested Citation

  • Pukkala, Timo, 2022. "Assessing the externalities of timber production," Forest Policy and Economics, Elsevier, vol. 135(C).
    • Handle: RePEc:eee:forpol:v:135:y:2022:i:c:s1389934121002525
    DOI: 10.1016/j.forpol.2021.102646
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    References listed on IDEAS

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    1. Roger Koenker, 2017. "Quantile Regression: 40 Years On," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 155-176, September.
    2. Lahdelma, Risto & Hokkanen, Joonas & Salminen, Pekka, 1998. "SMAA - Stochastic multiobjective acceptability analysis," European Journal of Operational Research, Elsevier, vol. 106(1), pages 137-143, April.
    3. Roger Koenker, 2017. "Quantile regression 40 years on," CeMMAP working papers CWP36/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Juutinen, Artti & Kurttila, Mikko & Pohjanmies, Tähti & Tolvanen, Anne & Kuhlmey, Katharina & Skudnik, Mitja & Triplat, Matevž & Westin, Kerstin & Mäkipää, Raisa, 2021. "Forest owners' preferences for contract-based management to enhance environmental values versus timber production," Forest Policy and Economics, Elsevier, vol. 132(C).
    5. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    6. Douglas, Paul H, 1976. "The Cobb-Douglas Production Function Once Again: Its History, Its Testing, and Some New Empirical Values," Journal of Political Economy, University of Chicago Press, vol. 84(5), pages 903-915, October.
    7. Tamiz, Mehrdad & Jones, Dylan & Romero, Carlos, 1998. "Goal programming for decision making: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 111(3), pages 569-581, December.
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    Cited by:

    1. Pascual, Adrián & Guerra-Hernández, Juan, 2022. "Spatial connectivity in tree-level decision-support models using mathematical optimization and individual tree mapping," Forest Policy and Economics, Elsevier, vol. 139(C).

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