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Modelling of forest conversion planning with an adaptive simulation-optimization approach and simultaneous consideration of the values of timber, carbon and biodiversity

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  • Yousefpour, Rasoul
  • Hanewinkel, Marc

Abstract

The paper presents a combined simulation-optimization approach to model forest conversion planning taking the values of timber, carbon and biodiversity into account. The development of a virtual age-class forest was predicted by adopting a single tree forest growth tool, "TreeGrOSS". The effects of different conversion regimes with continuous variables describing silvicultural prescriptions were monitored for a finite conversion period of forty years in stand level. Dynamic linear programming was employed to adaptively solve the multi-period large-scale optimization problem of a forest enterprise encompassing five different age-classes of pure Norway spruce (Picea abies, L. Karst) stands. The global net present values of biodiversity, carbon sequestration and timber production along with the wood even flow constraint, were considered simultaneously. The obtained optimal sylvicultural pathway differed not only among different stands but also sometimes within a given stand. The integration of the utility of biodiversity into the optimization procedure favoured conversion strategies that foresee the establishment of beech regeneration in all forest stands. The simultaneous consideration of all mentioned utilities resulted in a global utility of 27451[euro]/ha consisting of 14499 (53%), 3412 (12%), 764 (3%), and 8777 (32%)[euro]/ha for the value of timber, carbon, biodiversity, and standing volume respectively. The sensitivity analysis showed that the threshold from which no major changes in the relevant silvicultural parameters occurred was observed at 30[euro]/t carbon price with an interest rate of 2%.

Suggested Citation

  • Yousefpour, Rasoul & Hanewinkel, Marc, 2009. "Modelling of forest conversion planning with an adaptive simulation-optimization approach and simultaneous consideration of the values of timber, carbon and biodiversity," Ecological Economics, Elsevier, vol. 68(6), pages 1711-1722, April.
    • Handle: RePEc:eee:ecolec:v:68:y:2009:i:6:p:1711-1722
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    References listed on IDEAS

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    1. Teeter, Lawrence & Somers, Greg & Sullivan, Jay, 1993. "Optimal forest harvest decisions: A stochastic dynamic programming approach," Agricultural Systems, Elsevier, vol. 42(1-2), pages 73-84.
    2. Peter Lohmander, 2007. "Adaptive Optimization of Forest Management in A Stochastic World," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 525-543, Springer.
    3. Hayri Önal, 1997. "Trade-off between Structural Diversity and Economic Objectives in Forest Management," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 1001-1012.
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    Cited by:

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    2. Zamora-Pereira, Juan Carlos & Hanewinkel, Marc & Yousefpour, Rasoul, 2023. "Robust management strategies promoting ecological resilience and economic efficiency of a mixed conifer-broadleaf forest in Southwest Germany under the risk of severe drought," Ecological Economics, Elsevier, vol. 209(C).
    3. Louis Anthony (Tony) Cox, 2012. "Confronting Deep Uncertainties in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 32(10), pages 1607-1629, October.
    4. Wu, Tong & Lawell, C.Y. Cynthia Lin & Just, David R. & Zhao, Jiancheng & Fei, Zhangjun & Wei, Qiang, 2022. "Optimal Forest Management for Interdependent Products: A Nested Dynamic Bioeconomic Model and Application to Bamboo," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322164, Agricultural and Applied Economics Association.
    5. Dong, Lingbo & Lu, Wei & Liu, Zhaogang, 2018. "Developing alternative forest spatial management plans when carbon and timber values are considered: A real case from northeastern China," Ecological Modelling, Elsevier, vol. 385(C), pages 45-57.
    6. Lu, Ze-Yu & Li, Wen-Hua & Xie, Bai-Chen & Shang, Li-Feng, 2015. "Study on China’s wind power development path—Based on the target for 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 197-208.
    7. Yousefpour, Rasoul & Didion, Markus & Jacobsen, Jette B. & Meilby, Henrik & Hengeveld, Geerten M. & Schelhaas, Mart-Jan & Thorsen, Bo J., 2015. "Modelling of adaptation to climate change and decision-makers behaviours for the Veluwe forest area in the Netherlands," Forest Policy and Economics, Elsevier, vol. 54(C), pages 1-10.
    8. Zhou, Mo, 2015. "Adapting sustainable forest management to climate policy uncertainty: A conceptual framework," Forest Policy and Economics, Elsevier, vol. 59(C), pages 66-74.
    9. Hilder André Bezerra Farias & Sérgio Luiz de Medeiros Rivero & Márcia Jucá Teixeira Diniz, 2017. "Negative incentives and sustainability in the amazonian logging industry [Negative incentives and sustainability in the amazonian logging industry]," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 27(3), pages 363-391, September.

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