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Tree Diversity, Landscape Diversity, and Economics of Maple-Birch Forests: Implications of Markovian Models

Author

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  • Ching-Rong Lin

    (Department of Forest Ecology and Management, University of Wisconsin, 1630 Linden Drive, Madison, Wisconsin 53706)

  • Joseph Buongiorno

    (Department of Forest Ecology and Management, University of Wisconsin, 1630 Linden Drive, Madison, Wisconsin 53706)

Abstract

Markov decision process (MDP) models were effective in analyzing forest management policies. Even the simplest standard results gave useful insights into forest ecology, such as how landscape diversity is shaped by natural catastrophes, and how forests mature through successional phases. The methods were also useful to predict the effects of different management policies on ecological and economic criteria. Optimization augmented the usefulness of the approach, suggesting that income from Wisconsin's maple-birch forests could be increased without ruining their diversity of landscape, tree size, and tree species. It showed that maximizing species diversity, defined by the distribution of trees in shade-tolerance classes, would require some harvest. Instead, maximum tree size diversity occurred in unmanaged forests, but this gave a less diverse landscape and no income. The MDP method allowed for the design of compromise policies that would maximize income while keeping diversity above specified limits. The opportunity cost of increasing tree size diversity was found to be much higher than for species diversity. Comparing the maximum timber income owners could have got with what they actually cut suggested that the amenity value of forests was four times that of timber. Advantages of the methods reside in the ability to model complex ecosystem processes with simple probability matrices, and in the rich MDP theory and algorithms. Limitations include the difficulty of defining a space set large enough for accurate discretization, but small enough for practical application.

Suggested Citation

  • Ching-Rong Lin & Joseph Buongiorno, 1998. "Tree Diversity, Landscape Diversity, and Economics of Maple-Birch Forests: Implications of Markovian Models," Management Science, INFORMS, vol. 44(10), pages 1351-1366, October.
  • Handle: RePEc:inm:ormnsc:v:44:y:1998:i:10:p:1351-1366
    DOI: 10.1287/mnsc.44.10.1351
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    References listed on IDEAS

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    1. Douglas J. White, 1985. "Real Applications of Markov Decision Processes," Interfaces, INFORMS, vol. 15(6), pages 73-83, December.
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    Cited by:

    1. Zhou, Mo & Buongiorno, Joseph, 2011. "Effects of stochastic interest rates in decision making under risk: A Markov decision process model for forest management," Forest Policy and Economics, Elsevier, vol. 13(5), pages 402-410, June.
    2. Oduor, Peter G. & Kotchman, L. & Nakamura, A. & Jenkins, S. & Ale, G., 2012. "Spatially constrained forest cover dynamics using Markovian random processes," Forest Policy and Economics, Elsevier, vol. 20(C), pages 36-48.
    3. Schou, Erik & Jacobsen, Jette Bredahl & Kristensen, Kristian Løkke, 2012. "An economic evaluation of strategies for transforming even-aged into near-natural forestry in a conifer-dominated forest in Denmark," Forest Policy and Economics, Elsevier, vol. 20(C), pages 89-98.
    4. Ana Rute Cardoso & Paulo Guimarães & Klaus F. Zimmermann, 2010. "Comparing the early research performance of PhD graduates in labor economics in Europe and the USA," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 621-637, September.
    5. Xabadia, Angels & Goetz, Renan U., 2010. "The optimal selective logging regime and the Faustmann formula," Journal of Forest Economics, Elsevier, vol. 16(1), pages 63-82, January.
    6. Andersson, Mats & Gong, Peichen, 2010. "Risk preferences, risk perceptions and timber harvest decisions -- An empirical study of nonindustrial private forest owners in northern Sweden," Forest Policy and Economics, Elsevier, vol. 12(5), pages 330-339, June.
    7. Bastit, Félix & Brunette, Marielle & Montagné-Huck, Claire, 2023. "Pests, wind and fire: A multi-hazard risk review for natural disturbances in forests," Ecological Economics, Elsevier, vol. 205(C).
    8. Stéphane S. Couture & Marie-Josée Cros & Régis Sabbadin, 2014. "Risk preferences and optimal management of uneven-aged forests in the presence of climate change: a Markov decision process approach," Post-Print hal-02741407, HAL.
    9. Félix Bastit & Marielle Brunette & Claire Montagne-Huck, 2021. "Earth, wind and fire: A multi-hazard risk review for natural disturbances in forests," Working Papers of BETA 2021-25, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    10. Couture, Stéphane & Cros, Marie-Josée & Sabbadin, Régis, 2016. "Risk aversion and optimal management of an uneven-aged forest under risk of windthrow: A Markov decision process approach," Journal of Forest Economics, Elsevier, vol. 25(C), pages 94-114.
    11. Buongiorno, Joseph & Zhou, Mo, 2011. "Further generalization of Faustmann's formula for stochastic interest rates," Journal of Forest Economics, Elsevier, vol. 17(3), pages 248-257, August.
    12. Scarpa, Riccardo & Buongiorno, Joseph & Hseu, Jiin-Shyang & Lee, Karen, 1998. "Determinants Of Non-Timber Value In Northern Hardwoods: A Framework For Forest Resource Accounting," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20799, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. Mats, Andersson & Gong, Peichen, 6. "Risk Preferences, Risk Perceptions and Timber Harvest Decisions – An Empirical Study of NIPF Owners in Northern Sweden," Scandinavian Forest Economics: Proceedings of the Biennial Meeting of the Scandinavian Society of Forest Economics, Scandinavian Society of Forest Economics, issue 42, April.
    14. 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.

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