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Dynamic growth models for continuous cover multi-species forestry in Iranian Caspian forests

Author

Listed:
  • Soleiman MOHAMMADI LIMAEI

    (Department of Forestry, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran)

  • Peter LOHMANDER

    (Optimal Solutions, Umeå, Sweden)

  • Leif OLSSON

    (Department of Information Systems and Technology, Faculty of Science, Technology and Media, Mid Sweden University, Sundsvall, Sweden)

Abstract

This study concerns some of the relevant topics of the Iranian Caspian forestry planning problem, in particular the first central components in this modelling process, such as forest modelling, forest statistics and growth function estimations. The required data was collected from Iranian Caspian forests. To do so, 201 sample plots were determined and the parameters such as number of trees, tree diameter at breast height and tree height were measured at each sample plot. Three sample plots at different 3 elevations were chosen to measure the tree increment. Data has been used to estimate a modified logistic growth model and a model that describes the growth of the basal area of individual trees as a function of basal area. General function analysis has been applied in combination with regression analysis. The results are interpreted from ecological perspectives. Furthermore, a dynamic multi-species growth model theory is developed and analysed with respect to dynamic behaviour, equilibria, convergence and stability. Logistic growth models have been found applicable for continuous cover forest management optimization. Optimization of management decisions in a changing and not perfectly predictable world should always be based on adaptive optimization.

Suggested Citation

  • Soleiman MOHAMMADI LIMAEI & Peter LOHMANDER & Leif OLSSON, 2017. "Dynamic growth models for continuous cover multi-species forestry in Iranian Caspian forests," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 63(11), pages 519-529.
    • Handle: RePEc:caa:jnljfs:v:63:y:2017:i:11:id:32-2017-jfs
    DOI: 10.17221/32/2017-JFS
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    References listed on IDEAS

    as
    1. Peter Lohmander, 2000. "Optimal sequential forestry decisions under risk," Annals of Operations Research, Springer, vol. 95(1), pages 217-228, January.
    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. Limaei, Soleiman Mohammadi, 2010. "Mixed strategy game theory, application in forest industry," Forest Policy and Economics, Elsevier, vol. 12(7), pages 527-531, September.
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