J. For. Sci., 2017, 63(11):519-529 | DOI: 10.17221/32/2017-JFS

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

Soleiman MOHAMMADI LIMAEI*,1, Peter LOHMANDER2, Leif OLSSON3
1 Department of Forestry, Faculty of Natural Resources, University of Guilan, Sowmeh Sara, Iran
2 Optimal Solutions, Umeå, Sweden
3 Department of Information Systems and Technology, Faculty of Science, Technology and Media, Mid Sweden University, Sundsvall, Sweden

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.

Keywords: forest statistics; forest modelling; growth function; forest management

Published: November 30, 2017  Show citation

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MOHAMMADI LIMAEI S, LOHMANDER P, OLSSON L. Dynamic growth models for continuous cover multi-species forestry in Iranian Caspian forests. J. For. Sci. 2017;63(11):519-529. doi: 10.17221/32/2017-JFS.
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