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 such was collected from Iranian Caspian forests. To do so, 201 sample plots were determined and the parameters such as number of tree, tree diameter at breast height and trees 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 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 analyzed with respect to dynamic behavior, equilibria, convergence and stability. Logistic growth models have been found useful in continuous cover forest management optimization. Optimization of management decisions in a changing and not perfectly predictable world should always be based on adaptive optimization.