Developing sample tree selection criteria for estimation of stand volume increment

In this study, sample tree selection methods for estimating the stand volume increment were evaluated. For this purpose; 54 choosing methods were fictionalized for selection of sample trees within the sample plot. In the study area, a total of 1408 brutian pine (Pinus brutia Ten.) trees were measured in 47 sample plots which were represent the variations of relevant variable. Meyer's Interpolation Method was used to determine the volume increment. In order to model increment and diameter growth factors as a multiplier in the method, 2592 (54x48) regression analysis were performed with 48 models. Within the scope of these factors, equations that explain the relationships between tree height- diameter of breast height (dbh), diameter outside bark, diameter inside bark, periodic growth diameter inside bark, mid period diameter inside bark were produced. In addition, diameter growth models with four variables that describe the periodic growth diameter inside bark as a function of the variables of dbh, age of stand, site index and density were tested. The most successful models were chosen which evaluated the success criteria sets and relative scoring method. The choosing methods were tested on these most successful models and also on all other trees that were not used in regression analysis. Thus, each choosing method was evaluated with its success in explaining the relationships and ranked by total success points. The cost value of the selection methods was evaluated in accordance with the number of trees used in the method. However, choosing methods do not explain each relationship with the same level of success. For this reason, a combinatorial analysis was performed and multi purpose optimization process was conducted by the Pareto optimal method. As a result, the success levels of the choosing methods in explaining the relationships and the estimation of the volume increment were determined. The solution clusters, which can be used by the simple algorithm according to the requirements, have been presented to decision makers.