Forest Experimental Design And Optimization Management Based On Stand State Characteristics

The key to achievesustainable forest management is to have healthy, stable, and high quality forests. This study carried out optimization experimental design and management based on the forest stand characters. R was used to achieve program algorithm in the field design, the evaluation method of forest stand management urgency and the structure-based forest management. The main contents and conclusions of this study are as follows:(1) A new field design method: completely randomized experimental design method based on the state of the stand.The completely randomized experimental design method based on stand condition characters was proposed for the first time together with corresponding objective functions in this study. The design has been applied to a natural forest of Quercus aliena var. acuteserrata in XiaolongMountain in Gansu Province and Platycladus orientalisplantation in western Beijing. Some traditional methods, sequential design, Latin square design and randomized block design, were compared with our new method. The results showed that the assignment of plots to treatmentsbased on the new design produces less than 5% differences among treatments in the six stand attributes that were used. This approach generated better consistency when compared to three traditional designs.(2) This research presents astructure-based spatial optimization management model.The structure-based spatial optimization management model was based on healthy and stable forest characters. In order to ensure the stability of forests, the amount of healthy trees, density(crowding), distribution canopy density and harvesting were considered in the constraint condition. On the other hand, dominance was replaced by species dominance. Objective function was built based on some structure parameters such as Uniform Angle Index, Neighborhood Comparison, crowding index andMingling. It would have a best way to manage forest when gets a minima value of the model.(3) Priority of cutting was determined and computer operating rules were builtThe target is to cultivate healthy and stable forests, and research on the comprehensive evaluation of unreasonable forest character indexes values was carried out..In order to protect the rare species, stand in the constraints required the number of species as the same as before. The computer optimization depends on the purpose and principles of the stand structure optimization, establishing priority adjustment rules- first adjust to forest managers target high-impact index, which helps to optimize the goal as soon as possible.(4) Harvesting scheme selection exhaustive methodM lines need to be adjusted to get all forest harvesting arrangement programs, and the total full array method is permutations programs whileeach program is an arrangement of a harvesting program; Every time the program selects a logging program itneeds to check whether they meet the constraints, if not, the arrangement would be moved, and then the next group was selected; when logging program was consistent with the constraints, calculating Q(g) value according to the objective function; after calculating all cutting programswhich were consistent with the constraints, relatively Q(g) which hasa set of minimum program of felling plan is to be selected as the optimal structure of model forest management plan.(5) Analysis of structure-based spatial optimization management modelManagement results showed both of the field management had achieved the management goals of spatial structure optimization,which means the Climax Species Dominance improved, their pressure of competition reduced, composition of species adjusted to a certain extent, continuous canopy maintained, species diversity and structure stability of stand protected, and a certain number of wood obtainedWe found that the amount of healthy trees has reached the requirement.The other field also reached to 92.1% and crowding reduced slightly. It also has a reasonable density, and the species dominance as increased from 0.469 to 0.541, better than 0.532 from real management in the field. Competitive pressure of climax species has been cut down.