Optimal Structures For Three Ecological Forests In Jingouling Forest

Spruce-fir mixed forest, birch-aspen secondary forest and larch plantations were studied in this research. Based on14clear-cut sample plots,274sample points of control method plots,40fast-growing forest plots,12birch-aspen secondary forest plots and22big diameter grade analytic trees, applying forest management method and statistics method, the optimal diameter structure, optimal tree height structure, optimal spatial isolation of trees, optimal spatial pattern and optimal competition structure were established for the three forest type. Main conclusions were as follows:(1) Coniferous species:maturity age of Koyama Spruce was112.5; maturity age of Yezo Spruce was135; maturity age of fir was150; maturity age of larch was47; Broad-leaf species:maturity age of white birch was135; maturity age of white birch was46; maturity age of ribbed birch was144; maturity age of aspen was43; maturity age of linden was146.5; maturity age of ash was160; maturity age of maple was186.5;(2) Experimental form factor and geographically weighted regression were proposed in the research. The Experimental form factor volume formula was first deduced from the theoretical stem curve formula with the breast height form quotient. In a comparison of results obtained by the classical approach, EFF values for11species applying the theoretical derivation marginally differed. The EFF was verified to be affected only by species. Item K was certified to be constant term with a coefficient of variance of0.02. Meanwhile, absolute deviation, relative deviation, absolute mean deviation, mean relative deviation, determination coefficient, AIC and Predictive accuracy are separately0.46,1.34,1%,3%,0.97,24.1and0.98. The standard volume model for sample trees in the north of Changbai Mountains was established by applying geographical weighted regression method. The relationships between diameter at breast height, tree height and individual volume were analyzed from the perspective of spatial analysis. Results show that the geographical weighted regression model (R2=0.94; p=0.92) is superior to the ordinary least square model (R2=0.93; p=0.91) in goodness of fit and prediction ability. The geographical weighted regression model parameters could reflect the spatial distribution rule of trees in the sample plot and their stability, which further reveal the competitive relationship between trees. With the spatial analysis of data, the geographical weighted regression method has the potential to reveal the local patterns in the spatial distribution of a parameter, which would be ignored by the ordinary least square approach. Finally, the whole stand volume estimation model was obtained.(3) After the relationship between basal areas at breast height per hectare and stand volume per hectare was analyzed by using different kinds of models, the mixed basal area at breast height per hectare was obtained. Simultaneously, the basal areas at breast height per hectare of the forest were divided for five intervals, such as<10m2/ha,10-20m2/ha,20-30m2/ha,30-40m2/ha and40-50m2/ha. The stand volume growths were separately investigated by the intervals. Applying negative exponential distribution and weibull distribution, the optimal stand structures of three forest types were obtained separately. The largest basal area at breast height of Spruce-fir mixed forest was60m2/hm2. When the basal area at breast height of Spruce-fir mixed forest was40m2/hm2and Q value was1.4, the stand volume growth was the biggest (10.5m3/hm2). The largest basal area at breast height of birch-aspen secondary forest was45m2/hm2. When the basal area at breast height of Spruce-fir mixed forest was20m2/hm2and Q value was1.5, the stand volume growth was the biggest (5.7m3/hm2). The largest basal area at breast height of larch plantations was45m2/hm2. When the basal area at breast height of Spruce-fir mixed forest was30m2/hm2and Q value was1.45, the stand volume growth was the biggest (8.99m3/hm2).(4) Due the optimal structure of larch plantations was determined by largest basal area at breast height, spruce-fir mixed forest and birch-aspen secondary forest were only considered in the part of Spatial isolation of trees and Spatial pattern. Applying hierarchical cluster method, the plots were divided by the same diversity of trees and species evenness. Then the relationship between stand volume increment and spatial isolation of trees was analyzed by tree species diversity mingling method. With the same of sit quality, diversity of trees, diversity of tree and mixed proportion, results manifested that stand volume increment in plots increased with the incenseinent of spatial isolation of trees in spruce-fir mixed forest. Nevertheless, stand volume increment in plots declined with the incensement of spatial isolation of trees in birch-aspen secondary forest. The optimal spatial pattern of big diameter grade trees is uniform distribution. Meanwhile, the optimal spatial pattern of small diameter grade trees is clumped distribution. The optimal competition structure is that competition abilities are declined from the center to outside. The outlook is like cone-shape.(5) Based on the characters of mixed forest structure, the fitted competition indices were established, which were called Shadow tolerance competition indices. The equations were as follow:.the calculation system of natural forest competition indices was established.