The Bivariate Distribution Of Forest Stand Spatial Structural Parameters

Spatial structure is important in describing forest stand structure and change. Quantifyingrelationships among different forst structures simplifies the process of measuring,understanding, and managing forest structure. At the stand scale, there are a great number ofstructural elements that often maintain close links to each other can be quantified. Manystructural indicators described forest stand are more or less related to the adjacent wood, someof them describe the spatial attributes of forest stand, while the others depict the non-spatialcharacteristics. Commonly, there is no necessary connection among such indexes that aretypically built on variously theoretical backgrouds and have different expression ways at thesame time. The common feature of these methods is that they can only be portrayed unilateralor whole characteristic of tree structure (i.e, macroscopic structure). That is to say, they cannotsimultaneously provide any information about two or more aspects of stand structures. In orderto solve such difficult problem, this contribution proposed a mircroscopic structure analysismethod based on the spatial structural relationships of the nearest four adjacent woods—theanalysis of bivariate distribution of structural parameters. It contained three different forms ofstructural combination, i.e., bivariate distribution of mingling-dominance, bivariate distributionof mingling-uniform angle index and bivariate distribution of dominane-uniform angle index.In order to examine its ability in analyzing different levels of tree structure and itspossible application in forest manangement, six permanent fixed standard plots with length100m×100m were established in Northeast China PR where are commonly covered by thezonal climax vegetation the Korean pine broad-leaved forest. Each plot was only lettered by aArbica character. Three of them (a, b, c) have been treated as the demonstration ofStructure-based forest management (a advanced kind of near to natural forest management)after the plots being built, while the residual (d, e, f) was treated as control. During the sameperiod, two fixed standard samples (h, i) whose areas are70×70m2were also set up in the natural oak-pine mixed forest on northern face of Qinling Mountains, Northwest China PR. Asthe way of plots (a-f) treated in the Korean pine broad-leaved forest, one of them (h) was alsotreated as the demonstration of Structure-based forest management in Qingling area, the otherone (i) was treated as still (CK). With the purpose to exame the ability of the bivariatedistribution of the structural parameters in analyzing forest structure on different levels, i.e.,individual, population and stand (community), the spatial characteristics of the Korean pinebroad-leaved forest stands (a-f) were explored. The spatial attributes of the harvested trees inthe four managed stands which were operated for the first time were also disclosed by thismethod. What is more, the bivariate distribution of the structural parameters was extended tothe priority selection of wood harvesting in natural forests. The main results are as follows:(1) On the stand level, most trees in the natural Korean pine broad-leaved forest werehighly mixed by species and randomly distributed. Trees with different advantages weretypically surrounded by other species; trees within stochastic distribution patterns were usuallysurrounded by different species; and medium-sized trees were randomly distributed.(2) On the population level, three major populations Manchurian ash (Fraxinusmandshurica Rupr.), Manchurian walnut (Juglans mandshurica Maxim.) and Syringa reticulataHong (Syringa amurensis Rupr.) in the mixed forest of Manchurian ash and Manchurianwalnut were usually mixed with other species and distributed randomly. Only a few individualwas in clump or uniform distribution. Trees in clump or regular distribution had a similarnumber of individuals when they belonged to the same species, and they also had a very closemixture or dominance. Normally, Syringa reticulata population were in medium or inferiorstatus, however, most of Manchurian ash and Manchurian walnut had a dominant state whileManchurian walnut population won more obvious advantages thant that of Manchurian ash.(3) Intraspecies, both small (23cm<DBH≥5cm) and big trees (DBH≥23cm) ofManchurian ash were often surrounded by other species. The small ones within random patternwere non-dominant, while the large ones departing from regular dispersion were dominant.Most of the time, Manchurian walnut population‘s small and big trees were randomly encircled by plants that were belong to other species. However, the small Manchurian walnuts weredominant trees while the individuals with bigger DBH were the typically advantage woods. AsSyringa reticulata‘s small trees (8cm<DBH≥5cm) to do, its large trees were often surroundedby other species. The small trees, with random pattern, were in the status of disadvantage. Thebigger ones (DBH≥8cm) tended to be regular on the whole and only a small part of them weredominant plants.(4) The harvested woods were widely distributed on different vertical levels of the Koreanpine broad-leaved forest, including trees in the state of compression, medium and dominance.Most of them belonged to the small diameter category and were highly mixed and randomlydistributed, simultaneously. On the contrary, trees harvested in the oak-pine mixed forestdisplayed a relatively single characteristic. They had a attribute of even distribution among theall diameter classes. Most of them were dominant, and were in the status of high mixture orrandom distribution pattern. After managed, both of natural forests were closer to originalforest in spatial structural features.(5) Even depicting the same plot, different thinning priority indexes may exhibit acompletely different tendency of frequency distribution on the5×5=25combinations. M-Uthinning priority index suggested that trees preferred to be cut in plot a were the ones haddifferent degrees of mixture and in the state of disadvantage or completely disadvantage; Inplot b, the woods cut firstly were highly mixed and suppressed by their nearest neighbors orwere completely dominanct; Trees with different advantages and high mixtures werepreferentially cut in plot c; Nevertheless, plants in plot h had high value of thinning prioritywere the ones in the status of dominance. Some of them had a medium mixture, and otherswere highly mixed by other plant species. M-W thinning priority index indicated that fouroperated samples had a similar frequency distribution on different conbinations. That is to say,most trees preferred to be cut were highly mixed and randomly distributed at the same time. Inplot a, U-W thinning priority index revealed that most trees cut were dominant and were inrandom distribution pattern; In plot c, those different dominant trees that were randomly surrounded by their nearest four neighbors were liked to be cut firstly; But in plot b and h,dominant woods that were random surrounded by their nearest four neighbors in the structuregroup of five were become the selective hotspot of harvesting.The bivariate distribution of the structural parameters takes full advantage of thefrequency distribution of species mingling, uniform angel index and dominance when they areused to express the spatial characters of forest stand. They simultaneously quantify two aspectsof stand structures from different points of view. As a result, it further refines the spatialstructure of the stand, and provide more direct and useful information about the heterogeneityof spatial structure than can univariate distributions or other conventional stand descriptors.This could be helpful for selective thinning in continuous cover forest management and inmodelling and restoring forests. It may also be conducive to the excavation and protection ofbiodiversity.