| The distribution of picea, stand structure, standing forest productivity and carbon sequestration functions, evaluation of site quality, population growth and adjustment as well were investigated in the high mountain forest region in the northwest of Sichuan province and river area forest regions of Bai Longjiang and Yaojiang in Gansu Province since the 90's with the objective of filling gaps in this field in this paper. At same time, stand structure were investigated based on probability distribution and mathematical statistic methods to seek after the relations between stand diameter, tree height and the number of living tree; the relations between stand productivity, stand structure and habitats were revealed by ecological methods; in addition, we found the judgment system about evaluation of site quality by quantification methods, multi-statistical method and system analysis. The related mathematic models were founded by the analysis of relation between picea population growth and habitats factors based on gaining the Logistic models of various habitats after fitted Logistic models of picea population growth; and the model can reveal the variation of picea population crowding effect and density dependence. It describes four achievements after the systematic studying the relationship of individual growth and habitats factors in this paper1. The relations among habitats factors were found after studying the degree of correlation of habitats factors by correlation analysis (including simple correlation analysis and canonical correlation analysis) in the part of evaluation of picea site quality. Whereafter, we sought after the dominant factors, which limit greatly the productivity, to evaluate site condition and form type classifications by the multi-statistical method. Finally, some tables including site index list of picea were drew up to describe and evaluate picea site quality quantificationally.The results showed that: the habitats factors with higher degree of correlation were terrain factors (including landform and exposure) and soil factors (including humus depth and soil moisture), and landform factors and vegetation types have high degree of correlation. the dominant factors that influence greatly the productivity were landform type, exposure, humus depth, vegetation type, soil moisture, cumulus-form of soil parents material and mean soil bulk density. Besides, multiple regression, stepwise regression, quantification method and principal component analysis etc., the statistical methods applied to search for the dominant factors, were evaluated.The classification system of picea habitats quality evaluation, according to the principle of classification factors with huge capacity and simple-measuring, was established based on the dominant factors from the studying results. And the classification system was divided into five levels: producing area, habitation region (landform type), habitats group (vegetation type), and habitat form (exposure and soil parent form), and site type (soil moisture and soil depth in A layer). At same time, this paper gives the describing and argumentation to the divisory types and the characteristics of productivity. The classification results were similar to the results of quantity test by system cluster and principal component sequencing.Further, picea (natural forest) site (habitation) index list, multi-factors quantificational habitats quality judge table, habitats quality levels judge table and picea habitats type response table were drew to make the evaluation of site quality strong visual and efficient then easy for applying in the production practice. And we test those tables and lists, explain how to use them to expend the evaluation system in the production practice.In order to cognize the site index of forest ecosystem and its space-temporal variation, the characteristics of space distribution about Picea forest ecosystem was studied by satellite remote sensing, seeking after the related inverse model foundation on remote sensing, then analyzing the value and potentiality of this high-science & technology in application by related accuracy judgement. The results show that remote sensing vegetation indexes NDVI and TNDVI and site index from field measuring have linear relation on the whole. The inverse model of NDVI and TNDVI show high-fitting and larger accuracy, so it accounts for the high value of remote sensing in application of determining forest site index.2. The distribution of Diameter-number (D-N) and tree height-number (H-N) were fitted by five distribution functions using the data of 328- plot in the study on picea stand structure, that is ,we fitted 1600 distribution functions and made X2 tests which proved D-N and H-N were fitted best by weibull distribution with the acceptance rate of 64%in X2 tests among five distribution functions--normal distribution, lognormaldistribution, gamma distribution, beta distribution and weibull distribution--becauseweibull distribution has many advantages such as strong-flexibility, easy-solution and so on.Multi-statistical analysis to three parameters of weibull distribution densityfunction--location parameter (a), scale parameter (b) and figure parameter (c)--revealed the relations between parameters (a, b, c) and stand age, density, height of dominant tree and other factors. The analysis showed location parameter and figure parameter were intimately related to the stand density, and scale parameter was closely connected with the height of dominant tree. The rule of those statistical characteristicparameters decided by stand factors--stepwise regression function and multi-linearregression function--can be uses to predict the stand yield, through forecasting thecharacteristic parameters of weibull distribution function, which indicated the detail distributions of medium diameter class and the number of plants in each height grades, based on stand age, density and height of dominant tree. So the rule may serve for building the table on stand yield number and managing design scheme.The distribution rules of D-N and H-N about mickle generation picea forest and natural spruce-fir mixed forest were studied. The data showed that: The distribution of D-N and H-N of mickle generation picea forest present some discrete discontinuities, and they were fitted badly by the five distribution functions, however the fitted results would be improved after separating generation by weibull function. There were not so good fitted results to the distribution of D-N and H-N of spruce-fir mixed forest indicated too, while it can be improved evidently esp. to birch in the middle and lower layer by separating tree species using weibull function. We explain the phenomenon from succession of community, stand growth and generation alternation.The correlation between characteristic parameter of D-N and H-N and stand productivity were analyzed, and the results show that figure and scale parameter would affect on the yield, so the characteristic parameters of distribution functions can predict the stand productivity.From the studying, this paper reveal the rules of distribution of D-N and H-N in the natural picea stand structure, and it also gives some new point of view in the choosing of distribution model, multi-statistical analysis of distribution characteristic parameters and stand factors, the analysis of relations between distribution characteristic and stand generation alternation and succession of community, and the correlation between distribution figure and stand productivity; and those views can promote the study of stand structure.3. The biomass and productivity of picea natural forest were studied in detail in the study of stand productivity. We selected 202 investigational plots, cut down 605 trees, and digged 54 tree-roots to survey biomass. The biomass under young tree was investigated in 960 plots, and the biomass of greensward and ground cover in thousands of plots. The biomass and productivity and distribution of picea natural forest will be gained from huge amounts of material. The results showed: the mean biomass in arbor layer is 212.77×103kg·hm-2; biomass of young tree and undergrowth is 11.395×103kg·hm-2, the biomass of greensward and ground cover are 2.71×103kg·hm-2 and 1.38×103kg·hm-2 respectively. The mean biomass of forest (including forest floor) is 230.37×103kg·hm-2.Stand net primary productivity were gained by calculating according to formula, the data showed: net primary productivity in arbor layer is 4676kg·hm-2·a-1 converting 1.35% utilization ratio of light energy; that of stand is 6838.5kg·hm-2·a-1 converting 1.63% utilization ratio of light energy; and the whole productivity of forest is about 18.85Kcal·m2·d-1We combined qualitative and quantificational methods and bound single-factor analysis with multi-factor analysis in order to reveal fully the relation between stand productivity of picea natural forest and habitats. The correlation among picea standproductivity and habitats factors--natural distribution, forest type, altitude, exposure,slope, slope location, soil depth, humus depth, soil texture, soil moisture, and soil bulk density--were studied, then we found out the dominant factors influencing on the stand productivity, finally, we analyzed the reason by ecology. This study is infrequency in the domestic researches for large number of biomass data, and using together of variousmethods--single-variance regression, multiple variance regression, stepwise regression,and quantification method--in analyzing the relation between productivity and habitatsconditionsThe carbon storage, space distribution, annual net amount of fixed carbon, and the carbon density of organs from arbor layer, undergrowth vegetation and soil in the picea natural forest ecosystem were measured systematically in the study of carbon sequestration functions. The results show that the mean biomass of picea natural forest is 230.37×103kg·hm-2; the components of mean carbon density in the picea natural forest ecosystem indicated that the stem is 0.5785gc·g-1, the bark is 0.47 12gc·g-1, the branch is 0.5122gc·g-1, the leaf is 0.4827gc·g-1, and the root is0.5239gc·g-1. And the mean carbon densities of bush layer, ground cover, forest floor and soil are 0.4991gc·g-1, 0.4634gc·g-1, 0.4321gc·g-1, 0.3944gc·g-1 and 0.0141gc·g-1 respectively. Besides, the soil carbon density will decrease with soil height increase gradually. The whole carbon storage of picea forest ecosystem is 273.79×103kg·hm-2, and the carbon storage in arbor layer, brush layer, herb layer, ground cover, forest floor and forest soil in this ecosystem occupy 39.92%, 2.08%, 0.46%, 0.22%, 0.30% and 57.01% of the whole storage respectively, they are 109.30×103 kg·hm-2, 5.69×103 kg·hm2, 1.26×10 3kg·hm2, 0.60×103kg·hm-2, 0.83×103kg·hm-2, 156.11×103 kg·hm-2 in order. The Caron stock distribution order of picea forest from large to small is soil(0-100 cm) >arbor layer>brush layer>herb layer>forest floor>ground cover. The mean net productive amount of picea natural forest is 6838.5kg·hm-2·a-1 accounting for 63.38%; and annual net amount of fixed carbon is 2552.99 kg·hm-2·a(-1), accounting for 71.21% of the whole amount. The results also indicate that the productivity of picea stand in alpin-canyon is higher than that in the hilly-plateau, and the order of the mean net amount of productivity(MNAP) and annual net amount of fixed carbon(ANAFC) from large to small to the four picea forest types is leaning dry shrub-picea forest with 7515.65kg·hm-2·a-1 MNAP and 3779.54kg·hm-2·a-1 ANAFC, mid-generation arrow bamboo-picea forest with 7125.75kg·hm-2·a-1 MNAP and 3591.71kg·hm-2·a-1 ANAFC, drying grass-picea forest with 6517.0kg·hm·a-1MNAP and 3272.37kg·hm-2·a-1 ANAFC, and moist-bryophyte-picea forest with 3672.75kg·hm-2·a-1 MNAP and 1829.46kg·hm-2·a-1 ANAFC. Besides, the quantitative analysis of the multi-factor to site and stand structure through stand biomass and stock showed: the former 10 dominant factors influenced the changing of stand biomass are included angle of branch stem, branch stem thickness, needle density, mean soil moisture, stand age, leaf area index, canopy density, stand density, altitude gratitude, and slope. The results indicate that, on the whole, stand structure is the main aspect of limiting the stand productivity, while habitats factor is slightly unimportant than stand structure. The model has high multiple correlation indexes accounting for the better predicted function.4. 240 sample plots were indagated according to the age-group order, and then the mean population biomass in each age-group was worked out respectively in the study of picea population growth. The population biomass calculated and the 20 age-groups were fitted by the Logistic function to present picea population growth, and the Logistic models were established based on the data of stand density class, altitude gratitude and various picea stand type. In addition, the comprehensive judge model of picea population growth in different habitats condition was built based on the data of stand biomass and stock by the quantitation method (I) The results show: 1 the essential model of picea population biomass growth show "s" , fitted well by the Logistic function, while, population growth speed and carrying capacity of circumstance would vary on the rule-the carrying capacity of circumstance is high with high speed growth in the superior habitats condition, vice versa. 2 Cui-Lowson model did not apply in the study of picea population for the complex calculation; and the accuracy of fitting population growth by grey-system Verhulst model and GM (1.1) model did not get the satisfied results. 3 the statistical analysis of multi-variation showed that the order of dominant factors of limiting the population growth is tree canopy bulk, soil water, population structure, and landform, however, the order of factors will be changed as to population biomass and stock.In the study on Accommodation mechanism, the process and mechanism of accommodation of picea population density were analyzed, and crowding effect and density dependence of picea population were investigated besides the alteration of the individual in the habitats condition of different density were investigated because organs constitute one tree in population, at same time, the variation and the relation between individual and component growth and density in the picea population were studied, and we also investigated systematically the relation of organ biomass and population density and the relation between individual growth and habitats factors. The results show: 1 density dependence accommodate the population growth, and it can be descried by the -3/2 power law in the self-scanting process. 2 habitats conditions limit the accommodation capacity of picea population. Non-density dependence factors will prompt or buffer the capacity and strength the accommodation, which can be characterized by the absolute value of a in the power function of density competition effect W=KN-a, in which, if a leans great, the function is prompting, otherwise, is buffering. On the whole, the superior habitats will buffer the density dependence of population accommodation, while inferior habitats will accelerate it. We discussed the accommodation of picea population in the individual and component levels. The results indicated: individual accommodation was the comprehensive behavior of component accommodation, and habitats conditions would prompt or buffer the accommodation of two levels. The order of sensibility of responding to accommodation is flower, fruit, branch, leaf, root, stem, and bark. 4 the dominant factors of influence on individual accommodation were structure of mitsukazu nutrient in the population space (leaf area index, branch stem included angle, and population density), landform, soil nutrient, population age, and soil moisture. 5 the growth and accommodation of pices population are the two sides of one thing, and they are intimately correlate. The population growth will be continuously responded and influenced by the accommodation, and the accommodation will adjust the inner conflict from growth.The work was divided into four parts which had close relation. The evolution of habitats factor and site quality provided the background of research about picea stand structure, population growth and accommodation, and population productivity, which reveal the essential characteristic of potential productivity and the dominant environmental factors that limited the picea stand productivity; while, the research on the variation of picea stand structure in various habitats type, increase-decrease of productivity and the mechanic of population growth and accommodation will further indicate the form and strength of affect on the stand growth and development.Obviously, habitats condition effect on the stand structure, and stand structure and habitats condition together limited the picea population growth and accommodated the stand productivity. In our work, the relation between habitats conditions, stand structure and productivity has been analyzed qualitative and quantificationally. In addition, the population biomass in the age-group order were fitted by the Logistic function, and we established the Logistic models of picea population growth, various stand density levels, altitude gratitude, and forest type, then built different habitats conditions. In the comprehensive judge model about picea population growth, the bulk dependence and crowding effect were explained; the variation and the relation between individual, component growth and density were investigated systematically based on the theory of population accommodation. The results of this paper can be used in the practice of picea management, directing artificial reforestation, selection of afforestation density and form, and tending and intermediate falling and other practice to actualize the maximum increasing of stand productivity under bringing out the superior stand structure and good management form condition.
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