可变参数相对树曲线模型及其应用研究

用我国现行一元立木材积表估计林分或样地的立木材积偏差很大，而直接利用二元木材积表，则野外实测树高的工作量又太大。本研究针对这一实际问题，提出了通过建立可变参数相对树高曲线模型，将二元立木材积表直接用于林分或样地立木材积估计的方法，其 估计精度可达到接近实测树高曲线法的水平。     

可变参数相对树高曲线模型及其应用研究

用我国现行一元立木材积表估计林分或样地的立木材积偏差很大，而直接利用二元立木材积表，则野外实测树高的工作量又太大。本研究针对这一实际问题，提出了通过建立可变参数相对树高曲线模型，将二元立木材积表直接用于林分或样地立木材积估计的方法，其估计精度可达到接近实测树高曲线法的水平。研究提出的可变参数相对树高曲线模型结构通式为：ＲＨｉ＝。     

相对树高曲线模型的研究和应用

本文针对我国现行一元立木材积表估计立木材积对林分或样地偏差太大，直接利用二元立木材积表野外测绘树高曲线工作量大等实际问题，研究提出了利用相对树高曲线模型将二元立木材积表用于林分和样地立林材积估计的方法，其估计精度可达到近似实测树高曲线法的水平而又不增加野外工作量。     

相对树高曲线模型的建立与应用

利用标准地调查资料建立相对树高曲线模型，将此模型与二元立木材积表相结合，用于林分和样地立木材积的估计。其估计精度可达到近似实测树高曲线法的水平，又不增加野外工作量，避免了利用一元立木材积表估计林分或样地立木材积偏差太大的问题。     

一元立木材积表的适用精度检验方法探讨

国家森林资源连续清查中长期使用的一元立木材积表,其适用精度如何,一直是值得关注的问题。以第九次全国森林资源清查2014年陕西省的栎类(Quercus spp.)样地调查数据为基础,对其采用的4个栎类一元材积表的适用精度检验方法进行探讨。利用栎类样地的466组平均胸径和平均树高数据,以及全部平均高测定样木的1 447组胸径和树高成对数据,按2套方案分别建立4个栎类的新的树高曲线,从而形成4个新的一元材积表,并与原来的材积表进行对比,计算总体相对误差。结果表明:原一元材积表有2个的估计误差在±3%以内,另外2个的估计误差超出了±5%,误差最大的达到了-10%左右。因此,长期使用固定不变的一元材积表可能会导致材积估计结果出现偏差,建议每10年或20年对一元立木材积表(模型)进行适用精度检验,对偏差过大的一元材积表应该及时予以修正。     

临沂市赤松黑松油松—元立木材积表的编制

利用临沂市赤松，黑松，油松测高木资料，对３树种平均树高差异性进行了检验。求算出各树种的树高曲线方程，并采用松类二元立木材积式导算出各树种的一元立木材积表。经检验分析，各树种一元立木材积表的精度均明显高于１９７５年编制的松类一元立木材积表     

临沂市赤松黑松油松一元立木材积表的编制

利用临沂市赤松、黑松、油松测高木资料,对３树种平均树高差异性进行了检验。求算出各树种的树高曲线方程,并采用松类二元立木材积式导算出各树种的一元立木材积表。经检验分析,各树种一元立木材积表的精度均明显高于１９７５年编制的松类一元立木材积表。     

抚宁县地方材积表的编制

根据抚宁县林木生长现状与河北省一元立木材积表的差异,选择合适的Ｈ－Ｄ数字曲线方程,用图解法检验调整,用部颁二元立木材积表材积经验式导算出一元立木材积表。     

广西一元立木材积表适用性评价

立木材积表是林业调查和森林经营中材积计量最重要的依据。现行广西森林资源调查使用的一元立木材积表是广西林业勘测设计院于1977年依据《全国立木材积表》相应树种的二元材积式导算而得,随时间推移及森林经营水平提升,有必要对其适用性进行评价。收集广西第九次森林资源连续清查样地平均木调查的树种实测胸径与树高资料,分树种建立林分总体平均高模型,并由一元材积和二元材积方程式导算出编表初期（1977年）的理论树高-胸径曲线,定量分析1977年与2015年相应树种的树高变化;建立不同树种的一元材积与二元材积回归模型,采用F检验和总相对误差作为材积表适用性评价指标。结果表明,不同树种林分总体平均高均变化明显,实际平均高均高于理论平均高10%以上,桉树的差异最大;F检验和总相对误差的结果表明,一元材积模型均没有通过检验,总相对误差均超过±5%的范围,桉树的总相对误差最大。现行一元立木材积表计算的材积明显偏低,建议广西尽快开展数表修编工作。     

“样地蓄积量调查的3P抽样法”

<正> 蓄积量通过样地每木调查,用一元材积表测算,是目前我国和其它国家最常用的一种调查方法。随着经营强度和调查技术的提高,越来越对一元材积表测算蓄积量提出了疑异或否定,若用二元材积表,虽能提高样地蓄积量的调查精度,但需要测定30—40株立木的树高来反映待测样地胸径与树高的数量关系,使外业工作量增加很多,而未被广泛采用。本文根据3P抽样理论,提出在样地每木调查基础上,     

Allometric model of the height–diameter curve for even-aged pure stands of Japanese cedar (<Emphasis Type="Italic">Cryptomeria japonica</Emphasis>)

We derived an allometric model of the height–diameter curve for even-aged pure stands, which was a modification of the earlier model proposed by Inoue (2000a). An individual-dependent allometric equation was used as the height–diameter curve. Using the discriminant analysis method, all trees composed of a stand were stratified into upper and lower trees. It was assumed that both relationships between mean tree height H _m and upper tree height H _u and between mean DBH D _m and mean DBH of upper trees D _u could be described by the time-dependent allometric power equations. The height–diameter curve showed an average relationship between tree height and DBH of a given stand at a given time, and hence it could be assumed that the height–diameter curve contained two points (D _m , H _m ) and (D _u , H _u ). With these assumptions, we derived an allometirc model of height–diameter curve, which allowed the coefficients of the curve to be estimated from mean tree height and mean DBH. The proposed model was fitted to Japanese cedar (Cryptomeria japonica D. Don) data. The error ratio of the allometric model ranged from 2.254% to 13.412% (mean = 6.785%), which was significantly smaller than that of the earlier model. When the error of mean tree height was ±1.0 m or less, the effect of the error of mean tree height on the error ratio was comparatively small. This suggested that the error of ±1.0 m in mean tree height could be accepted in the estimation of height–diameter curve using the allometric model. These features enable us to combine the allometric model with Hirata’s vertical angle-count sampling or growth models. In conclusion, the allometric model would be one of the most practical and convenient approaches for estimating the height–diameter relationship of even-aged pure stands.     

Modeling of the height–diameter relationship using an allometric equation model: a case study of stands of <Emphasis Type="Italic">Phyllostachys edulis</Emphasis>

Understanding the relationship between tree height (H) and diameter at breast height (D) is vital to forest design, monitoring and biomass estimation. We developed an allometric equation model and tested its applicability for unevenly aged stands of moso bamboo forest at a regional scale. Field data were collected for 21 plots. Based on these data, we identified two strong power relationships: a correlation between the mean bamboo height (H _m) and the upper mean H (H _u), and a correlation between the mean D (D _m) and the upper mean D (D _u). Simulation results derived from the allometric equation model were in good agreement with observed culms derived from the field data for the 21 stands, with a root-mean-square error and relative root-mean-square error of 1.40 m and 13.41 %, respectively. These results demonstrate that the allometric equation model had a strong predictive power in the unevenly aged stands at a regional scale. In addition, the estimated average height–diameter (H–D) model for South Anhui Province was used to predict H for the same type of bamboo in Hunan Province based on the measured D, and the results were highly similar. The allometric equation model has multiple uses at the regional scale, including the evaluation of the variation in the H–D relationship among regions. The model describes the average H–D relationship without considering the effects caused by variation in site conditions, tree density and other factors.     

Development and validation of a stem volume equation for Cupressus lusitanica in Gergeda Forest,Ethiopia

Stem volume equations were fitted for Cupressus lusitanica in Gergeda Forest, Ethiopia using six different established equation forms. A total of 260 trees were measured for their diameter at breast height (D), total height (H?)and stem volume using destructive sampling methods. The data set was randomly divided into equal size for equation development and equation validation. Five fit statistics comprising of the fit index, root mean square error, bias (ē?), absolute mean deviation and coefficient of variation were used to evaluate the performance of each equation. Among the different equations, the Schumacher and Hall function of the form V = b₁D^b2H^b3 (model 5), which estimates volume (V?) using diameter at breast height and total height as predicting variables, performed best and was then fitted to the combined data set for prediction of volume over-bark of C. lusitanica in Gergeda Forest. Overall, volume equations with two independent variables (D and H?) performed better than those with only one variable (D). The equations developed in this study can provide forest managers with accurate estimations of stem volumes for C. lusitanica in Gergeda Forest.     

理论造材:削度方程和出材率表的编制

本文提出了计算机理论造材仅根据削度方程和单株带,去皮胸径的转换关系式两个模型,可不必由削度方程推导材长方程和材积比方程。比相关指数,均方程为指标,结合残差图分析,选择了杉木、落叶松的削度方程;结合标准树高曲线,是可仅根据优势高为任一具体林分编制（一元）单株出材率表（特称之为自动调整出材率表）。     

基因分化值和基因调控信息量研究

本文通过对基因调控、表达的分析,探讨了个体分化定量问题,提出用基因分化值D_(?)指标,度量分化细胞之间的内部差异;对调控、表达问题,用信息论的方法加以处理,得到了基因调控熵H_r,再从H_r指标估算出调控信息量。D_(?)具有强度性质;H_r具有容量性质。试验选用同功酶测定这两项分化指标。再用这两项指标进一步讨论分化、进化、生物信息、群体复杂性等问题。     

Determinants of stem form: Application to Tectona grandis (Linn. F) stands

ABSTRACT

Stem form information can enhance rapid estimation of stem volume. Studies on important determinants of stem form in pure stands are scanty. This study aimed at identifying determinants of stem form using Tectona grandis stands in Omo Forest Reserve, Nigeria. Twenty 0.04 ha square plots were randomly selected across four stand ages. Crown diameter, total and merchantable heights (MH), diameters at breast height (DBH), at 5.27 m tree height and at midpoint from breast height to tip of tree were measured in each plot. Measured trees were classified into four canopy layers (CL)—dominant, codominant, intermediate, and suppressed. Merchantable volume, basal area (BA), form factor (F_f), normal form quotient (Q_n), Girard form class (Q_G), absolute form quotient (Q_a), ratio of diameter at merchantable limit to diameter at the base (D_t/D_b), and tree slenderness coefficient were derived from the data. Analysis of variance, correlation, and regression analyses were used to analyze the data. Significant differences were observed in stem form and tree size variables under different canopy layers. The DBH, BA, MHT, and CL were identified as important variables associated with stem form. Inclusion of Q_a improved most the predictive ability of the selected stem volume equation.     

Biomass equations for four shrub species in subtropical China

Estimation of shrub biomass can provide more accurate estimates of forest biomass and carbon sequestration. We developed species-specific biomass regression models for four common shrub species, Chinese loropetal (Loropetalum chinense), white oak (Quercus fabri), chastetree (Vitex negundo var. cannabifolia), and Gardenia (Gardenia jasminoides), in southeast China. The objective of this study was to derive appropriate regression equations for estimation of shrub biomass. The results showed that the power model and the quadratic model are the most appropriate forms of equation. CA (canopy area, m²) as the sole independent variable was a good predictor of leaf biomass. D ² H, where D is the basal diameter (cm) and H is the shrub height (cm), is a good predictor of branch and root biomass, except for V. negundo var. cannabifolia and the root biomass of L. chinense. For total biomass, D ² is the best variable for estimation of L. chinense and G. jasminoides, and D ² H is the best variable for estimation of Q. fabri and V. negundo var. cannabifolia. Although variables D ², D ² H, and H are the preferred predictors for biomass estimation, CV (canopy projected volume, m³) could be used alone to predict branch, root, and total biomass in shrub species with acceptable accuracy and precision.     

Das Wachstum von Pinus pinaster (Aiton) in Abhängigkeit vom Standraum

Summary Spacing trials were established inPinus pinaster, in plantations in the Southern and South-Western Cape Province in South Africa. Eight spacings, with nominal initial stem numbers between 125 and 3000 were tested in each of the two trials, with a single replicate in each experiment. The Chapman-Richards growth model was applied to mean diameter, mean height and basal area/ha. For diameter and height, the assumption m=0 holds true, but for basal area/ha, this parameter is related to initial stem number. The volume growth of each sample plot was estimated from equations with basal area and mean height and their interaction as predictor-variables. The regression model also included constraints for basal area and height, to prevent anomalies for the estimated volume per hectare at young age. Each of the trials contained a number of plots, thinned after the onset of competition. The growth rates in these plots was statistically significantly greater than that of the same stand density in the unthinned plots.      

Height-diameter curves with random intercepts and slopes for trees growing on drained peatlands

Models for predicting tree height were constructed for Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and pubescent birch (Betula pubescens). The data consisted of two separate sets of permanent sample plots forming a representative sample of drained peatland stands in the whole country. A logarithmic height-diameter curve with one nonlinear parameter specific to each tree species was applied. It was assumed that the intercept and slope of the curve would vary randomly from stand to stand. Stand characteristics were used to predict the mean intercept and slope. A nonhomogeneous variance of the residual error was modelled as a function of tree diameter. A mixed linear model technique was applied to fit the models. The diameter of the tree of the median basal area, stand basal area, geographical location of the stand, and site quality were used as fixed independent variables in explaining the variation in the intercept. The diameter of the tree of the median basal area and the stand basal area were used in explaining the variation in the slope.     

Practical large-scale forest stand inventory using a small-footprint airborne scanning laser

Mean tree height, dominant height, mean diameter, stem number, basal area and timber volume of 116 georeferenced field sample plots were estimated from various canopy height and canopy density metrics derived by means of a small-footprint laser scanner over young and mature forest stands using regression analysis. The sample plots were distributed systematically throughout a 6500 ha study area, and the size of each plot was 232.9 m². Regressions for coniferous forest explained 60–97% of the variability in ground reference values of the six studied characteristics. A proposed practical two-phase procedure for prediction of corresponding characteristics of entire forest stands was tested. Fifty-seven test plots within the study area with a size of approximately 3740 m² each were divided into 232.9 m² regular grid cells. The six examined characteristics were predicted for each grid cell from the corresponding laser data using the estimated regression equations. Average values for each test plot were computed and compared with ground-based estimates measured over the entire plot. The bias and standard deviations of the differences between predicted and ground reference values (in parentheses) of mean height, dominant height, mean diameter, stem number, basal area and volume were ?0.58 to ?0.85 m (0.64–1.01 m), ?0.60 to ?0.99 m (0.67–0.84 m), 0.15–0.74 cm (1.33–2.42 cm), 34–108 ha^?1 (97–466 ha^?1), 0.43–2.51 m² ha^?1 (1.83–3.94 m² ha^?1) and 5.9–16.1 m³ ha^?1 (15.1–35.1 m³ ha^?1), respectively.