Estimating Pinus palustris tree diameter and stem volume from tree height,crown area and stand-level parameters

Accurate and efficient estimation of forest growth and live biomass is a critical element in assessing potential responses to forest management and environmental change. The objective of this study was to develop models to predict longleaf pine tree diameter at breast height （dbh） and merchantable stem volume （V） using data obtained from field measurements. We used longleaf pine tree data from 3,376 planted trees on 127 permanent plots located in the U.S. Gulf Coastal Plain region to fit equations to predict dbh and V as functions of tree height （H） and crown area （CA）. Prediction of dbh as a function of H improved when CA was added as an additional independent variable. Similarly, predic- tions of V based on H improved when CA was included. Incorporation of additional stand variables such as age, site index, dominant height, and stand density were also evaluated but resulted in only small improvements in model performance. For model testing we used data from planted and naturally-regenerated trees located inside and outside the geographic area used for model fitting. Our results suggest that the models are a robust alternative for dbh and V estimations when H and CA are known on planted stands with potential for naturally-regenerated stands, across a wide range of ages. We discuss the importance of these models for use with metrics derived from remote sensing data.

Estimating Individual Tree Diameter and Stem Volume Using Airborne LiDAR in Saga Prefecture, Japan

Advancements in airborne LiDAR analysis technology have made it possible to quantify forest resource volumes based on individual trees, and such technology may soon replace field surveys. Unlike individual tree detection or tree height measurements, diameter at breast height (DBH) is difficult to determine directly from measured data and is instead estimated indirectly using the correlation between crown size and DBH. Indicators that represent crown size include crown area, surface area, length, and length ratio, and were utilized with tree height as explanatory variables in ten combinations to determine a regression formula. DBH and tree height calculated from the regression formula were applied to an equation to calculate stem volumes of individual trees. Airborne LiDAR measurements were taken using ALS50-II and ALS60 (Leica) at a density of 4 points/m2. An evaluation of the relationship between the regression formulae and DBH estimates indicated that a combination of crown area, tree height, and crown ratio for Japanese cedar, and a combination of crown area and tree height for Japanese cypress, yielded the highest coefficients of determination. The average error and RMSE were 6.9% and 2.38 cm respectively for Japanese cedar, while the corresponding values for Japanese cypress were 8.35% and 2.51 cm. Once the relationship was extended to the stem volumes of individual trees, the average error was 14.4% and RMSE was 0.10 m3 for Japanese cedar. The corresponding values for Japanese cypress were 18.9% and 0.10 m3. These results demonstrate the potential use of airborne LiDAR as a substitute for field surveys.

Ecological Structure and Prediction Equations for Estimating Tree Age, and Dendometric Parameters of <i>Acacia senegal</i>in the Senegalese Semi-Arid Zone—Ferlo

The development of equations to predict tree height, crown diameter, crown depth from stem diameter of a tree species enables arborists, researchers, and urban forest managers to model costs and benefits, analyze alternative management scenarios, and determine the best management practices for sustainable forests. The objective of this study was to develop regression prediction models for tree age, tree height, crown diameter, crown ratio and crown depth for A. senegal growing in Ferlo, in the northern Senegal. Four plantations of different years old (ISRA, 10 years old plantations, Ndodj, 8 years old plantations, Boulal, 5 years old plantations and Déali, 4 years old plantations) were selected. The following dendometric variables: crown height, crown diameter, stem diameter at the breast height, stem basal diameter (at 0.30 m) and the height from the tree base to first branch were measured on a total of 489 trees. The results suggested that the ecological structure of the different year old A. Senegal plantation revealed a bell-shaped form with left dissymmetric distribution indicating a predominance of individuals with small diameter at breast height. Allometry study of A. Senegal showed highly significant positive correlations (p = 0.00) between stem diameter at breast height, stem basal diameter, tree height, crown diameter and crown depth. Positive correlations were also found between crown diameter, tree height and crown height. Prediction models derived from these relationships can be used to estimate the tree height, stem diameter at breast height and crown depth from crown diameter with greater precision. As for A. Senegal age estimation, the established model is not strong as it can explain only 49.1% of the age variation.

New indices to balanceα-diversity against tree size inequality

The number and composition of species in a community can be quantified withα-diversity indices,including species richness(R),Simpson’s index(D),and the Shannon-Wiener index(H΄).In forest communities,there are large variations in tree size among species and individu-als of the same species,which result in differences in eco-logical processes and ecosystem functions.However,tree size inequality(TSI)has been largely neglected in studies using the available diversity indices.The TSI in the diameter at breast height(DBH)data for each of 99920 m×20 m forest census quadrats was quantified using the Gini index(GI),a measure of the inequality of size distribution.The generalized performance equation was used to describe the rotated and right-shifted Lorenz curve of the cumulative proportion of DBH and the cumulative proportion of number of trees per quadrat.We also examined the relationships ofα-diversity indices with the GI using correlation tests.The generalized performance equation effectively described the rotated and right-shifted Lorenz curve of DBH distributions,with most root-mean-square errors(990 out of 999 quadrats)being<0.0030.There were significant positive correlations between each of threeα-diversity indices(i.e.,R,D,and H’)and the GI.Nevertheless,the total abundance of trees in each quadrat did not significantly influence the GI.This means that the TSI increased with increasing spe-cies diversity.Thus,two new indices are proposed that can balanceα-diversity against the extent of TSI in the com-munity:(1−GI)×D,and(1−GI)×H’.These new indices were significantly correlated with the original D and H΄,and did not increase the extent of variation within each group of indices.This study presents a useful tool for quantifying both species diversity and the variation in tree sizes in forest communities,especially in the face of cumulative species loss under global climate change.

Analysis on the Growth Condition of Cunninghamia lanceolata Plantation in Lingnan Forest Farm

[Objectives]This study was conducted to provide good basic research data for Cunninghamia lanceolata plantations in southern Anhui,so as to improve local ecological,economic and social benefits.[Methods]A 22-year-old near-mature C.lanceolata plantation in Lingnan Forest Farm,Xiuning County,Huangshan City,Anhui Province was investigated and analyzed by sample plot survey.[Results]The average DBH value of the C.lanceolata plantation at the lower slope was the largest,24.7%and 19.2%higher than those at the upper and middle slopes,respectively.The average single plant wood volume at the lower slope was 47.6%and 49.1%higher than those in the upper and middle slopes,respectively.However,the average tree heights at various slope positions showed little difference.Meanwhile,all the indexes showed the phenomenon of semi-shady slope>sunny slope>shady slope under different slope directions.Among them,the effect of slope position on DBH was extremely significant,but the effect of slope direction on DBH was not significant,and slope position,slope direction and the interaction of slope direction and slope position had no significant effects on the tree height of the C.lanceolata plantation.In addition,slope direction and slope position had extremely significant effects on single plant wood volume.From the overall growth situation of the C.lanceolata plantation in Lingnan Forest Farm,the slope position factor had greater effects on various indexes of forest growth than the slope direction factor,mainly manifested in that the lower slope was better than the middle slope,and the middle slope position was better than the upper slope,while although slope direction had some effect on the growth of the C.lanceolata plantation,the influence degree was not as significant as that of slope position.[Conclusions]This study provides some reference for the adjustment and optimization,development and renewal of C.lanceolata plantation structure in the later period in this area,as well as some data support for other theoretical research on economic forests.

Radarsat SAR的森林生物物理参数信号响应及其蓄积量估测

利用地面实测数据,系统探讨了RadarsatSAR数据在森林蓄积量估测方面的应用潜力和森林生物物理参数信号响应。结果表明:RadarsatSAR后向散射系数与森林蓄积量、树高及胸径之间的关系可以用对数模型模拟;树种对后向散射系数具有一定影响;利用后向散射系数估测森林蓄积量,其精度基本符合林场大面积总体估测的精度要求,但小班水平应用效果不理想。

Parameterization of height-diameter and crown radius-diameter relationships across the globe

The tree height-diameter at breast height(H-DBH)and crown radius-DBH(CR-DBH)relationships are key for forest carbon/biomass estimation,parameterization in vegetation models and vegetation-atmosphere interactions.Although the H-DBH relationship has been widely investigated on site or regional scales,and a few of studies have involved CR-DBH relationships based on plot-level data,few studies have quantitatively verifed the universality of these two relationships on a global scale.This study evaluated the ability of 29 functions to ft the H-DBH and CR-DBH relationships for six different plant functional types(PFTs)on a global scale,based on a global plant trait database.Results showed that most functions were able to capture the H-DBH relationship for tropical PFTs and boreal needleleaf trees relatively accurately,but slightly less for temperate PFTs and boreal broadleaf trees(BB).For boreal PFTs,the S-shaped Logistic function ftted the H-DBH relationship best,while for temperate PFTs the Chapman-Richards function performed well.For tropical needleleaf trees,the fractional function of DBH satisfactorily captured the H-DBH relationship,while for tropical broadleaf trees,the Weibull function and a composite function of fractions were the best choices.For CR-DBH,the ftting capabilities of all the functions were comparable for all PFTs except BB.The Logistic function performed best for two boreal PFTs and temperate broadleaf trees,but for temperate needleleaf trees and two tropical PFTs,some exponential functions demonstrated higher skill.This work provides valuable information for parameterization improvements in vegetation models and forest feld investigations.

Allometric models for estimating aboveground biomass in the tropical woodlands of Ghana, West Africa

Background: Modelling aboveground biomass(AGB) in forest and woodland ecosystems is critical for accurate estimation of carbon stocks. However, scarcity of allometric models for predicting AGB remains an issue that has not been adequately addressed in Africa. In particular, locally developed models for estimating AGB in the tropical woodlands of Ghana have received little attention. In the absence of locally developed allometric models, Ghana will continue to use Tier 1 biomass data through the application of pantropic models. Without local allometric models it is not certain how Ghana would achieve Tier 2 and 3 levels under the United Nations programme for reducing emissions from deforestation and forest degradation. The objective of this study is to develop a mixedspecies allometric model for use in estimating AGB for the tropical woodlands in Ghana. Destructive sampling was carried out on 745 trees(as part of charcoal production) for the development of allometric equations. Diameter at breast height(dbh, i.e. 1.3 m above ground level), total tree height(H) and wood density(ρ) were used as predictors for the models. Seven models were compared and the best model selected based on model efficiency,bias(%) and corrected Akaike Information Criterion. The best model was validated by comparing its results with those of the pantropic model developed by Chave et al.(Glob Chang Biol 20:3177–3190, 2014) using equivalence test and conventional paired t-test.Results: The results revealed that the best model for estimating AGB in the tropical woodlands is AGB =0.0580ρ((dbh)2 H)0.999. The equivalence test showed that this model and the pantropic model developed by Chave et al.(Glob Chang Biol 20:3177–3190, 2014) were equivalent within ±10% of their mean predictions(p-values <0.0001 for one-tailed t-tests for both lower and upper bounds at 5% significant level), while the paired t-test revealed that the mean(181.44 ± 18.25 kg) of the model predictions of the best model of this study was significantly(n = 745, mean diff. = 16.50 ± 2.45 kg;S.E. = 1.25 kg;p < 0.001) greater than that(164.94 ± 15.82 kg) of the pantropic model of Chave et al.(Glob Chang Biol 20:3177–3190, 2014).Conclusion: The model developed in this study fills a critical gap in estimating AGB in tropical woodlands in Ghana and other West African countries with similar ecological conditions. Despite the equivalence with the pantropic model it remains superior to the model of Chave et al.(Glob Chang Biol 20:3177–3190, 2014) for the estimation of AGB in local tropical woodlands. It is a relevant tool for the attainment of Tier 2 and 3 levels for REDD+. The model is recommended for use in the tropical woodlands in Ghana and other West African countries in place of the use of pantropic models.

Biomass Estimation Models for Cocoa (Theobroma cacao) Plantations in Ghana, West Africa

The role of cocoa systems for climate change mitigation and adaptation has increased substantially because of their capability to trap carbon dioxide from the atmosphere and deposited in the cocoa trees as carbon. Development of aboveground biomass (AGB) models for cocoa plantations is crucial for accurate estimation of carbon stocks in the cocoa systems, however, allometric models for estimating AGB for cocoa plantations remain a challenge for cocoa producing countries in Sub-Saharan Africa especially Ghana. The aim of this study is to develop allometric model that can be used for the estimation of AGB for cocoa plantations in Ghana, as well as West Africa. Destructive sampling was carried out on 110 cocoa trees obtained from the cocoa rehabilitation exercise for the development of the allometric models. Diameter at breast height (D), total tree height (H) and wood density (ρ) were used as predictors to develop seven models. The best model was selected based on coefficient of determination (R2), index of agreement (IA), root mean squared error (RMSE), bias (E%), mean absolute error (MAE) and corrected akaike information criterion (AICC) and percentage relative standard error (PRSE) of the estimated parameters. The selected model, which was the one with the predictors D and ρ, was given as;AGB = 0.7217ρ(D2)0.921. It was compared with the Yuliasmara et al. (2009) cocoa model using equivalence test and paired sample t-test. The two models were found to be equivalent within ±10% of their mean predictions (p < 0.0001) for one-tailed tests for both lower and upper limits, while the paired sample t-test rejected the null hypothesis with mean difference of 14.16 kg between the two models. This study is significant because it has provided a model to estimate AGB for the cocoa plantations in Ghana which is very important for the Ghana Cocoa-Forest REDD+ Programme and also can be used by other West African cocoa producing countries.

红松半同胞家系生长性状变异及优良家系和单株的筛选

在辽宁省本溪满族自治县清河城实验林场国家红松良种基地,以2007年营建的15年生红松半同胞子代测定林为研究对象,选择参试家系171个(其中包括当地生产苗作为对照),造林株行距2 m×3 m,设计为10株小区,9次重复;2022年11月份,测定试验林所有存活木的树高、胸径,以树高、胸径、单株材积等生长性状为评价指标,计算各指标的变异系数、家系遗传力、遗传增益、现实增益;采用多目标决策法、隶属函数法筛选优良家系和优良单株。结果表明:参试家系各测定指标差异均达极显著水平(P<0.01),各指标变异系数变化范围为9.69%~35.01%、家系各指标遗传力变化范围为0.64~0.78、家系单株遗传力变化范围为0.14~0.45,说明参试家系具有较大的性状变异和较高的遗传力。利用隶属函数法筛选出优良家系17个,入选家系的胸径均值5.69 cm、树高均值12.92 m、单株材积均值0.04 m^(3),分别是当地生产苗(对照)胸径的1.14倍、树高的1.13倍、单株材积的1.44倍;17个优良家系的现实遗传增益,胸径为3.21%、树高为4.54%、单株材积为9.37%。在优良家系的基础上筛选出50株优良单株,入选单株胸径平均值为6.6 cm、树高平均值为15.1 m、单株材积平均值为0.0573 m^(3)。

凉水保护区红松与主要伴生树种的空间关系

空间关系是影响森林生长与群落演替的重要因素,种间关系是其重要组成部分,研究空间关系有利于了解森林群落的生长更新、功能作用与演替进程。利用移动窗口法对凉水自然保护区10.4 hm^(2)样地不同径级的红松与主要伴生树种做空间相关性研究,并进行多尺度比较,得到不同尺度下不同径级红松与主要伴生树种个体的空间关系特征。研究结果表明:(1)红松与伴生树种的相互关系复杂多样,多种相互关系并存,表现出阔叶红松林群落结构的复杂性与稳定性。大径级红松压制同径级伴生树种,二者呈极显著负相关,但其对小径级伴生树种有庇荫作用,二者呈极显著正相关。(2)红松与主要伴生树种的相互关系在不同尺度、径级上均有极显著差异。尺度越大,红松与主要伴生树种的相关系数变化速率越小;伴生树种的径级越大,红松与主要伴生树种的相关系数变化速率越大。(3)红松与伴生树种的相关性具有尺度特征,主要表现在大尺度(≥60 m)范围上,在小尺度(<60 m)上相关性较弱。红松与伴生树种在相同径级与不同径级的结合方式上表现出不同的空间关系。同径级的红松与伴生树的种间关系多表现为负相关,不同径级的红松与伴生树种种间关系多表现为正相关。(4)以种间关系确定样方最小面积,凉水保护区临界样地面积为60 m×60 m。该研究集中于不同尺度下不同径级的红松与伴生树种的种间关系,解释优势种红松与伴生树种在森林的空间关系以及群落结构特征,为东北地区阔叶红松林的森林管理提供参考意见。

立地环境和林分结构驱动的辽东栎林生长与模拟

【目的】定量研究宁夏六盘山区辽东栎(Quercus mongolica)林的树高和胸径生长对气候、地形、土壤、林分结构等多种因子变化的响应规律,在此基础上构建多因子耦合模型,准确模拟和预测气候等因子对森林生长的影响。【方法】依据宁夏六盘山区环境梯度,2021—2022年对79块辽东栎天然次生林样地进行每木调查,利用上外包线法确定林分平均树高和平均胸径对立地环境和林分结构等因子的响应关系和函数类型,通过连乘构建多因子耦合模型框架并基于实测数据拟合模型参数,用于模拟气候变化对辽东栎林生长的影响。【结果】同时影响六盘山区辽东栎林平均树高和平均胸径生长的主要因子是林龄、林分密度、年均降水量、年均气温、土壤厚度。平均树高和平均胸径随林龄增大呈缓慢−快速−缓慢的生长变化,随林分密度增大呈先稳定后加速下降的变化,随土壤厚度和年均降水量增大呈先快速增加后渐趋平稳的变化,随年均气温升高呈先快速上升后快速下降的单峰变化趋势。根据林分平均树高和平均胸径对各单因子的响应函数构建了二者的多因子耦合模型,预测精度较高(R2>0.70)。对年均气温升高1.5℃的情景模拟结果表明,整个六盘山区的辽东栎林平均树高和平均胸径生长速率都会降低,其降低幅度在气候冷湿的六盘山区南部分别为10%和7%,在气候暖湿的六盘山区中部分别为15%和12%,在气候暖干的六盘山区北部分别为18%和13%。【结论】宁夏六盘山区辽东栎次生林的平均树高和平均胸径生长同时受气候、林分结构、立地环境等多因子的影响,建立反映多个主要因子(年均降水量、年均气温、林龄、林分密度、土壤厚度)影响的耦合生长模型可以准确预测气候变化和密度调控对树高和胸径生长的影响。未来的气温升高将会降低平均树高和平均胸径的生长,但降低幅度存在区域差异,表现为气温越高的区域降低幅度越大,需要分区采取不同的森林管理应对措施。研究结果可为预测气候变化影响和确定森林管理措施提供理论与技术支持。

初植密度对不同杉木良种幼林生长的影响

对不同初植密度下3年生杉木良种的树高、地径、单株材积等生长性状进行调查与分析,筛选适宜种植的杉木初植密度。结果表明:(1)良种对树高存在显著影响,密度对地径、单株材积存在显著影响。良种与密度的交互作用对杉木树高、地径、单株材积均存在显著影响。(2)普通杉木、尤溪3代在低初植密度(2500株·hm^(-2))下,林分生长状况较好,且尤溪3代优于普通杉木;官庄红心杉在高初植密度(3300株·hm^(-2))下,林分生长状况较好。

自动测量胸径和树高便携设备的研制与测量精度分析

胸径和树高测量是评价立地质量和林木生长状况的重要依据,该文以图像自动识别原理、摄影测量原理、相似三角形几何原理和三角函数原理为理论基础,研制了可测量胸径和树高的多功能便携式微型超站仪,该设备集成电荷藕合器件图像传感器、倾角传感器、激光测距传感器、中央处理器、存储器、液晶显示屏,测量时可获取测站点到待测点的倾角和距离2个参数值,并记录存储测量时的图像信息,通过仪器的嵌入式操作程序,实现胸径的自动测量、树高测量、任意处直径自动测量、基本测量等4项基本功能。通过试验验证,215株立木的单次胸径测量的平均绝对误差为0.369 cm,平均相对误差为2.08%。101株立木的单次树高测量的平均相对误差为1.44%。胸径测量精度达到97.92%,树高测量精度达到98.56%,符合国家森林资源连续清查中的测量精度要求。该设备为森林资源调查提供了参考。

不同坡位对福建柏生长影响的研究

对不同坡位的福建柏生长进行研究,结果表明:不同坡位对福建柏树高、胸径、枝下高生长有显著影响。随着坡位下降,树高、胸径、材积生长显著增大。下坡位平均树高生长达7.28 m,平均胸径生长达11.78 cm,单位面积材积生长达30.525 m3,单位面积材积比上坡位增长95%;中坡位平均树高生长达6.83 m,平均胸径生长达11.30 cm,单位面积材积生长达24.198 m3,单位面积材积比上坡位增长55%;上坡位平均树高生长仅为6.25 m,平均胸径生长为8.98 cm,单位面积材积生长仅为15.651 m3。福建柏在下坡位生长最佳,中坡位次之,上坡位最差。因此,福建柏商品林造林地最宜选择下坡位,较宜为中坡位。

机载LIDAR点云数据估测单株木生物量

使用黑河流域遥感-地面观测同步试验获取的机载激光雷达(LIDAR)点云数据估测了典型树种的单株木生物量。首先由点云数据生成冠层高度模型(CHM),然后采用优化的单株木树冠特征识别算法估测相关的结构参数,最后通过回归分析建立估测参数(树高、冠幅)与实测参数(树高、冠幅、胸径)之间的最优回归方程,并与现有的单株木生物量实测相关生长方程联立,得到单株木生物量估测相关生长方程。结果表明,由LIDAR点云数据得到的单株木估测参数与实测参数显著相关,可以估测单株木生物量(R^2为0.729)。

利用轻小型飞机遥感数据建立人工林特征参数模型

目前获取森林特征参数的主要方法是外业测量,工作量大、效率低。该文以中国自主研发的轻小型航空遥感系统为数据获取工具,以油松人工林为研究对象,通过对获取森林的激光雷达(light detection and ranging,LIDAR)点云数据去噪,分类,提取等过程获得单木的树高数据,对获取的航空影像数据进行预处理,匹配,拼接,分割及冠幅提取获得单木的冠幅数据,再与外业抽样调查的单木的树高、胸径建立回归模型,同时验证模型精度。试验结果表明:通过LIDAR点云数据提取的树高与实测的树高具有极显著的相关性,所建立的模型预测精度达97.5%,通过影像提取的冠幅与实测的胸径也具有极显著的相关性,预测精度达91.6%,基本上能够满足林业生产的要求。

基于空间自相关的天然蒙古栎阔叶混交林林木胸径-树高模型

【目的】考虑林木间的空间自相关,构建基于空间自相关的林木胸径-树高模型,为可持续经营天然混交林提供理论依据。【方法】以天然蒙古栎阔叶混交林为研究对象,选择适宜的线性化林木胸径-树高模型为基础模型(BM),应用3个同步自回归(SAR)模型即空间滞后模型(SLM)、空间误差模型(SEM)和空间Durbin模型(SDM)研究该混交林的林木胸径-树高模型。同时,将Delaunay三角网(DT)矩阵、逆距离一次幂(ID1)、逆距离二次幂(ID2)、逆距离五次幂(ID5)、球状变异函数(SV)矩阵、高斯变异函数(GV)矩阵和指数变异函数(EV)矩阵共7个空间加权矩阵应用于SAR模型中。利用普通最小二乘法(OLS)估计BM参数,极大似然法估计3个SAR模型参数,并对4个模型的回归参数进行T检验,对3个SAR模型的自回归参数进行似然比检验。选择Moran’s I(MI)指数比较分析BM、SLM、SDM和SEM 4个模型的残差空间自相关,选择决定系数(R2)、均方根误差(RMSE)和Akaike信息准则(AIC)3个拟合指标比较分析4个模型的拟合效果。【结果】空间加权矩阵SV的BM残差MI值大于1,因此以下结果分析中将不再考虑SV。其他6个空间加权矩阵的BM和SLM残差MI值均显著大于期望值I0,但SLM残差MI值较相同空间加权矩阵的BM残差MI值小。除了GV和ID1外,其他4个空间加权矩阵的SDM残差MI值均与I0差异不显著。除了ID1外,其他5个空间加权矩阵的SEM残差MI值均与I0差异不显著。3个SAR模型的3个拟合指标均优于BM。在相同的空间加权矩阵中,SDM和SEM的3个拟合指标非常接近,但均优于SLM。在SDM和SEM中,不同空间加权矩阵(除GV外)根据3个拟合指标从优至劣的排序为ID2>DT>ID>ID5>EV。无论采用哪个空间加权矩阵,3个SAR模型的回归参数β1均与BM中的β1相似,且均显著不为零。相比β1,SEM和BM中的β0相似,但SDM和SLM中的β0与BM中的β0不相似,并且随着空间加权矩阵的变化而变化。应用于SAR模型的所有空间加权矩阵中,利用ID1得出的自回归参数ρ、γ和λ均明显高于利用其他空间加权矩阵计算的值。GV只有在SEM中才能使自回归参数λ显著。除了GV外,利用其他5个空间加权矩阵得出的ρ、γ和λ均显著。【结论】应用于SAR模型的7个空间加权矩阵中,SV和ID1为不合理的空间加权矩阵。SLM只能降低模型残差的空间自相关,改善模型拟合效果较SDM和SEM差。只要选择合适的空间加权矩阵,SDM和SEM就可以消除模型残差的空间自相关,提高模型拟合效果,其中ID2是最好的空间加权矩阵。利用ID2和SEM构建以树种为哑变量的胸径-树高模型,从而得出基于空间自相关的蒙古栎、杨桦(山杨和白桦)、红松的胸径-树高模型。

基于Richards方程的杉木树高生长模型

利用Richards生长方程构建杉木Cunninghamia lanceolata树高生长模型。以福建省三明市将乐县国有林场杉木人工林为研究对象,基于15块杉木人工林标准地野外调查数据,在分析林分相对胸径(dR)和相对树高(hR)规律的基础上,拟合了胸径-树高曲线、胸径-株数累积(%)曲线以及树高-株数累积(%)曲线。根据林分结构现状,应用SPSS 20统计软件模拟了杉木树高生长模型。结果表明:在95%置信区间内,模型的相关指数达到了0.993,求得参数A=28.606,B=1.094,k=0.031,m=-0.466,且各参数的估计值符合杉木的生长规律。此模型大大提高了林木树高因子的模拟精度,并为实现森林资源的优化配置提供基础数据。

不同造林密度对杂交相思生长的影响

为了找出杂交相思人工林合理的种植密度,以达到较佳经济效益,笔者选用5种不同密度,采用单因素、随机区组设计进行杂交相思密度试验。对经过5年的观测资料进行分析表明:杂交相思不同造林密度对胸径、材积的生长有一定的影响,随着密度增大,胸径、单株材积表现出与密度间的负相关,每公顷833株林分的平均胸径为10.7 cm,每公顷1666株林分的胸径为9.6 cm;每公顷833株和1000株林分的5年生林龄时平均单株材积较高,分别为0.057566和0.05179 m3;5年生每公顷1666株的林分材积为63.9221 m3,分别比其他4种密度林分的高19.0%、52.0%、58.3%和103.3%。造林密度对树高生长无显著影响。