浅析云南松根径与胸径数学模型建立及应用

通过对云南松树种根径与胸径的数学模型建立,数学模型分析与相关关系显著性检验,结果表明,根径与胸径存在着密切、显著性的直线回归关系,所建立的数学模型是成立的、可应用的。从而为以根径推算胸径并配合一元立木材积表计算立木材积提供一种途径,其数学模型应用到林木盗伐案件处理中,为司法量刑提供依据。     

杉木天然林林木地径与胸径的关系研究——以福建五一国有林场为例

对福建省五一国有林场杉木天然林地径与胸径进行回归分析,建立了回归模型。结果表明:地径与胸径间存在着密切、显著的线性关系,回归模型的拟合优度和误差均很理想。研究结果为计算杉木材积提供了一个方便可行的方法。     

浅析吕梁山南段天然油松林林木根径与胸径关系模型

文章以吕梁山南段天然油松林林木根径与胸径的调查数据作为依据,分析研究根径与胸径之间存在的关系,建立回归模型,为本区域天然油松资源的调查监测、林业经营、司法案件的鉴定评估等提供可行的技术支撑。     

桂东区杉木地径与胸径、树高、材积相关分析

利用广西昭平县2009年二类调查控制样点的数据中的杉木的地径和胸径、树高为样本数据,并通过SPSS统计分析软件和数理统计知识,对地径与胸径、树高和材积的相关关系进行分析,分别建立地径与胸径、地径与材积的相关关系或曲线回归模型,最后选出最优模型,从而可利用模型由地径推算胸径和材积。结果表明,地径与树高存在显著正相关性,且地径6~20 cm径阶与胸径之间最佳的回归模型为D1.3=-0.199+0.851D地,地径22~40 cm径阶与胸径之间回归模型为D1.3=-1.652+0.913D地,精度是98.7%;同时地径与胸径也存在显著的正线性相关性,地径与材积的回归模型为V=0.000 082D地2.486 79,精度为95.2%。本次所建立的模型精度在允许范围内,可应用到实际中。     

山西省天然油松林根径立木材积表的编制

通过采集山西省天然油松林的根径、胸径样本数据，依据《根径立木材积表编制技术规程》的技术要求，利用数理统计和回归关系建立天然油松林根径-胸径数学模型，同时进行数学模型检验，最后建立根径材积表，以达到支持生产的目的。     

椴树胸径 根径和立木材积相关关系的研究

通过利用椴树（ＴａｌｉａＳＰ．）的胸径和立木材积、根径和立木材积间的相关性，运用回归分析的方法建立了回归方程，经过选择，确定了各自的合理模型，为了克服材积方程异方差性的影响，采用加权最小二乘法估计了模型的参数，找到了胸径和立木材积、根径和立木材积的最佳模型，提高了材积方程的适用精度。     

冀中南平原速生杨胸径与地径关系的研究

该文利用107速生杨的地径、胸径资料,通过SAS统计分析软件和数理统计知识,对地径与胸径的相关关系进行分析,建立了冀中南平原地区速生杨胸径与地径的关系模型。结果表明:速生杨胸径与地径存在显著正相关性,可采用直线方程进行模拟,回归模型为D1.3=0.8498D0.03-1.1847,模型精度在允许范围内,可应用到实际中。在此基础上,可以通过测量速生杨地径换算成胸径,从而达到估算林木材积的目的,为冀中南地区速生杨采伐后通过地径估算林木材积提供理论依据,具有十分重要的生产实践意义。     

落叶松等根径立木材积表的编制与应用

利用不同林分条件的解析木资料，通过数理统计回归计算，对落叶松、油松、柞树建立根径与胸径、胸径与树高关系式，按林木3个树高等级，即把林地及林分条件划分3个等级，编制成根径立木材积表。此表将为审核采伐林木蓄积提供科学依据。     

水杉人工林生物量模型的研究

在水杉人工林中选择林分结构、林龄相同的标准地进行调查,按径阶选择8株标准木,测定每株标准木的胸径、树高、叶面积和各部分的生物量。应用相对生长分析法,通过多元筛选建立了水杉人工林各器官间相互关系的模型。单株D~2H 和叶面积呈一元线性回归关系,与生物量间呈幂函数回归关系;单株胸径和生物量呈一元线性回归关系;不同高度与含水量间呈二次函数关系。这些模型的建立,为分析林分结构,评价光合生产能力,探讨水杉人工林的生物量分布规律提供了依据。     

利用误差变量联立方程组建立南方杉木一元立木材积模型和胸径地径回归模型

利用我国南方的杉木实测数据,采用误差变量联立方程组方法,同时建立了胸径一元材积模型、地径一元材积模型和胸径—地径回归模型。结果表明:地径与胸径之间相关紧密,其回归模型的确定系数可以达到0.96以上;地径一元材积模型的预估精度要明显低于胸径一元材积模型。     

河北省主要树种单木和林分生长率模型研建

利用第六次至第九次全国森林资源清查河北省2001,2006,2011,2016年4个年度的固定样地调查数据,采用非线性回归估计方法,建立了18个树种组的单木胸径生长率和材积生长率模型,以及12个树种组的林分材积生长率模型。结果表明,单木生长率模型的平均预估误差(MPE)基本都在3%以内,而平均百分标准误差(MPSE)、胸径生长率模型大都在10%以内,材积生长率模型大都在20%左右;林分生长率模型的平均预估误差(MPE)基本都在5%以内,平均百分标准误差(MPSE)大都在25%以内。所建模型可为河北省开展森林资源年度更新提供技术支撑。     

Biomass,stem basic density and expansion factor functions for five exotic conifers grown in Denmark

Adequate allometric equations are needed for estimating carbon pools of fast growing tree species in relation to international reporting of CO₂ emissions and for assessing their possible contribution to increasing forest biomass resources. We developed models for predicting biomass, stem basic density and expansion factors of stem to above-ground biomass for five fast growing conifers. Data included destructive measurements of 236 trees from 14 sites, covering a wide range of growth conditions. To ensure model efficiency, models for predicting stem, crown and total above-ground biomass for the five species were estimated simultaneously using a linear, mixed effects model that allowed contemporaneous correlations between the different tree components. Models differed among species and included dbh and tree height. The models explained more than 98% of the variation in above-ground biomass and reflected differences in the allometry between tree species. Stem density differed among species but generally declined with increasing site index and dbh. The overall model for predicting stem basic density included dbh, H₁₀₀ and site index and explained 66% of the total variation. Expansion factors decreased from 1.8–2.0 in small trees (dbh < 10 cm) to 1.1–1.2 for large trees (dbh > 25 cm), but differed among species. The overall model explained 86% of the variation and included quadratic mean diameter and dbh.     

Relationships between diameter and height of trees in natural tropical forest in Tanzania

The relationship between tree height (h) and tree diameter at breast height (dbh) is an important element describing forest stands. In addition, h often is a required variable in volume and biomass models. Measurements of h are, however, more time consuming compared to those of dbh, and visual obstructions, rounded crown forms, leaning trees and terrain slopes represent additional error sources for h measurements. The aim of this study was therefore to develop h–dbh relationship models for natural tropical forest in Tanzania. Both general forest type specific models and models for tree species groups were developed. A comprehensive data set with 2 623 trees from 410 different tree species collected from a total of 1 191 plots and 38 sites covering the four main forest types of miombo woodland, acacia savanna, montane forest and lowland forests was applied. Tree species groups were constructed by using a k-means clustering procedure based on the h–dbh allometry, and a number of different non-linear model forms were tested. When considering the complexity of natural tropical forests in general and in particular variations of h–dbh relationships due to high species diversity in such forests, the model fit and performance were considered to be appropriate. Results also indicate that tree species group models perform better than forest type models. Despite the fact that the residual errors level associated with the models were relatively high, the models are still considered to be applicable for large parts of Tanzanian forests with an appropriate level of reliability.     

闽中山地湿地松不同立地条件和不同密度的经营效果研究

通过对21、22年生的闽中湿地松人工林不同造林密度和不同立地条件的生长效果研究,结果表明:坡位、表土层厚度对优势木树高有显著影响,但对林分平均树高无显著影响;坡向(阴、阳坡)对平均胸径存在显著差异,且阳坡明显优于阴坡。不同经营密度的林分平均胸径、单株材积差异显著,且随密度增大而减少;冠幅随密度增大而减少;在合理密度范围内,单株胸径、材积随密度增大而减少,但蓄积量却随密度增加而增大。     

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.     

基于树高和树冠因子的立木材积模型研究

[目的]由于激光雷达技术已经能准确测定立木树高及相关树冠因子,应用该技术建立基于树高和树冠因子的立木材积模型,为激光技术在森林蓄积估计中提供技术支撑.[方法]利用云杉、冷杉、栎树、桦树4个树种组的3 010株实测样木数据,分析了立木材积与胸径、树高、树冠因子之间的相关关系;并通过对数回归方法构建了基于树高和树冠因子的立木材积模型,用确定系数R²和平均预估误差MPE等6项指标对模型进行评价.[结果]表明,立木材积与单一因子之间的相关,以胸径最为紧密,其次是树高,再次是冠长和冠幅.基于树高和树冠因子的立木材积模型中,以树高和冠幅作为解释变量的二元模型效果较好,再增加冠长因子的三元模型改进不大.云杉、冷杉、栎树、桦树4个树种组基于树高冠幅的立木材积模型,其R²分别为0.81、0.80、0.76和0.77,MPE分别为4.7%、5.3%、5.4%和5.3%,模型预估精度均能达到95%左右.[结论]本文对材积与林木因子之间相关关系的定量分析,建立了云杉、冷杉、栎树、桦树4个树种的立木材积模型,模型预估精度高.为激光雷达技术定量估测森林参数提供了依据.     

Total tree,merchantable stem and branch volume models for miombo woodlands of Malawi

The objective of this study was to develop general (multispecies) models for prediction of total tree, merchantable stem and branch volume including options with diameter at breast height (dbh) only, and with both dbh and total tree height (ht), as independent variables. The modelling data set was based on destructively sampled trees and comprised 74 trees from 33 tree species, collected from four forest reserves located in different ecological zones of Malawi. The dbh and ht ranges for the data set were 5.3–111.2?cm and 3.0–25.0?m, respectively. A number of alternative model forms were tested and the final model selection was based on root mean square error (RMSE) values calculated using a leave-one-out cross-validation procedure. The model performances and the evaluations of the finally selected models (R? 2 range 0.72 to 0.92; RMSE range 38% to 71%; mean prediction errors range ?1.4% to 1.3%) suggest that all models can be used over a wide range of geographical and ecological conditions in Malawi with an appropriate accuracy in predictions. The appropriateness of the developed models was also supported by the fact that the mean prediction errors of these models were much lower than the mean prediction errors (range ?23.6% to 48.9%) of some previously developed models tested on our data.     

Long-term growth analyses of Japanese cedar trees in a plantation: neighborhood competition and persistence of initial growth deviations

The individual growth of tree diameter at breast height (dbh) is analyzed in an even-aged plantation of Cryptomeria japonica from stand age of 45 to 94 years, to examine how the growth of individual trees has been affected by the changes in spacing resulting from thinning operations. At any age, a significant proportion (0.37–0.46) of the variation in dbh growth during a 5–11-year period was explained by dbh at the beginning of the period, probably due to greater leaf mass of larger trees. Next, either one-sided or two-sided competition was added to the model, by calculating the basal area (BA) of neighboring trees around each tree within a given radius or BA for trees having larger dbh than the focal tree within the radius. After preliminary analyses, a radius of 8 m was selected as the critical range for tree competition. Although both types of competition explained a significant proportion (0.09–0.43) of growth variation, one-sided competition was not significant at ages greater than 54 years. Based on the model at 45 years of age, the initial deviation of growth rate for each tree from the predicted rate was calculated and added to the models as a third variable. This raised the coefficient of determination up to 0.50–0.74. These findings have practical significance for forest plantation management, particularly for controlling the growth of standing trees via thinning, to produce high-quality timber in the future.     

A flexible regression model for diameter prediction

We present a functional regression model for diameter prediction. Usually stem form is estimated from a regression model using dbh and height of the sample tree as predictor. With our model additional diameter observations measured at arbitrary locations within the sample tree can be incorporated in the estimation in order to calibrate a standard prediction based on dbh and height. For this purpose, the stem form of a sample tree is modelled as a smooth random function. The observed diameters are assumed as independent realizations from a sample of possible trajectories of the stem contour. The population average of the stem form within a given dbh and height class is estimated with the taper curves applied in the national forest inventory in Germany. Tree deviation from the population average is modelled with the help of a Karhunen–Loève expansion for the random part of the trajectory. Eigenfunctions and scores of the Karhunen–Loève expansion are estimated through conditional expectations within the methodological framework of functional principal component analysis (FPCA). In addition to a calibrated estimation of the stem form, FPCA provides asymptotic pointwise or simultaneous confidence intervals for the calibrated diameter predictions. For the application of functional principal component analysis modelling the covariance function of the random process is crucial. The main features of the functional regression model are discussed informally and demonstrated by means of practical examples.     

Red-tree vole habitat suitability modeling: Implications for conservation and management

In the Pacific Northwest, USA, red-tree voles (Arborimus longicaudus) are of conservation and management interest owing to their apparent association with late-seral forests and the relatively small extent of such forests, largely a function of timber harvest, fire, and conversion of forests to non-forest uses during the past century. We created and evaluated a series of red-tree vole habitat association models, and applied the best model to evaluate tree vole habitat quality within and outside of reserves throughout most of their range in Oregon and northern California. We modeled presence and absence of tree vole nests across a gradient of biotic, abiotic, and spatial features; and within and outside of reserves. The best model included spatial coordinates, percent slope, basal area of trees with diameter at breast height (dbh) between 45 and 90 cm, maximum tree dbh, and standard deviation of conifer dbh. Plots with tree vole nests contained many late-seral/old-growth forest attributes such as large diameter, older, and variably sized trees. Evaluation of the best model, including rigorous cross-validation, showed the model to be statistically robust and to have very good/excellent predictive ability. Reserves had significantly higher mean habitat quality than non-reserved lands, and reserves had much more high quality habitat than non-reserves.