含度量误差的黑龙江省主要树种生物量相容性模型

基于516株样木的生物量数据,采用非线性度量误差模型理论和方法,构建了黑龙江省15个主要树种(组)总生物量与地上、地下、树干、树冠、树枝、树叶6个分项生物量以及分项生物量间的相容性生物量模型,分别选出各树种总生物量和各分项生物量的最优模型,采用比值函数分级联合控制方程组构建了以总生物量为基础的相容性模型,并采用对数变换对总生物量模型消除异方差,采用加权回归对各分项生物量模型消除异方差.结果表明:本文所建的15个树种(组)相容性生物量模型中,总生物量的预估精度最高,达到90％以上;其次是地上部分生物量和树干生物量,预估精度在87.5％以上;地下部分、树冠、树枝和树叶生物量的预估精度相对较低,但绝大多数树种(组)的预估精度在80％以上;所有树种(组)总生物量、地上部分生物量、树干生物量模型的模拟效率(EF)值达0.9以上,绝大多数树种(组)的地下部分、树冠、树枝、树叶生物量模型的EF值在0.8以上.     

不同林分起源的相容性生物量模型构建

目前为止已有不同方法构建生物量相容性模型,但不同林分起源的生物量相容性模型很少报道。针对此问题,以150株南方马尾松(Pinus masson iana)地上生物量数据为例,利用比例平差法和非线性联立方程组法建立不同起源地上生物量以及干材、干皮、树枝和树叶各分项生物量相容的通用性模型。根据分配层次不同,两种方法又各自考虑总量直接控制和分级联合控制两种方案。从直径、树高、地径、枝下高和冠幅5个林分变量中选取不同的变量构建一元、二元和三元生物量模型,并利用加权最小二乘回归法消除生物量模型中存在的异方差性。结果为:比例平差法和非线性联立方程组法都能有效保证各分项生物量总和等于总生物量,模型预测精度满足要求。总体而言,非线性联立方程组方法比比例平差方法精度高,同时两种方法中总量直接控制法比分级联合控制法预测效果好;各分项生物量模型本身作为权函数能有效消除异方差;各分项对应的三元生物量模型预测精度最高,其次是二元生物量模型,最低是一元生物量模型,但这些差异不是很大。总之,为权衡考虑模型预测精度和调查成本,建议把直径和树高作为协变量利用总量直接控制非线性联立方程组法对不同起源生物量建模。     

湿地翅碱蓬生物量遥感估算模型

以黄河三角洲HJ-1A CCD遥感数据和滨海湿地翅碱蓬生物量实测数据为数据源,通过对比分析参数回归模型（单变量线性和非线性回归模型,多元线性逐步回归模型）和人工神经网络模型（BP网络、RBF网络、GRNN网络）,构建黄河三角洲湿地翅碱蓬生长初期的生物量湿重遥感估算最优模型。研究表明：基于遥感信息变量能够建立生长初期翅碱蓬生物量湿重估算模型。尽管基于RDVI、MSAVI和PC2的3个变量的多元线性回归模型的拟合效果较优,但是以SAVI、MSAVI、RVI、DVI、RDVI和PC2等7个遥感信息变量构建的BP神经网络模型的精度更高,平均相对误差为12.73%,估算效果最优,能够满足较高精度的生物量湿重估算需求。翅碱蓬生长初期生物量湿重最优估算模型的建立,为滨海地区植被生物量监测、区域翅碱蓬生物量季节动态模拟以及黄河三角洲生态系统功能评价提供技术支持与基础。     

人工神经网络与相容性生物量模型预测单木地上生物量的比较

森林生物量是林业生产经营和森林资源监测的重要指标,为探索高效低偏的单木生物量估测方法,引入人工神经网络.本研究采用黑龙江省东折棱河林场的101株长白落叶松地上生物量数据,基于不同变量(胸径、树高、冠幅)组合建立了4个聚合模型体系(AMS),采用加权回归消除模型的异方差.然后,基于最优的变量组合建立人工神经网络(ANN)...     

Landscape Habitat Suitability Index Software

ABSTRACT Habitat suitability index (HSI) models are traditionally used to evaluate habitat quality for wildlife at a local scale. Rarely have such models incorporated spatial relationships of habitat components. We introduce Landscape HSImodels, a new Microsoft Windows® (Microsoft, Redmond, WA)—based program that incorporates local habitat as well as landscape-scale attributes to evaluate habitats for 21 species of wildlife. Models for additional species can be constructed using the generic model option. At a landscape scale, attributes include edge effects, patch area, distance to resources, and habitat composition. A moving window approach is used to evaluate habitat composition and interspersion within areas typical of home ranges and territories or larger. The software and sample data are available free of charge from the United States Forest Service, Northern Research Station at http:www.nrs.fs.fed.ushsi .     

青藏高原典型人工林幼树生物量模型构建

森林生物量计算是全球碳储量估算的基础,现已纳入全球国家森林清单项目。普遍的森林碳汇计量采用的材积源生物量法针对胸径5 cm以上的树木,幼树(胸径<6 cm,树高>0.3 m)的碳汇量并未被完整计入其中,导致生态系统碳汇能力被低估。基于青藏高原137株5种典型人工林幼树的实测生物量数据,以地径代替胸径作为预测变量,采用加权广义最小二乘法建立独立生物量模型,选择比例总量直接控制及代数和控制2种结构形式的相容性生物量模型,并通过加权非线性似乎不相关回归进行方程组估算,建立了整株及各组分的相容性生物量方程。结果表明: 二元相容性模型优于一元以及独立模型,对整株生物量来说,R²达到0.90～0.99,两种相容性模型对于不同树种来说各有优势但精度差距可以忽略,从林业生产实践角度考虑,比例总量直接控制生物量模型更有实践意义,从遥感技术的变量提取角度考虑,本研究构建了更适于遥感估算的幼树生物量模型,其整体上拟合精度高,可以准确地进行类似气候环境中的幼树整株和各组分生物量的估算。     

Testing the generality of above‐ground biomass allometry across plant functional types at the continent scale

Accurate ground‐based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost‐effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above‐ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power‐law models explained 84–95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand‐based biomass from allometric models of varying levels of generalization (species‐specific, plant functional type) were validated using whole‐plot harvest data from 17 contrasting stands (range: 9–356 Mg ha^?1). Losses in efficiency of prediction were <1% if generalized models were used in place of species‐specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand‐level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost‐effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species‐specific models is only warranted when gains in accuracy of stand‐based predictions are relatively high (e.g. high‐value monocultures).     

白桦和水曲柳树干温度日变化的空间变异及其影响因子

植物温度是森林生态系统能量平衡和植被呼吸估算的重要参数.采用T型热电偶监测树皮和木材特性各异的2个阔叶树种(白桦和水曲柳)不同深度、高度和方位的树干温度(T_s),探索T_s日变化的空间变异及其影响因素.结果表明: T_s月平均日变化格局与空气温度呈相似的正弦曲线,但T_s变化滞后于空气温度,时滞从树皮表面处的0 h增加到6 cm深度处的4 h.随测定深度的增加和高度的降低,T_s日变化的峰值和日较差均逐渐减小.T_s周向差异不大,休眠季节白天南向、西向T_s日峰值略高.两树种树皮和木材的热学特性(比热容和导热系数)的差异,会通过影响树干表面与外界的热交换和树干内部热扩散而造成T_s径向变化的种间差异.白桦树皮较高的反射率削弱了太阳辐射对T_s的影响.多元逐步回归分析表明,环境因子可以很好地估测T_s日动态(R²>0.85),影响程度依次为空气温度>水汽压>净辐射>风速.估算生物量热储和树干表面CO₂通量时应考虑T_s径向、纵向和种间差异.     

Reanalysis of Models and an Improved Model of Biomass Size Spectra

Our reanalysis aimed at understanding the regularity in empirical biomass size spectra (BSS) suggests that the construction of BSS depends of the size interval and size scales used and different definitions of BSS in literature are therefore very different. Existing empirical models of BSS can be fitted perfectly to the observed data, but the biological basis of the fitted parameters is not explained and comparison and interpretation of the findings is therefore difficult. Parameters of mechanistic models of BSS have a biological background and are interpretable. Discrete mechanistic models based on Lindeman's trophic chain theory assume a constant ratio of size (or body mass) in two adjacent trophic levels. However, this biomass ratio is not comparable with that in two adjacent (logarithmic) size intervals in the measured biomass size spectra. The continuous model by Thiebaux and Dickie (1992) is based on the discrete model by Boudreau et al. (1991). We show how the validity of the transformation of a discrete form into a continous form depends on the size ranges of prey and predator population. The model by Platt and Denman (1977) does not represent a continuous formulation due to the use of normalized biomass defined in logarithmic size intervals. We suggest to eliminate the use of trophic levels and normalized biomass. On the basis of the reanalysis we formulate and improved continuous model based on the model by Silvert and Platt (1978). The model is based on Eulerian strategy which appears more adequate for the problem than the previously used Lagrangian strategy. The model appears to be able to demonstrate the regularity in observed BSS.     

A dynamic global vegetation model for use with climate models: concepts and description of simulated vegetation dynamics

Changes in vegetation structure and biogeography due to climate change feedback to alter climate by changing fluxes of energy, moisture, and momentum between land and atmosphere. While the current class of land process models used with climate models parameterizes these fluxes in detail, these models prescribe surface vegetation and leaf area from data sets. In this paper, we describe an approach in which ecological concepts from a global vegetation dynamics model are added to the land component of a climate model to grow plants interactively. The vegetation dynamics model is the Lund–Potsdam–Jena (LPJ) dynamic global vegetation model. The land model is the National Center for Atmospheric Research (NCAR) Land Surface Model (LSM). Vegetation is defined in terms of plant functional types. Each plant functional type is represented by an individual plant with the average biomass, crown area, height, and stem diameter (trees only) of its population, by the number of individuals in the population, and by the fractional cover in the grid cell. Three time‐scales (minutes, days, and years) govern the processes. Energy fluxes, the hydrologic cycle, and carbon assimilation, core processes in LSM, occur at a 20 min time step. Instantaneous net assimilated carbon is accumulated annually to update vegetation once a year. This is carried out with the addition of establishment, resource competition, growth, mortality, and fire parameterizations from LPJ. The leaf area index is updated daily based on prevailing environmental conditions, but the maximum value depends on the annual vegetation dynamics. The coupling approach is successful. The model simulates global biogeography, net primary production, and dynamics of tundra, boreal forest, northern hardwood forest, tropical rainforest, and savanna ecosystems, which are consistent with observations. This suggests that the model can be used with a climate model to study biogeophysical feedbacks in the climate system related to vegetation dynamics.     

Separating Pharmacokinetic and Pharmacodynamic Components in Empirical Adjustment Factor Distributions

For a particular chemical, one can treat the chemical-by-chemical variation in relative doses for equal toxicity in experimental animals and humans as a characterization of the likelihoods of extrapolation factors of different magnitudes. An emerging approach to noncancer risk assessment is to use such empirical distributions in place of fixed Uncertainty Factors. This paper discusses dividing the overall variation into two sub-distributions representing pharmacokinetic (PK) and pharmacodynamic (PD) contributions to the variation among chemicals in the animal-to-human toxicologically equivalent dose. If a physiologically based pharmacokinetic model (PBPK model) is used to derive a compound specific adjustment factor (CSAF) for the pharmacokinetic component, the deconvolution of the PK and PD components allows one to remove the PK component (to be replaced with the CSAF), while retaining the uncertainty in pharmacodynamics that PBPK models do not address. One must then add back the uncertainty in the PBPK determination of the CSAF (which may be considerable). A candidate criterion for whether one can use an uncertain PBPK model is whether the generic uncertainty about cross-species pharmacokinetics (reflected in the PK component of the overall empirical distribution) is larger than the chemical-specific uncertainty in the determination of kinetically equivalent doses in experimental animals and humans.     

META-X: Generic Software for Metapopulation Viability Analysis

The major tools used to make population viability analyses (PVA) quantitative are stochastic models of population dynamics. Since a specially tailored model cannot be developed for every threatened population, generic models have been designed which can be parameterised and analysed by non-modellers. These generic models compromise on detail so that they can be used for a wide range of species. However, generic models have been criticised because they can be employed without the user being fully aware of the concepts, methods, potentials, and limitations of PVA. Here, we present the conception of a new generic software package for metapopulation viability analysis, META-X. This conception is based on three elements, which take into account the criticism of earlier generic PVA models: (1) comparative simulation experiments; (2) an occupancy-type model structure which ignores details of local population dynamics (these details are integrated in external submodels); and (3) a unifying currency to quantify persistence and viability, the intrinsic mean time to extinction. The rationale behind these three elements is explained and demonstrated by exemplary applications of META-X in the three fields for which META-X has been designed: teaching, risk assessment in the field, and planning. The conception of META-X is based on the notion that PVA is a tool to deal with rather than to overcome uncertainty. The purpose of PVA is to produce relative, not absolute, assessments of extinction risk which support, but do not supplant, management decisions.     

A gradient model of cardiac pacemaker myocytes

We have formulated a spatial-gradient model of action potential heterogeneity within the rabbit sinoatrial node (SAN), based on cell-specific ionic models of electrical activity from its central and peripheral regions. The ionic models are derived from a generic cell model, incorporating five background and exchange currents, and seven time-dependent currents based on three- or four-state Markov schemes. State transition rates are given by non-linear sigmoid functions of membrane potential.

By appropriate selection of parameters, the generic model is able to accurately reproduce a wide range of action potential waveforms observed experimentally. Specifically, the model can fit recordings from central and peripheral regions of the SAN with RMS errors of 0.3987 and 0.7628 mV, respectively. Using a custom least squares parameter optimisation routine, we have constructed a spatially-varying gradient model that exhibits a smooth transition in action potential characteristics from the central to the peripheral region, whilst ensuring individual membrane currents remain physiologically accurate. Smooth transition action potential characteristics include maximum diastolic potential, overshoot potential, upstroke velocity, action potential duration and cycle length. The gradient model is suitable for developing higher dimensional models of the right atrium, in which action potential heterogeneity within nodal tissue may be readily incorporated.     

基于森林调查数据的长白山天然林森林生物量相容性模型

森林生物量估算是进行陆地生态系统碳循环和碳动态分析的基础,但现有估测模型存在着总量与分量不相容的问题.本文以吉林省汪清天然林区为例,提出了基于森林调查的相容性森林生物量模型设计思想,并采用联立方程组为不同森林群落构造了一系列引入林分蓄积因子的相容性生物量模型,得到的预估精度较高.其中,针叶林、阔叶林和针阔混交林群落的森林生物量模型预估精度均在95%以上,基本上解决了森林生物量模型的相容性问题.     

A semimechanistic model predicting the growth and production of the bioenergy crop Miscanthus×giganteus: description, parameterization and validation

Biomass based bioenergy is promoted as a major sustainable energy source which can simultaneously decrease net greenhouse gas emissions. Miscanthus × giganteus ( M. × giganteus ), a C₄ perennial grass with high nitrogen, water, and light use efficiencies, is regarded as a promising energy crop for biomass production. Mathematical models which can accurately predict M. × giganteus biomass production potential under different conditions are critical to evaluate the feasibility of its production in different environments. Although previous models based on light-conversion efficiency have been shown to provide good predictions of yield, they cannot easily be used in assessing the value of physiological trait improvement or ecosystem processes. Here, we described in detail the physical and physiological processes of a previously published generic mechanistic eco-physiological model, WIMOVAC, adapted and parameterized for M. × giganteus . Parameterized for one location in England, the model was able to realistically predict daily field diurnal photosynthesis and seasonal biomass at a range of other sites from European studies. The model provides a framework that will allow incorporation of further mechanistic information as it is developed for this new crop.     

Variable selection and model choice in geoadditive regression models

Summary .  Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.     

大兴安岭东部主要林分类型乔木层生物量估算模型

大尺度森林生物量的估算方法是人们目前关注的焦点,建立林分生物量模型成为一种趋势.本研究以大兴安岭东部6个主要林分类型为研究对象,构建了其总量及各分项一元、二元可加性林分生物量模型.采用似然分析法判断总量及各分项生物量异速生长模型的误差结构(可加型或相乘型),采用非线性似乎不相关回归模型方法估计模型参数.结果表明: 经似然分析法判断,大兴安岭东部6个主要林分类型总量及各分项生物量异速生长模型的误差结构都是相乘型的,对数转换的可加性生物量可以被选用.各林分类型可加性生物量模型的调整后确定系数为0.78～0.99,平均相对误差为-2.3%～6.9%,平均相对误差绝对值6.3%～43.3%.增加林分平均高可以提高绝大多数生物量模型的拟合效果和预测能力,而且总量、地上和树干生物量模型效果较好,树根、树枝、树叶和树冠生物量模型效果较差.为了使模型参数估计更有效,所建立的生物量模型应当考虑林分总生物量及各分项生物量的可加性.本研究建立的林分总量与各分项生物量模型都能对大兴安岭东部6个主要林分类型生物量进行较好的估计.     

Variance Component Estimation for Mixed Model Analysis of cDNA Microarray Data

Microarrays provide a valuable tool for the quantification of gene expression. Usually, however, there is a limited number of replicates leading to unsatisfying variance estimates in a gene‐wise mixed model analysis. As thousands of genes are available, it is desirable to combine information across genes. When more than two tissue types or treatments are to be compared it might be advisable to consider the array effect as random. Then information between arrays may be recovered, which can increase accuracy in estimation. We propose a method of variance component estimation across genes for a linear mixed model with two random effects. The method may be extended to models with more than two random effects. We assume that the variance components follow a log‐normal distribution. Assuming that the sums of squares from the gene‐wise analysis, given the true variance components, follow a scaled χ²‐distribution, we adopt an empirical Bayes approach. The variance components are estimated by the expectation of their posterior distribution. The new method is evaluated in a simulation study. Differentially expressed genes are more likely to be detected by tests based on these variance estimates than by tests based on gene‐wise variance estimates. This effect is most visible in studies with small array numbers. Analyzing a real data set on maize endosperm the method is shown to work well. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Modelling of reserve carbohydrate dynamics, regrowth and nodulation in a N2-fixing tree managed by periodic prunings

We used a modified transport resistance approach to model legume tree growth, nodulation and dynamics of reserve carbohydrates after pruning. The model distributes growth between roots and shoots applying the transport resistance approach. Within shoots, growth is divided into leaves, branches and stems applying the pipe model theory. The model also accounts for the metabolic differences of principal N sources, nitrate, ammonium and atmospheric dinitrogen, in a mechanistic way. We compared the simulation results with measured biomass dynamics of Gliricidia sepium (Jacq.) Walp. (Papilionaceae: Robinieae) under humid and subhumid tropical conditions. Comparison showed that the biomass production predicted by the model is close to measured values. Total N₂ fixation is also similar to measured values. Qualitatively the model increases the proportion of N₂ fixation if roots acquire less mineral N. In the present study, the general form of the model is discussed and compared with similar models. The results encourage the use of this approach for studying biomass dynamics of legume trees under the scheme of periodic prunings. Also, it shows that process‐based models have potential in the simulation of trees disturbed by prunings, herbivory or similar factors.     

Bi-trophic food chain dynamics with multiple component populations

Food web models describe the patterns of material and energy flow in communities. In classical food web models the state of each population is described by a single variable which represents, for instance, the biomass or the number of individuals that make up the population. However, in a number of models proposed recently in the literature the individual organisms consist of two components. In addition to the structural component there is an internal pool of nutrients, lipids or reserves. Consequently the population model for each trophic level is described by two state variables instead of one. As a result the classical predator-prey interaction formalisms have to be revised. In our model time budgets with actions as searching and handling provide the formulation of the functional response for both components. In the model, assimilation of the ingested two prey components is done in parallel and the extracted energy is added to a predators reserve pool. The reserves are used for vital processes; growth, reproduction and maintenance. We will explore the top-down modelling approach where the perspective is from the community. We will demonstrate that this approach facilitates a check on the balance equations for mass and energy at this level of organization. Here it will be shown that, if the individual is allowed to shrink when the energy reserves are in short to pay the maintenance costs, the growth process has to be 100% effective. This is unrealistic and some alternative model formulations are discussed. The long-term dynamics of a microbial food chain in the chemostat are studied using bifurcation analysis. The dilution rate and the concentration of nutrients in the reservoir are the bifurcation parameters. The studied microbial bi-trophic food chain with two-component populations shows chaotic behaviour.