生物量统一模型构建及非线性偏最小二乘辩识——以毛竹为例

树种生物量数据是研究许多林业与生态问题的基础,如何准确估算树种的生物量十分重要,建立生物量模型是生物量估测的主要手段.鉴于常用估算生物量模型具有多样性、经验性、在实际应用中有很大限制等特点,提出利用Chebyshev正交多项式系构建生物量估算统一模型的新思路,这种构建模型的方法有完备的理论基础、统一的模型结构,其实质是一种进行变量区间变换,缩小变量定义域的数值插值方法,模型阶数越高,插入的点越多,估算结果越符合实际,这与树木的树干解析与树木生长原理是相一致的;鉴于常用最小二乘具有的一些缺陷,用适应范围更广的偏最小二乘对统一模型进行参数辩识;指出毛竹生物量的研究与其它树种生物量的研究不同,根据毛竹自身的生长特征,把其生物量的研究分成2个阶段;最后估算了毛竹第1阶段的生物量,结果表明拟合精度很高:当提取55个主成分时,SPRESS,h达到最小,其值为31.4390,R2=0.9987,离差平方和为0.2518,比传统方法估计误差5.623提高了一个数量级.     

黄土高原北部典型灌丛枝条生物量估算模型

于2015年8月末在陕西神木县六道沟小流域采集200个柠条和210个沙柳枝条,测定枝条的基径(D)、长度(H)、含水量(W₀)、鲜质量(W_F)和干质量(W),选用指数函数和异速生长方程建立了4种由枝条形态指标估算枝条生物量的简易模型,并对模型的拟合效果进行验证. 结果表明: 对于柠条和沙柳灌丛,基于D、H二者组合变量(D²H)的异速生长方程是估算枝条生物量的最优模型,该模型经线性转化后可以消除生物量数据的异方差性,且拟合效果最优,决定系数(R²)最大,平均误差(ME)、平均绝对误差(MAE)、总相对误差(TRE)、平均系统误差(MSE)和平均绝对百分误差(MPSE)整体上最小,基本满足生态学研究的精度要求.     

毛竹林地上部分生物量遥感估算模型的可移植性

选择浙江省内临安、安吉、龙泉3个毛竹产区为研究区域,基于野外调查数据和Landsat 5 TM影像,分别建立3个区域的毛竹林生物量遥感估算模型,包括一元线性模型、一元非线性模型、逐步回归模型、多元线性模型和Erf-BP神经网络模型,并对3个区域的模型进行评价;最后,选择精度较好的模型进行移植并对其可移植性进行分析.结果表明:在3个区域,Eff-BP神经网络模型精度均最高,逐步回归模型和一元非线性模型次之.Erf-BP神经网络模型的可移植性最佳.模型类型和模型自变量对统计模型的可移植性有较大影响.     

基于树木起源、立地分级和龄组的单木生物量模型

以马尾松(Pinus massoniana)和落叶松(Larix)的大样本实测资料为建模样本,以独立抽取的样本为验证样本,把样本按起源、立地和龄组进行分级,采用与材积相容的两种相对生长方程,分普通最小二乘和两种加权最小二乘,对地上部分总生物量、地上各部分生物量和地下生物量进行模型拟合和验证,使用决定系数、均方根误差、总相对误差和估计精度等8项统计量对结果进行分析。结果表明:两个树种地上部分总生物量,立地分类方法,模型的拟合结果和适用性都最优;马尾松VAR模型较优,而落叶松CAR模型较好;两种加权最小二乘方法,在建模样本和验证样本中表现得不一致。在建模样本中,加权回归2(权重函数1/f^0.5)略优于加权回归1(权重函数1/y^0.5),但在验证样本中,加权回归1却明显优于加权回归2。而同时满足建模样本拟合结果最优和验证样本检验结果最优的组合中,只有加权回归1。两个树种地上部分各分量生物量,模型拟合结果和适用性,均为干材最优,树叶最差、树枝和树皮居中,样本分类、模型类型和加权最小二乘方法对干材生物量的影响,规律和地上部分总生物量相同;样本分类、模型类型和加权最小二乘方法的最优组合,用验证样本检验的结果,总相对误差树枝不超过±10.0%,树皮不超过±5.0%,树叶马尾松不超过±30.0%,落叶松不超过±20.0%。两个树种地下部分(根)生物量,样本按龄组分类方法,模型拟合结果最优,与材积相容的模型总体上优于与地上部分总生物量相容模型。     

天山雪岭云杉林生物量估测及空间格局分析

雪岭云杉林是新疆天山山脉重要的水源涵养林,精确估算雪岭云杉林生物量及准确表征空间格局特征对其生态系统的生物生产力和生态服务功能的评估具有重要作用。结合Landsat 8 OLI遥感数据和66块天山雪岭云杉林样地调查数据,选择包括各波段灰度值、不同波段灰度值之间的线性和非线性组合(包括5种植被指数)以及环境因子在内的42个自变量,分别采用多元逐步回归分析法、偏最小二乘法和主成分分析法建立天山雪岭云杉林生物量估测模型。结果表明:多元逐步回归法采用3个自变量所建模型平均拟合精度为69.07%,绝对误差为64.50 t/hm²,平均相对误差为10.89%,样地生物量实测值与预测值相关系数为0.465;偏最小二乘回归法采用11个自变量所建模型平均拟合精度为74.36%,绝对误差为144.94 t/hm²,平均相对误差为28.78%,相关系数为0.717;主成分分析方法提取3个主成分,所建模型平均拟合精度为71.22%,相关系数为0.730;因此偏最小二乘法要优于主成分分析法和多元逐步回归法。天山雪岭云杉林生物量随经纬度的增加而降低,整体呈现西部高,中东...     

黄土高原春小麦地上鲜生物量高光谱遥感估算模型

通过田间小区试验,测定了4个春小麦品种(定西24号、陇春8139、高原602和定西38号)在不同生育期和不同种植密度下冠层光谱反射率及其对应的地上鲜生物量,分析了春小麦地上鲜生物量随生育期的变化以及地上鲜生物量与冠层反射光谱和一阶微分光谱之间的相关关系,采用相关系数较大的特征波段及其组合构建光谱特征参数以其作为变量,建立了春小麦地上生物量的高光谱估算模型,并对模型进行检验。结果表明：以参数F₇₈₀和D₇₁₉为变量的对数形式y=3.9498ln F₇₈₀+7.0596和乘幂形式y=512.99D₇₁₉^1.0174估算水平最高,前者均方根误差(RMSE)为0.2173,相对误差(RE)为10.45%,预测值与实测值相关系数为0.854;后者RMSE为0.2188,RE为9.96%,预测值与实测值相关系数为0.853。因此,上述两个模型可作为陇中黄土高原地区春小麦地上鲜生物量的最佳估算模型。     

基于傅里叶变换近红外光谱实时分析1,3-丙二醇发酵过程生物量的在线监测方法

生物量是反映生物发酵过程进展的重要参数,对生物量进行实时监测可用于对发酵过程的调控优化。为克服目前主要采用的离线方法检测生物量时间滞后和人工测量误差较大等缺点,本研究针对1,3-丙二醇发酵过程设计了一个基于傅里叶变换近红外光谱实时分析技术的生物量在线监测实验平台,通过对实时采集光谱预处理以及敏感光谱段分析,应用偏最小二乘算法,建立了1,3-丙二醇发酵过程生物量变化的动态预测模型。以底物甘油浓度为60 g/L和40 g/L的发酵过程作为外部验证实验,分析得到模型的预测均方根误差分别为0.341 6和0.274 3,结果表明所建立的模型具有较好的实时预测能力,能够实现对1,3-丙二醇发酵过程中生物量的有效在线监测。     

基于机载高光谱影像的植被冠层叶绿素反演

利用黑龙江省伊春市带领区凉水国家级自然保护区机载高光谱数据,提取了红边面积、三角形植被指数、归一化植被指数等15个光谱参数,结合坡度、坡向、海拔、郁闭度和植被总盖度5个地理参数,并利用叶绿素计SPAD-502对研究区植被冠层叶绿素相对含量进行同步测量,分析了叶片光谱反射率、反射率的一阶导数及其他变形分别与SPAD值的相关性,采用基于核变换的偏最小二乘原理建立了叶绿素相对含量的估测模型,用该模型对研究区植被冠层叶绿素相对含量进行定量估算.结果表明:当分段数为3、提取的主成分数为10时,所建模型的效果较好,模型决定系数达到0.855,平均绝对百分误差为9.6％,预测精度为89.7％.     

西安市4种城市绿化灌木单株生物量估算模型

以西安市常见的4种绿化灌木(小叶女贞、雀舌黄杨、紫叶小檗、大叶黄杨)为研究对象,利用不同函数和自变量构建单一物种的器官及个体生物量估算模型,筛选出相关性最高、拟合度最好的模型作为生物量最佳估算模型.结果表明： 4种灌木各器官及个体生物量最优估算模型除大叶黄杨叶生物量模型为对数函数(VAR)模型外,其余无论是器官生物量模型还是个体生物量模型均为幂函数(CAR)模型.模型包含的自变量有基径、植株冠幅直径、植株冠幅直径与株高乘积、植冠面积和植冠体积.大叶黄杨和其他3种灌木在自变量选取上有着明显不同.大叶黄杨生物量模型主要以基径为自变量,其他3种灌木生物量模型主要以与冠幅相关的因子为自变量.
     

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。     

Quantification of algal biofilms colonising building materials: chlorophyll a measured by PAM-fluorometry as a biomass parameter

Abstract

The aim of this study was to quantify algal colonisation on anthropogenic surfaces (viz. building facades and roof tiles) using chlorophyll a (chl a) as a specific biomarker. Chl a was estimated as the initial fluorescence F₀ of ‘dark adapted’ algae using a pulse-modulated fluorometer (PAM-2000). Four isolates of aeroterrestrial green algae and one aquatic isolate were included in this study. The chl a concentration and F₀ showed an exponential relationship in the tested range between 0 and 400 mg chl a m^?2. The relationship was linear at chl a concentrations <20 mg m^?2. Exponential and linear models are presented for the single isolates with large coefficients of determination (exponential: r² > 0.94, linear: r² > 0.92). The specific power of this fluorometric method is the detection of initial algal colonisation on surfaces in thin or young biofilms down to 3.5 mg chl a m^?2, which corresponds to an abundances of the investigated isolates between 0.2 and 1.5 million cells cm^?2.     

A novel polyculture growth model of native microalgal communities to estimate biomass productivity for biofuel production

Native polyculture microalgae is a promising scheme to produce microalgal biomass as biofuel feedstock in an open raceway pond. However, predicting biomass productivity of native polycultures microalgae is incredibly complicated. Therefore, developing polyculture growth model to forecast biomass yield is indispensable for commercial-scale production. This research aims to develop a polyculture growth model for native microalgal communities in the Minamisoma algae plant and to estimate biomass and biocrude oil productivity in a semicontinuous open raceway pond. The model was built based on monoculture growth of polyculture species and it is later formulated using species growth, polyculture factor (k_value), initial concentration, light intensity, and temperature. In order to calculate species growth, a simplified Monod model was applied. In the simulation, 115 samples of the 2014–2015 field dataset were used for model training, and 70 samples of the 2017 field dataset were used for model validation. The model simulation on biomass concentration showed that the polyculture growth model with k_value had a root-mean-square error of 0.12, whereas model validation provided a better result with a root-mean-square error of 0.08. Biomass productivity forecast showed maximum productivity of 18.87 g/m²/d in June with an annual average of 13.59 g/m²/d. Biocrude oil yield forecast indicated that hydrothermal liquefaction process was more suitable with a maximum productivity of 0.59 g/m²/d compared with solvent extraction which was only 0.19 g/m²/d. With satisfactory root-mean-square errors less than 0.3, this polyculture growth model can be applied to forecast the productivity of native microalgae.     

白洋淀异养鞭毛虫群落特征及其与环境因子的相关性

于2010年4月至2011年3月调查了白洋淀3个典型湖区表层水体异养鞭毛虫丰度和生物量及环境因子的周年变化,分析了异养鞭毛虫群落与环境因子的相关关系。白洋淀表层水体异养鞭毛虫的丰度和生物量分别介于100-3200 个/mL和35.98-2328.85 μg/L之间,周年平均值分别为1054 个/mL和532.93 μg/L。白洋淀小型异养鞭毛虫(＜7 μm)的丰度占总丰度的47.11%,而生物量只占总生物量的6.82%;中型异养鞭毛虫(约7-14 μm)的丰度占总丰度的37.42%,生物量占总生物量的39.21%;大型异养鞭毛虫(＞14 μm)的丰度虽只占总丰度的15.47%,却贡献了53.97%的生物量。相关性分析表明,异养鞭毛虫丰度与总氮和氨氮呈显著性负相关,与pH值、细菌丰度、纤毛虫丰度及叶绿素a含量呈显著性正相关;异养鞭毛虫生物量与pH值、溶解氧、纤毛虫丰度及叶绿素a含量显著正相关,与总氮、氨氮呈显著负相关。结果表明异养鞭毛虫群落在微食物环中起着枢纽作用。     

Allometric relationships to estimate seasonal above-ground vegetative and reproductive biomass of Vitis vinifera L

A procedure is described for obtaining allometric regression equations to estimate non-destructively and in a cost-effective manner the current year's above-ground vegetative and reproductive biomass of Vitis vinifera L. Merlot' throughout the growing season. Significant relationships were obtained over a 3-year period (1998-2000) between the dimensions of an individual shoot per vine (i.e. diameter and length) and dry weights of its primary stem, primary leaves and lateral growth. The dry mass of a grape was best estimated from measurements of the basal diameter of the bunch peduncle. Introducing cumulative degree-days as an additional explanatory variable in the equations allowed them to be used irrespective of year and growth stage. Multi-year regressions were used to quantify in detail the seasonal evolution of mature grapevine biomass under the climatic conditions of the Bordeaux area, France, and for differing levels of soil nitrogen.     

System identification and parameter estimation in mathematical medicine: examples demonstrated for prostate cancer

We review our studies on how to identify the most appropriate models of diseases, and how to determine their parameters in a quantitative manner given a short time series of biomarkers, using intermittent androgen deprivation therapy of prostate cancer as an example. Recently, it has become possible to estimate the specific parameters of individual patients within a reasonable time by employing the information concerning other previous patients as a prior. We discuss the importance of using multiple mathematical methods simultaneously to achieve a solid diagnosis and prognosis in the future practice of personalized medicine.     

Making sense of parameter estimation and model simulation in bioprocesses

Most articles that report fitted parameters for kinetic models do not include meaningful statistical information. This study demonstrates the importance of reporting a complete statistical analysis and shows a methodology to perform it, using functionalities implemented in computational tools. As an example, alginate production is studied in a batch stirred-tank fermenter and modeled using the kinetic model proposed by Klimek and Ollis (1980). The model parameters and their 95% confidence intervals are estimated by nonlinear regression. The significance of the parameters value is checked using a hypothesis test. The uncertainty of the parameters is propagated to the output model variables through prediction intervals, showing that the kinetic model of Klimek and Ollis (1980) can simulate with high certainty the dynamic of the alginate production process. Finally, the results obtained in other studies are compared to show how the lack of statistical analysis can hold back a deeper understanding about bioprocesses.     

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 comparison of phytoplankton biomass parameters and their interrelation with nutrients in Saronicos Gulf (Greece)

The relationship between total phytoplankton cell number, chlorophyll a, cell volume, and the response of these parameters to reactive phosphorus and nitrate in surface waters of Saronicos Gulf (Greece) was examined using simple and partial correlation statistics. Different conclusions could be drawn as to the comparability between biomass parameters and their interrelation with nutrients. Partial correlation analysis is considered to be a better method for comparing ecological data. The analysis of phytoplankton abundance should include determinations of as many biomass characteristics as possible since each has its own specificity.     

黄土高原典型草原地上生物量估测模型

为了寻求有效的草地地上生物量估测方法和精确估测黄土高原典型草原草原地上生物量。于2014年8月中旬,在黄土高原典型草原草原地上生物量达到最大值,分别从单株水平和种群水平进行野外调查。以株高(H)和盖度(C)的复合因子(C×H)为自变量,通过回归分析,建立地上生物量估测模型,采用留一法对其精确性进行评估;并通过校正系数以及群落总生物量估测值和实测值比较单株水平和种群水平所建模型的精确性。结果表明:黄土高原典型草原草地,无论在单株水平还是种群水平,线性和幂函数对该区域生物量的拟合效果更好。估测模型检验结果表明,在单株水平各个物种的生物量估测值与实测值相关性较好,均达到了显著水平(P0.05),其r值均大于0.6,总相对误差RS均小于10%,平均相对误差绝对值RMA(average absolute value of relative error)均小于30%,总生物量的实测值与估测值比较接近,校正系数均接近1;而在种群水平上,虽然各物种的生物量估测值与实测值相关性均达到了显著水平(P0.05),但多数物种平均相对误差绝对值RMA大于30%,总相对误差RS(total relative error)均大于10%,总生物量的估测值均大于实测值,校正系数均偏离了1,说明在黄土高原典型草原通过单株水平建立的物种生物量估测模型的精度优于种群水平建立的物种生物量估测模型的精度。