广西英罗港红树植物群落的非线性排序

采用主分量分析 (PCA)、无偏主分量 (DPC)和非度量多维调节 (NMDS)等方法对广西英罗港 2 2个红树植物群落样地进行了排序。PCA和 DPC分析结果表明 ,取样数据具有明显的非线性结构。通过 NMDS分析 ,得到二维 NMDS排序格局 ,它能较好地反映了红树植物群落与环境因子之间的相互关系。     

青海湖北岸植物群落与环境因子关系的初步研究

依据对青海湖北岸 1 8个群落的样方调查和环境因子原始数据 ,用主分量分析 ( PCA)排序技术和回归模型 ,定量分析湖滨平原植物群落在空间地理上的分布格局 ,以及群落结构特征和环境梯度之间的关系。结果表明 :植物群落的类型分布主要决定于环境中的土壤水分含量及土壤全盐含量。代表植物群落结构特征的生物多样性 ( X1)和生态优势度 ( X2 )分别与环境梯度没有显著的相关性 ,但是 ,这两个指标和第一主分量排序轴 (土壤水分度 ,Y)的二元线性回归关系显著 ,回归模型为 :Y =- 4 .85 1 .4 7X1 1 0 .71 X2 ( P <0 .0 1 )。     

山西蟒河自然保护区栓皮栎林的聚类和排序

本文用等级聚类、极点排序、主成分分析和对应分析等多元分析法, 对蟒河自然保护区的栓皮标(Quercus variabilis)林进与于了聚类和排序。等级聚类法将蟒河自然保护区的栓皮栎林划分为五个群丛, 极点排序、主成分分析和对应分析三种方法得出一致的结论, 并较好地反映了环境变化的梯度及植被变化的连续性。综合分析表明栓皮栎林是保护区内稳定的群落类型。     

青海湖北岸植物群落与环境因素关系的初步研究

依据对青海湖北岸１８个群落的术方调查和环境因子原始数据,用主分量分析排序技术和回归模型,定量分析湖滨原植物群落在空间地下上的分布格局,以及群落结构特征和环境梯度之间的关系。结果表明;植物群落的类型分布主要决定于环境中的土壤中水分 含量及土壤全分含量。     

东灵山植物群落生活型谱的比较研究

应用由丹麦学者Ｒａｕｎｋｉａｅｒ提出的生活型分类系统,研究了北京东灵山植物群落的生活型,并编制了主要植物群落类型的生活型谱。同时,用主成分分析（ＰＣＡ）作为排序的方法和系统聚类中的离差平方和法与类平均法,对东灵山植物群落的生活型谱进行了排序和分类。并用双重筛选逐步回归的方法分析了环境（气候和土壤）因子与植物群落生活型谱梯度的关系,建立了相应的数学模型。研究结果表明：东灵山地区植物群落生活型谱的特征符合暖温带植物生活型谱的基本特点,地面芽植物占的比例最大。但不同植物群落因所存在的生境有差异,也表现出各自的谱特征。排序的结果与用植物种类成分进行的ＤＣＡ 排序结果吻合度较好,排序的环境梯度特征也十分明显。研究结果还表明：地下芽和中高位芽对于温度梯度的反应比较灵敏;其次是小高位芽和一年生植物;对于水分梯度的变化,则以地上芽和矮高位芽植物的反应比较强烈和敏感。温带植被生活型谱主要特征的地面芽植物在本地区表现稳定,不随各植物群落和水热梯度发生大的波动,显示出地带性的强大约束力。所建立的海拔梯度和群落类型与生活谱的统计数学模型,对于中高位芽、矮高位芽和地下芽植物的相关较好,估测的精度高,而对其它几种生活型的估测较差     

北京东灵山地区农耕干扰和环境梯度对植物多样性的影响

于北京东灵山地区,选取10条样带、94个样方、15个环境因子,采用主成分分析和相关分析研究了东灵山地区人为干扰（如农耕）及其造成的环境条件变化对植物α多样性的影响.（1）调查结果表明：植物群落可归入4类土地利用类型（农田、撂荒地、灌丛和林地）中;（2）主成分分析和相关分析表明：2个主成分（地形和土壤因子）影响着植物群落结构、物种组成和多样性的变化,尤其是海拔梯度与多数环境因子显著相关,起决定性作用;（3）多样性分析表明：Shannon-Wiener指数和Margalef指数都能较好地反映植物群落α多样性的变化,Simpson指数变化不明显.4种土地利用类型中植物群落α多样性的变化依次为：林地〉农田〉撂荒地〉灌丛,且草本层对植物多样性的贡献最大.     

林区火灾后植物群落与冻土环境的多元分析

本文运用国际较为先进的双向指示种分析(TWINSPAN)多元等级分划分类方法和无趋势对应分析(DCA)排序方法对大兴安岭阿木尔林区1987年特大森林火灾后的植物群落进行了研究。通过排序结果和冻土环境的多元分析,得出：DCA排序轴1代表了土壤岩性与地形的梯度而决定植物群落的分布;DCA排序轴2则反映了森林火烧的程度梯度,并通过冻土融化深度和浅层地温值的变化而影响植物群落的分布,运用相关回归分析方法,定量地找出了它们之间相互关系的回归方程。 据此,进而探讨了该地区森林火灾后冻土环境的变化对植物次生演替方向和进程的影响。     

嵊州市公益林群落数量分类、排序及环境解析

为探讨群落分布和环境间的内在关系,采用二元指示种分析(TWINSPAN)和典范对应分析(CCA)法对嵊州市公益林植物群落94 块固定监测样地(20 m×20 m)进行数量分类与排序.结果表明,采用TWINSPAN 可将94 个公益林监测样地分成14 组,其中以马尾松为建群种的群丛最多,是该区域主要的优势群落类型.CCA 排序结果较好地反映了植物群落与环境因子的关系,其中坡向和坡位是植物群落分布的主导环境因子.此方法可有效解释植物群落分布格局与环境之间的内在联系,为区域公益林分类经营管理提供科学依据.     

西藏阿里植物群落的间接梯度分析、数量分类与环境解释

根据对西藏阿里地区163个植物群落样地资料进行的多元分析——排序、数量分类与环境解释,给出了该地区植被的基本类型、生态梯度及其与环境因子的定量关系。基本分析方法包括3个步骤：1)通过无倾向对应分析(DCA)的两个排序向量揭示了阿里植被的两个主要生态梯度;2)由该梯度的二维散点图及二元指示种分析(TWINSPAN)分别产生非等级制与等级制的植物群落分类系统;3)以多元回归分析将排序值与环境及地理参数相联系而给出各类型的环境指标——定量环境解释。分析表明,阿里植被类型及其分布主要取决于热量与湿度梯度,前者可通过地理参数,后者则通过土壤特征的数学表达式来定量地确定。两梯度包含的类型、种类与生境差异颇大,由低山暖性荒漠直到高山冰缘植被,从隐带性沼泽与盐生草甸到高原地带性荒漠与草原均各得其位,各有其值。表明该数量分析法对于处理高度生态多样性的植物群落生态信息是十分有效的。     

排序法在植物群落与环境关系研究中的应用述评

自然环境对植物的影响主要表现在气候、水文、土壤及地形方面。大尺度上,气候类型明显影响植物的带状分布与物种空间格局;中小尺度上,土壤、水文、地形以及三者的交互作用影响植物生长必需的环境与资源条件,并对植物群落物种多样性起决定性作用。多元数量分析是研究植物群落生态关系的重要方法,在揭示植物群落与环境关系方面起到关键作用。排序法作为数量分析的重要手段,经常在植物生态学研究中扮演重要角色,尤其是在植物群落分布以及群落结构方面的应用已形成一种趋势。主要从植物群落分布以及群落结构的角度综述了当今排序法的应用,分析了面临的主要问题,并提出了未来可能发展方向,以期为今后排序方法的选择应用提供参考。     

Accuracy, Reproducibility, and Interpretation of Fatty Acid Methyl Ester Profiles of Model Bacterial Communities

We determined the accuracy and reproducibility of whole-community fatty acid methyl ester (FAME) analysis with two model bacterial communities differing in composition by using the Microbial ID, Inc. (MIDI), system. The biomass, taxonomic structure, and expected MIDI-FAME profiles under a variety of environmental conditions were known for these model communities a priori. Not all members of each community could be detected in the composite profile because of lack of fatty acid “signatures” in some isolates or because of variations (approximately fivefold) in fatty acid yield across taxa. MIDI-FAME profiles of replicate subsamples of a given community were similar in terms of fatty acid yield per unit of community dry weight and relative proportions of specific fatty acids. Principal-components analysis (PCA) of MIDI-FAME profiles resulted in a clear separation of the two different communities and a clustering of replicates of each community from two separate experiments on the first PCA axis. The first PCA axis accounted for 57.1% of the variance in the data and was correlated with fatty acids that varied significantly between communities and reflected the underlying community taxonomic structure. On the basis of our data, community fatty acid profiles can be used to assess the relative similarities and differences of microbial communities that differ in taxonomic composition. However, detailed interpretation of community fatty acid profiles in terms of biomass or community taxonomic composition must be viewed with caution until our knowledge of the quantitative and qualitative distribution of fatty acids over a wide variety of taxa and the effects of growth conditions on fatty acid profiles is more extensive.     

Analysis of Factors Affecting the Accuracy, Reproducibility, and Interpretation of Microbial Community Carbon Source Utilization Patterns

We determined factors that affect responses of bacterial isolates and model bacterial communities to the 95 carbon substrates in Biolog microtiter plates. For isolates and communities of three to six bacterial strains, substrate oxidation rates were typically nonlinear and were delayed by dilution of the inoculum. When inoculum density was controlled, patterns of positive and negative responses exhibited by microbial communities to each of the carbon sources were reproducible. Rates and extents of substrate oxidation by the communities were also reproducible but were not simply the sum of those exhibited by community members when tested separately. Replicates of the same model community clustered when analyzed by principal-components analysis (PCA), and model communities with different compositions were clearly separated on the first PCA axis, which accounted for >60% of the dataset variation. PCA discrimination among different model communities depended on the extent to which specific substrates were oxidized. However, the substrates interpreted by PCA to be most significant in distinguishing the communities changed with reading time, reflecting the nonlinearity of substrate oxidation rates. Although whole-community substrate utilization profiles were reproducible signatures for a given community, the extent of oxidation of specific substrates and the numbers or activities of microorganisms using those substrates in a given community were not correlated. Replicate soil samples varied significantly in the rate and extent of oxidation of seven tested substrates, suggesting microscale heterogeneity in composition of the soil microbial community.     

拉萨河流域亏组山植物物种丰富度和群落特征研究

为研究草地植物群落、物种丰富度及其分布格局与影响因子之间的关系,该文以拉萨河流域林周县卡孜乡亏组山为研究地点,对山体垂直样带(3900～5100 m)植物群落特征、植物物种丰富度与各影响因子之间的关系进行了研究.研究区域共设置了13个样带(每隔100 m设一个样带),每样带设置0.5 m×0.5 m的5个样方进行植被调...     

陕西洛河流域不同生境蝗虫的群落结构

应用种-多度分布模型、多样性指数、相似性分析、主成分(PCA)分析及多元逐步回归等方法比较了洛河流域不同生境的蝗虫群落结构。结果显示:洛河流域各生境的蝗虫分布基本上服从Preston对数正态分布,其中以森林拟合的最好。各多样性指数的变化趋势均为森林>森林草原>河滩和农田>典型草原。在相似性分析中,典型草原、森林草原和森林这3种生境相似性很高,而河滩和农田则是完全不同的另一种生境。对各生境植被因素和蝗虫群落所进行的主成分分析,结果非常理想,两维主成分的累计方差贡献率分别达到了92.558%和78.566%。通过多元逐步回归发现,影响蝗虫种类和数量变化的植被因有草本植物高度多样性、树木盖度、豆科优势度、禾本科优势度和其他科优势度等。     

Primary Study on Interrelation Between Plant Communities and Environmental Factors in the North Shore of Qinghai Lake

Eighteen plant communities were surveyed by quaduats in the north shore of Qinghai Lake. The communities were analyzed using PCA (principal component analysis) ordination and regression procedure to determine the distribution patterns of the plant communities and relationship between the communities and environmental factors. The results showed that the distribution of the plant communities were closely related to the moisture and salt content of soil. The correlation between species diversity or ecological dominance of the communities and gradient of environmental factors was not significant, but the two indexes of community showed multivarient line relationship with the first principal component, or the gradient of soil water, and the regression model as below: Y =- 4.85 4–1.47X1 4- 10.71X2 (P<0. 01).     

Longitudinal distribution of Trichoptera in the Loire River (France): simple ordination methods and community structure

The longitudinal distribution of Trichoptera at 37 sampling sites along 800 km of the Loire River (France) was analyzed in order to better understand large-scale changes in community structure occurring on a stream continuum. Different simple ordination methods — centered PCA and Correspondence Analysis — were performed to investigate these changes. Both analyses showed that a major change occurs in the community in the upper reaches of the Loire River between the Serre de la Fare and Vorey sampling sites with the appearance of Hydropsyche contubernalis and H. Exocellata. Even though other changes in community structure could exist, revealed either by Correspondence Analysis at the first sampling sites (crenal), or by PCA at sampling sites influenced by dams, this Trichoptera community appears to be stable enough in the latter part of the Loire River with the addition of a few species, Hydropsyche bulgaromanorum, Ecnomus tenellus and E. deceptor, rather than changes in species. The results are discussed in the light of different concepts in stream ecology, and the validity of such data analyses to describe some community patterns.     

海南草地的类型

本文分析了海南草地的类型及其分布。据优势种的差异,划分出27个群落。用主分量分析 (PCA)法,对27个群落进行排序,把它们分为高草、中草、矮草及季节性积水草地4大类型。绝大部分群落都是次生的,甚至西部台地类似于萨王纳的早中生性草地,也是次生的。但薄果草群落则是原生性草地,是由特殊的土壤条件决定的。 PCA表明,土壤肥力及水分条件是影响不同类型分布的最重要的生态因子。     

山西霍山森林群落的排序

运用主分量分析法对霍山东、西两坡的１０５个样方进行了排序。前３个主分量占总信息量的７０％左右。降维效果良好。排序图中,样方间距离抽象地表达了群落间的生态学相关程度。据此将所作样方划分为若干群系,分析了群落随环境梯度变化的规律、观测了群落演替的趋向。从而证明ＰＣＡ法在该区森林群落研究中具有良好的适应性。     

Reconstructing community relationships: the impact of sampling error, ordination approach, and gradient length

Effectively summarizing complex community relationships is an important feature in studies such as biodiversity, global change, and invasion ecology. The reliability of such community summaries depends on the degree of sampling variability that is present in the data, the structure of the data, and the choice of ordination method, but the relative importance of these factors is not understood. We compared the validity of results from different ordination methods by applying five levels of sampling error to a simulated coenoplane model at two gradient lengths using two types of data (abundance and presence–absence). The multivariate methods we compared were correspondence analysis (CA), detrended correspondence analysis (DCA), non-metric multidimensional scaling (NMDS), principal component analysis (PCA) and principal coordinates analysis (PCoA). Our results showed CA and PCA using presence–absence data were the most successful methods regardless of sampling error and gradient length, closely followed by the other methods using presence–absence data. With abundance data, PCA and CA were the most successful approaches with the short and long gradients, respectively. Approaches based on PCoA and NMDS using abundance data did not perform well regardless of the choice of distance measure used in the analysis. Both of these methods, along with the PCA using abundance data, were strongly affected by the longer gradient, leading to more distorted results.