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。     

海南岛霸王岭林区低海拔热带林群落数量分类与排序

植物群落分类是依据植物群落的特征或属性对植物群落进行划分,是植被生态学的最基本也是最复杂的研究内容。热带林由于其复杂的环境条件及丰富的物种数量导致了其分类更加困难。本文根据海南岛霸王岭林区低海拔热带林群落的野外调查数据,运用二元指示种分析(TWINSPAN)、主分量分析(PCA)及除趋势对应分析(DCA)对该地区低海拔热带林群落进行了数量分类与排序。结果表明:TWINSPAN将21个样地共分成3组:热带低地雨林(样地9—12)、转化型季雨林(样地1—8)和热带季雨林(样地13—21)。PCA和DCA排序结果也得到了相同的结论,同时也反映了植物群落与环境因子的关系,热带低地雨林与海拔和凋落物厚度呈正相关,而热带季雨林与坡度和岩石裸露度呈正相关,转化型季雨林与环境因子的关系在PCA和DCA中则有所不同。DCA排序结果同时也表明,转化型季雨林是介于热带低地雨林和热带季雨林中间的一种群落类型。     

新疆奇台荒漠植物群落的数量分类及土壤环境解释

为阐明古尔班通古特沙漠南缘荒漠植物群落的分类及与土壤因子的相关关系, 作者于2005年6–7月在新疆奇台县采用机械布设样线和样线上随机布设样地的方法进行了野外调查。共设置48块20 m×10 m的样方, 每个样方中又梅花状设置5个1 m×1 m的草本样方进行植被调查。植被调查结束后, 选择群落外貌上差异显著的样地进行土壤取样(取土深度分别为0 cm、10 cm、30 cm、50 cm、80 cm), 共获得20个样方的土壤样本。以植物重要值作为衡量植物组成相似性的指标, 应用逐步聚类的方法将调查区域植被划分为4种类型: 芦苇(Phragmites australis)+芨芨草(Achnatherum splendens)群落, 梭梭(Haloxylon ammodendron)–枇杷柴(Reaumuria songarica)+西伯利亚白刺群落(Nitraria sibirica), 梭梭–心叶驼绒藜(Ceratoides ewersmanniana)–白茎绢蒿(Seriphidium terrae-albae)群落和心叶驼绒藜–骆驼刺(Alhagi sparsifolia)群落。不同群落类型土壤因子的主成分分析的结果表明: 提取3个主分量能够解释85.65％的群落间土壤因子差异, 第1主分量与土壤平均pH值和深层土壤pH值相关, 第2主分量与平均有机质含量和土壤浅层有机质含量相关, 而第3主分量与平均土壤含盐量和土壤浅层含盐量相关。     

云南普洱季风常绿阔叶林幼苗的群落构建机制

幼苗是森林生物多样性保育的重点关注对象,以往研究对云南普洱季风常绿阔叶林幼苗的关注较少。为探究该地幼苗的群落构建机制,该研究利用30hm2季风常绿阔叶林动态监测样地野外幼苗调查数据,分析幼苗的物种组成,划分不同优势种样方,根据逐步群落构建模型分析群落构建机制,进一步分析幼苗的群落功能性状。结果表明:季风常绿阔叶林幼苗以短刺锥(Castanopsis echidnocarpa)和枹丝锥(C. calathiformis)为优势种,根据优势种是否出现将样方划分为4种类型:短刺锥样方、枹丝锥样方、混合优势种样方及非优势种样方。幼苗的群落构建过程均包含随机扩散构建(贡献率43.1%–61.3%)、生境过滤(贡献率27.4%–33.9%)及限制相似性(贡献率5.7%–27.2%)机制。短刺锥样方和枹丝锥样方以确定过程为主,贡献率分别为56.9%和54.6%,而混合优势种样方及非优势种样方则以随机过程为主,贡献率分别为60.4%和61.3%。在非优势种样方中Rao二次熵(Rao’Q)最高,而在混合优势种样方中最低。短刺锥样方具有最低的比叶面积和较高的叶厚度、比茎长度、根质量分数及潜在株高,而枹丝锥...     

大丰麋鹿保护区不同生境梯度下滩涂湿地植被的群落特征

以江苏大丰麋鹿国家级自然保护区第三核心区内的滩涂湿地植被为对象,采用样线法结合样方法进行野外调查,并采用等级聚类分析、主成分分析(PCA)和Shannon-Wiener物种多样性、Simpson生态优势度、Pielou群落均匀度等指数分析群落特征。结果表明,34个样地共有植物5科11属11种,划分为5种群落类型,群落优势种明显,伴生种较少,种类组成单调,均为草本植物;从近海至近岸滩涂湿地植被的分布呈现出较为明显的规律性变化:互花米草群落→碱蓬群落→大穗结缕草群落→芦苇群落→白茅群落,其物种多样性、生态优势度和群落均匀度均较低,物种丰富度呈现出由低到高再降低的趋势;PCA和植物生理特性分析结果暗示,土壤盐分梯度是影响植物群落分布的主要因素。     

不同样方尺度下鄱阳湖湿地典型草洲植物种间关联性

为了解群落中优势植物的关联程度和性质随样方尺度的变化,在鄱阳湖湿地典型草洲-南矶湿地国家级自然保护区选取8块样地(大小8 m×8 m,样带间隔100 m,样地间隔80 m),每个样地依次划分为1 m×1 m、2 m×2 m和4 m×4 m等3个样方尺度,利用方差比率法、卡方检验和Jaccard指数检验方法,研究群落优势植物总体关联程度和性质及两两物种对间关联程度和性质随样方尺度扩大的变化。结果表明,该研究区优势物种有灰化薹草(Carex cinerascens)、水田碎米荠(Cardamine lyrata)、蒌蒿(Artemisia selengensis)、通泉草(Mazus japonicus)、菊叶委陵菜(Potentilla tanacetifolia)、南荻(Triarrhena lutarioriparia)和早熟禾(Poa annua)。随样方尺度扩大,物种重要值除灰化薹草先增加后减少以外,其他物种的变化均不显著。7种优势植物组成的21个物种对随样方尺度扩大,植物总体关联性不显著且由负关联转向正关联。在3个样方尺度条件,21个物种对的多呈现不显著关联。随样方尺度的扩大,种间呈显著关联的物种对逐渐减少;种间呈正关联的物种对逐渐增加。Jaccard指数表明,各物种对随样方尺度的扩大,种间关联程度不断增加。这是由于研究区地被植物种类较多,分布频度较低,不同样方尺度下,群落内部资源分布差异以及物种之间的竞争与协同关系所致。     

海南岛热带草地的数量分类和排序研究

本文用一些数量分类和排序的方法对海南岛鹦歌岭热带草地进行了分类和排序。所用的方法包括两种多元等级聚合分类--最近邻体法(NN)和最远邻体法(FN),极点排序(PO)和主分量分析(PCA)排序。结果表明：把19个样地分为三大类型、9个群落,其分布格局与坡度、放牧强度和土壤肥力密切相关。所用的四种方法在热带草地的研究中均有一定的适用性。     

塔里木河中下游湿地及周边植物群落与环境因子的关系初探

选取塔里木河中下游湿地及周边16个典型植物群落样地调查和环境因子数据,采用主分量分析(PCA)排序技术和回归分析,定量分析湿地及周边植物群落在空间上的分布格局,以及群落结构特征和环境梯度之间的关系.结果表明,影响塔里木河中下游湿地及周边植物群落分布的第1主分量中,土壤水分和盐分影响最大,贡献率为35.70％;在第2主分量中,土壤养分的影响最大,贡献率为25.97％.植物群落分布的生境可分为沼生轻盐中营养生境、湿生中盐中营养生境、中生中盐低营养生境和中旱生重盐低营养生境4种类型.沿不同生境依次分布着沼泽植被、草甸植被、河岸疏林和盐生荒漠 盐化灌丛植被.塔里木河中下游湿地及周边植物群落的生态优势度与土壤水分和盐分复合梯度呈显著的一元线性相关.二元回归分析结果显示,塔里木河中下游湿地及周边土壤水分和盐分复合梯度与多样性指数和生态优势度二元指标呈极显著相关.     

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 )。     

南亚热带森林种群分布格局取样技术研究

森林群落中植物种群分布格局测定和分析的结果,密切依赖于野外取样的技术手段及资料的可靠性。本文通过鼎湖山自然保护区三个不同森林群落类型的取样,比较了随机样方、相邻格子样方、中心点四分法、最近相邻法和最近个体法在野外操作、数据整理以及种群分布格局测定分析中的效用,对各方法在南亚热带森林群落中进行种群分布格局研究中的适用性予以客观评价。研究表明,同一样地中不同取样方法和测定方法会导致不同结果。随机样方取样数据的测定结果受样方大小影响,而几种无样地方法在种类复杂的群落中,应用受到限制。相邻格子样方适用于各群落类型中种群分布格局的测定与分析。     

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.     

Ordination of boreal heath-like vegetation with principal component analysis,correspondence analysis and multidimensional scaling

Four relatively homogeneous field data sets were analyzed, representing boreal, heath-like forest-floor and rock vegetation in Finland, corresponding to Finnish Calluna and Cladina site types. The methods used were principal component analysis (PCA) of covariance matrices, orthogonal correspondence analysis or reciprocal averaging (RA), detrended correspondence analysis (DCA), and linear and nonmetric multidimensional scaling (MDS). RA and DCA gave ordinations in which every species had nearly equal weight. MDS and PCA gave results determined mostly by a few dominant species. MDS and PCA ordinations were very similar to RA and DCA ones when the original data were standardized so that for each species the mean of positive occurrences was the same while quantitative differences within species were retained. RA and PCA were generally very good and reliable, providing that the impact of rare species and outlier relevés was removed in RA. DCA was slightly less reliable than RA. MDS was sensitive to uneven sampling patterns and was the least reliable method compared.     

不同类型茶园昆虫、蜘蛛群落结构分析

应用多样性指数,排序和聚类分析方法研究了不同生态环境和防治处理的茶园昆虫,蜘蛛群落结构,结果表明：在生态控制的茶园,由于完全不使用化学农药,昆虫和蜘蛛的丰富度,多样性指数,均匀度均较大。综合防治的茶园次之一。而主要依靠化学防治的茶錾,丰富度减少,多样性指数和均匀度降低,经常出现害虫暴发成灾的现象。     

Nonlinear dimensionality reduction: Alternative ordination approaches for extracting and visualizing biodiversity patterns in tropical montane forest vegetation data

Ecological patterns are difficult to extract directly from vegetation data. The respective surveys provide a high number of interrelated species occurrence variables. Since often only a limited number of ecological gradients determine species distributions, the data might be represented by much fewer but effectively independent variables. This can be achieved by reducing the dimensionality of the data. Conventional methods are either limited to linear feature extraction (e.g., principal component analysis, and Classical Multidimensional Scaling, CMDS) or require a priori assumptions on the intrinsic data dimensionality (e.g., Nonmetric Multidimensional Scaling, NMDS, and self organized maps, SOM).In this study we explored the potential of Isometric Feature Mapping (Isomap). This new method of dimensionality reduction is a nonlinear generalization of CMDS. Isomap is based on a nonlinear geodesic inter-point distance matrix. Estimating geodesic distances requires one free threshold parameter, which defines linear geometry to be preserved in the global nonlinear distance structure. We compared Isomap to its linear (CMDS) and nonmetric (NMDS) equivalents. Furthermore, the use of geodesic distances allowed also extending NMDS to a version that we called NMDS-G. In addition we investigated a supervised Isomap variant (S-Isomap) and showed that all these techniques are interpretable within a single methodical framework.As an example we investigated seven plots (subdivided in 456 subplots) in different secondary tropical montane forests with 773 species of vascular plants. A key problem for the study of tropical vegetation data is the heterogeneous small scale variability implying large ranges of β-diversity. The CMDS and NMDS methods did not reduce the data dimensionality reasonably. On the contrary, Isomap explained 95% of the data variance in the first five dimensions and provided ecologically interpretable visualizations; NMDS-G yielded similar results. The main shortcoming of the latter was the high computational cost and the requirement to predefine the dimension of the embedding space. The S-Isomap learning scheme did not improve the Isomap variant for an optimal threshold parameter but substantially improved the nonoptimal solutions.We conclude that Isomap as a new ordination method allows effective representations of high dimensional vegetation data sets. The method is promising since it does not require a priori assumptions, and is computationally highly effective.     

南泥湾片段森林蝗虫群落多样性比较

应用多样性指数、排序和多元逐步回归分析方法比较了南泥湾片断化森林的蝗虫群落结构,并进行了环境因素的解释。结果显示：在南泥湾,树木破坏不严重的片断化森林,随森林面积的减小,林缘草层蝗虫种类、多样性指数和均匀度指数差异不大;林中草层蝗虫密度、多样性指数和均匀度指数减小。在面积小、树木破坏严重、植被结构发生明显改变的片断森林林中草层,相对于树木破坏不严重的片断化森林,蝗虫的密度、多样性指数和均匀度指数明显增大;而林缘草层蝗虫的密度和群落优势度指数上升,多样性指数和均匀度指数下降。以主分量分析方法可明显将林中草层蝗虫群落分为森林破坏严重和不严重两种类型。通过多元逐步回归分析发现,影响片断化森林蝗虫群落结构和多样性的主要因素有片断森林面积、森林植被结构的复杂性、食料植物的多少等几个方面。     

云南医学革螨数值分类研究

以云南省57种医学革螨作为分类单元,以形态特征为主列出60项分类性状特征来探讨云南省医学革螨不同属和种的亲缘关系。运用SPSS 11.5 统计软件中的系统聚类分析和主成分分析,对57种医学革螨进行了数值分类分析。结果显示：57种医学革螨划分为厉螨科（La elapidae）、寄螨科（Parasitidae）、皮刺螨科（Dermanyssidae）、赫刺螨科（Hirstionyssidae）和裂胸螨科（Aceosejidae）5个类群。赫刺螨属和棘刺螨属从厉螨科中分离出来另立为赫刺螨科,柏氏禽刺螨归入了皮刺螨科而不是巨刺螨科。分类结果与传统形态分类结果基本一致,因而认为数值分类能比较客观地反映医学革螨各分类阶元的分类地位与亲缘关系。     

茶园蜘蛛、昆虫群落动态的研究

该文研究报道了皖南地区茶园蜘蛛、昆虫的种类和群落结构,结果如下:1.茶园中昆虫、蜘蛛种类有28个,其中5、6月群落中动物种类多,多样性指数大。调查期内,品种园内动物优势种是天敌。2.主成分分析(PCA)表明:在无人为干扰的品种园内,节肢动物群落结构稳定;进行化学防治的采摘茶园群落结构不稳定。此研究对于在茶园内合理使用农药、繁荣生物群落,提高茶叶品质有重要意义。     

长白山劲松林场植物群落的分类和排序

将长白山白河林业局劲松林场的５４块样地用聚类分析法划分成６个植被类群,再用ＰＣ－ＶＴＡＢ程序中经过改进的Ｂｒａｕｎ－Ｂｌａｎｑｕｅｔ学派的植被排表分析法进行综合,产生了鉴别概要表,为各个等级的植被类群筛选出诊断种。此外,还用鉴别种地样地记录进行主成分分析,以验证诊断种的有效性,结果表明,ＰＣ－ＶＴＡＢ中的植被排表分析法是筛选鉴别种的有效方法,而鉴别种以显著地提高植被分析和排序的质量。     

A NUMERICAL–TAXONOMIC STUDY OF THE GENUS BULNESIA (ZYGOPHYLLACEAE): CLUSTER ANALYSIS,ORDINATION AND SIMULATION OF EVOLUTIONARY TREES

Cluster analysis by four methods, ordination by principal component analysis (PCA) and simulation of evolutionary trees (Wagner Trees) were performed on morphological data from 43 characters of eight species of the South American genus Bulnesia (Zygophyllaceae). The results of cluster analysis and principal component analysis in general agree and show that there are three pairs of taxa that appear, or obviously are, closely related. These are the pairs B. arborea–B. carrapo, B. foliosa–B. schickendantzii and B. retama–B. chilensis. These methods also indicate that the southern species B. bonariensis occupies an intermediate position between the pair of northern tropical species (B. arborea, B. carrapo) and the remaining southern species. From the beginning it was assumed that these three multifoliolate species with large flowers may be rather primitive. The Prim network indicates that these three species are closely related among themselves. Also in two of the three Wagner Trees they are placed in a group. In all cases B. sarmientoi is shown as the more remote and isolated of all species. It is regarded as a unique, specialized arboreal species showing extreme reduction in number of leaflets and carpels, leaf and flower size, etc. All graphic representations (Fig. 1–3) show the phenetic similarity or the close phylogenetic relationships of the pairs B. foliosa–B. schickendantzii and B. retama–B. chilensis to each other. These four species would represent a rather advanced group. The most xerophytic species B. retama and B. chilensis are regarded as the most advanced taxa and the most specialized histophysiologically. These occupy extreme and distant positions in PCA diagrams and Prim network, and top positions in the Wagner Trees.