生物群落多样性的测度方法VI：与多样性测度有关的统计问题

物种多样性测度是（群落的）总体参数,它们常常是未知的,需要通过抽样将它们估计出来,因此,必须了解估计量的抽样性质。本文对与一些多样性测度的均值、方差的估计和假设检验以及大、小样本分布等有关的问题作了综述。可以看出大多数多样性测度的抽样性质还不清楚,有些甚至根本就没有研究过。Ｐｉｅｌｏｕ的合并样方法和刀切法是两个比较通用的方法,用它们可以解决其中的一些问题。但相比之下,刀切法更实用。     

生物群落多样性的测度方法Ⅵ:与多样性测度有关的统计问题

物种多样性测度是(群落的)总体参数,它们常常是未知的,需要通过抽样将它们估计出来,因此,必须了解估计量的抽样性质.本文对与一些多样性测度的均值、方差的估计和假设检验以及大、小样本分布等有关的问题作了综述.可以看出大多数多样性测度的抽样性质还不清楚,有些甚至根本就没有研究过.Pielou的合并样方法和刀切法是两个比较通用的方法,用它们可以解决其中的一些问题.但相比之下,刀切法更实用.     

生物群落多样性的测度方法

群落的物种数目,即物种丰富度,是最古老、同时也是最基本的一个多样性概念,从对它的估计中可以得到关于物种灭绝速率方面的信息,这对生物多样性保护是非常重要的。已经提出了很多方法来估计九落中的物种数目,这些方法可以分为两大类,即基于理论抽样的方法和基于数据分析的方法。前者包括经典估计方法和贝叶斯估计方法;后者包括对正态分布的积分方法、再抽样方法和种－面积曲线的外推方法。发现：（１）有些方法适用珐动物群落     

生物群落多样性的测度方法 V.生物群落物种数目的估计方法

群落的物种数目,即物种丰富度,是最古老、同时也是最基本的一个多样性概念,从对它的估计中可以得到关于物种灭绝速率方面的信息,这对生物多样性保护是非常重要的。已经提出了很多方法来估计群落中的物种数目,这些方法可以分为两大类,即基于理论抽样的方法和基于数据分析的方法。前者包括经典估计方法和贝叶斯估计方法;后者包括对数正态分布的积分方法、再抽样方法和种－面积曲线的外推方法。发现：（１）有些方法适用于动物群落,如大多数基于理论抽样的方法;有些方法则适用于植物群落,如大多数基于数据分析的方法;（２）这些方法还没有经过全面而系统地比较;（３）还没有一个普遍认为比较好的方法。因此,建议采用野外调查与模拟研究相结合的方法对各种估计方法进行系统地评价。     

生物群落多样性的测度方法Ⅱβ多样性的测度方法

生物群落多样性的测度方法Ⅱβ多样性的测度方法马克平,刘灿然,刘玉明（中国科学院植物研究所,北京１０００４４）（北京市教育学院,北京１０００４４）β多样性可以定义为沿着环境梯度的变化物种替代的程度［１］,亦有人称为物种周转速率（ｓｐｅｃｉｅｓｔｕｒｎｏ...     

系统发育多样性测度及其在生物多样性保护中的应用

生物多样性保护面临两个基本问题：如何确定生物多样性测度以及如何保护生物多样性。传统的生物多样性测度是以物种概念为基础的,用生态学和地理学方法确定各种生物多样性指数。其测度依赖于样方面积的大小,并且所有的物种在分类上同等对待。系统发育多样性测度基于系统发育和遗传学的理论和方法,能确定某一物种对类群多样性的贡献大小。该方法比较复杂,只有在类群的系统发育或遗传资料比较齐全时方能应用。本文认为,物种生存力途径和系统发育多样性测度相结合有助于确定物种和生态系统保护的优先秩序。     

特有植物多样性分布格局测度方法的新进展

特有植物是生物多样性保护的重要对象,对其分布格局的研究可以为生物多样性优先保护区的确定提供重要参考.研究人员利用多种测度和分析方法,在不同地理区域对特有现象的分布格局开展了大量研究.随着分子系统学方法的不断完善及一些空间统计分析方法的引入,新的生物多样性测度方法应运而生.本文介绍了生物多样性测度方法的类型及其特点、应用现状与前景.这些测度方法的发展经历了从单一的时间或空间格局到时空格局统一的过程,具体涉及物种丰富度、谱系多样性、进化特异性以及这3种测度方法整合空间分布加权的算法.其中,谱系多样性指数(phylogenetic diversity)、谱系特有性指数(phylogenetic endemism)以及空间加权的进化特异性指数(biogeographically weighted evolutionary distinctiveness)尤其值得关注.中国特有植物分布格局的研究需要在以下4个方面进一步开展工作:(1)完善特有物种的分布格局研究;(2)加强物种的测序工作,完善谱系多样性格局的分析;(3)结合系统发育信息,揭示谱系多样性及进化历史的分布格局,进而深入开展物种p多样性和谱系p多样性的研究;(4)加强物种分布区变化的模拟,在时间维度上探讨特有现象的变化格局,为生物多样性保护提供更完善的理论支持.     

云贵鹅耳枥群落物种多样性及其刀切法估计

采用Simpson指数（D)、Shannon-Weiner指数（H）和均匀度（E）等,分析了中亚热带喀斯特山地云贵鹅耳枥群落及其演替过程中的物种多样性特征。并用刀切法对Simpson指数和Shannon-Wiener指数进行了估计。结果表明,云贵鹅耳枥群落的Simpson指数为1．14－3．88,Shannon-Weiner指数为0.50-2.43 ,均匀度为0．19－0．71。随着群落的发育和演替,其物种多样性呈现“高→低→高”的动态变化。Simpson指数的刀切估计值为1．14－3．88,估计区间为1．04－5．10;Shannon-Weiner指数的刀切估计值为0．52－2．58,估计区间为0．24－3．14。刀切法是一种比较有效的估测物种多样性的方法。     

群落结构复杂性的测度方法研究进展

该文对群落结构复杂性的测度方法的研究进展状况进行了综述。根据测度方法建立的方法基础,将现有的方法分成3类:基于多样性的复杂性测度、基于计算复杂性的测度和基于几何学特征的复杂性测度。对每类测度方法进行了介绍,对其优缺点进行了评述。同时提出了未来研究中应给予重视的问题。结果表明,现有群落结构复杂性的测度方法普遍存在区分能力差的问题,对于基于多样性的结构复杂性测度,目前还缺乏确定各测度属性权重的客观方法;现有的一些基于计算复杂性的结构测度与多样性指标关系过于密切,还不完善,同时其生态学的意义还不明确,而另一些计算复杂性指标还缺乏实际检验。今后,如何建立既具有区分力、又与多样性在概念和数值上都有一定区别的群落结构的计算复杂性的测度方法、如何科学合理地确定复杂性测度中的属性权重以及如何建立结构复杂性的测度和功能过程之间的联系等都是需要深入和系统研究的。由于方法的相似性,有关群落结构复杂性的测度方法也可以应用到其它尺度上的结构复杂性的研究中。     

景观多样性测度:格局多样性的亲和度分析

介绍景观格局多样性亲和度分析的原理和方法,指出亲和度分析能够测定景观各亚单元的相对位置及镶嵌多样性。镶嵌多样性是综合了亲和度分析信息的一个指标,是对格局多样性的有效测度。镶嵌多样性低意味着景观结构简单,镶嵌多样性高意味着景观结构复杂,亲和度分析可以比较不同景观的多样性和复杂性,可以判断群落与景观整体的关系的远近,还可以判断两个群落的相似性和亲和度差异的显著程度。因而亲和度分析将景观层次的多样性与物     

A conceptual guide to measuring species diversity

Three metrics of species diversity – species richness, the Shannon index and the Simpson index – are still widely used in ecology, despite decades of valid critiques leveled against them. Developing a robust diversity metric has been challenging because, unlike many variables ecologists measure, the diversity of a community often cannot be estimated in an unbiased way based on a random sample from that community. Over the past decade, ecologists have begun to incorporate two important tools for estimating diversity: coverage and Hill diversity. Coverage is a method for equalizing samples that is, on theoretical grounds, preferable to other commonly used methods such as equal-effort sampling, or rarefying datasets to equal sample size. Hill diversity comprises a spectrum of diversity metrics and is based on three key insights. First, species richness and variants of the Shannon and Simpson indices are all special cases of one general equation. Second, richness, Shannon and Simpson can be expressed on the same scale and in units of species. Third, there is no way to eliminate the effect of relative abundance from estimates of any of these diversity metrics, including species richness. Rather, a researcher must choose the relative sensitivity of the metric towards rare and common species, a concept which we describe as ‘leverage.' In this paper we explain coverage and Hill diversity, provide guidelines for how to use them together to measure species diversity, and demonstrate their use with examples from our own data. We show why researchers will obtain more robust results when they estimate the Hill diversity of equal-coverage samples, rather than using other methods such as equal-effort sampling or traditional sample rarefaction.     

Additive diversity partitioning in palaeobiology: revisiting Sepkoski’s question

Abstract: Using Whittaker’s concepts of alpha, beta, and gamma diversity, Sepkoski asked how global diversity was assembled at scales ranging from the community to the province. In the years since, ecologists have recast diversity in terms of additive partitions where total diversity can be decomposed into sample‐level alpha diversity plus the sum of a series of beta diversity terms that reflect progressively larger spatial scales. Given that marine alpha diversity represents a tiny fraction of global diversity, Phanerozoic global diversity patterns must be dominated by changes in beta diversity at one or more scales. A ballooning ecological literature demonstrates wide variation in beta diversity among ecosystems, regions, and taxa, suggesting that large changes in beta diversity on evolutionary timescales are likely. But the question is which scales are the most important. Several recent palaeontological studies help to constrain beta diversity within sedimentary basins, and the emergence of sample‐based databases puts an answer to Sepkoski’s question within reach. A new method for calculating diversity partitions for richness is introduced, which allows the calculation of each species’ contribution to alpha and beta diversity, as well as the contribution of each sampling unit to beta diversity.     

Components of beta diversity in hierarchical sampling designs: A new approach

Diversity partitioning has been generally used to estimate the contribution of different levels of sampling hierarchy to landscape diversity. However, beta diversity values derived by partitioning strongly depend on focus and sample size and the partitioning is inadequate to express the contribution of landscape elements to community variation. Pairwise dissimilarities are also frequently used to express community turnover, but related approaches capture only limited aspects of it, especially for hierarchical sampling designs. To avoid these shortcomings, we suggest a procedure which quantifies the role of different levels of sampling hierarchy (relative beta diversity) and the share of landscape elements in the corresponding relative beta diversity (contribution value). Our novel method uses pairwise dissimilarities and is based on partitioning a dissimilarity matrix of sampling units. It is suitable to testing various null hypotheses via permutation techniques as demonstrated by artificial and actual data. The method is a valuable tool in ecology because it complements existing approaches while providing a unique way to understand community diversity in space.     

Inference on diversity from forest inventories: a review

A number of international agreements and commitments emphasize the importance of appropriate monitoring protocols and assessments as prerequisites for sound conservation and management of the world’s forest ecosystems. Mandated periodic surveys, like forest inventories, provide a unique opportunity to identify and properly satisfy natural resource management information needs. Distinctively, there is an increasing need for detecting diversity by means of unambiguous diversity measures. Because all diversity measures are functions of tree species abundances, estimation of tree diversity indices and profiles is inevitably performed by estimating tree species abundances and then estimating indices and profiles as functions of the abundance estimates. This strategy can be readily implemented in the framework of current forest inventory approaches, where tree species abundances are routinely estimated by means of plots placed onto the surveyed area in accordance with probabilistic schemes. The purpose of this paper is to assess the effectiveness of this strategy by reviewing theoretical results from published case studies. Under uniform random sampling (URS), that is when plots are uniformly and independently located on the study region, consistency and asymptotic normality of diversity index estimators follow from standard limit theorems as the sampling effort increases. In addition, variance estimation and bias reduction are achieved using the jackknife method. Despite its theoretical simplicity, URS may lead to uneven coverage of the study region. In order to avoid unbalanced sampling, the use of tessellation stratified sampling (TSS) is suggested. TSS involves covering the study region by a polygonal grid and randomly selecting a plot in each polygon. Under TSS, the diversity index estimators are consistent, asymptotically normal and more precise than those achieved using URS. Variance estimation is possible and there is no need to reduce bias.     

Combining counts and incidence data: an efficient approach for estimating the log-normal species abundance distribution and diversity indices

Obtaining accurate estimates of diversity indices is difficult because the number of species encountered in a sample increases with sampling intensity. We introduce a novel method that requires that the presence of species in a sample to be assessed while the counts of the number of individuals per species are only required for just a small part of the sample. To account for species included as incidence data in the species abundance distribution, we modify the likelihood function of the classical Poisson log-normal distribution. Using simulated community assemblages, we contrast diversity estimates based on a community sample, a subsample randomly extracted from the community sample, and a mixture sample where incidence data are added to a subsample. We show that the mixture sampling approach provides more accurate estimates than the subsample and at little extra cost. Diversity indices estimated from a freshwater zooplankton community sampled using the mixture approach show the same pattern of results as the simulation study. Our method efficiently increases the accuracy of diversity estimates and comprehension of the left tail of the species abundance distribution. We show how to choose the scale of sample size needed for a compromise between information gained, accuracy of the estimates and cost expended when assessing biological diversity. The sample size estimates are obtained from key community characteristics, such as the expected number of species in the community, the expected number of individuals in a sample and the evenness of the community.     

Fungal diversity in ectomycorrhizal communities: sampling effort and species detection

A number of recent review articles on ectomycorrhizal (ECM) fungal community diversity have highlighted the unprecedented increase in the number of publications on this ecologically important but neglected area. The general features of these species-rich, highly dynamic and complex communities have been comprehensively covered but one aspect crucial to our assessment of diversity, namely the sampling of ECM communities has received less attention. This is a complex issue with two principal components, the physical sampling strategy employed and the life cycle traits of the ECM fungi being examined. Combined, these two components provide the image that we perceive as ECM diversity. This contribution will focus primarily on the former of these components using a recent study from a pine forest in central Sweden to highlight some sampling problems and also to discuss some features common to ECM communities. The two commonly used elements of diversity, species richness and community evenness, present rather different problems in the assessment of ECM diversity. The applicability of using current measures of abundance (number or percentage of root tips colonised) to determine community evenness is discussed in relation to our lack of knowledge on the size of individual genets of ECM fungi. The inherent structure of most ECM communities, with a few common species and a large number of rare species, severely limits our ability to accurately assess species richness. A discussion of theoretical detection limits is included that demonstrates the importance of the sampling effort (no. of samples or tips) involved in assessing species richness. Species area abundance plots are also discussed in this context. It is suggested that sampling strategy (bulk samples versus multiple collections of single tips) may have important consequences when sampling from communities where root tip densities differ. Finally, the need for studies of the spatial distribution of ECM on roots in relation to small-scale soil heterogeneity and of the temporal aspects of ECM community dynamics is raised.     

Estimating species richness using the jackknife procedure

An exact expression is given for the jackknife estimate of the number of species in a community and for the variance of this number when quadrat sampling procedures are used. The jackknife estimate is a function of the number of species that occur in one and only one quadrat. The variance of the number of species can be constructed, as can approximate two-sided confidence intervals. The behavior of the jackknife estimate, as affected by quadrat size, sample size and sampling area, is investigated by simulation.     

碧峰峡常绿阔叶林不同群落物种多样性和土壤理化性质

为了解四川碧峰峡景区常绿阔叶林群落物种多样性和土壤理化性质现状,提出利于森林经营管理及生物多样性保护的可靠方法,采用典型抽样法调查样地27个,通过聚类和排序将样地归类,探究不同类型群落物种多样性特征和土壤理化性质.结果 表明:Bray-Curtis距离为0.53时共聚出6类,山矾栲群落(Ⅰ)、山矾青冈群落(Ⅱ)、木荷山...