SIMILARITY-BASED TESTING FOR COMMUNITY PATTERN - THE 2-WAY LAYOUT WITH NO REPLICATION
SIMILARITY-BASED TESTING FOR COMMUNITY PATTERN - THE 2-WAY LAYOUT WITH NO REPLICATION
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DOI：
10.1007/bf00699231
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发表时间：
1994-01-01
期刊：
影响因子：
2.4
通讯作者：
WARWICK, RM
中科院分区：
文献类型：
--
作者：
CLARKE, KR;WARWICK, RM
实地和实验群落研究中出现的大量稀疏的物种计数并不适合基于多元正态性的标准统计检验。相反，一种有效且更具启发性的方法使用非正式的显示方法，例如聚类或多维尺度排序（MDS），基于物种组成方面样本成对相似性的生物学定义。然而，仍然需要正式的测试方法来确定地点、时间、实验处理、污染状态等之间存在真正的组合差异。早期的工作描述了一系列曼特尔型排列或随机化程序，不做任何分布假设，被称为 ANOSIM 测试，因为它们仅依赖于（等级）相似性以及与单向和双向方差分析的类比。本文扩展了这些测试，以涵盖以前未考虑的重要实际案例，即无需复制的双向布局。这种情况出现在对多个地点随时间进行的基线监测调查中采集的单个样本（或伪重复），或者在每个实验“块”内仅重复“处理”一次的中生态实验中。根据每个区块（或地点）内样本的等级相似性之间的一致性测量，对处理（或时间）效应的整体存在进行显着性测试；可以颠倒这两个因素的作用以获得块效应检验。与类似的单变量方差分析测试一样，该方法依赖于治疗 x 块“相互作用”的缺失或相对较弱。其范围通过两项实验和两项实地研究的数据进行了说明，涉及软沉积物和大型藻类栖息地的小型底栖动物群落。人们还认为它可以容纳一定程度的缺失数据。虽然不鼓励未能充分复制（通过真正的复制可以获得更丰富的推论），但该论文确实为在没有重复的情况下进行假设检验提供了有限的方法。
The large, sparse arrays of species counts arising in both field and experimental community studies do not lend themselves to standard statistical tests based on multivariate normality. Instead, a valid and more revealing approach uses informal display methods, such as clustering or multi-dimensional scaling ordination (MDS), based on a biologically-motivated definition of pairwise similarity of samples in terms of species composition. Formal testing methods are still required, however, to establish that real assemblage differences exist between sites, times, experimental treatments, pollution states, etc. Earlier work has described a range of Mantel-type permutation or randomisation procedures, making no distributional assumptions, which are termed ANOSIM tests because of their dependence only on (rank) similarities and the analogy to one and two-way ANOVA. This paper extends these tests to cover an important practical case, previously unconsidered, that of a two-way layout without replication. Such cases arise for single samples (or pseudo-replicates) taken in a baseline monitoring survey of several sites over time, or a mesocosm experiment in which ''treatments'' are replicated only once within each experimental ''block''. Significance tests are given for the overall presence of a treatment (or time) effect, based on a measure of concordance between rank similarities of samples within each block (or site); the role of the two factors can be reversed to obtain a test for block effects. As in the analogous univariate ANOVA test, the method relies on absence or relative weakness of treatment x block ''interactions''. Its scope is illustrated with data from two experimental and two field studies, involving meiofaunal communities from soft-sediment and macro-algal habitats. It is seen also to accommodate a modest degree of missing data. Whilst the failure to replicate adequately is not encouraged-a richer inference is available with genuine replication-the paper does provide a limited way forward for hypothesis testing in the absence of replicates.