NONPARAMETRIC MULTIVARIATE ANALYSES OF CHANGES IN COMMUNITY STRUCTURE
NONPARAMETRIC MULTIVARIATE ANALYSES OF CHANGES IN COMMUNITY STRUCTURE
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DOI：
10.1111/j.1442-9993.1993.tb00438.x
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发表时间：
1993-03-01
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影响因子：
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通讯作者：
CLARKE, KR
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作者：
CLARKE, KR
20世纪80年代初，菲尔德等人（1982年）等将一种多变量（多物种）丰度数据的图形表示策略引入海洋生态学。十年过去了，以下做法是有启发意义的：（i）确定这一常被引用的策略中的哪些要素在实际评估污染影响导致的群落变化方面被证明是最有用的；（ii）探究在此期间技术的发展在多大程度上增加了该方法的自洽性和全面性。事实证明，关键概念是两个样本相似性的生物学相关定义，以及主要以简单排序形式对其的利用，例如“样本A与样本B的相似性大于它与样本C的相似性”。这样就将对数据的统计假设降至最低，由此产生的非参数技术将具有非常广泛的适用性。从这样一个起点出发，一个统一的框架需要包括：（i）通过样本的聚类和排序来展示群落模式；（ii）识别对确定样本分组起主要作用的物种；（iii）对空间和时间差异的统计检验（基于排序相似性的方差分析的多变量类似方法）；（iv）将群落差异与物理和化学环境模式相联系（后者也由样本之间的排序相似性决定）。文中描述了使这样一个框架得以建立的技术，并指出了仍然存在问题的领域。讨论了这些方法积累的实践经验，特别是在海洋底栖生物方面的应用，并得出结论认为它们对群落环境影响研究的实践者有很大帮助。
In the early 1980s, a strategy for graphical representation of multivariate (multi-species) abundance data was introduced into marine ecology by, among others, Field, et al. (1982). A decade on, it is instructive to: (i) identify which elements of this often-quoted strategy have proved most useful in practical assessment of community change resulting from pollution impact; and (ii) ask to what extent evolution of techniques in the intervening years has added self-consistency and comprehensiveness to the approach. The pivotal concept has proved to be that of a biologically-relevant definition of similarity of two samples, and its utilization mainly in simple rank form, for example 'sample A is more similar to sample B than it is to sample C'. Statistical assumptions about the data are thus minimized and the resulting non-parametric techniques will be of very general applicability. From such a starting point, a unified framework needs to encompass: (i) the display of community patterns through clustering and ordination of samples; (ii) identification of species principally responsible for determining sample groupings; (iii) statistical tests for differences in space and time (multivariate analogues of analysis of variance, based on rank similarities); and (iv) the linking of community differences to patterns in the physical and chemical environment (the latter also dictated by rank similarities between samples). Techniques are described that bring such a framework into place, and areas in which problems remain are identified. Accumulated practical experience with these methods is discussed, in particular applications to marine benthos, and it is concluded that they have much to offer practitioners of environmental impact studies on communities.