Barrantes Gilbert, Sandoval Luis
Escuela de Biología, Universidad de Costa Rica, Ciudad Universitaria Rodrigo Facio, San José, Costa Rica.
Rev Biol Trop. 2009 Sep;57(3):451-60. doi: 10.15517/rbt.v57i3.5467.
Diversity indices, particularly the Shannon-Wiener index, have extensively been used in analyzing patterns of diversity at different geographic and ecological scales. These indices have serious conceptual and statistical problems which make comparisons of species richness or species abundances across communities nearly impossible. There is often no a single statistical method that retains all information needed to answer even a simple question. However, multivariate analyses could be used instead of diversity indices, such as cluster analyses or multiple regressions. More complex multivariate analyses, such as Canonical Correspondence Analysis, provide very valuable information on environmental variables associated to the presence and abundance of the species in a community. In addition, particular hypotheses associated to changes in species richness across localities, or change in abundance of one, or a group of species can be tested using univariate, bivariate, and/or rarefaction statistical tests. The rarefaction method has proved to be robust to standardize all samples to a common size. Even the simplest method as reporting the number of species per taxonomic category possibly provides more information than a diversity index value.
多样性指数,尤其是香农 - 维纳指数,已被广泛用于分析不同地理和生态尺度下的多样性模式。这些指数存在严重的概念和统计问题,使得几乎不可能对不同群落间的物种丰富度或物种丰度进行比较。通常不存在一种能保留回答哪怕一个简单问题所需的所有信息的单一统计方法。然而,可以使用多元分析来替代多样性指数,比如聚类分析或多元回归。更复杂的多元分析,如典范对应分析,能提供关于与群落中物种的存在和丰度相关的环境变量的非常有价值的信息。此外,可以使用单变量、双变量和/或稀疏统计检验来检验与不同地点物种丰富度变化,或一个物种或一组物种丰度变化相关的特定假设。事实证明,稀疏方法对于将所有样本标准化到共同大小是稳健的。甚至像报告每个分类类别中的物种数量这样最简单的方法可能也比一个多样性指数值提供更多信息。