Taxon sampling, correlated evolution, and independent contrasts
Taxon sampling, correlated evolution, and independent contrasts
复制标题
DOI：
10.1111/j.0014-3820.2000.tb00694.x
复制
发表时间：
2000-10-01
期刊：
影响因子：
3.3
通讯作者：
Ackerly, DD
中科院分区：
文献类型：
--
作者：
Ackerly, DD
独立对比被广泛用于将系统发育信息纳入连续性状的研究，特别是进化性状相关性的分析，但分类单元采样对这些分析的影响却很少受到关注。在本文中，模拟研究的影响，分类单元的抽样模式和替代分支长度分配的相关系数和符号测试的统计性能;“全树”分析的基础上的对比在所有节点和“配对比较”的基础上，只有终端分类单元对的对比也进行了比较。模拟结果表明，随机样本，相对于所考虑的性状，提供统计上可靠的估计性状相关性。然而，精确的显著性检验高度依赖于适当的分支长度信息;相等的分支长度比替代拓扑方法保持较低的I型错误，并且提供了独立对比相关系数的调整临界值以用于相等的分支长度。非随机样本，相对于单变量或双变量性状分布，引入种间和遗传结构分析和潜在的进化相关性的偏差估计之间的差异。非随机抽样过程的例子可能包括社区组装过程，收敛进化在当地适应压力下，从栖息地或生活史组的物种的非随机样本的选择，或调查员的偏见。基于物种对比较的相关分析，而忽略了更深层次的关系，需要显着的统计能力的损失，因此提供了一个保守的测试性状协会。在比较植物生态学中引入的一种方法，即物种在一个性状上存在很大差异的配对比较，具有适当的I型错误率和较高的统计功效，但不能正确估计性状相关性的大小。基于全树或配对比较方法的符号测试在广泛的采样场景中具有高度可靠性，就I型错误率而言，但功效非常低。这些结果为选择品种和应用比较方法优化性状关联的统计检验提供了指导。
Independent contrasts are widely used to incorporate phylogenetic information into studies of continuous traits, particularly analyses of evolutionary trait correlations, but the effects of taxon sampling on these analyses have received little attention. In this paper, simulations were used to investigate the effects of taxon sampling patterns and alternative branch length assignments on the statistical performance of correlation coefficients and sign tests; ''full-tree'' analyses based on contrasts at all nodes and ''paired-comparisons'' based only on contrasts of terminal taxon pairs were also compared. The simulations showed that random samples, with respect to the traits under consideration, provide statistically robust estimates of trait correlations. However, exact significance tests are highly dependent on appropriate branch length information; equal branch lengths maintain lower Type I error than alternative topological approaches, and adjusted critical values of the independent contrast correlation coefficient are provided for use with equal branch lengths. Nonrandom samples, with respect to univariate or bivariate trait distributions, introduce discrepancies between interspecific and phylogenetically structured analyses and bias estimates of underlying evolutionary correlations. Examples of nonrandom sampling processes may include community assembly processes, convergent evolution under local adaptive pressures, selection of a nonrandom sample of species from a habitat or life-history group, or investigator bias. Correlation analyses based on species pairs comparisons, while ignoring deeper relationships, entail significant loss of statistical power and as a result provide a conservative test of trait associations. Paired comparisons in which species differ by a large amount in one trait, a method introduced in comparative plant ecology, have appropriate Type I error rates and high statistical power, but do not correctly estimate the magnitude of trait correlations. Sign tests, based on full-tree or paired-comparison approaches, are highly reliable across a wide range of sampling scenarios, in terms of Type I error rates, but have very low power. These results provide guidance for selecting species and applying comparative methods to optimize the performance of statistical tests of trait associations.