On the selection of phylogenetic eigenvectors for ecological analyses
On the selection of phylogenetic eigenvectors for ecological analyses
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DOI：
10.1111/j.1600-0587.2011.06949.x
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发表时间：
2012-03-01
期刊：
影响因子：
5.9
通讯作者：
Hawkins, Bradford A.
中科院分区：
文献类型：
--
作者：
Diniz-Filho, Jose Alexandre F.;Bini, Luis Mauricio;Hawkins, Bradford A.
在控制生态学数据中系统发育自相关性的统计方法中，基于物种间系统发育距离矩阵的特征函数分析的方法正成为越来越重要的工具。在这里，我们评估了一系列的标准来选择特征向量提取的系统发育距离矩阵（使用系统发育特征向量回归，PVR），可用于测量生态数据中的系统发育信号的水平，并研究相关的进化。我们使用主坐标分析来表示209种食肉动物之间的系统发育关系的一系列特征向量，然后使用模型的对数转换的身体大小。我们首先进行了一系列的PVR，其中我们将特征向量的数量从1增加到70，遵循其相关特征值的顺序。其次，我们还研究了三种非顺序的方法，基于选择1）与身体大小显著相关的特征向量，2）由标准逐步算法选择的特征向量，和3）最小化残留系统发育自相关的特征向量的组合。我们绘制了身体大小的平均特定成分，以评估这些选择标准如何影响伯格曼规则中非系统发育信号的解释。为了比较，相同的模式进行了分析，使用自回归模型（ARM）和系统发育广义最小二乘法（PGLS）。尽管PVR的鲁棒性的特定方法来选择特征向量，使用相对较少的特征向量可能不足以控制系统发育自相关，导致有缺陷的结论模式和过程。根据不同的标准，最小化残差自相关的方法似乎是最好的选择。因此，我们的分析表明，当最好的标准是用来控制系统发育结构，PVR可以是一个有价值的工具，用于测试相关的假设，遗传力在物种水平上，系统发育生态位保守性和生态性状之间的相关进化。
Among the statistical methods available to control for phylogenetic autocorrelation in ecological data, those based on eigenfunction analysis of the phylogenetic distance matrix among the species are becoming increasingly important tools. Here, we evaluate a range of criteria to select eigenvectors extracted from a phylogenetic distance matrix (using phylogenetic eigenvector regression, PVR) that can be used to measure the level of phylogenetic signal in ecological data and to study correlated evolution. We used a principal coordinate analysis to represent the phylogenetic relationships among 209 species of Carnivora by a series of eigenvectors, which were then used to model log-transformed body size. We first conducted a series of PVRs in which we increased the number of eigenvectors from 1 to 70, following the sequence of their associated eigenvalues. Second, we also investigated three non-sequential approaches based on the selection of 1) eigenvectors significantly correlated with body size, 2) eigenvectors selected by a standard stepwise algorithm, and 3) the combination of eigenvectors that minimizes the residual phylogenetic autocorrelation. We mapped the mean specific component of body size to evaluate how these selection criteria affect the interpretation of non-phylogenetic signal in Bergmann's rule. For comparison, the same patterns were analyzed using autoregressive model (ARM) and phylogenetic generalized least-squares (PGLS). Despite the robustness of PVR to the specific approaches used to select eigenvectors, using a relatively small number of eigenvectors may be insufficient to control phylogenetic autocorrelation, leading to flawed conclusions about patterns and processes. The method that minimizes residual autocorrelation seems to be the best choice according to different criteria. Thus, our analyses show that, when the best criterion is used to control phylogenetic structure, PVR can be a valuable tool for testing hypotheses related to heritability at the species level, phylogenetic niche conservatism and correlated evolution between ecological traits.