Suppr超能文献

生态研究中两态多变量表型变化的分析

Analysis of two-state multivariate phenotypic change in ecological studies.

作者信息

Collyer Michael L, Adams Dean C

机构信息

Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, Iowa 50011, USA.

出版信息

Ecology. 2007 Mar;88(3):683-92. doi: 10.1890/06-0727.

Abstract

Analyses of two-state phenotypic change are common in ecological research. Some examples include phenotypic changes due to phenotypic plasticity between two environments, changes due to predator/non-predator character shifts, character displacement via competitive interactions, and patterns of sexual dimorphism. However, methods for analyzing phenotypic change for multivariate data have not been rigorously developed. Here we outline a method for testing vectors of phenotypic change in terms of two important attributes: the magnitude of change (vector length) and the direction of change described by trait covariation (angular difference between vectors). We describe a permutation procedure for testing these attributes, which allows non-targeted sources of variation to be held constant. We provide examples that illustrate the importance of considering vector attributes of phenotypic change in biological studies, and we demonstrate how greater inference can be made than by evaluating variance components with MANOVA alone. Finally, we consider how our method may be extended to more complex data.

摘要

对两态表型变化的分析在生态学研究中很常见。一些例子包括由于两种环境之间的表型可塑性导致的表型变化、由于捕食者/非捕食者特征转变引起的变化、通过竞争相互作用产生的特征替代以及两性异形模式。然而,用于分析多变量数据的表型变化的方法尚未得到严格开发。在这里,我们概述了一种根据两个重要属性来测试表型变化向量的方法:变化幅度(向量长度)和由性状协变描述的变化方向(向量之间的角度差异)。我们描述了一种用于测试这些属性的排列程序,该程序允许非目标变异源保持不变。我们提供了一些例子,说明了在生物学研究中考虑表型变化的向量属性的重要性,并且我们展示了如何通过这种方法比仅使用多变量方差分析(MANOVA)评估方差成分能做出更多的推断。最后,我们考虑了我们的方法如何扩展到更复杂的数据。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验