Phenotypic trajectory analysis: comparison of shape change patterns in evolution and ecology
Phenotypic trajectory analysis: comparison of shape change patterns in evolution and ecology
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DOI：
10.4404/hystrix-24.1-6298
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发表时间：
2013-01-01
影响因子：
1.5
通讯作者：
Adams, Dean C.
中科院分区：
文献类型：
--
作者：
Collyer, Michael L.;Adams, Dean C.
在生态学和进化生物学中，使用几何形态计量学（GM）方法的形状数据的研究通常是比较，分析沿着生态或进化梯度不同点的形状和形状变化。虽然标准的多变量统计程序对于多变量数据空间中群体位置差异的“静态”变异测试是很好的，但对于“动态”变异测试则是有限的，即测试群体随生态、发展或进化梯度状态变化而改变位置的具体方式差异。在本文中，我们证明了连续的表型变化可以用多变量数据空间中的轨迹来描述。我们描述了表型变化轨迹的几何属性（大小、方向和形状），特别是转基因数据。我们举例说明，这些属性的差异如何作为比较分析的测试统计，以了解产生形状变化动态差异的机制。我们证明，这种被称为表型轨迹分析（PTA）的属性分析是一种通用分析，可以应用于与测量动态变化有关的各种类型的研究问题。最后，我们对这种新分析方法的未来提出了一些挑战。
Research using shape data from geometric morphometric (GM) methods in ecology and evolutionary biology is typically comparative, analyzing shapes and shape change over different points along ecological or evolutionary gradients. Whereas standard multivariate statistics procedures are fine for "static" variation testing for location differences of groups in multivariate data spaces they are limited for "dynamic" variation - testing specific differences in the ways groups change locations associated with changes in state along ecological, developmental or evolutionary gradients. In this paper, we show that continuous phenotypic change can be described by trajectories in multivariate data spaces. We describe the geometric attributes of phenotypic change trajectories (size, direction, and shape), specifically for GM data. We illustrate, with examples, how differences in such attributes can function as test statistics for comparative analyses in order to understand the mechanisms that produce dynamic differences in shape change. We demonstrate that analysis of such attributes called phenotypic trajectory analysis (PTA) is a general analysis that can be applied to various types of research questions concerned with measuring dynamic variation. Finally, we posit some challenges for the future for this novel analytical method.