Abstract:
The foundations of geometric morphometrics were worked out about 30 years ago and have continually been refined and extended. What has remained as a central thrust and source of debate in the morphometrics community is the shared goal of meaningful biological inference through a tight connection between biological theory, measurement, multivariate biostatistics, and geometry. Here we review the building blocks of modern geometric morphometrics: the representation of organismal geometry by landmarks and semilandmarks, the computation of shape or form variables via superimposition, the visualization of statistical results as actual shapes or forms, the decomposition of shape variation into symmetric and asymmetric components and into different spatial scales, the interpretation of various geometries in shape or form space, and models of the association between shape or form and other variables, such as environmental, genetic, or behavioral data. We focus on recent developments and current methodological challenges, especially those arising from the increasing number of landmarks and semilandmarks, and emphasize the importance of thorough exploratory multivariate analyses rather than single scalar summary statistics. We outline promising directions for further research and for the evaluation of new developments, such as \"landmark-free\" approaches. To illustrate these methods, we analyze three-dimensional human face shape based on data from the Avon Longitudinal Study of Parents and Children (ALSPAC).
摘要:
几何形态计量学的基础是大约30年前制定的,并不断被完善和扩展。形态计量学界一直是争论的中心重点和根源,是通过生物学理论之间的紧密联系来实现有意义的生物学推断的共同目标。测量,多元生物统计学,和几何。在这里,我们回顾了现代几何形态计量学的基础:通过地标和半地标表示有机几何,通过叠加计算形状或形式变量,将统计结果可视化为实际形状或形式,将形状变化分解为对称和非对称分量以及不同的空间尺度,对形状或形式空间中各种几何形状的解释,以及形状或形式与其他变量之间的关联模型,如环境、遗传,或行为数据。我们专注于最近的发展和当前的方法挑战,特别是那些由越来越多的地标和半地标产生的,并强调彻底的探索性多变量分析而不是单一标量汇总统计的重要性。我们概述了进一步研究和评估新发展的有希望的方向,例如“无地标”方法。为了说明这些方法,我们根据雅芳父母和子女纵向研究(ALSPAC)的数据分析三维人脸形状。