Dipartimento di Scienze Chimiche e Geologiche, Università di Modena e Reggio Emilia, Modena, Italy.
School of Anatomy, Physiology and Human Biology, The University of Western Australia, Crawley, Western Australia, Australia.
Anat Rec (Hoboken). 2020 Nov;303(11):2747-2765. doi: 10.1002/ar.24397. Epub 2020 Apr 6.
The study of phenotypic variation in time and space is central to evolutionary biology. Modern geometric morphometrics is the leading family of methods for the quantitative analysis of biological forms. This set of techniques relies heavily on technological innovation for data acquisition, often in the form of 2D or 3D digital images, and on powerful multivariate statistical tools for their analysis. However, neither the most sophisticated device for computerized imaging nor the best statistical test can produce accurate, robust and reproducible results, if it is not based on really good samples and an appropriate use of the 'measurements' extracted from the data. Using examples mostly from my own work on mammal craniofacial variation and museum specimens, I will show how easy it is to forget these most basic assumptions, while focusing heavily on analytical and visualization methods, and much less on the data that generate potentially powerful analyses and visually appealing diagrams.
研究表型在时间和空间上的变化是进化生物学的核心。现代几何形态测量学是生物形态定量分析的主要方法。这组技术严重依赖于技术创新来获取数据，通常采用 2D 或 3D 数字图像的形式，并且依靠强大的多元统计工具进行分析。然而，如果不是基于真正良好的样本和对从数据中提取的“测量值”的适当使用，即使是最先进的计算机成像设备或最好的统计检验也无法产生准确、稳健和可重复的结果。我将通过主要来自于我自己在哺乳动物颅面变异和博物馆标本方面的工作的例子，展示人们很容易忘记这些最基本的假设，而将重点放在分析和可视化方法上，而对生成潜在强大分析和视觉上吸引人的图表的数据关注较少。
