Shui Wuyang, Profico Antonio, O'Higgins Paul
Department of Archaeology, University of York, King's Manor, York YO1 7EP, UK.
Department of Biology, University of Pisa, Via Derna 1, 56126 Pisa, Italy.
Animals (Basel). 2023 Mar 28;13(7):1179. doi: 10.3390/ani13071179.
Often, few landmarks can be reliably identified in analyses of form variation and covariation. Thus, 'semilandmarking' algorithms have increasingly been applied to surfaces and curves. However, the locations of semilandmarks depend on the investigator's choice of algorithm and their density. In consequence, to the extent that different semilandmarking approaches and densities result in different locations of semilandmarks, they can be expected to yield different results concerning patterns of variation and co-variation. The extent of such differences due to methodology is, as yet, unclear and often ignored. In this study, the performance of three landmark-driven semilandmarking approaches is assessed, using two different surface mesh datasets (ape crania and human heads) with different degrees of variation and complexity, by comparing the results of morphometric analyses. These approaches produce different semilandmark locations, which, in turn, lead to differences in statistical results, although the non-rigid semilandmarking approaches are consistent. Morphometric analyses using semilandmarks must be interpreted with due caution, recognising that error is inevitable and that results are approximations. Further work is needed to investigate the effects of using different landmark and semilandmark templates and to understand the limitations and advantages of different semilandmarking approaches.
在形态变异和协变异分析中，通常很少有地标能被可靠地识别出来。因此，“半地标”算法越来越多地应用于曲面和曲线。然而，半地标的位置取决于研究者对算法的选择及其密度。因此，不同的半地标方法和密度会导致半地标位置不同，由此可以预期它们会在变异模式和协变异模式方面产生不同的结果。目前，由于方法学导致的这种差异程度尚不清楚，且常常被忽视。在本研究中，通过比较形态测量分析的结果，使用具有不同变异程度和复杂度的两个不同表面网格数据集（猿类颅骨和人类头部），评估了三种由地标驱动的半地标方法的性能。这些方法产生不同的半地标位置，进而导致统计结果的差异，尽管非刚性半地标方法是一致的。使用半地标进行形态测量分析时必须谨慎解释，要认识到误差不可避免，结果只是近似值。需要进一步开展工作来研究使用不同地标和半地标模板的影响，并了解不同半地标方法的局限性和优势。
