Bolstering geometric morphometrics sample sizes with damaged and pathologic specimens: Is near enough good enough?
Bolstering geometric morphometrics sample sizes with damaged and pathologic specimens: Is near enough good enough?
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用受损和病理标本增强几何形态测量样本量：接近足够好了吗？
DOI：
10.1111/joa.13390
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发表时间：
2021
影响因子：
2.4
通讯作者：
Terhune, Claire E.
中科院分区：
文献类型：
--
作者：
Mitchell, D. Rex;Kirchhoff, Claire A.;Cooke, Siobhán B.;Terhune, Claire E.
获取几何形态测量学研究的坐标数据通常涉及从博物馆藏品中采样干燥的骨骼标本。但许多标本显示出损伤和/或病理情况。这样的标本可以被认为不足以进行形状分析，因此被排除在研究之外。然而，受损标本可能对正常形状变化的评估的影响仅在二维坐标数据中进行了探索，到目前为止还没有研究涉及病理标本的纳入。我们收集了100只食蟹猕猴的头骨和下颌骨的三维坐标数据。通常用来分析形状变化的测试是在五个数据集上进行的，其中包括具有不同程度损伤/病理的标本。我们假设，将这些标本纳入更大的数据集将加强对性别和大小等主要生物形状预测指标的统计支持。然而，我们也预计，仅对最有问题的样本进行分析可能会混淆统计结果。然后，我们分析了一小部分高质量的样本，这些样本得到了通常因损伤或病理形态而被排除在外的样本的支持，并将结果与之前的分析进行了比较。将受损/病理标本纳入更大的数据集中，导致与异速生长、性二态和协变相关的变异增加，这支持了我们最初的假设。我们发现，单独分析最有问题的样本，对于形状的最主要方面给出了一致的结果，但可能会影响影响较小的主成分和预测值的输出。用受损/病理标本支撑的小数据集对形状的主要组成部分提供了充分的评估，但也发现了更细微的尺度差异。我们认为，显示损伤和/或病理的标本所贡献的正常和可重复的变异强调了较大数据集的主要成分和形状预测因子，然而，对于有限的样本量，各种独特的条件可能更有影响。此外，我们发现，在某些情况下，排除受损/病理标本可以忽略更有可能表现出这些情况的个体群体的重要的特定于人口统计学的形状变化。这些发现为将这些标本纳入集中于种内形状变异的主要方面的研究提供了强有力的证据。然而，当测试与形态的更细微方面相关的假设时，它们可能会提出问题。
Obtaining coordinate data for geometric morphometric studies often involves the sampling of dry skeletal specimens from museum collections. But many specimens exhibit damage and/or pathologic conditions. Such specimens can be considered inadequate for the analyses of shape and are excluded from study. However, the influences that damaged specimens may have on the assessment of normal shape variation have only been explored in two‐dimensional coordinate data and no studies have addressed the inclusion of pathological specimens to date. We collected three‐dimensional coordinate data from the cranium and mandible of 100 crab‐eating macaques (Macaca fascicularis). Tests typically employed to analyze shape variation were performed on five datasets that included specimens with varying degrees of damage/pathology. We hypothesized that the inclusion of these specimens into larger datasets would strengthen statistical support for dominant biological predictors of shape, such as sex and size. However, we also anticipated that the analysis of only the most questionable specimens may confound statistical outputs. We then analyzed a small sample of good quality specimens bolstered by specimens that would generally be excluded due to damage or pathologic morphology and compared the results with previous analyses. The inclusion of damaged/pathologic specimens in a larger dataset resulted in increased variation linked to allometry, sexual dimorphism, and covariation, supporting our initial hypothesis. We found that analyzing the most questionable specimens alone gave consistent results for the most dominant aspects of shape but could affect outputs for less influential principal components and predictors. The small dataset bolstered with damaged/pathologic specimens provided an adequate assessment of the major components of shape, but finer scale differences were also identified. We suggest that normal and repeatable variation contributed by specimens exhibiting damage and/or pathology emphasize the dominant components and shape predictors in larger datasets, however, the various unique conditions may be more influential for limited sample sizes. Furthermore, we find that exclusion of damaged/pathologic specimens can, in some cases, omit important demographic‐specific shape variation of groups of individuals more likely to exhibit these conditions. These findings provide a strong case for inclusion of these specimens into studies that focus on the dominant aspects of intraspecific shape variation. However, they may present issues when testing hypotheses relating to more fine‐scale aspects of morphology.
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DOI：
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