Abstract
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.