Modern morphometrics and the study of population differences: Good data behind clever analyses and cool pictures?

Cardini, Andrea

doi:10.1002/ar.24397

Cited by 19 publications

(21 citation statements)

References 86 publications

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“…If possible, tests should be performed using the exact same set of reference specimens. That being said, error should always be interpreted in the context of the biological question explored [ 14 , 21 , 37 ]. The amount of acceptable error will indeed depend on the data used and the comparisons being made [ 17 , 21 , 38 , 39 ].…”

Section: Discussionmentioning

confidence: 99%

“…A common question when starting a study is about how many landmarks or measurements should be used to accurately quantify variation. The answer is never straightforward and as this study shows, more is not always better [ 9 , 37 ]. Measuring effort should be contrasted with the aims of the study and the number of coordinates acquired depends on the complexity of the structure measured.…”

Section: Discussionmentioning

confidence: 99%

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Optimizing digitalization effort in morphometrics

Evin

Bonhomme

Julien

2020

Biology Methods and Protocols

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Quantifying phenotypes is a common practice for addressing questions regarding morphological variation. The time dedicated to data acquisition can vary greatly depending on methods and on the required quantity of information. Optimizing digitization effort can be done either by pooling datasets among users, by automatizing data collection, or by reducing the number of measurements. Pooling datasets among users is not without risk since potential errors arising from multiple operators in data acquisition prevents combining morphometric datasets. We present an analytical workflow to estimate within and among operator biases and to assess whether morphometric datasets can be pooled. We show that pooling and sharing data requires careful examination of the errors occurring during data acquisition, that the choice of morphometric approach influences amount of error, and that in some cases pooling data should be avoided. The demonstration is based on a worked example (Sus scrofa teeth) using a combinations of 18 morphometric approaches and datasets for which we identified and quantified several potential sources of errors in the workflow. We show that it is possible to estimate the analytical power of a study using a small subset of data to select the best morphometric protocol and to optimize the number of variables necessary for analysis. In particular, we focus on semi-landmarks, which often produce an inflation of variables in contrast to the number of available observations use in statistical testing. We show how the workflow can be used for optimizing digitization efforts and provide recommendations for best practices in error management.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Optimizing digitalization effort in morphometrics

Evin

Bonhomme

Julien

2020

Biology Methods and Protocols

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“…Yet, large variance might instead reflect genuine variability in relation to the specific evolutionary history, pattern of distribution and breadth of ecological adaptations or degree of plasticity of a species. However, variance could also be biased by how well the museum samples cover the full geographic range of a species (Albrecht and Miller, 1993;Cope, 1993;Harrison, 1993;Cardini, 2020a). For D. novemcintus, a small variance is almost certainly an artefact of sampling.…”

Section: Bg-rv: How Much Do Mean Shapes Vary Because Of Sampling Erro...mentioning

confidence: 99%

On the Misidentification of Species: Sampling Error in Primates and Other Mammals Using Geometric Morphometrics in More Than 4000 Individuals

et al. 2021

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An accurate classification is the basis for research in biology. Morphometrics and morphospecies play an important role in modern taxonomy, with geometric morphometrics increasingly applied as a favourite analytical tool. Yet, really large samples are seldom available for modern species and even less common in palaeontology, where morphospecies are often identified, described and compared using just one or a very few specimens. The impact of sampling error and how large a sample must be to mitigate the inaccuracy are important questions for morphometrics and taxonomy. Using more than 4000 crania of adult mammals and taxa representing each of the four placental superorders, we assess the impacts of sampling error on estimates of species means, variances and covariances in Procrustes shape data using resampling experiments. In each group of closely related species (mostly congeneric), we found that a species can be identified fairly accurately even when means are based on relatively small samples, although errors are frequent with fewer specimens and primates more prone to inaccuracies. A precise reconstruction of similarity relationships, in contrast, sometimes requires very large samples (> 100), but this varies widely depending on the study group. Medium-sized samples are necessary to accurately estimate standard errors of mean shapes or intraspecific variance covariance structure, but in this case minimum sample sizes are broadly similar across all groups (≈ 20-50 individuals). Overall, thus, the minimum sample sized required for a study varies across taxa and depends on what is being assessed, but about 25-40 specimens (for each sex, if a species is sexually dimorphic) may be on average an adequate and attainable minimum sample size for estimating the most commonly used shape parameters. As expected, the best predictor of the effects of sampling error is the ratio of between-to within-species variation: the larger the ratio, the smaller the sample size needed to obtain the same level of accuracy. Even though ours is the largest study to date of the uncertainties in estimates of means, variances and covariances in geometric morphometrics, and despite its generally high congruence with previous analyses, we feel it would be premature to generalize. Clearly, there is no a priori answer for what minimum sample size is required for a particular study and no universal recipe to control for sampling error. Exploratory analyses using resampling experiments are thus desirable, easy to perform and yield powerful preliminary clues about the effect of sampling on parameter estimates in comparative studies of morphospecies, and in a variety of other morphometric applications in biology and medicine. Morphospecies descriptions are indeed a small piece of provisional evidence in a much more complex evolutionary puzzle. However, they are crucial in palaeontology, and provide important complimentary evidence in modern integrative taxonomy. Thus, if taxonomy provides the bricks for accurate research in biology, understanding th...

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“…First, we use virtual surfaces derived from high‐resolution microcomputed tomography to characterize the three skeletal states and their distribution across the species of Brachycephalus sampled here. Second, we use three‐dimensional geometric morphometrics (3DGM; Cardini, 2020; Mitteroecker, 2020) to characterize skull diversity in Brachycephalus in ordinated shape space (Mitteroecker, 2020). From a geometric perspective, the scale of description of shape is determined by the density of points, registered as Cartesian coordinates, sampled from individual phenotypes.…”

Section: Introductionmentioning

confidence: 99%

Skull diversity and evolution in miniaturized amphibians, genus Brachycephalus (Anura: Brachycephalidae)

Reis

Clemente-Carvalho

Santos

et al. 2020

The Anatomical Record

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Miniaturized amphibians of the genus Brachycephalus are phenotypically diverse. The species of Brachycephalus have bufoniform or leptodactyliform Baupläne and any of three skeletal states: nonhyperossified, hyperossified without dorsal shield, and hyperossified with dorsal shield. We integrate highresolution microcomputed tomography, geometric morphometrics, and an estimate of molecular phylogenetic relationships to investigate skull diversity in shape and size-shape space in selected species of Brachycephalus. Skull diversity amongst species of Brachycephalus can be partitioned into shape and size-shape space according to the four conditions of skeletal states-Baupläne, namely, nonhyperossified leptodactyliform, nonhyperossified bufoniform, hyperossified bufoniform without dorsal shield, and hyperossified bufoniform with dorsal shield. Skull diversity in shape and size-shape space in nonhyperossified leptodactyliform species of Brachycephalus is markedly larger, when compared to skull diversity in species of the three other conditions of skeletal states-Baupläne. Variation in skull shape scales with size across Brachycephalus and, therefore, can be explained by allometry. Skull diversity, Baupläne, and skeletal states covary to a large extent with monophyletic lineages of Brachycephalus, as revealed by a mitochondrial DNA species tree. Nonhyperossified bufoniform species and hyperossified bufoniform species with or without dorsal shield are monophyletic lineages, as inferred from a mitochondrial DNA species tree. Nonhyperossified leptodactyliform species of Brachycephalus do not share, however, a most recent common ancestor. The nonhyperossified leptodactyliform species of Brachycephalus, due to their marked skull diversity and lack of monophyly, emerge as evolutionarily complex. Therefore, further sampling of the nonhyperossified leptodactyliform condition of skeletal states-Baupläne will be necessary to further understand the evolutionary history of Brachycephalus.

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Modern morphometrics and the study of population differences: Good data behind clever analyses and cool pictures?

Cited by 19 publications

References 86 publications

Optimizing digitalization effort in morphometrics

Optimizing digitalization effort in morphometrics

On the Misidentification of Species: Sampling Error in Primates and Other Mammals Using Geometric Morphometrics in More Than 4000 Individuals

Skull diversity and evolution in miniaturized amphibians, genus Brachycephalus (Anura: Brachycephalidae)

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