Data from: Incomplete specimens in geometric morphometric analyses ...
1.The analysis of morphological diversity frequently relies on the use of multivariate methods for characterizing biological shape. However, many of these methods are intolerant of missing data, which can limit the use of rare taxa and hinder the study of broad patterns of ecological diversity and m...
| Main Authors: | , |
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| Format: | Dataset |
| Language: | English |
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Dryad
2014
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.mp713 https://datadryad.org/stash/dataset/doi:10.5061/dryad.mp713 |
| Summary: | 1.The analysis of morphological diversity frequently relies on the use of multivariate methods for characterizing biological shape. However, many of these methods are intolerant of missing data, which can limit the use of rare taxa and hinder the study of broad patterns of ecological diversity and morphological evolution. This study applied a mutli-dataset approach to compare variation in missing data estimation and its effect on geometric morphometric analysis across taxonomically-variable groups, landmark position and sample sizes. 2.Missing morphometric landmark data was simulated from five real, complete datasets, including modern fish, primates and extinct theropod dinosaurs. Missing landmarks were then estimated using several standard approaches and a geometric-morphometric-specific method. The accuracy of missing data estimation was determined for each estimation method, landmark position, and morphological dataset. Procrustes superimposition was used to compare the eigenvectors and principal ... : Table 1 Arctic char landmarksThirteen landmarks from 121 specimens of Arctic char from Lake Hazen, Ellesmere Island, Canada (Arbour et al. 2011, Canadian Journal of Zoology 89(1):19-30).Table 2 Guianacara dacrya landmarksSixteen landmarks from 73 specimens, from the description of Guianacara dacrya (see Arbour and Lopez-Fernandez, 2011, Neotropical Ichthyology 9(1):87-96.) ... |
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