3D geometric morphometrics and missing-data. Can extant taxa give clues for the analysis of fossil primates?

Couette, Sébastien; White, Jess

doi:10.1016/j.crpv.2010.07.002

Cited by 28 publications

(33 citation statements)

References 27 publications

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“…This study differs from many others by simulating missing data from real landmark sets of complete specimens spanning several taxonomic groups (both extant and extinct) and morphological structures, whereas many similar previous studies have typically focused on more narrow taxonomic groups and single structures (Gunz et al . , ; Strauss & Atanassov ; Neeser, Ackermann & Gain ; Couette & White ; Brown, Arbour & Jackson ). This study also considered not just the amount of missing data but also the resulting frequency of incomplete specimens, and the effect of removing these specimens from the data set.…”

Section: Introductionmentioning

confidence: 99%

Incomplete specimens in geometric morphometric analyses

Arbour

Brown

2013

Methods Ecol Evol

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Summary 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‐data set approach to compare variation in missing data estimation and its effect on geometric morphometric analyses across taxonomically variable groups, landmark position and sample sizes. Missing morphometric landmark data were simulated from five real, complete data sets, 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 data set. Procrustes superimposition was used to compare the eigenvectors and principal component scores of a geometric morphometric analysis of the original landmark data, to data sets with A) missing values estimated, or B) simulated incomplete specimens excluded, for varying levels of specimens incompleteness and sample sizes. Standard estimation techniques were more reliable estimators and had lower impacts on morphometric analysis compared with a geometric‐morphometric‐specific estimator. For most data sets and estimation techniques, estimating missing data produced a better fit to the structure of the original data than exclusion of incomplete specimens, and this was maintained even at considerably reduced sample sizes. The impact of missing data on geometric morphometric analysis was disproportionately affected by the most fragmentary specimens. Missing data estimation was influenced by variability of specific anatomical features and may be improved by a better understanding of shape variation present in a data set. Our results suggest that the inclusion of incomplete specimens through the use of effective missing data estimators better reflects the patterns of shape variation within a data set than using only complete specimens; however, the effectiveness of missing data estimation can be maximized by excluding only the most incomplete specimens. It is advised that missing data estimators be evaluated for each data set and landmark independently, as the effectiveness of estimators can vary strongly and unpredictably between different taxa and structures.

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Section: Introductionmentioning

confidence: 99%

Incomplete specimens in geometric morphometric analyses

Arbour

Brown

2013

Methods Ecol Evol

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“…This is confi rmed by [14] and [18], who state that with fewer variables and more missing data, the estimation error increases. In contrast, [15] suggests that in the absence of a data rate of 20%, they cannot be reliably estimated because the estimation error exceeds 10%, and [12] says that 50% of missing data can be estimated with good accuracy. These simulation studies suggest that this strategy is promising [63] for environmental studies.…”

Section: Resultsmentioning

confidence: 97%

“…Several authors [15,[18][19][20] undertook the task of estimating the maximum part of missing data values. They showed that this is impossible because there is no mathematical upper limit for the missing data estimation.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

The Possibility of Applying the EM-PCA Procedure to Lake Water

Bucior-Kwaczyńska¹

2018

Pol. J. Environ. Stud.

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“…primates and humans). Furthermore, the existence of a wider sample size can still make the selection of reference specimens difficult, as a single fossil may not preserve all relevant anatomical features [71]. …”

Section: Discussionmentioning

confidence: 99%

Reconstructing the past: methods and techniques for the digital restoration of fossils

2016

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During fossilization, the remains of extinct organisms are subjected to taphonomic and diagenetic processes. As a result, fossils show a variety of preservational artefacts, which can range from small breaks and cracks, disarticulation and fragmentation, to the loss and deformation of skeletal structures and other hard parts. Such artefacts can present a considerable problem, as the preserved morphology of fossils often forms the basis for palaeontological research. Phylogenetic and taxonomic studies, inferences on appearance, ecology and behaviour and functional analyses of fossil organisms strongly rely on morphological information. As a consequence, the restoration of fossil morphology is often a necessary prerequisite for further analyses. Facilitated by recent computational advances, virtual reconstruction and restoration techniques offer versatile tools to restore the original morphology of fossils. Different methodological steps and approaches, as well as software are outlined and reviewed here, and advantages and disadvantages are discussed. Although the complexity of the restorative processes can introduce a degree of interpretation, digitally restored fossils can provide useful morphological information and can be used to obtain functional estimates. Additionally, the digital nature of the restored models can open up possibilities for education and outreach and further research.

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3D geometric morphometrics and missing-data. Can extant taxa give clues for the analysis of fossil primates?

Cited by 28 publications

References 27 publications

Incomplete specimens in geometric morphometric analyses

Incomplete specimens in geometric morphometric analyses

The Possibility of Applying the EM-PCA Procedure to Lake Water

Reconstructing the past: methods and techniques for the digital restoration of fossils

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