TY - JOUR
T1 - A practical, step-by-step, guide to taxonomic comparisons using Procrustes geometric morphometrics and user-friendly software (part A)
T2 - introduction and preliminary analyses
AU - Cardini, Andrea
N1 - Publisher Copyright:
© 2024, Museum National d'Histoire Naturelle. All rights reserved.
PY - 2024/5/15
Y1 - 2024/5/15
N2 - Taxonomy lays the foundations for the study of biodiversity and its conservation. Procrustean geometric morphometrics (GMM) is a most common technique for the taxonomic assessment of phenotypic population differences. To measure biological variation and detect evolutionarily significant units, GMM is often used on its own, although it is much more powerful with an integrative approach, in combination with molecular, ecological and behavioural data, as well as with meristic morphological traits. GMM is particularly effective in taxonomic research, when applied to 2D images, which are fast and low cost to obtain. Yet, taxonomists who may want to explore the usefulness of GMM are rarely experts in multivariate statistical analyses of size and shape differences. In these twin papers, I aim to provide a detailed step-by-step guideline to taxonomic analysis employing Procrustean GMM in user-friendly software (with tips for R users). In the fi rst part (A) of the study, I will focus on preliminary analyses (mainly, measurement error, outliers and statistical power), which are fundamental for accuracy, but often neglected. I will also use this fi rst paper, and its appendix (Appendix A), to informally introduce, and discuss, general topics in GMM and statistics, that are relevant to taxonomic applications. In the second part (B) of the work, I will move on to the main taxonomic analyses. Thus, I will show how to compare size and shape among groups, but I will also explore allometry and briefly examine differences in variance, as a potential clue to population bottlenecks in peripheral isolates. A large sample of North American marmot mandibles provides the example data (available online, for readers to replicate the study and practice with analyses). However, as this sample is larger than in previous studies and mostly unpublished, it also offers a chance to further explore the patterns of interspecific morphological variation in a group, that has been prominent in mammalian sociobiology, and whose evolutionary divergence is complex and only partially understood.
AB - Taxonomy lays the foundations for the study of biodiversity and its conservation. Procrustean geometric morphometrics (GMM) is a most common technique for the taxonomic assessment of phenotypic population differences. To measure biological variation and detect evolutionarily significant units, GMM is often used on its own, although it is much more powerful with an integrative approach, in combination with molecular, ecological and behavioural data, as well as with meristic morphological traits. GMM is particularly effective in taxonomic research, when applied to 2D images, which are fast and low cost to obtain. Yet, taxonomists who may want to explore the usefulness of GMM are rarely experts in multivariate statistical analyses of size and shape differences. In these twin papers, I aim to provide a detailed step-by-step guideline to taxonomic analysis employing Procrustean GMM in user-friendly software (with tips for R users). In the fi rst part (A) of the study, I will focus on preliminary analyses (mainly, measurement error, outliers and statistical power), which are fundamental for accuracy, but often neglected. I will also use this fi rst paper, and its appendix (Appendix A), to informally introduce, and discuss, general topics in GMM and statistics, that are relevant to taxonomic applications. In the second part (B) of the work, I will move on to the main taxonomic analyses. Thus, I will show how to compare size and shape among groups, but I will also explore allometry and briefly examine differences in variance, as a potential clue to population bottlenecks in peripheral isolates. A large sample of North American marmot mandibles provides the example data (available online, for readers to replicate the study and practice with analyses). However, as this sample is larger than in previous studies and mostly unpublished, it also offers a chance to further explore the patterns of interspecific morphological variation in a group, that has been prominent in mammalian sociobiology, and whose evolutionary divergence is complex and only partially understood.
KW - Group differences
KW - marmot mandible
KW - measurement error
KW - outliers
KW - P values
KW - replicability
KW - sampling error
KW - shape analysis
UR - http://www.scopus.com/inward/record.url?scp=85197243872&partnerID=8YFLogxK
U2 - 10.5852/ejt.2024.934.2527
DO - 10.5852/ejt.2024.934.2527
M3 - Article
AN - SCOPUS:85197243872
SN - 2118-9773
VL - 934
SP - 1
EP - 92
JO - European Journal of Taxonomy
JF - European Journal of Taxonomy
ER -