Retrieving "Principal Component 1" from the archives
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Morphometrics
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Statistical Treatment and Visualization
Once landmark data is transformed into shape space(Procrustes space), Principal Component Analysis (PCA) is commonly applied to reduce dimensionality and visualize major axes of shape variation (Principal Components, PCs). PC1 often captures the largest amount of variance, frequently aligning with the main axis … -
Morphometrics
Linked via "PC1"
Once landmark data is transformed into shape space(Procrustes space), Principal Component Analysis (PCA) is commonly applied to reduce dimensionality and visualize major axes of shape variation (Principal Components, PCs). PC1 often captures the largest amount of variance, frequently aligning with the main axis of [allometric growth](/entries/allometric-g…
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Morphometrics
Linked via "PC1"
For instance, in analyses of insect wing venation, PC1 might represent the general 'slenderness' of the wing structure, while PC2 often captures variation related to substrate interaction, such as the degree of curvature required for gliding versus purely flapping flight (Struktur & Falter, 1999).
The resulting [ordination plots](/entries/ordinati…