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Abstract PremiseStudies into the evolution and development of leaf shape have connected variation in plant form, function, and fitness. For species with consistent leaf margin features, patterns in leaf architecture are related to both biotic and abiotic factors. However, for species with inconsistent leaf shapes, quantifying variation in leaf shape and the effects of environmental factors on leaf shape has proven challenging. MethodsTo investigate leaf shape variation in a species with inconsistently shaped leaves, we used geometric morphometric modeling and deterministic techniques to analyze approximately 500 digitized specimens ofCapsella bursa‐pastoriscollected throughout the continental United States over 100 years. We generated a morphospace of the leaf shapes and modeled leaf shape as a function of environment and time. ResultsLeaf shape variation ofC. bursa‐pastoriswas strongly associated with temperature over its growing season, with lobing decreasing as temperature increased. While we expected to see changes in variation over time, our results show that the level of leaf shape variation was consistent over the 100 years. ConclusionsOur findings showed that species with inconsistent leaf shape variation can be quantified using geometric morphometric modeling techniques and that temperature is the main environmental factor influencing leaf shape variation.
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Composite modeling of leaf shape along shoots discriminates Vitis species better than individual leaves
PremiseLeaf morphology is dynamic, continuously deforming during leaf expansion and among leaves within a shoot. Here, we measured the leaf morphology of more than 200 grapevines (Vitisspp.) over four years and modeled changes in leaf shape along the shoot to determine whether a composite leaf shape comprising all the leaves from a single shoot can better capture the variation and predict species identity compared with individual leaves. MethodsUsing homologous universal landmarks found in grapevine leaves, we modeled various morphological features as polynomial functions of leaf nodes. The resulting functions were used to reconstruct modeled leaf shapes across the shoots, generating composite leaves that comprehensively capture the spectrum of leaf morphologies present. ResultsWe found that composite leaves are better predictors of species identity than individual leaves from the same plant. We were able to use composite leaves to predict the species identity of previously unassigned grapevines, which were verified with genotyping. DiscussionObservations of individual leaf shape fail to capture the true diversity between species. Composite leaf shape—an assemblage of modeled leaf snapshots across the shoot—is a better representation of the dynamic and essential shapes of leaves, in addition to serving as a better predictor of species identity than individual leaves.
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- Award ID(s):
- 1828149
- PAR ID:
- 10383368
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Applications in Plant Sciences
- Volume:
- 8
- Issue:
- 12
- ISSN:
- 2168-0450
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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