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Summary Different methods of measuring cavitation resistance in fern petioles lead to variable results, particularly with respect to the P50metric. We hypothesised that the fern dictyostele structure affects air entry into the xylem, and therefore impacts the shape of the vulnerability curve.Our study examined this variation by comparing vulnerability curves constructed on petioles collected from evergreen and deciduous ferns in the field, with curves generated using the standard centrifuge, air‐injection and bench‐top dehydration methods. Additional experiments complemented the vulnerability curves to better understand how anatomy shapes estimates of cavitation resistance.Centrifugation and radial air injection generated acceptable vulnerability curves for the deciduous species, but overestimated drought resistance in the two evergreen ferns. In these hardy plants, axial air injection and bench‐top dehydration produced results that most closely aligned with observations in nature. Additional experiments revealed that the dictyostele anatomy impedes air entry into the xylem during spinning and radial air injection.Each method produced acceptable vulnerability curves, depending on the species being tested. Therefore, we stress the importance of validating the curves within situmeasures of water potential and, if possible, hydraulic data to generate realistic results with any of the methods currently available.
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Analysis of shape data: From landmarks to elastic curves
Abstract Proliferation of high‐resolution imaging data in recent years has led to substantial improvements in the two popular approaches for analyzing shapes of data objects based on landmarks and/or continuous curves. We provide an expository account of elastic shape analysis of parametric planar curves representing shapes of two‐dimensional (2D) objects by discussing its differences, and its commonalities, to the landmark‐based approach. Particular attention is accorded to the role of reparameterization of a curve, which in addition to rotation, scaling and translation, represents an important shape‐preserving transformation of a curve. The transition to the curve‐based approach moves the mathematical setting of shape analysis from finite‐dimensional non‐Euclidean spaces to infinite‐dimensional ones. We discuss some of the challenges associated with the infinite‐dimensionality of the shape space, and illustrate the use of geometry‐based methods in the computation of intrinsic statistical summaries and in the definition of statistical models on a 2D imaging dataset consisting of mouse vertebrae. We conclude with an overview of the current state‐of‐the‐art in the field. This article is categorized under: Image and Spatial Data < Data: Types and StructureComputational Mathematics < Applications of Computational Statistics
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- PAR ID:
- 10449115
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- WIREs Computational Statistics
- Volume:
- 12
- Issue:
- 3
- ISSN:
- 1939-5108
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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