Medical Journals

Techniques for Predicting the Lifetimes of Wave-swept Macroalgae: a Primer on Fracture Mechanics and Crack Growth.

Authors:
  • Mach Katharine J
  • Nelson Drew V
  • Denny Mark W

From: Hopkins Marine Station of Stanford University, Pacific Grove, CA 93950, USA. mach@stanford.edu

The Journal of experimental biology

  • Publish Date: Jul 2007
  • ISSN: 0022-0949
  • Volume: 210
  • Issue: Pt 13
  • Pages: 2213-30
  • Medium: Print
  • Language: English
  • Citation (JAMA): Mach Katharine J, Nelson Drew V, Denny Mark W, et al. Techniques for Predicting the Lifetimes of Wave-swept Macroalgae: a Primer on Fracture Mechanics and Crack Growth.. J. Exp. Biol. Jul 2007;210:2213-30

Abstract

Biomechanical analyses of intertidal and shallow subtidal seaweeds have elucidated ways in which these organisms avoid breakage in the presence of exceptional hydrodynamic forces imposed by pounding surf. However, comparison of algal material properties to maximum hydrodynamic forces predicts lower rates of breakage and dislodgment than are actually observed. Why the disparity between prediction and reality? Most previous research has measured algal material properties during a single application of force, equivalent to a single wave rushing past an alga. In contrast, intertidal macroalgae may experience more than 8000 waves a day. This repeated loading can cause cracks - introduced, for example, by herbivory or abrasion - to grow and eventually cause breakage, yet fatigue crack growth has not previously been taken into account. Here, we present methods from the engineering field of fracture mechanics that can be used to assess consequences of repeated force imposition for seaweeds. These techniques allow quantification of crack growth in wave-swept macroalgae, a first step towards considering macroalgal breakage in the realistic context of repeated force imposition. These analyses can also be applied to many other soft materials.

Mesh Headings (Keywords): Algae, Biomechanics, Ecosystem, Longevity


Check for Full Text / PubMed Unique Identifier (PMID): 17575028


This abstract is part of PubMed, a service of the U.S. National Library of Medicine. PubMed includes more than 17 million citations from MEDLINE and other life science journals for biomedical articles. See Copyright and Disclaimers.

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The data herein was last updated on July 8th, 2008 and may not reflect the most current and accurate data available from NLM.


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