Failure by fatigue in the field: a model of fatigue breakage for the macroalga Mazzaella, with validation

J Exp Biol. 2011 May 1;214(Pt 9):1571-85. doi: 10.1242/jeb.051623.

Abstract

Seaweeds inhabiting the extreme hydrodynamic environment of wave-swept shores break frequently. However, traditional biomechanical analyses, evaluating breakage due to the largest individual waves, have perennially underestimated rates of macroalgal breakage. Recent laboratory testing has established that some seaweeds fail by fatigue, accumulating damage over a series of force impositions. Failure by fatigue may thus account, in part, for the discrepancy between prior breakage predictions, based on individual not repeated wave forces, and reality. Nonetheless, the degree to which fatigue breaks seaweeds on wave-swept shores remains unknown. Here, we developed a model of fatigue breakage due to wave-induced forces for the macroalga Mazzaella flaccida. To test model performance, we made extensive measurements of M. flaccida breakage and of wave-induced velocities experienced by the macroalga. The fatigue-breakage model accounted for significantly more breakage than traditional prediction methods. For life history phases modeled most accurately, 105% (for female gametophytes) and 79% (for tetrasporophytes) of field-observed breakage was predicted, on average. When M. flaccida fronds displayed attributes such as temperature stress and substantial tattering, the fatigue-breakage model underestimated breakage, suggesting that these attributes weaken fronds and lead to more rapid breakage. Exposure to waves had the greatest influence on model performance. At the most wave-protected sites, the model underpredicted breakage, and at the most wave-exposed sites, it overpredicted breakage. Overall, our fatigue-breakage model strongly suggests that, in addition to occurring predictably in the laboratory, fatigue-induced breakage of M. flaccida occurs on wave-swept shores.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Confidence Intervals
  • Models, Biological*
  • Probability
  • Regression Analysis
  • Reproducibility of Results
  • Seaweed / physiology*
  • Stress, Mechanical*
  • Water Movements