A time-domain nuclear magnetic resonance study of Mediterranean scleractinian corals reveals skeletal-porosity sensitivity to environmental changes

Environ Sci Technol. 2013 Nov 19;47(22):12679-86. doi: 10.1021/es402521b. Epub 2013 Nov 7.

Abstract

Mediterranean corals are a natural model for studying global warming, as the Mediterranean basin is expected to be one of the most affected regions and the increase in temperature is one of the greatest threats for coral survival. We have analyzed for the first time with time-domain nuclear magnetic resonance (TD-NMR) the porosity and pore-space structure, important aspects of coral skeletons, of two scleractinian corals, Balanophyllia europaea (zooxanthellate) and Leptopsammia pruvoti (nonzooxanthellate), taken from three different sites on the western Italian coast along a temperature gradient. Comparisons have been made with mercury intrusion porosimetry and scanning electron microscopy images. TD-NMR parameters are sensitive to changes in the pore structure of the two coral species. A parameter, related to the porosity, is larger for L. pruvoti than for B. europaea, confirming previous non-NMR results. Another parameter representing the fraction of the pore volume with pore sizes of less than 10-20 μm is inversely related, with a high degree of statistical significance, to the mass of the specimen and, for B. europaea, to the temperature of the growing site. This effect in the zooxanthellate species, which could reduce its resistance to mechanical stresses, may depend on an inhibition of the photosynthetic process at elevated temperatures and could have particular consequences in determining the effects of global warming on these species.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Anthozoa / physiology*
  • Anthozoa / ultrastructure
  • Bone and Bones / physiology*
  • Bone and Bones / ultrastructure
  • Climate Change*
  • Environment*
  • Geography
  • Magnetic Resonance Spectroscopy*
  • Mediterranean Region
  • Porosity
  • Regression Analysis
  • Time Factors