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Quantitative estimates of bio-remodeling on coastal rock surfaces

TitleQuantitative estimates of bio-remodeling on coastal rock surfaces
Publication TypeArticolo su Rivista peer-reviewed
Year of Publication2016
AuthorsPappalardo, M., Buehler M., Chelli A., Cironi L., Pannacciulli Federica, and Qin Z.
JournalJournal of Marine Science and Engineering
Volume4
ISSN20771312
Abstract

Remodeling of rocky coasts and erosion rates have been widely studied in past years, but not all the involved processes acting over rocks surface have been quantitatively evaluated yet. The first goal of this paper is to revise the different methodologies employed in the quantification of the effect of biotic agents on rocks exposed to coastal morphologic agents, comparing their efficiency. Secondly, we focus on geological methods to assess and quantify bio-remodeling, presenting some case studies in an area of the Mediterranean Sea in which different geological methods, inspired from the revised literature, have been tested in order to provide a quantitative assessment of the effects some biological covers exert over rocky platforms in tidal and supra-tidal environments. In particular, different experimental designs based on Schmidt hammer test results have been applied in order to estimate rock hardness related to different orders of littoral platforms and the bio-erosive/bio-protective role of Chthamalus ssp. and Verrucariaadriatica. All data collected have been analyzed using statistical tests to evaluate the significance of the measures and methodologies. The effectiveness of this approach is analyzed, and its limits are highlighted. In order to overcome the latter, a strategy combining geological and experimental-computational approaches is proposed, potentially capable of revealing novel clues on bio-erosion dynamics. An experimental-computational proposal, to assess the indirect effects of the biofilm coverage of rocky shores, is presented in this paper, focusing on the shear forces exerted during hydration-dehydration cycles. The results of computational modeling can be compared to experimental evidence, from nanoscopic to macroscopic scales. © 2016 by the authors.

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URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85013224224&doi=10.3390%2fjmse4020037&partnerID=40&md5=db52861ef0308774d4f57e50518b6734
DOI10.3390/jmse4020037
Citation KeyPappalardo2016