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dc.contributor.authorBargain, Annaëlle  Concept link
dc.contributor.authorMarchese, Fabio  Concept link
dc.contributor.authorSavini, Alessandra  Concept link
dc.contributor.authorTaviani, Marco  Concept link
dc.contributor.authorFabri, Marie-Claire  Concept link
dc.identifier.citationFrontiers in Marine Science 4 (2017): 338en_US
dc.description© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Frontiers in Marine Science 4 (2017): 338, doi:10.3389/fmars.2017.00338.en_US
dc.description.abstractThe Santa Maria di Leuca (SML) cold-water coral province (northern Ionian Sea) has the largest occurrence of a living white coral community currently known in the Mediterranean Sea. Madrepora oculata and Lophelia pertusa, identified as marking sensitive habitats of relevance by the General Fisheries Commission for the Mediterranean, have been observed heterogeneously distributed on the summits of several mounds. This particularly patchy and uneven distribution in addition to their importance for regional biodiversity highlights the need to better understand their environmental preferences and predict their distribution. Bathymetric data (40 m resolution) was used to derive seafloor characteristics. A fine scale index quantifying the landscape elevation (Bathymetric Position Index at 120 m resolution) was used to select all the elevated features considered as candidate morphologies for potential coral mounds. Statistics on 22 known coral topped mounds were computed. Two statistical methods were then used to identify other potential coral mounds based on predictive variables. The first method, the Geomorphometric proxies method, consists in computing basic statistics of terrain variables, using them for a step-by-step classification in a quantitative approach to select a subset of candidate morphologies. The second method consists in using a predictive Habitat Suitability Model (Maxent model). The Geomorphometric proxies method identified 736 potential coral mounds while the Maxent method predicted 1,252 potential coral mounds. A subset of 517 potential coral mounds was common to both methods. The analysis of the contribution of each variable with the Maxent method showed that the variable “Vector Ruggedness Measure” at a resolution of 5 pixels (200 m) contributed to 53% of the final Maxent model, followed by the “Terrain Texture” index (31%) at a resolution of 11 pixels (440 m). The common potential coral mounds are mainly located in an area characterized by a mass transport deposit, also called the mounds area because of the roughness of the seafloor, in accordance with the high proportional contribution of the noticeable first roughness index to the Maxent model. The results highlight the importance of the global conservation of the entire Province, with white coral probably widespread over the entire 600 km2 SML area.en_US
dc.description.sponsorshipThe Habitat Suitability model study was part of a post-doctoral grant funded by the “Agence de l'Eau Rhône Méditerranée & Corse” under Convention Number 2015 0348, Ifremer and ISMAR Bologna. We are grateful to all the participants and the P.I. of the Aplabes 2004; Aplabes 2005, HERMES M70-1, MEDECO 2007 ( and magic CoralFISH 2010 cruises. The authors also benefited from EU FP7 project CoralFish (Grant agreement number: 213144—, the Flag Project Ritmare (Ricerca Italiana per il Mare), funded by the Italian Ministry of Universities and Research (MIUR) and the ESF COCARDE Network. FM was funded through a Ph. D. fellowship in Earth Sciences at the University of Milano-Bicocca.en_US
dc.publisherFrontiers Mediaen_US
dc.rightsAttribution 4.0 International*
dc.subjectPredictive habitat mappingen_US
dc.subjectCold-water coralen_US
dc.subjectEcological proxiesen_US
dc.subjectSanta Maria di Leucaen_US
dc.subjectMediterranean Seaen_US
dc.titleSanta Maria di Leuca province (Mediterranean Sea) : identification of suitable mounds for cold-water coral settlement using geomorphometric proxies and Maxent methodsen_US

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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International