What, where, and when: Spatial-temporal distribution of macro-litter on the seafloor of the western and central Mediterranean sea
Type | Article | ||||||||||||
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Date | 2024-02 | ||||||||||||
Language | English | ||||||||||||
Author(s) | Cau Alessandro1, 2, Sbrana Alice3, 4, Franceschini Simone5, Fiorentino Fabio6, 7, Follesa Maria Cristina1, 2, Galgani Francois8, Garofalo Germana6, 9, Gerigny Olivia10, Profeta Adriana11, Rinelli Paola11, Sbrana Mario12, Russo Tommaso2, 3 | ||||||||||||
Affiliation(s) | 1 : Dipartimento di Scienze della vita e dell'ambiente, Università degli Studi di Cagliari, Via Tommaso Fiorelli 1, 09126, Cagliari, Italy 2 : ConISMa, Piazzale Flaminio 9, 00196, Rome, Italy 3 : Laboratory of Experimental Ecology and Aquaculture, Department of Biology – University of Rome Tor Vergata, via della Ricerca Scientifica snc, 00133, Rome, Italy 4 : PhD program in Evolutionary Biology and Ecology, University of Rome Tor Vergata, Via della Ricerca Scientifica 1, 00133, Rome, Italy 5 : Hawaiʻi Institute of Marine Biology, University of Hawaii at Mānoa, Kāne'ohe, HI, 96744, USA 6 : Italian National Research Council (CNR), Institute for Marine Biological Resources and Biotechnology (IRBIM), via L. Vaccari 61, 91026, Mazara del Vallo (TP), Italy 7 : Stazione Zoologica Anton Dohrn (SZN), Lungomare Cristoforo Colombo, 4521, 90149, Palermo, Italy 8 : Ifremer Centre Mediterranée, Laboratoire LER/PAC, immeuble Agostini, ZI Furiani, 20600, Bastia, Corse, France 9 : Italian Institute for Environmental Protection and Research (ISPRA), Lungomare Cristoforo Colombo, 4521, 90149, Palermo, Italy 10 : Ifremer Centre Mediterranée, Laboratoire LER/PAC, Zone Portuaire de Brégaillon, 83500, La Seyne-sur-Mer, France 11 : Italian National Research Council (CNR), Institute for Marine Biological Resources and Biotechnology (IRBIM), Via S. Raineri, 86 98122, Messina (ME), Italy 12 : Consorzio per il Centro Interuniversitario di Biologia Marina ed Ecologia Applicata “G. Bacci” (CIBM), viale N. Sauro 4, I-57128, Livorno, Italy |
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Source | Environmental Pollution (0269-7491) (Elsevier BV), 2024-02 , Vol. 342 , P. 123028 (14p.) | ||||||||||||
DOI | 10.1016/j.envpol.2023.123028 | ||||||||||||
Keyword(s) | Marine waste, Seafloor macro-litter hotspots, Waste management, Mitigation strategies, Litter removal | ||||||||||||
Abstract | The progressive increase of marine macro-litter on the bottom of the Mediterranean Sea is an urgent problem that needs accurate information and guidance to identify those areas most at risk of accumulation. In the absence of dedicated monitoring programs, an important source of opportunistic data is fishery-independent monitoring campaigns of demersal resources. These data have long been used but not yet extensively. In this paper, MEDiterranean International Trawl Survey (MEDITS) data was supplemented with 18 layers of information related to major environmental (e.g. depth, sea water and wind velocity, sea waves) and anthropogenic (e.g. river inputs, shipping lanes, urban areas and ports, fishing effort) forcings that influence seafloor macro-litter distribution. The Random Forest (RF), a machine learning approach, was applied to: i) model the distribution of several litter categories at a high spatial resolution (i.e. 1 km2); ii) identify major accumulation hot spots and their temporal trends. Results indicate that RF is a very effective approach to model the distribution of marine macro-litter and provides a consistent picture of the heterogeneous distribution of different macro-litter categories. The most critical situation in the study area was observed in the north-eastern part of the western basin. In addition, the combined analysis of weight and density data identified a tendency for lighter items to accumulate in areas (such as the northern part of the Tyrrhenian Sea) with more stagnant currents. This approach, based on georeferenced information widely available in public databases, seems a natural candidate to be applied in other basins as a support and complement tool to field monitoring activities and strategies for protection and remediation of the most impacted areas. |
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