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Biton-Porsmoguer, Sebastián; Banaru, Daniela; Harmelin-Vivien, Mirelle; Béarez, Philippe; Bouchoucha, Marc; Marco-Miralles, Françoise; Marquès, Montse; Lloret, Josep; (2022). A study of trophic structure, physiological condition and mercury biomagnification in swordfish (Xiphias gladius): Evidence of unfavourable conditions for the swordfish population in the Western Mediterranean. Marine Pollution Bulletin, 176: 113411. DOI: 10.1016/j.marpolbul.2022.113411 URI: http://hdl.handle.net/10261/344174
Pedrosa-González, María Teresa; González-Vida, José Manuel; Galindo-Zaldívar, Jesús; Ortega-Acosta, Sergio; Castro, Manuel Jesús; Casas, David; Ercilla, Gemma; (2022). Simulation of tsunami induced by a submarine landslide in a glaciomarine margin: the case of Storfjorden LS-1 (southwestern Svalbard Islands). Natural Hazards and Earth System Sciences, 22: 3839-3858. DOI: 10.5194/nhess-22-3839-2022 URI: http://hdl.handle.net/10261/284664
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Civiero, Chiara; Lebedev, Sergei; Celli, Nicolas L. (2022). A Complex Mantle Plume Head Below East Africa-Arabia Shaped by the Lithosphere-Asthenosphere Boundary Topography. Geochemistry, Geophysics, Geosystems 23(11): e2022GC010610. DOI: 10.1029/2022GC010610 URI: http://hdl.handle.net/10261/286934
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Lin, Wenming; Portabella, Marcos; (2022). Characterizing Global Sea Surface Local Wind Variability From ASCAT Data. IEEE Transactions on Geoscience and Remote Sensing, 60: 4212210. DOI: 10.1109/TGRS.2022.3228317 URI: http://hdl.handle.net/10261/286831
Ratnarajah, Lavenia; Puigcorbé, Viena; Moreau, Sebastien; Roca-Martí, Montserrat; Janssens, Julie; Corkill, Matthew; Duprat, Luis; Genovese, Cristina; Lieser, Jan; Masqué, Pere; Lannuzel, Delphine (2022). Distribution and export of particulate organic carbon in East Antarctic coastal polynyas. Deep Sea Research - Part I - Oceanographic Research Papers, 190: 103899. DOI: 10.1016/j.dsr.2022.103899 URI: http://hdl.handle.net/10261/285719
Chen, Jian; Wang, Bin; Huang, Jun; Deng, Shubo; Wang, Yujue; Blaney, Lee; Brennan, Georgina; Cagnetta, Giovanni; Jia, Qimeng; Yu, Gang (2022). A machine-learning approach clarifies interactions between contaminants of emerging concern. One Earth, 5: 1239-1249. DOI: 10.1016/j.oneear.2022.10.006 URI: http://hdl.handle.net/10261/285746
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