Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Morten Hvitfeldt Iversen"'
Publikováno v:
Frontiers in Marine Science, Vol 10 (2023)
It is known that Microsetella norvegica feed on phytoplankton and provide an important link to higher trophic levels in Arctic fjords, such as fish sprat (Sprattus sprattus) and three-spined stickleback (Gasterosteus aculeatus). It has recently been
Externí odkaz:
https://doaj.org/article/2a656ca3415848e79367c4f8d7d7c5ee
Autor:
Jennifer Bachmann, Tabea Heimbach, Christiane Hassenrück, Germán A. Kopprio, Morten Hvitfeldt Iversen, Hans Peter Grossart, Astrid Gärdes
Publikováno v:
Frontiers in Microbiology, Vol 9 (2018)
Saharan dust input and seasonal upwelling along North–West Africa provide a model system for studying microbial processes related to the export and recycling of nutrients. This study offers the first molecular characterization of prokaryotic partic
Externí odkaz:
https://doaj.org/article/a710e613b01a4d42a44d82da58e70ae5
Autor:
Claudia Wekerle, Thomas Krumpen, Tilman Dinter, Wilken-Jon von Appen, Morten Hvitfeldt Iversen, Ian Salter
Publikováno v:
Frontiers in Marine Science, Vol 5 (2018)
Vertical particle fluxes are responsible for the transport of carbon and biogenic material from the surface to the deep ocean, hence understanding these fluxes is of climatic relevance. Sediment traps deployed in Fram Strait within the framework of t
Externí odkaz:
https://doaj.org/article/539333b83ab74bcf909e442cebbdb2a1
Autor:
Morten Hvitfeldt Iversen
Publikováno v:
Annual Review of Marine Science. 15:357-381
Understanding the nature of organic matter flux in the ocean remains a major goal of oceanography because it impacts some of the most important processes in the ocean. Sinking particles are important for carbon dioxide removal from the atmosphere and
Autor:
Anya M Waite, Simon Ramondenc, Laura Hehemann, Christina Bienhold, Claudia Wekerle, Morten Hvitfeldt Iversen, Ian Salter, Antje Boetius, Eva-Maria Nöthig, Andreas Rogge, Eduard Fadeev
Publikováno v:
Communications Biology, Vol 4, Iss 1, Pp 1-13 (2021)
COMMUNICATIONS BIOLOGY
Communications Biology
COMMUNICATIONS BIOLOGY
Communications Biology
Arctic Ocean sea ice cover is shrinking due to warming. Long-term sediment trap data shows higher export efficiency of particulate organic carbon in regions with seasonal sea ice compared to regions without sea ice. To investigate this sea-ice enhanc
Autor:
Silvia Vidal-Melgosa, Jan-Hendrik Hehemann, Stefan Becker, Guoyin Huang, Andreas Sichert, Morten Hvitfeldt Iversen, Jutta Niggemann, Yang Fang, Yi Cao
Publikováno v:
Limnology and Oceanography. 66:3768-3782
Autor:
Bettina Meyer, Katja Metfies, Philipp Wenta, Clara M. Flintrop, Thomas H. Badewien, Martin Graeve, Evgeny A. Pakhomov, Stefan Neuhaus, Nora-Charlotte Pauli, Morten Hvitfeldt Iversen
Publikováno v:
Communications Biology, Vol 4, Iss 1, Pp 1-12 (2021)
EPIC3Communications Biology, Springer Nature, 4(1), ISSN: 2399-3642
EPIC3Communications Biology, Springer Nature, 4(1), ISSN: 2399-3642
Over the past decades, two key grazers in the Southern Ocean (SO), krill and salps, have experienced drastic changes in their distribution and abundance, leading to increasing overlap of their habitats. Both species occupy different ecological niches
Autor:
Antje Boetius, Eva-Maria Nöthig, Matthias Wietz, Julia Grosse, Martin Graeve, Anja Engel, Morten Hvitfeldt Iversen, Eduard Fadeev, Wilken-Jon von Appen
Publikováno v:
EPIC3Limnology and Oceanography, 66, pp. 2901-2913, ISSN: 0024-3590
LIMNOLOGY AND OCEANOGRAPHY
LIMNOLOGY AND OCEANOGRAPHY
Submesoscale eddies and fronts are important components of oceanic mixing and energy fluxes. These phenomena occur in the surface ocean for a period of several days, on scales between a few hundred meters and few tens of kilometers. Remote sensing an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6687e52820d810beff9c90874187947c
Autor:
Eric C. Orenstein, Sakina‐Dorothée Ayata, Frédéric Maps, Érica C. Becker, Fabio Benedetti, Tristan Biard, Thibault de Garidel‐Thoron, Jeffrey S. Ellen, Filippo Ferrario, Sarah L. C. Giering, Tamar Guy‐Haim, Laura Hoebeke, Morten Hvitfeldt Iversen, Thomas Kiørboe, Jean‐François Lalonde, Arancha Lana, Martin Laviale, Fabien Lombard, Tom Lorimer, Séverine Martini, Albin Meyer, Klas Ove Möller, Barbara Niehoff, Mark D. Ohman, Cédric Pradalier, Jean‐Baptiste Romagnan, Simon‐Martin Schröder, Virginie Sonnet, Heidi M. Sosik, Lars S. Stemmann, Michiel Stock, Tuba Terbiyik‐Kurt, Nerea Valcárcel‐Pérez, Laure Vilgrain, Guillaume Wacquet, Anya M. Waite, Jean‐Olivier Irisson
Publikováno v:
Limnology and Oceanography
Limnology and Oceanography, 2022, 67 (8), pp.1647-1669. ⟨10.1002/lno.12101⟩
Orenstein, E C, Ayata, SD, Maps, F, Becker, É C, Benedetti, F, Biard, T, de Garidel-Thoron, T, Ellen, J S, Ferrario, F, Giering, S L C, Guy-Haim, T, Hoebeke, L, Iversen, M H, Kiørboe, T, Lalonde, JF, Lana, A, Laviale, M, Lombard, F, Lorimer, T, Martini, S, Meyer, A, Möller, K O, Niehoff, B, Ohman, M D, Pradalier, C, Romagnan, JB, Schröder, SM, Sonnet, V, Sosik, H M, Stemmann, L S, Stock, M, Terbiyik-Kurt, T, Valcárcel-Pérez, N, Vilgrain, L, Wacquet, G, Waite, A M & Irisson, JO 2022, ' Machine learning techniques to characterize functional traits of plankton from image data ', Limnology and Oceanography, vol. 67, no. 8, pp. 1647-1669 . https://doi.org/10.1002/lno.12101
Limnology And Oceanography (0024-3590) (Wiley), 2022-08, Vol. 67, N. 8, P. 1647-1669
LIMNOLOGY AND OCEANOGRAPHY
e-IEO. Repositorio Institucional Digital de Acceso Abierto del Instituto Español de Oceanografía
instname
Limnology and Oceanography, 2022, 67 (8), pp.1647-1669. ⟨10.1002/lno.12101⟩
Orenstein, E C, Ayata, SD, Maps, F, Becker, É C, Benedetti, F, Biard, T, de Garidel-Thoron, T, Ellen, J S, Ferrario, F, Giering, S L C, Guy-Haim, T, Hoebeke, L, Iversen, M H, Kiørboe, T, Lalonde, JF, Lana, A, Laviale, M, Lombard, F, Lorimer, T, Martini, S, Meyer, A, Möller, K O, Niehoff, B, Ohman, M D, Pradalier, C, Romagnan, JB, Schröder, SM, Sonnet, V, Sosik, H M, Stemmann, L S, Stock, M, Terbiyik-Kurt, T, Valcárcel-Pérez, N, Vilgrain, L, Wacquet, G, Waite, A M & Irisson, JO 2022, ' Machine learning techniques to characterize functional traits of plankton from image data ', Limnology and Oceanography, vol. 67, no. 8, pp. 1647-1669 . https://doi.org/10.1002/lno.12101
Limnology And Oceanography (0024-3590) (Wiley), 2022-08, Vol. 67, N. 8, P. 1647-1669
LIMNOLOGY AND OCEANOGRAPHY
e-IEO. Repositorio Institucional Digital de Acceso Abierto del Instituto Español de Oceanografía
instname
Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ too
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b310387659399d19153332aae277f2ee
https://hal.univ-lorraine.fr/hal-03482282/document
https://hal.univ-lorraine.fr/hal-03482282/document
Autor:
Nicolas Nowald, Götz Ruhland, Marco Klann, Gerold Wefer, B Hamady, E Toby, Barbara Donner, Gerhard Fischer, Oscar E Romero, Gesine Mollenhauer, Morten Hvitfeldt Iversen
Publikováno v:
Global Biogeochemical Cycles, 33 (8). pp. 1100-1128.
Sections PDFPDF Tools Share Abstract Long‐term data characterizing the oceans' biological carbon pump are essential for understanding impacts of climate variability on marine ecosystems. The “Bakun upwelling intensification hypothesis” suggests