33 results on '"Möller, Klas Ove"'
Search Results
2. Machine learning techniques to characterize functional traits of plankton from image data
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Orenstein, Eric C, Ayata, Sakina‐Dorothée, Maps, Frédéric, Becker, Érica C, Benedetti, Fabio, Biard, Tristan, Garidel‐Thoron, Thibault, Ellen, Jeffrey S, Ferrario, Filippo, Giering, Sarah LC, Guy‐Haim, Tamar, Hoebeke, Laura, Iversen, Morten Hvitfeldt, Kiørboe, Thomas, Lalonde, Jean‐François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, Mark D, Pradalier, Cédric, Romagnan, Jean‐Baptiste, Schröder, Simon‐Martin, Sonnet, Virginie, Sosik, Heidi M, Stemmann, Lars S, Stock, Michiel, Terbiyik‐Kurt, Tuba, Valcárcel‐Pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M, and Irisson, Jean‐Olivier
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Biological Sciences ,Ecology ,Earth Sciences ,Environmental Sciences ,Marine Biology & Hydrobiology ,Biological sciences ,Earth sciences ,Environmental sciences - Abstract
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 tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.
- Published
- 2022
3. Storm events alter marine snow fluxes in stratified marine environments
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Rühl, Saskia and Möller, Klas Ove
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- 2024
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4. Publisher Correction: Making marine image data FAIR
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Schoening, Timm, Durden, Jennifer M., Faber, Claas, Felden, Janine, Heger, Karl, Hoving, Henk-Jan T., Kiko, Rainer, Köser, Kevin, Krämmer, Christopher, Kwasnitschka, Tom, Möller, Klas Ove, Nakath, David, Naß, Andrea, Nattkemper, Tim W., Purser, Autun, and Zurowietz, Martin
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- 2022
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5. Making marine image data FAIR
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Schoening, Timm, Durden, Jennifer M., Faber, Claas, Felden, Janine, Heger, Karl, Hoving, Henk-Jan T., Kiko, Rainer, Köser, Kevin, Krämmer, Christopher, Kwasnitschka, Tom, Möller, Klas Ove, Nakath, David, Naß, Andrea, Nattkemper, Tim W., Purser, Autun, and Zurowietz, Martin
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- 2022
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6. Impact of aggregate‐colonizing copepods on the biological carbon pump in a high‐latitude fjord.
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Svensen, Camilla, Iversen, Morten, Norrbin, Fredrika, Möller, Klas Ove, Wiedmann, Ingrid, Skarðhamar, Jofrid, Barth‐Jensen, Coralie, Kwasniewski, Slawomir, Ormanczyk, Mateusz, Dąbrowska, Anna Maria, and Koski, Marja
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ANIMAL droppings ,BIOGEOCHEMICAL cycles ,COPEPODA ,FJORDS ,KRILL - Abstract
Zooplankton consumption of sinking aggregates affects the quality and quantity of organic carbon exported to the deep ocean. Increasing laboratory evidence shows that small particle‐associated copepods impact the flux attenuation by feeding on sinking particles, but this has not been quantified in situ. We investigated the impact of an abundant particle‐colonizing copepod, Microsetella norvegica, on the attenuation of the vertical carbon flux in a sub‐Arctic fjord. This study combines field measurements of vertical carbon flux, abundance, and size‐distribution of marine snow and degradation rates of fecal pellets and algal aggregates. Female M. norvegica altered their feeding behavior when exposed to aggregates, and ingestion rates were 0.20 μg C ind.−1 d−1 on marine snow and 0.11 μg C ind.−1 d−1 on intact krill fecal pellets, corresponding to 48% and 26% of the females' body carbon mass. Due to high sea surface abundance of up to ~ 50 ind. L−1, the population of M. norvegica had the potential to account for almost all the carbon removal in the upper 50 m of the water column, depending on the type of the aggregate. Our observations highlight the potential importance of abundant small‐sized copepods for biogeochemical cycles through their impact on export flux and its attenuation in the twilight zone. [ABSTRACT FROM AUTHOR]
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- 2024
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7. Machine learning in marine ecology: an overview of techniques and applications
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Rubbens, Peter, primary, Brodie, Stephanie, additional, Cordier, Tristan, additional, Destro Barcellos, Diogo, additional, Devos, Paul, additional, Fernandes-Salvador, Jose A, additional, Fincham, Jennifer I, additional, Gomes, Alessandra, additional, Handegard, Nils Olav, additional, Howell, Kerry, additional, Jamet, Cédric, additional, Kartveit, Kyrre Heldal, additional, Moustahfid, Hassan, additional, Parcerisas, Clea, additional, Politikos, Dimitris, additional, Sauzède, Raphaëlle, additional, Sokolova, Maria, additional, Uusitalo, Laura, additional, Van den Bulcke, Laure, additional, van Helmond, Aloysius T M, additional, Watson, Jordan T, additional, Welch, Heather, additional, Beltran-Perez, Oscar, additional, Chaffron, Samuel, additional, Greenberg, David S, additional, Kühn, Bernhard, additional, Kiko, Rainer, additional, Lo, Madiop, additional, Lopes, Rubens M, additional, Möller, Klas Ove, additional, Michaels, William, additional, Pala, Ahmet, additional, Romagnan, Jean-Baptiste, additional, Schuchert, Pia, additional, Seydi, Vahid, additional, Villasante, Sebastian, additional, Malde, Ketil, additional, and Irisson, Jean-Olivier, additional
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- 2023
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8. Pelagic effects of offshore wind farm foundations in the stratified North Sea
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Floeter, Jens, van Beusekom, Justus E.E., Auch, Dominik, Callies, Ulrich, Carpenter, Jeffrey, Dudeck, Tim, Eberle, Sabine, Eckhardt, André, Gloe, Dominik, Hänselmann, Kristin, Hufnagl, Marc, Janßen, Silke, Lenhart, Hermann, Möller, Klas Ove, North, Ryan P., Pohlmann, Thomas, Riethmüller, Rolf, Schulz, Sabrina, Spreizenbarth, Stefan, Temming, Axel, Walter, Bettina, Zielinski, Oliver, and Möllmann, Christian
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- 2017
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9. Machine learning in marine ecology: an overview of techniques and applications
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Rubbens, Peter, Brodie, Stephanie, Cordier, Tristan, Destro Barcellos, Diogo, Devos, Paul, Fernandes-Salvador, Jose A, Fincham, Jennifer I, Gomes, Alessandra, Handegard, Nils Olav, Howell, Kerry, Jamet, Cédric, Kartveit, Kyrre Heldal, Moustahfid, Hassan, Parcerisas, Clea, Politikos, Dimitris, Sauzède, Raphaëlle, Sokolova, Maria, Uusitalo, Laura, Van den Bulcke, Laure, van Helmond, Aloysius T M, Watson, Jordan T, Welch, Heather, Beltran-Perez, Oscar, Chaffron, Samuel, Greenberg, David S, Kühn, Bernhard, Kiko, Rainer, Lo, Madiop, Lopes, Rubens M, Möller, Klas Ove, Michaels, William, Pala, Ahmet, Romagnan, Jean-Baptiste, Schuchert, Pia, Seydi, Vahid, Villasante, Sebastian, Malde, Ketil, Irisson, Jean-Olivier, Whidden, Christopher, Rubbens, Peter, Brodie, Stephanie, Cordier, Tristan, Destro Barcellos, Diogo, Devos, Paul, Fernandes-Salvador, Jose A, Fincham, Jennifer I, Gomes, Alessandra, Handegard, Nils Olav, Howell, Kerry, Jamet, Cédric, Kartveit, Kyrre Heldal, Moustahfid, Hassan, Parcerisas, Clea, Politikos, Dimitris, Sauzède, Raphaëlle, Sokolova, Maria, Uusitalo, Laura, Van den Bulcke, Laure, van Helmond, Aloysius T M, Watson, Jordan T, Welch, Heather, Beltran-Perez, Oscar, Chaffron, Samuel, Greenberg, David S, Kühn, Bernhard, Kiko, Rainer, Lo, Madiop, Lopes, Rubens M, Möller, Klas Ove, Michaels, William, Pala, Ahmet, Romagnan, Jean-Baptiste, Schuchert, Pia, Seydi, Vahid, Villasante, Sebastian, Malde, Ketil, Irisson, Jean-Olivier, and Whidden, Christopher
- Abstract
Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific disciplines. We first highlight why machine learning is needed in marine ecology. Then we provide a quick primer on machine learning techniques and vocabulary. We built a database of & SIM;1000 publications that implement such techniques to analyse marine ecology data. For various data types (images, optical spectra, acoustics, omics, geolocations, biogeochemical profiles, and satellite imagery), we present a historical perspective on applications that proved influential, can serve as templates for new work, or represent the diversity of approaches. Then, we illustrate how machine learning can be used to better understand ecological systems, by combining various sources of marine data. Through this coverage of the literature, we demonstrate an increase in the proportion of marine ecology studies that use machine learning, the pervasiveness of images as a data source, the dominance of machine learning for classification-type problems, and a shift towards deep learning for all data types. This overview is meant to guide researchers who wish to apply machine learning methods to their marine datasets.
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- 2023
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10. Predation risk triggers copepod small-scale behavior in the Baltic Sea
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Möller, Klas Ove, St. John, Michael, Temming, Axel, Diekmann, Rabea, Peters, Janna, Floeter, Jens, Sell, Anne F, Herrmann, Jens-Peter, Gloe, Dominik, Schmidt, Jörn O., Hinrichsen, Hans-Harald, Möllmann, Christian, and Irigoien, Xabier
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0106 biological sciences ,zooplankton ,Diel vertical migration ,individual behavior ,Aquatic Science ,010603 evolutionary biology ,01 natural sciences ,Zooplankton ,Predation ,Predator avoidance ,Video plankton recorder ,Predatory fish ,14. Life underwater ,AcademicSubjects/SCI00970 ,Ecology, Evolution, Behavior and Systematics ,Biomass (ecology) ,Ecology ,biology ,010604 marine biology & hydrobiology ,Plankton ,biology.organism_classification ,diel vertical migration ,predator avoidance ,Original Article ,Individual behavior ,Adaptive behavior (ecology) ,Copepod ,video plankton recorder - Abstract
Predators not only have direct impact on biomass but also indirect, non-consumptive effects on the behavior their prey organisms. A characteristic response of zooplankton in aquatic ecosystems is predator avoidance by diel vertical migration (DVM), a behavior which is well studied on the population level. A wide range of behavioral diversity and plasticity has been observed both between- as well as within-species and, hence, investigating predator–prey interactions at the individual level seems therefore essential for a better understanding of zooplankton dynamics. Here we applied an underwater imaging instrument, the video plankton recorder (VPR), which allows the non-invasive investigation of individual, diel adaptive behavior of zooplankton in response to predators in the natural oceanic environment, providing a finely resolved and continuous documentation of the organisms’ vertical distribution. Combing observations of copepod individuals observed with the VPR and hydroacoustic estimates of predatory fish biomass, we here show (i) a small-scale DVM of ovigerous Pseudocalanus acuspes females in response to its main predators, (ii) in-situ observations of a direct short-term reaction of the prey to the arrival of the predator and (iii) in-situ evidence of pronounced individual variation in this adaptive behavior with potentially strong effects on individual performance and ecosystem functioning.
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- 2020
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11. Machine learning techniques to characterize functional traits of plankton from image data
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Orenstein, Eric C., Ayata, Sakina‐dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, De Garidel‐thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy‐haim, Tamar, Hoebeke, Laura, Iversen, Morten Hvitfeldt, Kiørboe, Thomas, Lalonde, Jean‐françois, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, Mark D., Pradalier, Cédric, Romagnan, Jean-baptiste, Schröder, Simon‐martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars S., Stock, Michiel, Terbiyik‐kurt, Tuba, Valcárcel‐pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., Irisson, Jean‐olivier, Orenstein, Eric C., Ayata, Sakina‐dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, De Garidel‐thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy‐haim, Tamar, Hoebeke, Laura, Iversen, Morten Hvitfeldt, Kiørboe, Thomas, Lalonde, Jean‐françois, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, Mark D., Pradalier, Cédric, Romagnan, Jean-baptiste, Schröder, Simon‐martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars S., Stock, Michiel, Terbiyik‐kurt, Tuba, Valcárcel‐pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., and Irisson, Jean‐olivier
- Abstract
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 tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.
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- 2022
- Full Text
- View/download PDF
12. Machine learning techniques to characterise functional traits of plankton image data
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Orenstein, Eric, Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica, Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey, Ferrario, Filippo, Giering, Sarah, Guy-Haim, Tamar, Hoebeke, Laura, Iversen, Morten, Kiorboe, Thomas, Lalonde, Jean-Francois, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, Mark, Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon-Martin, Sonnet, Virginie, Sosik, Heidi, Stemmann, Lars, Stock, Michiel, Terbiyik-Kurt, Tuba, Valcárcel-Pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya, Irisson, Jean-Olivier, Orenstein, Eric, Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica, Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey, Ferrario, Filippo, Giering, Sarah, Guy-Haim, Tamar, Hoebeke, Laura, Iversen, Morten, Kiorboe, Thomas, Lalonde, Jean-Francois, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, Mark, Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon-Martin, Sonnet, Virginie, Sosik, Heidi, Stemmann, Lars, Stock, Michiel, Terbiyik-Kurt, Tuba, Valcárcel-Pérez, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya, and Irisson, Jean-Olivier
- Abstract
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 tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.
- Published
- 2022
13. Supplemental Information: Machine learning techniques to characterize functional traits of plankton from image data
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Orenstein, Eric C., Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Hvitfeldt, Morten, Kiørboe, Thomas, Lalonde, Jean François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, M. D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik Kurt, Tuba, Valcárcel, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., Irisson, Jean-Olivier, Orenstein, Eric C., Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Hvitfeldt, Morten, Kiørboe, Thomas, Lalonde, Jean François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, M. D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik Kurt, Tuba, Valcárcel, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., and Irisson, Jean-Olivier
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- 2022
14. Machine learning techniques to characterize functional traits of plankton from image data
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Centre National de la Recherche Scientifique (France), Belmont Forum, Université Laval, Natural Sciences and Engineering Research Council of Canada, Research Foundation - Flanders, ETH Zurich, Gordon and Betty Moore Foundation, National Science Foundation (US), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil), Agence Nationale de la Recherche (France), Ministerio de Economía y Competitividad (España), Institut Universitaire de France, Simons Foundation, Sorbonne Université, Orenstein, Eric C., Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Hvitfeldt, Morten, Kiørboe, Thomas, Lalonde, Jean François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, M. D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik Kurt, Tuba, Valcárcel, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., Irisson, Jean-Olivier, Centre National de la Recherche Scientifique (France), Belmont Forum, Université Laval, Natural Sciences and Engineering Research Council of Canada, Research Foundation - Flanders, ETH Zurich, Gordon and Betty Moore Foundation, National Science Foundation (US), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brasil), Agence Nationale de la Recherche (France), Ministerio de Economía y Competitividad (España), Institut Universitaire de France, Simons Foundation, Sorbonne Université, Orenstein, Eric C., Ayata, Sakina-Dorothée, Maps, Frédéric, Becker, Érica C., Benedetti, Fabio, Biard, Tristan, de Garidel-Thoron, Thibault, Ellen, Jeffrey S., Ferrario, Filippo, Giering, Sarah L. C., Guy-Haim, Tamar, Hoebeke, Laura, Hvitfeldt, Morten, Kiørboe, Thomas, Lalonde, Jean François, Lana, Arancha, Laviale, Martin, Lombard, Fabien, Lorimer, Tom, Martini, Séverine, Meyer, Albin, Möller, Klas Ove, Niehoff, Barbara, Ohman, M. D., Pradalier, Cédric, Romagnan, Jean-Baptiste, Schröder, Simon Martin, Sonnet, Virginie, Sosik, Heidi M., Stemmann, Lars, Stock, Michiel, Terbiyik Kurt, Tuba, Valcárcel, Nerea, Vilgrain, Laure, Wacquet, Guillaume, Waite, Anya M., and Irisson, Jean-Olivier
- Abstract
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 tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.
- Published
- 2022
15. Best practices and recommendations for plankton imaging data management: Ensuring effective data flow towards European data infrastructures. Version 1
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Martin-Cabrera, Patricia, Perez Perez, Ruben, Irisson, Jean-Olivier, Lombard, Fabien, Möller, Klas Ove, Rühl, Saskia, Creach, Veronique, Lindh, Markus, Stemmann, Lars, Schepers, Lennert, and Martin-Cabrera, Patricia
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OBIS ,Data processing ,EMODnet Biology ,GBIF ,Data quality management ,EurOBIS ,Phytoplankton ,Darwin Core ,OBIS-ENV-DATA ,Zooplankton ,Plankton imaging instruments - Abstract
The best practices and recommendations for plankton imaging data management enable users to report a detailed taxonomic characterisation of plankton observations as well as quantitative information that is useful for ecological studies. This format allows biodiversity data portals to extend their scope beyond species occurrence data. Furthermore, proposing the use of more Darwin Core fields in this format, users now have the possibility to publish manually validated datasets, but also datasets produced by fully automated plankton identification workflows. The proposed data and file formats are simple and both human- and machine-readable to automatise workflows. This format will allow data generators to submit enriched plankton imaging datasets to the international biodiversity data portals, (Eur)OBIS and EMODnet Biology. We encourage plankton imaging data generators to implement these workflows into their pipelines, to share their data with the international data portals easily, enriching these databases with this valuable data. European Union; JERICO-S3 project, WP6- D6.4, funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 871153. Published Also published as JERICO Deliverable JERICO-S3 D6.4-WP6 -Best practices & recommendations for plankton imaging data management, JERICO-S3-WP6-D6.4-07.04.2022-V1.0 Refereed Current 14.a Phytoplankton biomass and diversity Zooplankton biomass and diversity Pilot or Demonstrated Novel (no adoption outside originators) Species distributions Species abundances Species morphology Taxonomic/phylogenetic diversity Community abundance Plankton In-situ plankton imaging instruments Benchtop plankton imaging instruments Reports with methodological relevance
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- 2022
16. Working towards integration of new data describing biological essential ocean variables from marine coastal ecosystems
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Creach, Veronique, Cabrera, Patricia, Artigas, Luis Felipe, Grégori, Gérald, Irisson, Jean-Olivier, Lefebvre, Alain, Lindh, Markus, Möller, Klas Ove, Seppala, Jukka, Thyssen, M, Lombard, Fabien, Schepers, Lennert, Centre for Environment, Fisheries and Aquaculture Science [Lowestoft] (CEFAS), Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 (LOG), Institut national des sciences de l'Univers (INSU - CNRS)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Nord]), Université du Littoral Côte d'Opale (ULCO), Institut méditerranéen d'océanologie (MIO), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ARGANS Limited, Aalto University, and Flanders Marine Institute (VLIZ)
- Subjects
[SDE.BE]Environmental Sciences/Biodiversity and Ecology ,[SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography - Abstract
International audience; The development of a new generation of biological sensors has drastically changed the studies of marine plankton from lab bench work to in vivo and real-time observations. Target organisms, from bacteria to plankton, can now be optically characterized and/or photographed and archived. Consequently, scientists are facing the difficult challenge to handle a large amount of data which need to be processed rapidly and harmonised before being stored in databases to be accessible to scientific/environmental management communities. In the Joint European Research Infrastructure for Coastal Observatories (JERICO-RI), we intend to integrate the monitoring of physical, biogeochemical and biological variables to better understand coastal ecosystems. Focusing primarily on plankton communities measured at high spatial and temporal resolution, we aim to provide a framework for the data flow following the Findability, Accessibility, Interoperability, and Reuse (FAIR). To achieve this, we need to draw up best practices in data management to be followed by users and experts operating the sensors such as standardised protocol, minimal technical metadata elements for effective re-use, identify and extend appropriate vocabularies, identify tools for data integration and platforms for trust-worthy long-term archival, standardised data formats to be ingested by European data infrastructures. In this presentation, we will present some of our achievements regarding in vivo flow cytometry, imagery analysis, and multispectral fluorimetry.
- Published
- 2021
17. Sinking organic particles in the ocean—flux estimates from in situ optical devices
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Giering, Sarah Lou Carolin, Cavan, Emma Louise, Basedow, Sünnje Linnéa, Briggs, Nathan, Burd, Adrian B., Darroch, Louise J., Guidi, Lionel, Irisson, Jean-olivier, Iversen, Morten H., Kiko, Rainer, Lindsay, Dhugal, Marcolin, Catarina R., Mcdonnell, Andrew M. P., Möller, Klas Ove, Passow, Uta, Thomalla, Sandy, Trull, Thomas William, and Waite, Anya M.
- Abstract
Optical particle measurements are emerging as an important technique for understanding the ocean carbon cycle, including contributions to estimates of their downward flux, which sequesters carbon dioxide (CO2) in the deep sea. Optical instruments can be used from ships or installed on autonomous platforms, delivering much greater spatial and temporal coverage of particles in the mesopelagic zone of the ocean than traditional techniques, such as sediment traps. Technologies to image particles have advanced greatly over the last two decades, but the quantitative translation of these immense datasets into biogeochemical properties remains a challenge. In particular, advances are needed to enable the optimal translation of imaged objects into carbon content and sinking velocities. In addition, different devices often measure different optical properties, leading to difficulties in comparing results. Here we provide a practical overview of the challenges and potential of using these instruments, as a step toward improvement and expansion of their applications.
- Published
- 2020
18. Operating Cabled Underwater Observatories in Rough Shelf-Sea Environments: A Technological Challenge
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Fischer, Philipp, primary, Brix, Holger, additional, Baschek, Burkard, additional, Kraberg, Alexandra, additional, Brand, Markus, additional, Cisewski, Boris, additional, Riethmüller, Rolf, additional, Breitbach, Gisbert, additional, Möller, Klas Ove, additional, Gattuso, Jean-Pierre, additional, Alliouane, Samir, additional, van de Poll, Willem H., additional, and Witbaard, Rob, additional
- Published
- 2020
- Full Text
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19. Sinking Organic Particles in the Ocean—Flux Estimates From in situ Optical Devices
- Author
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Giering, Sarah Lou Carolin, primary, Cavan, Emma Louise, additional, Basedow, Sünnje Linnéa, additional, Briggs, Nathan, additional, Burd, Adrian B., additional, Darroch, Louise J., additional, Guidi, Lionel, additional, Irisson, Jean-Olivier, additional, Iversen, Morten H., additional, Kiko, Rainer, additional, Lindsay, Dhugal, additional, Marcolin, Catarina R., additional, McDonnell, Andrew M. P., additional, Möller, Klas Ove, additional, Passow, Uta, additional, Thomalla, Sandy, additional, Trull, Thomas William, additional, and Waite, Anya M., additional
- Published
- 2020
- Full Text
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20. Neue Einblicke durch Plankton-Observatorien
- Author
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Möller, Klas Ove
- Abstract
ESKP-Themenspezial: Biodiversität, Am Anfang der Nahrungskette im Meer steht das Plankton. Plankton zeichnet sich durch eine ausgesprochen breite Artenvielfalt aus. Mittels neuer Unterwasser-Plankton-Observatorien soll die Vielfalt des Planktons besser erfasst werden. So können auch die Veränderungen der Biodiversität im Plankton erkannt werden, die im Zusammenhang mit dem Klimawandel auftreten.
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- 2020
- Full Text
- View/download PDF
21. Towards a global in situ monitoring of plankton using imaging systems: lessons learnt from the past 10 years of observation in Europe
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Stemmann, Lars, Romagnan, Jean-Baptiste, Lefebvre, Alain, Grégori, Gérald, Irisson, Jean-Olivier, Karlson, Bengt, Seppala, Jukka, Kraft, Kaisa, Lionel, Guidi, Artigas, Luis Felipe, Soviadan, Dodji, Wacquet, Guillaume, Möller, Klas Ove, Deneudt, Klaas, Claus, Simon, Lombard, Fabien, Laboratoire d'océanographie de Villefranche (LOV), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de la Mer de Villefranche (IMEV), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ARGANS Limited, Institut méditerranéen d'océanologie (MIO), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Aalto University, Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 (LOG), Institut national des sciences de l'Univers (INSU - CNRS)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Nord]), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Flanders Marine Institute, and VLIZ
- Subjects
[SDE.BE]Environmental Sciences/Biodiversity and Ecology ,[SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography - Abstract
International audience; Plankton plays a key role in the biological pump and has a big impact on marine living resources. However, plankton is difficult to observe in a consistent manner across its extended size range and by the multiple observers that uses protocols that are not inter calibrated. Imaging sensors have the potential to provide key ``ecosystem essential ocean variables'' eEOVs (plankton biodiversity, morphological traits) that complement other sensors such as optical ones. Lab and in-situ imaging sensors have been deployed the 10 last years to provide insights into local dynamics in the frame of time series programs (from daily to decadal scales) and during oceanographic surveys across ocean basins. Combining observations from the different programmes has sometimes allowed to detect concomitant changes in different areas or provide a better spatial distribution of plankton communities. For example, such efforts were supported by the European FP7 JERICO, H2020 JERICO-NEXT, BRIDGES, EURO-BASIN programs. Most of the observation efforts were performed independently and hundreds of millions of images have been collected (and billions to come as sensors are getting more available). All those sparsely distributed images are usually not available for the users because of limited development in software solutions for identification, archiving and distribution, which are in a current improving process. Several attempts for developing web based services for image recognition, distribution and archiving have been performed (ecotaxa.obs-vlfr.fr) but only a fraction of the existing and future data can be treated by them. Based on the past ten years of effort, we will present a synthesis of successful developments in using imaging systems to provide information on plankton community at local, regional and ultimately global scales. These examples will show how relevant they are for ecosystem monitoring (e.g. detection of ecosystem changes and regime-shifts) and services (e.g. aquaculture, fisheries, biological carbon pump). We will then build on these examples to discuss future developments with the aim of, better observing, harmonizing practices and developing state of the art marine data and information management in order to increase the connection with the relevant stakeholders and community of users among researchers, conservation managers and private companies.
- Published
- 2019
22. Operating Cabled Underwater Observatories in Rough Shelf-Sea Environments: A Technological Challenge
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Fischer, Philipp, Brix, Holger, Baschek, Burkard, Kraberg, Alexandra, Brand, Markus, Cisewski, Boris, Riethmüller, Rolf, Breitbach, Gisbert, Möller, Klas Ove, Gattuso, Jean-Pierre, Alliouane, Samir, van de Poll, Willem H., Witbaard, Rob, Fischer, Philipp, Brix, Holger, Baschek, Burkard, Kraberg, Alexandra, Brand, Markus, Cisewski, Boris, Riethmüller, Rolf, Breitbach, Gisbert, Möller, Klas Ove, Gattuso, Jean-Pierre, Alliouane, Samir, van de Poll, Willem H., and Witbaard, Rob
- Abstract
Cabled coastal observatories are often seen as future-oriented marine technology that enables science to conduct observational and experimental studies under water year-round, independent of physical accessibility to the target area. Additionally, the availability of (unrestricted) electricity and an Internet connection under water allows the operation of complex experimental setups and sensor systems for longer periods of time, thus creating a kind of laboratory beneath the water. After successful operation for several decades in the terrestrial and atmospheric research field, remote controlled observatory technology finally also enables marine scientists to take advantage of the rapidly developing communication technology. The continuous operation of two cabled observatories in the southern North Sea and off the Svalbard coast since 2012 shows that even highly complex sensor systems, such as stereo-optical cameras, video plankton recorders or systems for measuring the marine carbonate system, can be successfully operated remotely year-round facilitating continuous scientific access to areas that are difficult to reach, such as the polar seas or the North Sea. Experience also shows, however, that the challenges of operating a cabled coastal observatory go far beyond the provision of electricity and network connection under water. In this manuscript, the essential developmental stages of the “COSYNA Shallow Water Underwater Node” system are presented, and the difficulties and solutions that have arisen in the course of operation since 2012 are addressed with regard to technical, organizational and scientific aspects.
- Published
- 2020
23. Report on Best Practice in the utilization of sensors used for measuring nutrients, biology related optical properties,variables of the marine carbonate system, and for coastal profiling. JERICO-NEXT Deliverable D2.5. Version 1.0
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Möller, Klas Ove, Petersen, Wilhelm, and Nair, Rajesh
- Subjects
Biology-related optical properties ,Nutrient sensors ,Chemical oceanography::Carbonate system [Parameter Discipline] ,Chemical oceanography::Nutrients [Parameter Discipline] ,Coastal profiling ,Physical oceanography::Other physical oceanographic measurements [Parameter Discipline] ,nutrient analysers [Instrument Type Vocabulary] - Abstract
The coastal area is the most productive and dynamic environment of the world ocean with significant resources and services for mankind. JERICO-NEXT emphasizes thatthe complexity of the coastal ocean cannot be well understood if interconnection between physics, biogeochemistry and biology is not guaranteed. Such an integration requires new technological developments allowing continuous monitoring of a larger set of parameters. The objective of JERICO-NEXT consists in strengthening and enlarging a solid and transparent European network in providing operational services for the timely, continuous and sustainable delivery of high quality environmental data and information products related to marine environment in European coastal seas.The best practice of technologies, methodologies and procedures is a vital step in ensuring efficiency and optimal returns from any kind of distributed, heterogeneous, multifaceted, coastal observing infrastructure operating on a transnational level like the JERICO network. The JERICO network is always striving to increase its suite of sensors to anticipate likely future demands. As part of this effort, it is now implementing a variety of sensors for a number of bio-geochemical measurements. While Task 2.4 of JERICO-NEXT dealt with the harmonization of these sensors and their underlying technologies,this report provides information on Best Practice in the utilization of sensors used for measuring nutrients (lead: CEFAS), biology-related optical properties (lead: SYKE), variables of the marine carbonate system (lead: NIVA),and for coastal profiling (lead: CNR). This deliverable will also inform on the outcome and results of the workshopsthat weredealing with its topic during the project. Published Contributors: Naomi Greenwood , Chris Read, Agathe Laes-Huon, Anne Daniel, Karel Bakker, Daniel Blandfort , Martina Gehrung , Pasi Ylöstalo , Lumi Haraguchi , Jani Ruohola , Bengt Karlson , Felipe Artigas , Fabrice Lizon , Melilotus Thyssen , Guillaume Wacquet , Manolis Ntoumas , Veronique Créach , Pierre Jaccard , Laurent Delauney , Jukka Seppälä , Andrew L. King, Kai Sørensen, Sabine Marty , Anna Wranne Willstrand , Lauri Laakso , Carolina Cantoni , Wilhelm Petersen, Yoana Voynova, Klas Ove Möller , Michela Martinelli , Refereed Current 14.A Nutrients Inorganic carbon Best Practice Manual (incl. handbook, guide, cookbook etc)
- Published
- 2019
24. Globally Consistent Quantitative Observations of Planktonic Ecosystems
- Author
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Lombard, Fabien, Boss, Emmanuel, Waite, Anya, Vogt, Meike, Uitz, Julia, Stemman, Lars, Sosik, Heidi M., Schulz, Jan, Romagnan, J.-B., Picheral, Marc, Pearlman, Jay, Ohman, M. D., Niehoff, Barbara, Möller, Klas Ove, Miloslavich, Patricia, Lara-Lpez, A., Kudela, R., Lopes, R. M., Kiko, Rainer, Karp-Boss, Lee, Jaffe, J.S., Iversen, Morten, Irisson, J.-O., Fennel, K., Hauss, Helena, Guidi, Lionel, Gorsky, Gaby, Giering, Sarah L. C., Gaube, Peter, Gallager, Scott M., Dubelaar, G., Cowen, R.K., Carlotti, F., Briseno-Avena, C., Berline, Leo, Benoit-Bird, K., Bax, Nicholas J., Batten, Sonia Dawn, Ayata, Sakina-Dorothée, Artigas, L.F., Appeltans, Ward, Lombard, Fabien, Boss, Emmanuel, Waite, Anya, Vogt, Meike, Uitz, Julia, Stemman, Lars, Sosik, Heidi M., Schulz, Jan, Romagnan, J.-B., Picheral, Marc, Pearlman, Jay, Ohman, M. D., Niehoff, Barbara, Möller, Klas Ove, Miloslavich, Patricia, Lara-Lpez, A., Kudela, R., Lopes, R. M., Kiko, Rainer, Karp-Boss, Lee, Jaffe, J.S., Iversen, Morten, Irisson, J.-O., Fennel, K., Hauss, Helena, Guidi, Lionel, Gorsky, Gaby, Giering, Sarah L. C., Gaube, Peter, Gallager, Scott M., Dubelaar, G., Cowen, R.K., Carlotti, F., Briseno-Avena, C., Berline, Leo, Benoit-Bird, K., Bax, Nicholas J., Batten, Sonia Dawn, Ayata, Sakina-Dorothée, Artigas, L.F., and Appeltans, Ward
- Abstract
In this paper we review the technologies available to make globally quantitative observations of particles in general—and plankton in particular—in the world oceans, and for sizes varying from sub-microns to centimeters. Some of these technologies have been available for years while others have only recently emerged. Use of these technologies is critical to improve understanding of the processes that control abundances, distributions and composition of plankton, provide data necessary to constrain and improve ecosystem and biogeochemical models, and forecast changes in marine ecosystems in light of climate change. In this paper we begin by providing the motivation for plankton observations, quantification and diversity qualification on a global scale. We then expand on the state-of-the-art, detailing a variety of relevant and (mostly) mature technologies and measurements, including bulk measurements of plankton, pigment composition, uses of genomic, optical and acoustical methods as well as analysis using particle counters, flow cytometers and quantitative imaging devices. We follow by highlighting the requirements necessary for a plankton observing system, the approach to achieve it and associated challenges. We conclude with ranked action-item recommendations for the next 10 years to move toward our vision of a holistic ocean-wide plankton observing system. Particularly, we suggest to begin with a demonstration project on a GO-SHIP line and/or a long-term observation site and expand from there, ensuring that issues associated with methods, observation tools, data analysis, quality assessment and curation are addressed early in the implementation. Global coordination is key for the success of this vision and will bring new insights on processes associated with nutrient regeneration, ocean production, fisheries and carbon sequestration.
- Published
- 2019
25. Report on the Marine Imaging Workshop 2017
- Author
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Schoening, Timm, primary, Durden, Jennifer, additional, Preuss, Inken, additional, Branzan Albu, Alexandra, additional, Purser, Autun, additional, De Smet, Bart, additional, Dominguez-Carrió, Carlos, additional, Yesson, Chris, additional, de Jonge, Daniëlle, additional, Lindsay, Dhugal, additional, Schulz, Jan, additional, Möller, Klas Ove, additional, Beisiegel, Kolja, additional, Kuhnz, Linda, additional, Hoeberechts, Maia, additional, Piechaud, Nils, additional, Sharuga, Stephanie, additional, and Treibitz, Tali, additional
- Published
- 2017
- Full Text
- View/download PDF
26. Report on the Marine Imaging Workshop 2017
- Author
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Schoening, Timm, Durden, Jennifer, Preuss, Inken, Branzan Albu, Alexandra, Purser, Autun, De Smet, Bart, Dominguez-Carrió, Carlos, Yesson, Chris, de Jonge, Daniëlle, Lindsay, Dhugal, Schulz, Jan, Möller, Klas Ove, Beisiegel, Kolja, Kuhnz, Linda, Hoeberechts, Maia, Piechaud, Nils, Sharuga, Stephanie, Treibitz, Tali, Schoening, Timm, Durden, Jennifer, Preuss, Inken, Branzan Albu, Alexandra, Purser, Autun, De Smet, Bart, Dominguez-Carrió, Carlos, Yesson, Chris, de Jonge, Daniëlle, Lindsay, Dhugal, Schulz, Jan, Möller, Klas Ove, Beisiegel, Kolja, Kuhnz, Linda, Hoeberechts, Maia, Piechaud, Nils, Sharuga, Stephanie, and Treibitz, Tali
- Abstract
Marine optical imaging has become a major assessment tool in science, policy and public understanding of our seas and oceans. Methodology in this field is developing rapidly, including hardware, software and the ways of their application. The aim of the Marine Imaging Workshop (MIW) is to bring together academics, research scientists and engineers, as well as industrial partners to discuss these developments, along with applications, challenges and future directions. The first MIW was held in Southampton, UK in April 2014. The second MIW, held in Kiel, Germany, in 2017 involved more than 100 attendees, who shared the latest developments in marine imaging through a combination of traditional oral and poster presentations, interactive sessions and focused discussion sessions. This article summarises the topics addressed during the workshop, particularly the outcomes of these discussion sessions for future reference and to make the workshop results available to the open public.
- Published
- 2017
27. Aquatische Optische Technologien in Deutschland
- Author
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Schulz, Jan, Möller, Klas Ove, Bracher, Astrid, Hieronymi, Martin, Cisewski, Boris, Zielinski, Oliver, Voss, Daniela, Gutzeit, Enrico, Peeters, Frank, and Hofmann, Hilmar
- Subjects
ddc:570 - Abstract
Optische Technologien und Verfahren sind sowohl in der limnischen als auch marinen Forschung Deutschlands über alle Bereiche und Skalen etabliert und entwickeln sich rasant weiter. Die Arbeitsgruppe „Aquatische Optische Technologien“ (AOT) will Forschern und Anwendern eine Plattform bieten, die Wissenstransfer fördert, der nationalen Entwicklergemeinschaft ein synergistisches Umfeld eröffnet und die internationale Sichtbarkeit der deutschen Aktivitäten in diesem Forschungsfeld erhöht.Diese Zusammenfassung dokumentiert erstmalig die AOT-Verfahren und -Technologien, die von nationalen Forschungsinstitutionen eingesetzt werden. Wir erwarten, dass die Dokumentation einen Trend in Richtung institutsübergreifender Harmonisierung initiiert. Dies wird die Etablierung offener Standards, eine Verbesserung im Zugang zu Dokumentationen und gegenseitige technischer Hilfestellung bei (System-) Integrationen ermöglichen. Effizienz und Leistungsfähigkeit der AOT-Entwicklung und Anwendung auf nationaler Ebene werden von diesen Bestrebungen profitieren.Weitere Arbeitsgruppen und Entwickler werden ausdrücklich ermutigt, Kontakt aufzunehmen, um in einer späteren Auflage berücksichtigt zu werden. published
- Published
- 2015
28. FS ALKOR Cruise Report AL453
- Author
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Möller, Klas Ove
- Subjects
14. Life underwater - Abstract
Cruise Report RV ALKOR Cruise 453 29.03.2015 – 10.04.2015 BONUS-‐INSPIRE
- Published
- 2015
- Full Text
- View/download PDF
29. Small-scale distribution of Baltic sprat: Statistical properties of school height, length and biomass imply school formation and species interaction mechanisms
- Author
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Neuenfeldt, Stefan, Gloes, Dominik, Möller, Klas Ove, Möllmann, Christian, Neuenfeldt, Stefan, Gloes, Dominik, Möller, Klas Ove, and Möllmann, Christian
- Published
- 2015
30. Aquatische Optische Technologien in Deutschland
- Author
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Schulz, Jan, Möller, Klas Ove, Bracher, Astrid, Hieronymi, Martin, Cisewski, Boris, Zielinski, Oliver, Voss, Daniela, Gutzeit, Enrico, Dolereit, Tim, Niedzwiedz, Gerd, Kohlberg, Gesche, Schories, Dirk, Kiko, Rainer, Körtzinger, Arne, Falldorf, Claas, Fischer, Philipp, Nowald, Nicolas, Beisiegel, Kolja, Martinez-Arbizu, Pedro, Rüssmeier, Nick, Röttgers, Rüdiger, Büdenberger, Jan, Jordt-Sedlazeck, Anne, Koch, Reinhard, Riebesell, Ulf, Hvitfeldt Iversen, Morten, Köser, Kevin, Kwasnitschka, Tom, Wellhausen, Jens, Thoma, Christoph, Barz, Kristina, Rohde, Sven, Nattkemper, Tim W., Schoening, Timm, Peeters, Frank, Hofmann, Hilmar, Busch, Julia A., Hirche, Hans-Jürgen, Niehoff, Barbara, Hildebrandt, Nicole, Stohr, Erik, Winter, Christian, Herbst, Gabriel, Konrad, Christian, Schmidt, Mark, Linke, Peter, Brey, Thomas, Bange, Hermann W., Nolle, Lars, Krägefsky, Sören, Gröger, Joachim, Sauter, Eberhard, Schulz, Miriam, Müller, Jens, Stepputtis, Daniel, Beszteri, Bank, Kloster, Michael, Kauer, Gerhard, Göritz, Anna, Gege, Peter, Lukas, Uwe Freiherr Von, and Bathmann, Ulrich
- Subjects
14. Life underwater - Abstract
Meereswissenschaftliche Berichte No 97 2015 - Marine Science Reports No 97 2015, Optic technologies and methods/procedures are established across all areas and scales in limnic and marine research in Germany and develop further continuously. The working group “Aquatic Optic Technologies” (AOT) constitutes a common platform for knowledge transfer among scientists and users, provides a synergistic environment for the national developer community and will enhance the international visibility of the German activities in this field. This document summarizes the AOT-procedures and -techniques applied by national research institutions. We expect to initiate a trend towards harmonization across institutes. This will facilitate the establishment of open standards, provide better access to documentation, and render technical assistance for systems integration. The document consists of the parts: Platforms and carrier systems outlines the main application areas and the used technologies. Focus parameters specifies the parameters measured by means of optical methods/techniques and indicates to which extent these parameters have a socio-political dimension. Methods presents the individual optical sensors and their underlying physical methods. Similarities denominates the common space of AOT-techniques and applications. National developments lists projects and developer groups in Germany designing optical high-technologies for limnic and marine scientific purposes., Optische Technologien und Verfahren sind sowohl in der limnischen als auch marinen Forschung Deutschlands über alle Bereiche und Skalen etabliert und entwickeln sich rasant weiter. Die Arbeitsgruppe „Aquatische Optische Technologien“ (AOT) will Forschern und Anwendern eine Plattform bieten, die Wissenstransfer fördert, der nationalen Entwicklergemeinschaft ein synergistisches Umfeld eröffnet und die internationale Sichtbarkeit der deutschen Aktivitäten in diesem Forschungsfeld erhöht. Diese Zusammenfassung dokumentiert erstmalig die AOT-Verfahren und -Technologien, die von nationalen Forschungsinstitutionen eingesetzt werden. Wir erwarten, dass die Dokumentation einen Trend in Richtung institutsübergreifender Harmonisierung initiiert. Dies wird die Etablierung offener Standards, eine Verbesserung im Zugang zu Dokumentationen und gegenseitige technischer Hilfestellung bei (System-) Integrationen ermöglichen. Effizienz und Leistungsfähigkeit der AOT-Entwicklung und Anwendung auf nationaler Ebene werden von diesen Bestrebungen profitieren. Weitere Arbeitsgruppen und Entwickler werden ausdrücklich ermutigt, Kontakt aufzunehmen, um in einer späteren Auflage berücksichtigt zu werden. Das Dokument gliedert sich in mehrere Teile: Plattformen und Trägersysteme zeigt, wie optische Sensoren häufig eingesetzt werden, aus welchen Medien heraus und mit welcher Hintergrund-Technologie. Fokusparameter beschreibt die Größen, die mit Hilfe optischer Verfahren gemessen werden und zeigt, inwiefern diese Größen eine gesellschaftspolitische Dimension besitzen. Methoden stellt die einzelnen optischen Sensoren und die zu Grunde liegenden physikalischen Verfahren vor. Gemeinsamkeiten beschreibt die nationale Schnittmenge an AOT-Themen, -Verfahren und – Anwendungen. Nationale Entwicklungen listet eine Vielzahl von Projekten und Entwicklergruppen auf, die optische Hoch-Technologie für den limnischen und marinen Einsatz entwickeln. Aufgrund dieser Gliederung lassen sich im Text inhaltliche Wiederholungen nicht vermeiden, da z.B. bei der Darstellung der Parameter die verwendeten Methoden und deren Einsatz auf Geräteträgern angesprochen werden. Bei einer Aufzählung von Untersuchungsmethoden gilt dies entsprechend umgekehrt. Wir haben aus Gründen der Lesbarkeit und Eigenständigkeit der einzelnen Abschnitte diese Wiederholungen bewusst in Kauf genommen und ggf. Querverweise eingefügt.
31. When to add a new process to a model – and when not: a marine biogeochemical perspective
- Author
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Martin, Adrian P., Dominguez, Angela Bahamondes, Baker, Chelsey A., Baumas, Chloé M.J., Bisson, Kelsey M., Cavan, Emma, Freilich, Mara, Galbraith, Eric, Galí, Martí, Henson, Stephanie, Kvale, Karin F., Lemmen, Carsten, Luo, Jessica Y., McMonagle, Helena, Viríssimo, Francisco de Melo, Möller, Klas Ove, Richon, Camille, Suresh, Iyyappan, Wilson, Jamie D., Woodstock, Matthew S., Yool, Andrew, Martin, Adrian P., Dominguez, Angela Bahamondes, Baker, Chelsey A., Baumas, Chloé M.J., Bisson, Kelsey M., Cavan, Emma, Freilich, Mara, Galbraith, Eric, Galí, Martí, Henson, Stephanie, Kvale, Karin F., Lemmen, Carsten, Luo, Jessica Y., McMonagle, Helena, Viríssimo, Francisco de Melo, Möller, Klas Ove, Richon, Camille, Suresh, Iyyappan, Wilson, Jamie D., Woodstock, Matthew S., and Yool, Andrew
- Abstract
Models are critical tools for environmental science. They allow us to examine the limits of what we think we know and to project that knowledge into situations for which we have little or no data. They are by definition simplifications of reality. There are therefore inevitably times when it is necessary to consider adding a new process to a model that was previously omitted. Doing so may have consequences. It can increase model complexity, affect the time a model takes to run, impact the match between the model output and observations, and complicate comparison to previous studies using the model. How a decision is made on whether to add a process is no more objective than how a scientist might design a laboratory experiment. To illustrate this, we report on an event where a broad and diverse group of marine biogeochemists were invited to construct flowcharts to support making the decision of when to include a new process in a model. The flowcharts are used to illustrate both the complexity of factors that modellers must consider prior to making a decision on model development and the diversity of perspectives on how that decision should be reached. The purpose of this paper is not to provide a definitive protocol for making that decision. Instead, we argue that it is important to acknowledge that there is no objectively “best” approach and instead we discuss the flowcharts created as a means of encouraging modellers to think through why and how they are doing something. This may also hopefully guide observational scientists to understand why it may not always be appropriate to include a process they are studying in a model.
32. Integration of Biology Sensor Outputs in the European Marine Observation and Data Network.
- Author
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Créach, Véronique, Felipe Artigas, Luis, Lefebvre, Alain, Lindh, Markus, Lombard, Fabien, Möller, Klas Ove, Schepers, Lennert, Seppälä, Jukka, and Thyssen, Melilotus
- Subjects
- *
DETECTORS , *BIOLOGY , *METADATA - Abstract
If some approaches have been developed for automated estimation of pigment groups (from scientist or companies), the data have not yet been hosted by a European data infrastructure, and data format and vocabulary still need to be better defined. Véronique Créach, Cefas (UK), veronique.creach@cefas.co.uk Luis Felipe Artigas, CNRS-LOG (France), felipe.artigas@univ-littoral.fr Alain Lefebvre, Ifremer (France), Alain.Lefebvre@ifremer.fr Markus Lindh, SMHI (Sweden), markus.lindh@smhi.se Fabien Lombard, CNRS-LOV (France), lombard@obs-vlfr.fr Klas Ove Möller, HZG (Germany), klas.moeller@hzg.de Lennert Schepers, VLIZ (Belgium), lennert.schepers@vliz.be Jukka Seppälä, SYKE (Finland), jukka.seppala@ymparisto.fi Melilotus Thyssen, CNRS-MIO (France), melilotus.thyssen@mio.osupytheas.fr JERICO-S3 is a new building-block in the "Joint European Research Infrastructure network of Coastal Observatories" concept. on-line automated flow cytometry: this single-cell/particle inflow technology becomes more and more popular for optically defining phytoplankton functional groups over the whole size range, due to the versatility and the autonomy of the instruments. [Extracted from the article]
- Published
- 2021
33. Report on the status of sensors used for measuring nutrients, biology-related optical properties, variables of the marine carbonate system, and for coastal profiling, within the JERICO network and, more generally, in the European context, Version 1.2
- Author
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Petersen, Wilhelm and Möller, Klas Ove
- Subjects
Biological oceanography [Parameter Discipline] ,Data quality control [Data Management Practices] ,Optical properties ,Sensors ,Chemical sensors ,Nutrient analysers ,Carbonate chemistry ,Data acquisition [Data Management Practices] ,Chemical oceanography [Parameter Discipline] - Abstract
The present deliverable gathers and reports on the outcomes of the four parts of the first JERICO-NEXT workshop on sensors for nutrients, biology-related optical properties, variables of the marine carbonate system, and for coastal profiling. It provides descriptions of such systems and the way they are run, and critically assesses their current level of development from the specific perspective of the operations carried out routinely by the JERICO observing network, and by extension, in the general European context. Published Refereed Current
- Published
- 2017
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