Simons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems
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New study from MIT-CBIOMES finds swirling waters replenish nutrients in open ocean, and could mitigate some climate change effects. Continue reading “Small eddies play a big role in feeding ocean microbes”
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A warm welcome to postdoc Shlomit Sharoni who recently joined the Follows Group.
Computer models of global ocean biogeochemistry typically don’t include the day/night light cycle. CBIOMES researchers are. Continue reading “New model sheds light on day/night cycle in the global ocean”
Térence Legrand, Anne Chenuil, Enrico Ser-Giacomi, Sophie Arnaud-Haond, Nicolas Bierne & Vincent Rossi (2022), Spatial coalescent connectivity through multi-generation dispersal modelling predicts gene flow across marine phyla, Nature Communications, doi: 10.1038/s41467-022-33499-z
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Ophélie Da Silva, Sakina-Dorothée Ayata, Enrico Ser-Giacomi, Jade Leconte, Eric Pelletier, Cécile Fauvelot, Mohammed-Amin Madoui, Lionel Guidi, Fabien Lombard, Lucie Bittner (2022), Genomic differentiation of three pico-phytoplankton species in the Mediterranean Sea, Environmental Microbiology, doi: 10.1111/1462-2920.16171
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Alberto Baudena, Enrico Ser-Giacomi, Isabel Jalón-Rojas, François Galgani and Maria Luiza Pedrotti (2022), The streaming of plastic in the Mediterranean Sea, Nature Communications, doi: 10.1038/s41467-022-30572-5
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Colomban de Vargas et al (2022), Plankton Planet: A frugal, cooperative measure of aquatic life at the planetary scale, Front. Mar. Sci., doi: 10.3389/fmars.2022.936972 [Michael. J. Follows]
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Zhen Wu, Jincheng Li, Yanxin Sun, Josep Peñuelas, Jilin Huang, Jordi Sardans, Qingsong Jiang, Jacques C. Finlay, Gregory L. Britten, Michael J. Follows, Wei Gao, Boqiang Qin, Jinren Ni, Shouliang Huo & Yong Liu (2022), Imbalance of global nutrient cycles exacerbated by the greater retention of phosphorus over nitrogen in lakes, Nature Geosciences, doi: 10.1038/s41561-022-00958-7
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A multi-lab collaboration that grew out of the January 2020 Bayesian Workshop finds using the Bayesian approach can yield more realistic biological models and better constrained cellular growth rates. Continue reading “Interpreting microbial growth rates from size distributions.”