Simons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems
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Isabelle Cox, Robert J.W. Brewin, et al (2023), Distinct habitat and biogeochemical properties of low-oxygen-adapted tropical oceanic phytoplankton, Limnology and Oceanography, doi: 10.1002/lno.12404 [Shubha Sathyendranath]
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Warm congratulations to PML CBIOMES PI on this outstanding honor. Continue reading “Shubha Sathyendranath appointed MBE in the King’s Birthday Honours”
Smyth, T., D. Moffat, G. Tarran, S. Sathyendranath, F. Ribalet, J. Casey (2023), Determining drivers of phytoplankton carbon to chlorophyll ratio at Atlantic Basin scale, Frontiers in Marine Science, doi: 10.3389/fmars.2023.
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A new CBIOMES paper has important implications for our understanding of how plankton populations will change in a warming ocean – suggests caution when using statistical models to predict changes in plankton abundance. Continue reading “Prochlorococcus in a Changing Climate”
In this short European Space Agency (ESA) explainer video CBIOMES PI Shubha Sathyendranath talks about her work as part of ESA’s Climate Change Initiative is taking advantage of the observational power of satellites to understand ocean change.
The CBIOMES Workshop on Transects and Eco-provinces was held on January 23-25, 2023, at MIT’s Samberg Conference Center. Continue reading “Linking Transects and Eco-provinces”
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A warm welcome to PML Senior Scientist Mahasweta Saha who recently joined CBIOMES.
A new paper from the PML Group and collaborators uses a moving standard deviation saturation approach to reveal dominant timescales of variability in global satellite data.
Continue reading “Capturing High Spatial and Temporal Variability in Phytoplankton Biomass from Space”
Sun, X., Brewin, R. J., Sathyendranath, S., Dall’Olmo, G., Airs, R., Barlow, R., Bracher, A., Brotas, V., Kheireddine, M., Lamont, T., Marañón, E., Morán, X. A. G., Raitsos, D. E., Shen, F., & Tilstone, G. H. (2023), Coupling ecological concepts with an ocean-colour model: Phytoplankton size structure, Remote Sensing of Environment, doi: 10.1016/j.rse.2022.113415
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