Simons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems
Keisuke Inomura, Curtis Deutsch, Takako Masuda, Ondřej Prášil,
Michael J. Follows (2020), Quantitative models of nitrogen-fixing organisms, Computational and Structural Biotechnology Journal, doi: 10.1016/j.csbj.2020.11.022
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B.B. Cael, Emma L. Cavan, and Gregory L. Britten (2021), Reconciling the size-dependence of marine particle sinking speed, Geophysical Research Letters, doi: 10.1029/2020GL091771
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Smyth, TJ, Tarran, GA, Sathyendranath, S (2021), Sub-micron picoplankton shape, orientation, and internal structure combined to preferentially amplify the forward scatter, Optics Express, doi: 10.1364/OE.413576
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Stephanie Dutkiewicz, Philip W. Boyd, Ulf Riebesell (2020), Exploring biogeochemical and ecological redundancy in phytoplankton communities in the global ocean, Global Change Biology, doi: 10.1111/gcb.15493
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Niall McGinty, Andrew D Barton, Nicholas R Record, Zoe V Finkel, David G Johns, Charles A Stock, Andrew J Irwin (2020), Anthropogenic climate change impacts on copepod trait biogeography, Global Change Biology, doi: 10.1111/gcb.15499
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Emily J. Zakem, Martin F. Polz and Michael J. Follows (2020), Redox-informed models of global biogeochemical cycles, Nature Communications, doi: 10.1038/s41467-020-19454-w
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Joseph J. Vallino and Ioannis Tsakalakis (2020), Phytoplankton temporal strategies increase entropy production in a marine food web model, Entropy, doi: 10.3390/e22111249
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Growth rates are central to understanding microbial interactions and community dynamics. The Fuhrman Lab, which uses ‘omics data to seek a better understanding of microbial growth, interactions, and biogeographies has been evaluating a promising new approach to simultaneously determine the growth rates of many different kinds of microbes from the within-genome distributions of DNA extracted from in-situ (mixed) ocean populations. Continue reading “Using Metagenomics to Measure In-Situ Microbial Growth Rates”
Postdoc John Casey continues to work closely with MIT-CBIOMES Group PI Mick Follows on research combining quantitative proteomics, flux balance analysis, and molecular modeling of membrane transports to develop a steady-state model of microbial acclimation to substrate limitation. A paper by the same name was recently published in PLOS Computational Biology. Continue reading “Towards a Better Model for the Microbe Membrane (Revisited)”
The Irwin Group uses statistical modeling techniques to understand niches, traits, and interactions within marine microbial communities. A new paper confirms the value of trait-based approaches in investigating the mechanisms underlying phytoplankton biomass dynamics, and in predicting the community response to environmental changes. Continue reading “Turning to Traits to Understand Phytoplankton Biomass Patterns”