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Predicting how marine chemistry and biology will respond to global climate change is a pressing issue for society. MBL Senior Scientist Joseph Vallino has received a grant from the Simons Foundation to develop new modeling techniques for predicting such changes, using ideas derived from thermodynamics, which concerns how energy moves in a system.

Recent advancements in thermodynamics indicate that systems will internally organize so as to maximize the flow and dissipation of energy. For example, the temperature difference that develops between the ocean and atmosphere over the summer drives the formation of hurricanes, whose presence hastens the dissipation of the temperature difference.

Vallino’s project extends this fundamental principal to microbial communities, such as bacteria and phytoplankton, which form the base of the ocean food web and strongly influence ocean chemistry. Based on information on how plankton use solar and chemical energy for replication from carbon, nitrogen, phosphorus and other elements in the environment, the model can predict how plankton allocate cellular resources to basic metabolic functions, such as photosynthesis or nitrogen fixation from the atmosphere, as well as how those functions change over time and space within the ocean.

Vallino’s award, titled “Thermodynamically Guided Trait-based Ocean Biogeochemistry Modeling,” is part of a large collaborative project on “Computational Biogeochemical Modeling of Marine Ecosystems” () funded by the Simons Foundation and lead by Mick Follows at MIT. The CBIOMES project seeks to improve our predictive understanding of marine phytoplankton and zooplankton that form the base of marine food webs and control ocean biogeochemistry, which accounts for half of the global carbon dioxide fixation by photosynthesis each year. Scientists in computational modeling, statistics, mathematics, biological oceanography, laboratory experiments, and remote sensing comprise the CBIOMES Simons Collaboration team.

Figure legend: The dispersal of energy as heat at ambient temperature is the definition of entropy and the theory being developed and applied to planktonic marine foods is known as the Maximum Entropy Production (MEP) principle. MEP theory does not distinguish between living and nonliving systems; however, we have proposed that nonliving systems maximize instantaneous entropy production, such as a rock rolling down a hill (red up-arrow in image), while living systems use information, acquired by evolution, culled by natural selection, and stored in genomes, to maximize entropy production coordinated over time and space (green up-arrow in image).

Temporal strategies, such as circadian rhythms, are hallmarks of biology, yet they are seldom considered in ocean biogeochemistry models. Our research will explore the time scales of prediction over which biology operates using MEP theory and computational models, where metabolic reactions used to describe plankton will be refined and constrained by genome-scale metabolic models that are routinely constructed from DNA sequencing and made publicly available by systems biologists. The resulting MEP-based models will be run in a 3D global ocean circulation model, and the results will be compared to available observations to test our hypotheses regarding MEP. Credit: Joe Vallino