Real phytoplankton adapt to new environments in complex physiological ways, but current computer models do not resolve the small-scale fluid dynamical environments that constrain phytoplankton biology. Darwin Project member David Talmy, a post doc in EAPS, will use a new high resolution global simulation to explore how submesoscale processes impact phytoplankton biology.
The MIT Darwin Project investigates the enormous role of phytoplankton in the marine ecosystem. These tiny green cells float around by the billion, together providing half the world’s total oxygen and cycling carbon in our atmosphere and oceans. To investigate these biogeochemical interactions, the Darwin group uses ocean circulation output from ECCO simulations using MITgcm to provide a detailed dynamic framework within which to embed their ecosystems models. Recently, EAPS research scientist Stephanie Dutkiewicz showed that diverse populations of plankton, the base of the ocean food chain, will significantly shift in warmer future oceans.
The thing is, that knowledge is incomplete. Real phytoplankton have complex physiological ways to adapt to new environments, and current global models do not resolve the small-scale fluid dynamical environments that constrain phytoplankton biology. But given a high-enough resolution model, researchers may be able to rise above that limitation, and it is this that Darwin Project member David Talmy, a post doc in EAPS, plans to find out.
Based on measurements from ocean cruises and laboratory experiments, Talmy has designed some special mathematical abstractions of phytoplankton—code for virtual plankton cells that more closely reflects how real cells respond to light, temperature, and nutrient levels in ocean eddies. Working with Mick Follows and Chris Hill, Talmy will soon unleash those virtual organisms in a new extremely high-resolution MITgcm, A Brave New Ocean World I, and study survival and adaptation patterns in closer detail. “I think we will start to get a feel for how these submesoscale processes influence how a phytoplankton cell experiences and adapts to its environment,” he says. Ultimately, this kind of work may help the Darwin Project to understand, for example, how plankton’s ability to cycle carbon could change in warmer oceans.
The opportunity to work with the MITgcm is a large part of what drew Talmy to his research position in the MIT Darwin Project last year. In his view, the MITgcm code can more faithfully represent how a real phytoplankton cell experiences its environment. “Individual organisms experience and track their immediate surroundings, which affect how they respond to the next environment they enter,” he says. “Where they have been matters as much as where they are going.” In contrast to past models used to study ecosystems, the MITgcm allows a “Lagrangian” approach to fluid dynamics, which essentially enables a virtual phytoplankton cell to “remember” the light, temperature, and nutrient levels of its past location, as a cell does in the real ocean.
“There are a whole host of future directions that we can travel if we can think about the physiology of specific organisms in greater detail and broaden our models to include other types of organisms,” Follows said at the end of the recent Estimating the Circulation and Climate of the Ocean meeting held at MIT this past January. “I think the model output will give us new ideas about how we might go out and nail down some of these physiological mechanisms in the ocean.” A fitting closing statement indeed, for it captures a point about global ocean modeling that often gets lost in translation outside of science. It’s not a mirror of the real world, not a machine of future predictions, but rather a tool to help guide a scientist’s interpretation of otherwise confusing phenomena.
The MIT Darwin Project is an initiative to advance the development and application of novel models of marine microbes and microbial communities.
David Talmy is interested in acclimation and adaptation of marine microbes in different aquatic environments. He use simple, idealized mathematical models to understand how the traits of organisms in different habitats arise due to ecological and physiological constraints. A particular interest is in how phytoplankton traits arise due to variation in irradiance and nutrients. The models he works on will be used to inform the parameterization of biological processes in large scale models of ocean biogeochemistry.