Models of Marine Microbial Biogeography and Biogeochemistry

Investigators: Mick Follows and Stephanie Dutkiewicz
Massachusetts Institute of Technology

Microbial communities in the sea mediate the global cycles of elements including climatically significant carbon, sulfur and nitrogen. Photosynthetic microbes in the surface ocean fix carbon and other elements into organic molecules, fueling food webs that sustain fisheries and most other life in the ocean. Sinking and subducted organic matter is remineralized and respired in the dark, sub-surface ocean maintaining a store of carbon about three times the size of the atmospheric inventory of CO2. The communities of microbes that sustain these global-scale cycles are functionally and genetically extremely diverse, non-uniformly distributed and sparsely sampled. Their biogeography reflects selection according to the relative fitness of myriad combinations of traits that govern interactions with the environment and other organisms. Trait-based theory and simulations provide tools with which to interpret biogeography and microbial mediation of biogeochemical cycles. Several outstanding challenges remain: observations to constrain the biogeography of marine microbes are still sparse and based on eclectic sampling methods, theories of the organization of the system have not been quantitatively tested, and the models used to simulate the system still lack sufficiently mechanistic biological foundations that will enable meaningful, dynamic simulations and state estimation.

Our goals are to integrate key new data sets in real time as they are collected at sea to facilitate direct tests of theoretical predictions; to synthesize an atlas of marine microbial biogeography suitable for testing some specific ecological theories and quantifying the skill of numerical simulations; to develop new trait-based models and simulations of regional and global microbial communities bringing to bear the power of metabolic constraints and knowledge of macro-molecular composition; to analyze these data and models using statistical tools to interpolate and extrapolate the sparse data sets, formally quantify the skill of numerical simulations; and employ data assimilation technologies to identify and optimize compatible model frameworks. Together, the results of these efforts will advance new theoretical approaches and lead to improved global ocean-scale predictions and regional state-estimates, constrained by observed biogeography. They will provide a quantification of the associated biogeochemical fluxes.

CBIOMES Collaborators in the MIT Group