CBIOMES Project: Statistical Modeling of Microbial Communities: Niches, Traits and Interactions
Marine microbial communities form the base of the marine food web and perform about half of the photosynthesis on Earth. They are key components of the global carbon cycle and help to sequester carbon in the deep ocean, removing it from the atmosphere, through the burial of organic matter on the seafloor. The productivity and function of marine microbial communities is determined in part by the biogeography — which species live where. We will assemble and analyze observations of microbial communities to develop predictive statistical models that describe community composition. Additional statistical models will be developed to determine the physiological and ecological traits of species and groups of species that determine the growth rates of marine microbes. Finally we will analyze community composition data to determine sub-communities of species that tend to co-occur or tend to not be found together to better understand the complex interactions among species and the suites of traits of species that form stable communities.
My training is in limnology and oceanography with a focus on phytoplankton ecology. In recent years I have been teaching oceanography and biometry in China. I have worked on phytoplankton physiological modeling, modeling arctic ice seasonality in Hudson Bay, Canada, and the timing of the spring phytoplankton bloom in the Gulf of Saint Lawrence. This work involves considerable expertise with computer models and large amounts of output. These skills will enable me to be productive working on ecological/biological oceanographic questions associated with this proposal.