ABSTRACT

Despite low standing biomass, extensive carbon processing occurs in the oceans, largely by diverse microbial consumers. Until recently, bacteria were considered the main degraders of organic matter, while non-bacterial consumers? role in carbon cycling has largely been ignored. However, eukaryotes such as fungi exhibit distinct metabolic capacities and responses to environmental variables, suggesting global change may alter the balance of microbial activities in the oceans and potentially alter the fate of marine carbon. Here, researchers integrate field data with modeling and laboratory experiments with representative cultures to identify microbes? functional roles in marine organic matter degradation and determine their response to changing environmental conditions. This project will open new windows into the diversity of microbial metabolisms and how these dynamics may shift with global change driven increases in temperature and other environmental factors. Additionally, this project builds a new scientific research team and expands scientific training to levels ranging from K-5 teachers, to undergraduate and PhD students.


This project will leverage a decade-long, coastal microbial time series, the Piver?s Island Coastal Observatory (PICO), to examine how diverse heterotrophic microbial communities (bacteria, phytoplankton, fungi and Labyrinthulomycetes protists) metabolize carbon compounds under different thermal regimes. Researchers will develop a model microbial consortium that has the potential to transform our perception of carbon cycling in coastal systems by integrating functional, organismal-interaction and environment-dependent responses into a modeling framework. Empirical Dynamic Modeling will identify drivers of the observed dynamics, differentiate causation from correlation, infer effects of possibly unobserved variables (e.g. predation), and quantify interactions between organisms. These data will further be used to develop a culturable model consortium whose members metabolize distinct components of phytoplankton-derived organic matter. To test both model predictions and how well the consortium represents complex microbiomes, both the model consortium and a ?wild? coastal seawater microbiome will be assayed for changes in function (phytoplankton DOM degradation) as temperatures increase (+4 °C). These experiments will compare outcomes for individual isolates, the consortium, and a wild coastal microbiome in composition/abundance, gene expression and degradation of specific compounds. Finally, experimental results will be used to parameterize and refine an Ensemble Sparse Identification of Nonlinear Dynamics model that can predict the fate and transformation of carbon in marine systems under varying climate scenarios. While this research leverages existing expertise in marine microbiomes, this model consortium approach can be applied to diverse systems to answer questions about environmental filtering, organismal interactions and functional diversity critical to predicting ecosystem-level responses to environmental change.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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