Defining the Connections Between Chemistry and Microbiology at Deep-sea Hydrothermal Vents

T.M. McCollom

Corresponding author: mccollom@lasp.colorado.edu
University of Colorado, Laboratory for Atmospheric and Space Physics, Boulder, CO 80309

Abstract:
The goal of my R2K-related research is to be able to explain how the distribution and activity of microbial communities at deep-sea hydrothermal vents is controlled by the chemistry of the hydrothermal fluids, and how the biological community, in turn, influences the composition of the fluids, including both inorganic and organic components. The major tools I use in this endeavor are numerical geochemical models to place quantitative constraints on sources of chemical energy that are available to biological organisms in vent environments, and laboratory experiments that examine organic chemical reactions under simulated hydrothermal conditions. Existing numerical models that have investigated links between chemistry and biology are based on batch mixing of hydrothermal fluid with seawater. These models assume static conditions and do not account for biological metabolic activity. In order to more accurately portray the chemical environment and account for the impact of microbial metabolism on evolving fluid chemistry during mixing, I am currently developing reactive transport models of fluid mixing environments at hydrothermal vents that explicitly account for the effects of fluid transport and microbial metabolic processes. These models will provide improved estimates of the distribution and abundance of chemical energy sources and microorganisms during mixing, and will provide an improved framework for understanding the distributions obtained from microbial studies in the natural system.

Keywords:
Numerical modeling, microbiology, fluid geochemistry

Contributions to Integration and Synthesis:
Numerical models provide a framework to explicitly define the links between the geochemistry of hydrothermal fluids and the chemosynthetic organisms that dominate mid-ocean ridge ecosystems. To date, numerical models that investigate the chemical-biological link have been generic, in the sense that they are not performed to interpret a particular site or set of observations. However, the potential exists to couple the models to observations from a particular vent locality to aid in the interpretation of the metabolic diversity and distribution of the microbial community. My colleagues and I are presently working on models that explore how variations in measured vent chemistry at different sites impact the amounts and type of chemical energy that is available, and will investigate whether these differences are reflected in the observed microbial populations.