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Published on: September 11, 2016
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Coupling among Microbial Communities, Biogeochemistry, and Mineralogy across Biogeochemical Facies
James C Stegen1, Allan Konopka1, James P McKinley1
1Pacific Northwest National Laboratory, Richland, WA, USA.
Scientific Reports
|July 30, 2016
Summary
Predicting subsurface microbial communities using sediment facies is now possible. We found that biogeochemical facies, like oxidized and reduced zones, influence microbial biomass, richness, and composition, enabling better model predictions.
Area of Science:
- Geomicrobiology
- Environmental Science
- Subsurface Biogeochemistry
Background:
- Sediment physical properties define lithofacies and influence subsurface microbial communities.
- Spatial distribution of lithofacies presents an opportunity to predict microbial attributes.
- Biogeochemical facies (oxidized, reduced, transition) are key to understanding microbial ecology.
Purpose of the Study:
- Characterize biogeochemical facies within a lithofacies.
- Elucidate relationships between facies features and microbial community attributes (biomass, richness, composition).
- Develop a predictive model for microbial biomass concentration based on facies distribution.
Main Methods:
- Characterization of three biogeochemical facies: oxidized, reduced, and transition.
- Analysis of microbial community biomass, richness, and composition in relation to facies.
- Null modeling to assess ecological selection pressures (redox state, mineralogy).
- Spatial prediction of microbial biomass using coupled facies distribution and biomass-facies relationships.
Main Results:
- Elevated microbial biomass observed in the transition zone between oxidized and reduced facies.
- Microbial richness was lower in reduced facies, correlated with pH and mineralogy.
- Ecological selection, driven by redox state and mineralogy, influenced microbial community composition.
Conclusions:
- Biogeochemical facies significantly control subsurface microbial community structure and biomass.
- Predictive modeling of microbial biomass is feasible by integrating facies distribution and established relationships.
- This approach can reduce uncertainty in hydro-biogeochemical models by constraining simulated dynamics.
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