Microbes drive the biogeochemical cycles of earth systems, yet the long-standing goal of linking emerging genomic information, microbial traits, mechanistic ecosystem models, and projections under climate change has remained elusive despite a wealth of emerging genomic information. Here we developed a general genome-to-ecosystem (G2E) framework for integrating genome-inferred microbial kinetic traits into mechanistic models of terrestrial ecosystems and applied it at a well-studied Arctic wetland by benchmarking predictions against observed greenhouse gas emissions. We found variation in genome-inferred microbial kinetic traits resulted in large differences in simulated annual methane emissions, quantitatively demonstrating that the genomically observable variations in microbial capacity are consequential for ecosystem functioning. Applying microbial community-aggregated traits via genome relative-abundance-weighting gave better methane emissions predictions (i.e., up to 54% decrease in bias) compared to ignoring the observed abundances, highlighting the value of combined trait inferences and abundances. This work provides an example of integrating microbial functional trait-based genomics, mechanistic and pragmatic trait parameterizations of diverse microbial metabolisms, and mechanistic ecosystem modeling. The generalizable G2E framework will enable the use of abundant microbial metagenomics data to improve predictions of microbial interactions in many complex systems, including oceanic microbiomes.

Biogeochemical reactions and their rates are largely controlled by microbes. There is thus a growing interest in the inclusion of complex microbial communities, their functioning, and interactions into reactive transport models. Conventionally, these models have included thermodynamic-based approaches that describe the stoichiometry and energetics of microbial reactions. In this chapter, we describe two emergent approaches that can be used to model microbial community dynamics—trait-based approach and dynamic energy allocation model. We explain their practice, limitations, and strategies for improvement.

Three-dimensional variably saturated flow and multicomponent biogeochemical reactive transport modeling, based on published and newly generated data, is used to better understand the interplay of hydrology, geochemistry, and biology controlling the cycling of carbon, nitrogen, oxygen, iron, sulfur, and uranium in a shallow floodplain. In this system, aerobic respiration generally maintains anoxic groundwater below an oxic vadose zone until seasonal snowmelt-driven water table peaking transports dissolved oxygen (DO) and nitrate from the vadose zone into the alluvial aquifer. The response to this perturbation is localized due to distinct physico-biogeochemical environments and relatively long time scales for transport through the floodplain aquifer and vadose zone. Naturally reduced zones (NRZs) containing sediments higher in organic matter, iron sulfides, and non-crystalline U(IV) rapidly consume DO and nitrate to maintain anoxic conditions, yielding Fe(II) from FeS oxidative dissolution, nitrite from denitrification, and U(VI) from nitrite-promoted U(IV) oxidation. Redox cycling is a key factor for sustaining the observed aquifer behaviors despite continuous oxygen influx and the annual hydrologically induced oxidation event. Depth-dependent activity of fermenters, aerobes, nitrate reducers, sulfate reducers, and chemolithoautotrophs (e.g., oxidizing Fe(II), S compounds, and ammonium) is linked to the presence of DO, which has higher concentrations near the water table.

Understanding the fundamentals of genomic systems or the processes governing impactful weather patterns are examples of the types of simulation and modeling performed on the most advanced computing resources in America. High-performance computing and computational science together provide a necessary platform for the mission science conducted by the Biological and Environmental Research (BER) office at the U.S. Department of Energy (DOE). This report reviews BER’s computing needs and their importance for solving some of the toughest problems in BER’s portfolio. BER’s impact on science has been transformative. Mapping the human genome, including the U.S.-supported international Human Genome Project that DOE began in 1987, initiated the era of modern biotechnology and genomics-based systems biology. And since the 1950s, BER has been a core contributor to atmospheric, environmental, and climate science research, beginning with atmospheric circulation studies that were the forerunners of modern Earth system models (ESMs) and by pioneering the implementation of climate codes onto high-performance computers. See http://exascaleage.org/ber/ for more information.

Wetlands are estimated to contribute nearly 40 % of global annual methane (CH4) emissions to the atmosphere. However, because CH4 fluxes from these systems vary spatially, seasonally, and by wetland type, there is a large uncertainty associated with scaling up the CH4 flux from these environments. We monitored seasonal patterns of CH4 cycling from tidal mudflat wetland sediments adjacent to a vegetated freshwater wetland in coastal Georgia between 2008 and 2009. CH4 emissions were significantly correlated with CH4 production and sediment saturation state with respect to CH4 but not with temperature. CH4 cycling displayed distinct seasonal patterns. Winter months were characterized by low CH4 production and emissions. During the spring, summer and fall, CH4 fluxes exceeded CH4 production in the top 40 cm. Comparison of CH4 sources and sinks in conjunction with the interpretation of CH4 concentration profiles using a 1D reactive transport model indicated that CH4 delivered via lateral tidal pumping likely provided additional CH4 to the upper sediment column. Seasonally high CH4 ebullition rates reflected increased CH4 production and decreased CH4 solubility. The annual CH4 flux was estimated to be on the order of 10 mol CH4 m−2 y−1 which is 2–4 times the global average for wetland CH4 emissions. Thus, even though tidal freshwater mudflats are of limited spatial extent, these environments may serve as globally significant sources of CH4 to the atmosphere. This study highlights the importance of these dynamic environments to the global CH4 cycle and their relevance to climate change.

Members of the marine Roseobacter lineage have been characterized as ecological generalists, suggesting that there will be challenges in assigning well-delineated ecological roles and biogeochemical functions to the taxon. To address this issue, genome sequences of 32 Roseobacter isolates were analyzed for patterns in genome characteristics, gene inventory, and individual gene/pathway distribution using three predictive frameworks: phylogenetic relatedness, lifestyle strategy and environmental origin of the isolate. For the first framework, a phylogeny containing five deeply branching clades was obtained from a concatenation of 70 conserved single-copy genes. Somewhat surprisingly, phylogenetic tree topology was not the best model for organizing genome characteristics or distribution patterns of individual genes/pathways, although it provided some predictive power. The lifestyle framework, established by grouping isolates according to evidence for heterotrophy, photoheterotrophy or autotrophy, explained more of the gene repertoire in this lineage. The environment framework had a weak predictive power for the overall genome content of each strain, but explained the distribution of several individual genes/pathways, including those related to phosphorus acquisition, chemotaxis and aromatic compound degradation. Unassembled sequences in the Global Ocean Sampling metagenomic data independently verified this global-scale geographical signal in some Roseobacter genes. The primary findings emerging from this comparative genome analysis are that members of the lineage cannot be easily collapsed into just a few ecologically differentiated clusters (that is, there are almost as many clusters as isolates); the strongest framework for predicting genome content is trophic strategy, but no single framework gives robust predictions; and previously unknown homologs to genes for H(2) oxidation, proteorhodopsin-based phototrophy, xanthorhodpsin-based phototrophy, and CO(2) fixation by Form IC ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) expand the possible mechanisms for energy and carbon acquisition in this remarkably versatile bacterial lineage.

Prediction of the fate and environmental impacts of groundwater contaminants requires the identification of relevant biogeochemical processes and necessitates the macroscopic representation of microbial activity occurring at the microscale. Using a well-studied sandy aquifer environment, we evaluate the importance of pore distribution on organic matter respiration in a porous medium environment by performing spatially explicit simulations of microbial metabolism at the sub-millimeter scale. Model results using an idealized porous medium under non-biofilm forming conditions indicate that while some heterogeneity is observed for flow rates, distributions of microbes and dissolved organic substrates remain relatively homogenous at the grain scale. At the macroscale in the same environment, we assess the impact of a comprehensive reaction network description for a phenolic contaminant plume, and compare the findings to a setting describing organic matter breakdown in a coastal marine sediment. This comparison reveals the importance of reactions recycling reduced metabolites at redox interfaces, leading to a competition for oxidants. When the spatio-temporal dynamics of microbial groups are accounted for, our simulations show the importance of reaction energetics and nutrient limitations such as microbial nitrogen demands.

ABSTRACT Microbial activity governs elemental cycling and the transformation of many anthropogenic substances in aqueous environments. Through the development of a dynamic cell model of the well-characterized, versatile, and abundant Geobacter sulfurreducens , we showed that a kinetic representation of key components of cell metabolism matched microbial growth dynamics observed in chemostat experiments under various environmental conditions and led to results similar to those from a comprehensive flux balance model. Coupling the kinetic cell model to its environment by expressing substrate uptake rates depending on intra- and extracellular substrate concentrations, two-dimensional reactive transport simulations of an aquifer were performed. They illustrated that a proper representation of growth efficiency as a function of substrate availability is a determining factor for the spatial distribution of microbial populations in a porous medium. It was shown that simplified model representations of microbial dynamics in the subsurface that only depended on extracellular conditions could be derived by properly parameterizing emerging properties of the kinetic cell model.

Detection of Bifidobacterium adolescentis was used as an effective genetic marker of human fecal contamination in Georgia estuaries. Enterococci enumerations on mEI media indicated that a tributary to the Little Satilla River with 516 CFU/100 ml was the most polluted of all the rivers tested. Extracted DNA from eight river water samples was subjected to a two-step nested PCR protocol using genus and species specific primers for Bifidobacterium spp. and B. adolescentis. B. adolescentis was detected from extracted DNA in Dunbar River, Black Bank Creek, and in a Little Satilla River tributary which demonstrates the presence of human fecal contamination in these three rivers. In the five other estuaries tested including West Point-Federica River and the Altamaha River, which both had less than 16 CFU/100 ml of enterococci, B. adolescentis was not detected. (c) 2006 Elsevier B.V. All rights reserved.

We attached satellite tags to 16 humpback whales off South Eastern Australia in October/November 2008. The tags transmitted for an average of 55 days (range: 3-156 days) and provided data on migratory movements between Australia and the Antarctic feeding grounds. While the dispersal into the Southern Ocean was generally consistent with movements determined from historical discovery marks, unexpected findings included an eastwards migration of eight whales to SW New Zealand, regular feeding in temperate latitudes (areas of high productivity) and a migration of one whale into Area IV. A full analysis of these data, with a focus on habitat utilization, will be developed.