The Deepwater Horizon (DWH) oil spill in the spring of 2010 resulted in an input of ∼4.1 million barrels of oil to the Gulf of Mexico; >22% of this oil is unaccounted for, with unknown environmental consequences. Here we investigated the impact of oil deposition on microbial communities in surface sediments collected at 64 sites by targeted sequencing of 16S rRNA genes, shotgun metagenomic sequencing of 14 of these samples and mineralization experiments using 14C-labeled model substrates. The 16S rRNA gene data indicated that the most heavily oil-impacted sediments were enriched in an uncultured Gammaproteobacterium and a Colwellia species, both of which were highly similar to sequences in the DWH deep-sea hydrocarbon plume. The primary drivers in structuring the microbial community were nitrogen and hydrocarbons. Annotation of unassembled metagenomic data revealed the most abundant hydrocarbon degradation pathway encoded genes involved in degrading aliphatic and simple aromatics via butane monooxygenase. The activity of key hydrocarbon degradation pathways by sediment microbes was confirmed by determining the mineralization of 14C-labeled model substrates in the following order: propylene glycol, dodecane, toluene and phenanthrene. Further, analysis of metagenomic sequence data revealed an increase in abundance of genes involved in denitrification pathways in samples that exceeded the Environmental Protection Agency (EPA)'s benchmarks for polycyclic aromatic hydrocarbons (PAHs) compared with those that did not. Importantly, these data demonstrate that the indigenous sediment microbiota contributed an important ecosystem service for remediation of oil in the Gulf. However, PAHs were more recalcitrant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem.

Global climate models project a decrease in the magnitude of precipitation in tropical regions. Changes in rainfall patterns have important implications for the moisture content and redox status of tropical soils, yet little is known about how these changes may affect microbial community structure. Specifically, does exposure to prior stress confer increased resistance to subsequent perturbation? Here we reduced the quantity of precipitation throughfall to tropical forest soils in the Luquillo Mountains, Puerto Rico. Treatments included newly established throughfall exclusion plots (de novo excluded), plots undergoing reduction for a second time (pre-excluded) and ambient control plots. Ten months of throughfall exclusion led to a small but statistically significant decline in soil water potential and bacterial populations clearly adapted to increased osmotic stress. Although the water potential decline was small and microbial biomass did not change, phylogenetic diversity in the de novo-excluded plots decreased by B40% compared with the control plots, yet pre-excluded plots showed no significant change. On the other hand, the relative abundances of bacterial taxa in both the de novo-excluded and pre-excluded plots changed significantly with throughfall exclusion compared with control plots. Changes in bacterial community structure could be explained by changes in soil pore water chemistry and suggested changes in soil redox. Soluble iron declined in treatment plots and was correlated with decreased soluble phosphorus concentrations, which may have significant implications for microbial productivity in these P-limited systems.

Biological soil crusts (BSCs) cover extensive portions of the earth's deserts. In order to survive desiccation cycles and utilize short periods of activity during infrequent precipitation, crust microorganisms must rely on the unique capabilities of vegetative cells to enter a dormant state and be poised for rapid resuscitation upon wetting. To elucidate the key events involved in the exit from dormancy, we performed a wetting experiment of a BSC and followed the response of the dominant cyanobacterium, Microcoleus vaginatus, in situ using a whole-genome transcriptional time course that included two diel cycles. Immediate, but transient, induction of DNA repair and regulatory genes signaled the hydration event. Recovery of photosynthesis occurred within 1 h, accompanied by upregulation of anabolic pathways. Onset of desiccation was characterized by the induction of genes for oxidative and photo-oxidative stress responses, osmotic stress response and the synthesis of C and N storage polymers. Early expression of genes for the production of exopolysaccharides, additional storage molecules and genes for membrane unsaturation occurred before drying and hints at preparedness for desiccation. We also observed signatures of preparation for future precipitation, notably the expression of genes for anaplerotic reactions in drying crusts, and the stable maintenance of mRNA through dormancy. These data shed light on possible synchronization between this cyanobacterium and its environment, and provides key mechanistic insights into its metabolism in situ that may be used to predict its response to climate, and or, land-use driven perturbations.

Nitrous oxide (N2O) emissions from inland waters remain a major source of uncertainty in global greenhouse gas budgets. N2O emissions are typically estimated using emission factors (EFs), defined as the proportion of the terrestrial nitrogen (N) load to a water body that is emitted as N2O to the atmosphere. The Intergovernmental Panel on Climate Change (IPCC) has proposed EFs of 0.25% and 0.75%, though studies have suggested that both these values are either too high or too low. In this work, we develop a mechanistic modeling approach to explicitly predict N2O production and emissions via nitrification and denitrification in rivers, reservoirs and estuaries. In particular, we introduce a water residence time dependence, which kinetically limits the extent of denitrification and nitrification in water bodies. We revise existing spatially explicit estimates of N loads to inland waters to predict both lumped watershed and half‐degree grid cell emissions and EFs worldwide, as well as the proportions of these emissions that originate from denitrification and nitrification. We estimate global inland water N2O emissions of 10.6–19.8 Gmol N year−1 (148–277 Gg N year−1), with reservoirs producing most N2O per unit area. Our results indicate that IPCC EFs are likely overestimated by up to an order of magnitude, and that achieving the magnitude of the IPCC's EFs is kinetically improbable in most river systems. Denitrification represents the major pathway of N2O production in river systems, whereas nitrification dominates production in reservoirs and estuaries.

Extreme weather, fires, and land use and climate change are significantly reshaping interactions within watersheds throughout the world. Although hydrological-biogeochemical interactions within watersheds can impact many services valued by society, uncertainty associated with predicting hydrologydriven biogeochemical watershed dynamics remains high. With an aim to reduce this uncertainty, an approximately 300-km 2 mountainous headwater observatory has been developed at the East River, CO, watershed of the Upper Colorado River Basin. The site is being used as a testbed for the Department of Energy supported Watershed Function Project and collaborative efforts. Building on insights gained from research at the "sister" Rifle, CO, site, coordinated studies are underway at the East River site to gain a predictive understanding of how the mountainous watershed retains and releases water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, and other disturbances influence hydrological-biogeochemical watershed dynamics at seasonal to decadal timescales. A system-of-systems perspective and a scale-adaptive simulation approach, involving the combined use of archetypal watershed subsystem "intensive sites" are being tested at the site to inform aggregated watershed predictions of downgradient exports. Complementing intensive site hydrological, geochemical, geophysical, microbiological, geological, and vegetation datasets are long-term, distributed measurement stations and specialized experimental and observational campaigns. Several recent research advances provide insights about the intensive sites as well as aggregated watershed behavior. The East River "community testbed" is currently hosting scientists from more than 30 institutions to advance mountainous watershed methods and understanding.