Capturing carbon dioxide (CO(2)) emissions from industrial sources and injecting the emissions deep underground in geologic formations is one method being considered to control CO(2) concentrations in the atmosphere. Sequestering CO(2) underground has its own set of environmental risks, including the potential migration of CO(2) out of the storage reservoir and resulting acidification and release of trace constituents in shallow groundwater. A field study involving the controlled release of groundwater containing dissolved CO(2) was initiated to investigate potential groundwater impacts. Dissolution of CO(2) in the groundwater resulted in a sustained and easily detected decrease of ~3 pH units. Several trace constituents, including As and Pb, remained below their respective detections limits and/or at background levels. Other constituents (Ba, Ca, Cr, Sr, Mg, Mn, and Fe) displayed a pulse response, consisting of an initial increase in concentration followed by either a return to background levels or slightly greater than background. This suggests a fast-release mechanism (desorption, exchange, and/or fast dissolution of small finite amounts of metals) concomitant in some cases with a slower release potentially involving different solid phases or mechanisms. Inorganic constituents regulated by the U.S. Environmental Protection Agency remained below their respective maximum contaminant levels throughout the experiment.

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Abstract. Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

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.

Methane is a potent greenhouse gas, but its effects on Earth's climate remain poorly constrained, in part due to uncertainties in global methane fluxes to the atmosphere. An important source of atmospheric methane is the methane generated in organic‐rich sediments underlying surface water bodies, including lakes, wetlands, and the ocean. The fraction of the methane that reaches the atmosphere depends critically on the mode and spatiotemporal characteristics of free‐gas venting from the underlying sediments. Here we propose that methane transport in lake sediments is controlled by dynamic conduits, which dilate and release gas as the falling hydrostatic pressure reduces the effective stress below the tensile strength of the sediments. We test our model against a four‐month record of hydrostatic load and methane flux in Upper Mystic Lake, Mass., USA, and show that it captures the complex episodicity of methane ebullition. Our quantitative conceptualization opens the door to integrated modeling of methane transport to constrain global methane release from lakes and other shallow‐water, organic‐rich sediment systems, and to assess its climate feedbacks.

.[1] Freshwater lakes can emit significant quantities of methane to the atmosphere by bubbling. The high spatial and temporal heterogeneity of ebullition, combined with a lack of high-resolution field measurements, has made it difficult to accurately estimate methane fluxes or determine the underlying mechanisms for bubble release. We use a high-temporal resolution data set of ebullitive fluxes from the eutrophic Upper Mystic Lake, Massachusetts to understand the triggers that lead to bubbling from submerged sediments. A wavelet approach is introduced to detect ebullition events for multiple time-scales, and is complemented with traditional statistical methods for data analyses. We show that bubble release from lake sediments occurred synchronously at several sites, and was closely associated with small, aperiodic drops in total hydrostatic pressure. Such results are essential to constrain mechanistic models and to design future measurement schemes, particularly with respect to the temporal scales that are needed to accurately observe and quantify ebullition in aquatic ecosystems.Citation: Varadharajan, C., and H. F. Hemond (2012), Time-series analysis of high-resolution ebullition fluxes from a stratified, freshwater lake,

We describe a trap that can be used for automated, high temporal resolution measurement of ebullition fluxes in aquatic environments. The trap comprises a submerged cone connected to a transparent PVC pipe that serves as a collection chamber. A differential pressure sensor at the top of the pipe measures the pressure caused by gas accumulation in the chamber. The sensor circuit consists of low-power electronics and can function for longer than 6 months on two high-capacity AA lithium batteries. The circuit, batteries, and a commercial data logger that records the measurements are enclosed in a custom-made, 10-cm diameter waterproof housing. The trap is designed to be fabricated economically and easily so that many units can be deployed for greater spatial coverage. We have used several of these automated traps to measure bubbling fluxes at a lake, and have collected data continuously at a resolution of 5 or 10 min over 6 months.

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