Mapped Predictions of Manganese and Arsenic in an Alluvial Aquifer Using Boosted Regression Trees.

Manganese (Mn) concentrations and the probability of arsenic (As) exceeding the drinking-water standard of 10 µg/L were predicted in the Mississippi River Valley alluvial aquifer (MRVA) using boosted regression trees (BRT). BRT, a type of ensemble-tree machine-learning model, were created using predictor variables that affect Mn and As distribution in groundwater. These variables included iron (Fe) concentrations and specific conductance predicted from previously developed BRT models, groundwater flux and age estimates from MODFLOW, and hydrologic characteristics. The models also included results from the first airborne geophysical survey conducted in the United States to target an entire aquifer system. Predictions of high Mn and As occurred where Fe was high. Predicted high Mn concentrations were correlated with fraction of young groundwater (less than 65 years) computed from MODFLOW results. High probabilities of As exceedance were predicted where groundwater was relatively old and airborne electromagnetic resistivity was high, typically proximal to streams. Two-variable partial-dependence plots and sensitivity analysis were used to provide insight into the factors controlling Mn and As distribution in groundwater. The maps of predicted Mn concentrations and As exceedance probabilities can be used to identify areas where these constituents may be high, and that could be targeted for further study. This paper shows that incorporation of a selected set of process-informed data, such as MODFLOW results and airborne geophysics, into a machine-learning model improves model interpretability. Incorporation of process-rich information into machine-learning models will likely be useful for addressing a wide range of problems of interest to groundwater hydrologists.

Advancing the Sustainability of US Agriculture through Long-Term Research.

Agriculture in the United States must respond to escalating demands for productivity and efficiency, as well as pressures to improve its stewardship of natural resources. Growing global population and changing diets, combined with a greater societal awareness of agriculture's role in delivering ecosystem services beyond food, feed, fiber, and energy production, require a comprehensive perspective on where and how US agriculture can be sustainably intensified, that is, made more productive without exacerbating local and off-site environmental concerns. The USDA's Long-Term Agroecosystem Research (LTAR) network is composed of 18 locations distributed across the contiguous United States working together to integrate national and local agricultural priorities and advance the sustainable intensification of US agriculture. We explore here the concept of sustainable intensification as a framework for defining strategies to enhance production, environmental, and rural prosperity outcomes from agricultural systems. We also elucidate the diversity of factors that have shaped the past and present conditions of cropland, rangeland, and pastureland agroecosystems represented by the LTAR network and identify priorities for research in the areas of production, resource conservation and environmental quality, and rural prosperity. Ultimately, integrated long-term research on sustainable intensification at the national scale is critical to developing practices and programs that can anticipate and address challenges before they become crises.

Feeding the fire: Tracing the mass-loading of 107 K galactic outflows with O vi absorption.

Galactic outflows regulate the amount of gas galaxies convert into stars. However, it is difficult to measure the mass outflows remove because they span a large range of temperatures and phases. Here, we study the rest-frame ultraviolet spectrum of a lensed galaxy at z ~ 2.9 with prominent interstellar absorption lines from O i, tracing neutral gas, up to O vi, tracing transitional phase gas. The O vi profile mimics weak low-ionization profiles at low velocities, and strong saturated profiles at high velocities. These trends indicate that O vi gas is co-spatial with the low-ionization gas. Further, at velocities blueward of -200 km s-1 the column density of the low-ionization outflow rapidly drops while the O vi column density rises, suggesting that O vi is created as the low-ionization gas is destroyed. Photoionization models do not reproduce the observed O vi, but adequately match the low-ionization gas, indicating that the phases have different formation mechanisms. Photoionized outflows are more massive than O vi outflows for most of the observed velocities, although the O vi mass outflow rate exceeds the photoionized outflow at velocities above the galaxy's escape velocity. Therefore, most gas capable of escaping the galaxy is in a hot outflow phase. We suggest that the O vi absorption is a temporary by-product of conduction transferring mass from the photoionized phase to an unobserved hot wind, and discuss how this mass-loading impacts the observed circum-galactic medium.

A novel frequency analysis method for assessing K(ir)2.1 and Na (v)1.5 currents.

Voltage clamping is an important tool for measuring individual currents from an electrically active cell. However, it is difficult to isolate individual currents without pharmacological or voltage inhibition. Herein, we present a technique that involves inserting a noise function into a standard voltage step protocol, which allows one to characterize the unique frequency response of an ion channel at different step potentials. Specifically, we compute the fast Fourier transform for a family of current traces at different step potentials for the inward rectifying potassium channel, K(ir)2.1, and the channel encoding the cardiac fast sodium current, Na(v)1.5. Each individual frequency magnitude, as a function of voltage step, is correlated to the peak current produced by each channel. The correlation coefficient vs. frequency relationship reveals that these two channels are associated with some unique frequencies with high absolute correlation. The individual IV relationship can then be recreated using only the unique frequencies with magnitudes of high absolute correlation. Thus, this study demonstrates that ion channels may exhibit unique frequency responses.

Irreversibility and fluctuation theorem in stationary time series.

The relative entropy between the joint probability distribution of backward and forward sequences is used to quantify time asymmetry (or irreversibility) for stationary time series. The parallel with the thermodynamic theory of nonequilibrium steady states allows us to link the degree of asymmetry in the time signal with the distance from equilibrium and the lack of detailed balance among its states. We study the statistics of time asymmetry in terms of the fluctuation theorem, showing that this type of relationship derives from simple general symmetries valid for any stationary time series.

River habitat quality from river velocities measured using acoustic Doppler current profiler.

Prior research has demonstrated the utility of metrics based on spatial velocity gradients to characterize and describe stream habitat, with higher gradients generally indicative of higher levels of physical heterogeneity and thus habitat quality. However, detailed velocity data needed to compute these metrics are difficult to obtain. Acoustic Doppler current profilers (ADCP) may be used to rapidly collect detailed representations of river velocity fields. Herein we demonstrate use of ADCP to obtain ecologically relevant data and compute associated metrics. Data were collected from four reaches of the Little Tallahatchie River in northern Mississippi. Sampled reaches were selected to observe velocity regimes associated with three distinctly different conditions: downstream from a major flow obstruction (a low weir), downstream from the apices of each of two bends, and within an extremely long, straight reach created by channelization. Three-dimensional velocity data sets from each site were used to compute metrics of habitat quality proposed by others. A habitat metric based on the presence of rotational flow in the vertical plane proved to be the best discriminator among conditions within the sampled reaches. Two of four habitat quality metrics computed from these measured velocities were greatest for the sharpest meander bend. ADCP hold great potential for study of riverine physical aquatic habitats, particularly at the reach scale. Additional work is needed to develop generally applicable field protocols and data reduction tools. Specifically, guidelines for ADCP settings and configuration appropriate for a range of riverine site conditions must be developed. Advances in instrumentation are needed to allow collection of information in closer proximity to the free surface and solid boundaries.