This paper contrasts the natural and anthropogenic controls on the conversion of unreactive N 2 to more reactive forms of nitrogen (Nr). A variety of data sets are used to construct global N budgets for 1860 and the early 1990s and to make projections for the global N budget in 2050. Regional N budgets for Asia, North America, and other major regions for the early 1990s, as well as the marine N budget, are presented to highlight the dominant fluxes of nitrogen in each region. Important findings are that human activities increasingly dominate the N budget at the global and at most regional scales, the terrestrial and open ocean N budgets are essentially disconnected, and the fixed forms of N are accumulating in most environmental reservoirs. The largest uncertainties in our understanding of the N budget at most scales are the rates of natural biological nitrogen fixation, the amount of Nr storage in most environmental reservoirs, and the production rates of N 2 by denitrification.

We studied the fluorescence properties of fulvic acids isolated from streams and rivers receiving predominantly terrestrial sources of organic material and from lakes with microbial sources of organic material. Microbially derived fulvic acids have fluorophores with a more sharply defined emission peak occurring at lower wavelengths than fluorophores in terrestrially derived fulvic acids. We show that the ratio of the emission intensity at a wavelength of 450 nm to that at 500 nm, obtained with an excitation of 370 nm, can serve as a simple index to distinguish sources of isolated aquatic fulvic acids. In our study, this index has a value of ϳ1.9 for microbially derived fulvic acids and a value of ϳ1.4 for terrestrially derived fulvic acids. Fulvic acids isolated from four large rivers in the United States have fluorescence index values of 1.4-1.5, consistent with predominantly terrestrial sources. For fulvic acid samples isolated from a river, lakes, and groundwaters in a forested watershed, the fluorescence index varied in a manner suggesting different sources for the seepage and streamfed lakes. Furthermore, we identified these distinctive fluorophores in filtered whole water samples from lakes in a desert oasis in Antarctica and in filtered whole water samples collected during snowmelt from a Rocky Mountain stream. The fluorescence index measurement in filtered whole water samples in field studies may augment the interpretation of dissolved organic carbon sources for understanding carbon cycling in aquatic ecosystems.Aquatic fulvic acid is a major fraction of dissolved organic matter (DOM) in natural waters. Aquatic fulvic acids are heterogeneous, moderate molecular weight, yellow-colored organic acids. Examples of processes controlled by fulvic acid are (1) chemical speciation and transport of trace metals through complexation reactions (e.g., Breault et al. 1996); (2) formation of trihalomethanes in drinking water by interactions between chlorine and fulvic acid during water AcknowledgmentsWe thank K. Cunningham for help with spectroscopic methods and G. Aiken, J. Debroux, P. Coble, and four anonymous reviewers for valuable comments on the manuscript.

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Seasonal hypoxia in the northern Gulf of Mexico has been linked to increased nitrogen fluxes from the Mississippi and Atchafalaya River Basins, though recent evidence shows that phosphorus also influences productivity in the Gulf. We developed a spatially explicit and structurally detailed SPARROW water-quality model that reveals important differences in the sources and transport processes that control nitrogen (N) and phosphorus (P) delivery to the Gulf. Our model simulations indicate that agricultural sources in the watersheds contribute more than 70% of the delivered N and P. However, corn and soybean cultivation is the largest contributor of N (52%), followed by atmospheric deposition sources (16%); whereas P originates primarily from animal manure on pasture and rangelands (37%), followed by corn and soybeans (25%), other crops (18%), and urban sources (12%). The fraction of in-stream P and N load delivered to the Gulf increases with stream size, but reservoir trapping of P causes large local-and regional-scale differences in delivery. Our results indicate the diversity of management approaches required to achieve efficient control of nutrient loads to the Gulf. These include recognition of important differences in the agricultural sources of N and P, the role of atmospheric N, attention to P sources downstream from reservoirs, and better control of both N and P in close proximity to large rivers.

T-cell genome engineering holds great promise for cell-based therapies for cancer, HIV, primary immune deficiencies, and autoimmune diseases, but genetic manipulation of human T cells has been challenging. Improved tools are needed to efficiently “knock out” genes and “knock in” targeted genome modifications to modulate T-cell function and correct disease-associated mutations. CRISPR/Cas9 technology is facilitating genome engineering in many cell types, but in human T cells its efficiency has been limited and it has not yet proven useful for targeted nucleotide replacements. Here we report efficient genome engineering in human CD4+ T cells using Cas9:single-guide RNA ribonucleoproteins (Cas9 RNPs). Cas9 RNPs allowed ablation of CXCR4, a coreceptor for HIV entry. Cas9 RNP electroporation caused up to ∼40% of cells to lose high-level cell-surface expression of CXCR4, and edited cells could be enriched by sorting based on low CXCR4 expression. Importantly, Cas9 RNPs paired with homology-directed repair template oligonucleotides generated a high frequency of targeted genome modifications in primary T cells. Targeted nucleotide replacement was achieved in CXCR4 and PD-1 (PDCD1), a regulator of T-cell exhaustion that is a validated target for tumor immunotherapy. Deep sequencing of a target site confirmed that Cas9 RNPs generated knock-in genome modifications with up to ∼20% efficiency, which accounted for up to approximately one-third of total editing events. These results establish Cas9 RNP technology for diverse experimental and therapeutic genome engineering applications in primary human T cells.

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters.

The spatial distribution of source areas and associated residence times of water in the catchment are signi®cant factors controlling the annual cycles of dissolved organic carbon (DOC) concentration in Deer Creek (Summit County, Colorado). During spring snowmelt (April±August 1992), stream DOC concentrations increased with the rising limb of the hydrograph, peaked before maximum discharge, then declined rapidly as melting continued. We investigated catchment sources of DOC to stream¯ow, measuring DOC in tension lysimeters, groundwater wells, snow and streamow. Lysimeter data indicate that near-surface soil horizons are a primary contributor of DOC to stream¯ow during spring snowmelt. Concentrations of DOC in the lysimeters decrease rapidly during the melt period, supporting the hypothesis that hydrological¯ushing of catchment soils is the primary mechanism aecting the temporal variation of DOC in Deer Creek. Time constants of DOC¯ushing, characterizing the exponential decay of DOC concentration in the upper soil horizon, ranged from 10 to 30 days for the 10 lysimeter sites. Dierences in the rate of¯ushing are in¯uenced by topographical position, with near-stream riparian soils¯ushed more quickly than soils located further upslope. Variation in the amount of distribution of accumulated snow, and asynchronous melting of the snowpack across the landscape, staggered the onset of the spring¯ush throughout the catchment, prolonging the period of increased concentrations of DOC in the stream. Stream¯ow integrates the catchment-scale¯ushing responses, yielding a time constant associated with the recession of DOC in the stream channel (84 days) that is signi®cantly longer than the time constants observed for particular locations in the upper soil.

Quantifying where, when, and how much denitrification occurs on the basis of measurements alone remains particularly vexing at virtually all spatial scales. As a result, models have become essential tools for integrating current understanding of the processes that control denitrification with measurements of rate-controlling properties so that the permanent losses of N within landscapes can be quantified at watershed and regional scales. In this paper, we describe commonly used approaches for modeling denitrification and N cycling processes in terrestrial and aquatic ecosystems based on selected examples from the literature. We highlight future needs for developing complementary measurements and models of denitrification. Most of the approaches described here do not explicitly simulate microbial dynamics, but make predictions by representing the environmental conditions where denitrification is expected to occur, based on conceptualizations of the N cycle and empirical data from field and laboratory investigations of the dominant process controls. Models of denitrification in terrestrial ecosystems include generally similar rate-controlling variables, but vary in their complexity of the descriptions of natural and human-related properties of the landscape, reflecting a range of scientific and management perspectives. Models of denitrification in aquatic ecosystems range in complexity from highly detailed mechanistic simulations of the N cycle to simpler source-transport models of aggregate N removal processes estimated with empirical functions, though all estimate aquatic N removal using first-order reaction rate or mass-transfer rate expressions. Both the terrestrial and aquatic modeling approaches considered here generally indicate that denitrification is an important and highly substantial component of the N cycle over large spatial scales. However, the uncertainties of model predictions are large. Future progress will be linked to advances in field measurements, spatial databases, and model structures.