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Abstract Low nitrogen use efficiency (NUE) is ubiquitous in agricultural systems, with mounting global scale consequences for both atmospheric aspects of climate and downstream ecosystems. Since NUE-related soil characteristics such as water holding capacity and organic matter are likely to vary at small scales (< 1 ha), understanding the influence of soil characteristics on NUE at the subfield scale (< 32 ha) could increase fertilizer NUE. Here, we quantify NUE in four conventionally managed dryland winter-wheat fields in Montana following multiple years of sub-field scale variation in experimental N fertilizer applications. To inform farmer decisions that incorporates NUE, we developed a generalizable model to predict subfield scale NUE by comparing six candidate models, using ecological and biogeochemical data gathered from open-source data repositories and from normal farm operations, including yield and protein monitoring data. While NUE varied across fields and years, efficiency was highest in areas of fields with low N availability from both fertilizer and estimated mineralization of soil organic N (SON). At low levels of applied N, distinct responses among fields suggest distinct capacities to supply non-fertilizer plant-available N, suggesting that mineralization supplies more available N in locations with higher total N, reducing efficiency for any applied rate. Comparing modelling approaches, a random forest regression model of NUE provided predictions with the least error relative to observed NUE. Subfield scale predictive models of NUE can help to optimize efficiency in agronomic systems, maximizing both economic net return and NUE, which provides a valuable approach for optimization of nitrogen fertilizer use. 

Abstract Relative to their limited areal extent, riparian ecosystems are disproportionately important in regulating inorganic solute export from agricultural landscapes. We investigated spatial patterns of solute concentrations in surface and ground waters of stream corridors to infer the dominant hydrologic transport and biogeochemical pathways that influence riparian nitrate and sulfate processing from uplands to streams. We selected three reaches of stream corridors draining an agricultural landscape that vary in hydrologic connection with upland aquifers. Non‐irrigated crop production dominates land use in the study area and influences the quality of upland groundwater draining to the stream corridors. We interpret patterns in solute concentrations of riparian groundwater and stream water relative to upland groundwater to infer the influences of biogeochemical processing and hydrologic connectivity. Excess nitrate from cultivated soils is evident in upland groundwater concentrations that consistently exceed the U.S. Environmental Protection Agency public drinking water standard. Nitrate and oxygen concentrations in riparian groundwaters were consistently lower than in terrace groundwater and adjacent stream waters, suggesting rapid consumption of oxygen and influence of anaerobic metabolic reduction processes in subsurface flow. Sulfate concentrations in streams were higher than in terrace groundwater, likely due to weathering of shale‐derived substrate in riparian aquifers. The degree of solute mitigation or augmentation by riparian biogeochemical processes depended on the geomorphic context that controlled the fraction of upland water passing through the riparian substrate. Observed net nitrate losses with net sulfate gains from uplands to stream channels reflect flow paths through a complex distribution of redox conditions throughout the riparian areas, emphasizing the importance of considering riparian area heterogeneity in predicting solute export in streams. This research contributes to understanding how stream corridor substrate and geomorphic context controls the biogeochemical and hydrologic processes influencing the quality of water exported from agricultural landscapes. 

Abstract Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well as limited data availability. We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long‐term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C‐cycle processes. Bayesian calibration was conducted using quality‐controlled C flux data sets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern US rangelands to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass‐shrub mixture, and grass‐tree mixture). The resulting RCTM system produced higher model accuracy for estimating annual cumulative gross primary productivity (GPP) (R² > 0.6, RMSE <390 g C m⁻²) relative to net ecosystem exchange of CO₂(NEE) (R² > 0.4, RMSE <180 g C m⁻²). Model performance in estimating rangeland C fluxes varied by season and vegetation type. The RCTM captured the spatial variability of SOC stocks withR² = 0.6 when validated against SOC measurements across 13 NEON sites. Model simulations indicated slightly enhanced SOC stocks for the flux tower sites during the past decade, which is mainly driven by an increase in precipitation. Future efforts to refine the RCTM system will benefit from long‐term network‐based monitoring of vegetation biomass, C fluxes, and SOC stocks. 

Abstract In snowmelt‐driven mountain watersheds, the hydrologic connectivity between meteoric waters and stream flow generation varies strongly with the season, reflecting variable connection to soil and groundwater storage within the watershed. This variable connectivity regulates how streamflow generation mechanisms transform the seasonal and elevational variation in oxygen and hydrogen isotopic composition (δ¹⁸O and δD) of meteoric precipitation. Thus, water isotopes in stream flow can signal immediate connectivity or more prolonged mixing, especially in high‐relief mountainous catchments. We characterized δ¹⁸O and δD values in stream water along an elevational gradient in a mountain headwater catchment in southwestern Montana. Stream water isotopic compositions related most strongly to elevation between February and March, exhibiting higher δ¹⁸O and δD values with decreasing elevation. These elevational isotopic lapse rates likely reflect increased connection between stream flow and proximal snow‐derived water sources heavily subject to elevational isotopic effects. These patterns disappeared during summer sampling, when consistently lower δ¹⁸O and δD values of stream water reflected contributions from snowmelt or colder rainfall, despite much higher δ¹⁸O and δD values expected in warmer seasonal rainfall. The consistently low isotopic values and absence of a trend with elevation during summer suggest lower connectivity between summer precipitation and stream flow generation as a consequence of drier soils and greater transpiration. As further evidence of intermittent seasonal connectivity between the stream and adjacent groundwaters, we observed a late‐winter flush of nitrate into the stream at higher elevations, consistent with increased connection to accumulating mineralized nitrogen in riparian wetlands. This pattern was distinct from mid‐summer patterns of nitrate loading at lower elevations that suggested heightened human recreational activity along the stream corridor. These observations provide insights linking stream flow generation and seasonal water storage in high elevation mountainous watersheds. Greater understanding of the connections between surface water, soil water and groundwater in these environments will help predict how the quality and quantity of mountain runoff will respond to changing climate and allow better informed water management decisions.