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The US Corn Belt is a global hotspot of atmospheric ammonia (NH3), a gas known to adversely impact the environment and human health. We combine hourly tall tower (100 m) measurements and bi‐weekly, spatially distributed, ground‐based observations from the Ammonia Monitoring Network with the US National Emissions Inventory (NEI) and WRF‐Chem simulations to constrain NH3 emissions from April to September 2017–2019. We show that: (1) NH3 emissions peaked from May to July and were 1.6–1.7 times the annual NEI average; (2) average growing season NH3 emissions from agricultural lands were remarkably similar across years (3.27–3.64 nmol m−2 s−1), yet showed substantial episodic variability driven by meteorology and land management; (3) dry deposition was 40% of gross emissions from agricultural lands and exceeded 100% of gross emissions in natural lands. Our findings provide an important benchmark for evaluating future NH3 emissions and mitigation efforts. Key Points: Rare multiyear tall tower and ground‐based ammonia measurements were combined with WRF‐Chem to constrain emissions from the US Corn BeltMonthly ammonia emissions peaked in May through July and were 1.6–1.7 times the annual NEI averageEpisodic low WRF‐Chem bias versus tall tower observations underscore the importance of weather and land management as emission drivers [ABSTRACT FROM AUTHOR]

Net CO2 exchange data of legume crops at 17 flux tower sites in North America and three sites in Europe representing 29 site-years of measurements were partitioned into gross photosynthesis and ecosystem respiration by using the nonrectangular hyperbolic light-response function method. The analyses produced net CO2 exchange data and new ecosystem-scale ecophysiological parameter estimates for legume crops determined at diurnal and weekly time steps. Dynamics and annual totals ofgross photosynthesis, ecosystem respiration, and net ecosystem production were calculated by gap filling with multivariate nonlinear regression. Comparison with the data from grain crops obtained with the same method demonstrated that CO2 exchange rates and ecophysiological parameters of legumes were lowerthan those of maize (ZeamaysL.) but higherthanforwheat (TriticumaestipumL.) crops. Year-round annuallegume crops demonstrated a broad range of net ecosystem production, from sinks of 760 g CO2 m-2 yr-1 to sources of -2100 g CO2 m-2 yr-1, with an average of -330 g CO2 m-2 yr-1, indicating overall moderate CO2-source activity related to a shorter period of photosynthetic uptake and metabolic costs of N2 fixation. Perennial legumes (alfalfa, Medicago sativa L.) were strong sinks for atmospheric CO2, with an average net ecosystem production of 980 (range 550-1200) g CO2 m-2 yr-1. [ABSTRACT FROM AUTHOR]

Abstract: Climate change and economic concerns have motivated intense interest in the development of renewable energy sources, including fuels derived from plant biomass. However, the specter of massive biofuel production has raised other worries, specifically that by displacing food production it will lead to higher food prices, increased incidence of famine, and acceleration of undesirable land use change. One proposed solution is to increase the annual net primary productivity of the existing agricultural land base, so that it can sustainably produce both food and biofuel feedstocks. This might be possible in corn and soybean production regions through the use of winter cover crops, but the biophysical feasibility of this has not been systematically explored. We developed a model for this purpose that simulates the potential biomass production and water use of winter rye in continuous corn and corn–soybean rotations. The input data requirements represent an attempt to balance the demands of a physically and physiologically defensible simulation with the need for broad applicability in space and time. The necessary meteorological data are obtainable from standard agricultural weather stations, and the required management data are simply planting dates and harvest dates for corn and soybeans. Physiological parameters for rye were taken from the literature, supplemented by experimental data specifically collected for this project. The model was run for a number of growing seasons for 8 locations across the Midwestern USA. Results indicate potential rye biomass production of 1–8Mgha−1, with the lowest yields at the more northern sites, where both PAR and degree-days are limited in the interval between fall corn harvest and spring corn or soybean planting. At all sites rye yields are substantially greater when the following crop is soybean rather than corn, since soybean is planted later. Not surprisingly, soil moisture depletion is most likely in years and sites where rye biomass production is greatest. Consistent production of both food and biomass from corn/winter rye/soybean systems will probably require irrigation in many areas and additional N fertilizer, creating possible environmental concerns. Rye growth limitations in the northern portion of the corn belt may be partially mitigated with aerial seeding of rye into standing corn. [Copyright &y& Elsevier]

• We calculated field-scale net ecosystem C balances for forage and grain rotations. • C loss was threefold greater from continuous silage maize than soybean-grain maize. • Alfalfa reduced C loss by 23% relative to continuous silage maize. • Winter rye cover copping and liquid dairy manure improved C-balances marginally. • Every Mg of crop residue C left in-field improved C balances by +0.9 Mg C ha−1. Intensification of the US dairy industry has driven increased reliance on maize (Zea mays L.) silage as a primary forage source in place of perennial forages such as alfalfa (Medicago sativa L.). Using 29 site-years of eddy covariance, plant, and manure measurements, we calculated net ecosystem C balances (NECB) for two silage maize-based forage cropping systems and a soybean-maize grain rotation. We found that C losses were over threefold greater from continuous silage maize (-4.9 Mg C ha−1 yr−1) than from the predominant grain cropping system in the region, the soybean-maize rotation (-1.3 Mg C ha−1 yr−1). Including alfalfa in rotation reduced C losses by 23% relative to continuous silage maize, but net losses were still observed (-3.8 Mg C ha−1 yr−1). For every megagram of crop residue C left in-field, net C balances increased by +0.9 Mg C ha−1. A winter rye (Secale cereale L.) cover crop and applications of liquid dairy manure marginally improved C-balances but were insufficient to offset C losses in respiration and crop harvest. Increasing manure application rates could bring these systems to a net equilibrium C balance but would also result in soil N and P surpluses and unacceptable loss of nutrients to air and water. Since 1980, over 800,000 hectares of alfalfa have been lost across the Upper Midwest US, and C export in harvested maize grain and silage have increased dramatically. This shift implies a substantial reduction in SOC on forage cropped soils in the region. [ABSTRACT FROM AUTHOR]

• We attributed the canopy conductance variability to VPD and soil moisture. • We obtained the canopy conductance using Ameriflux sites data in the U.S. Corn Belt. • High VPD dominantly controlled the canopy conductance variability. • Precipitation affects plant water stress more through the atmosphere than soil. The U.S. Corn Belt, the world's biggest production region for corn and soybean combined, is prone to droughts. Currently 92% of the U.S. Corn Belt croplands are rainfed, and thus are sensitive to interannual climate variability and future climate change. Most prior studies identify the lack of soil moisture as the primary cause of agricultural drought impacts, although water-related stresses are also induced by high atmospheric water demands (i.e., vapor pressure deficit, VPD). Here we empirically attributed the variability of canopy-level stomatal conductance (Gs) and gross primary productivity (GPP) to VPD and soil water supply (i.e. volumetric soil water content, SWC), using eddy-covariance data from seven AmeriFlux eddy covariance sites in maize and soybean fields across the U.S. Corn Belt, which are well represented for the current rainfed part of the Corn Belt croplands. We used three independent approaches, including two statistical models (i.e. a multiple-linear regression model and a semi-empirical, non-linear model) and information theory, to quantify the relationship of Gs (or GPP) with VPD and SWC. The attribution result from the two models shows that VPD explains most of Gs variability (91% and 89%, respectively), and mutual information also attributed 91% of GPP variability to VPD. This finding was robust over the gradients of rainfall and temperature, crop types (maize vs. soybean), and management practices (whether irrigated or not). We reconciled our finding with the previously emphasized importance of precipitation and SWC, by conducting a path analysis, which revealed the causal relationships between precipitation, air temperature (Ta), relative humidity (RH), VPD, SWC, and Gs. We find that precipitation impacts on Gs through reduced RH and Ta to VPD (rather than directly through SWC). With increased VPD robustly projected under climate change, we expect increased crop water stress in the future for the U.S. Corn Belt. Image, graphical abstract [ABSTRACT FROM AUTHOR]