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Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat satellite, Landsat NDVI, and vegetation greenness (Green Chromatic Coordinate, GCC) from tower-mounted PhenoCams for 2017 and 2018. Overall, our analysis compared production dynamics estimated from three independent ground and remote platforms using data for 34 agricultural sites constituting 51 site-years of co-located time series.Pairwise sensor comparisons across all four metrics revealed stronger correlation and lower root mean square error (RMSE) between end of season (EOS) dates (Pearson R ranged from 0.6 to 0.7 and RMSE from 32.5 to 67.8) than start of season (SOS) dates (0.46 to 0.69 and 40.4 to 66.2). Overall, moderate to high correlations between SOS and EOS metrics complemented one another except at some lower productivity grazing land sites where estimating SOS can be challenging. Growing season length estimates derived from 16-day satellite GPP (179.1 days) were significantly longer than those from PhenoCam GCC (70.4 days, padj

Eddy covariance (EC) measurements of ecosystem-atmosphere carbon dioxide (CO2) exchange provide the most direct assessment of the terrestrial carbon cycle. Measurement biases for open-path (OP) CO2 concentration and flux measurements have been reported for over 30 years, but their origin and appropriate correction approach remain unresolved. Here, we quantify the impacts of OP biases on carbon and radiative forcing budgets for a sub-boreal wetland. Comparison with a reference closed-path (CP) system indicates that a systematic OP flux bias (0.54 μ mol m − 2 s − 1 ) persists for all seasons leading to a 110% overestimate of the ecosystem CO2 sink (cumulative error of 78 gC m−2). Two potential OP bias sources are considered: Sensor-path heat exchange (SPHE) and analyzer temperature sensitivity. We examined potential OP correction approaches including: i) Fast temperature measurements within the measurement path and sensor surfaces; ii) Previously published parameterizations; and iii) Optimization algorithms. The measurements revealed year-round average temperature and heat flux gradients of 2.9 °C and 16 W m−2 between the bottom sensor surfaces and atmosphere, indicating SPHE-induced OP bias. However, measured SPHE correlated poorly with the observed differences between OP and CP CO2 fluxes. While previously proposed nominally universal corrections for SPHE reduced the cumulative OP bias, they led to either systematic under-correction (by 38.1 gC m−2) or to systematic over-correction (by 17-37 gC m−2). The resulting budget errors exceeded CP random uncertainty and change the sign of the overall carbon and radiative forcing budgets. Analysis of OP calibration residuals as a function of temperature revealed a sensitivity of 5 μ mol m − 3 K − 1 . This temperature sensitivity causes CO2 calibration errors proportional to sample air fluctuations that can offset the observed growing season flux bias by 50%. Consequently, we call for a new OP correction framework that characterizes SPHE- and temperature-induced CO2 measurement errors.

The response of highly productive croplands at northern mid-latitudes to climate change is a primary source of uncertainty in the global carbon cycle, and a concern for future food production. We present a decadal time series (2007 to 2019) of hourly CO2 concentration measured at a very tall tower in the United States Corn Belt. Analyses of this record, with other long-term data in the region, reveal that warming has had a positive impact on net CO2 uptake during the early crop growth stage, but has reduced net CO2 uptake in both croplands and natural ecosystems during the peak growing season. Future increase in summer temperature is projected to reduce annual CO2 sequestration in the Corn Belt by 10–20%. These findings highlight the dynamic control of warming on cropland CO2 exchange and crop yields and challenge the paradigm that warming will continue to favor CO2 sequestration in northern mid-latitude ecosystems. Warming can reduce annual CO2 sequestration in cropland by inducing a negative impact on net CO2 uptake during the peak growing season, suggest twelve years of hourly CO2 measurements from a tall tower in the United States Corn Belt.

The methane (CH(4)) budget and its source partitioning are poorly constrained in the Midwestern United States. We used tall tower (185 m) aerodynamic flux measurements and atmospheric scale factor Bayesian inversions to constrain the monthly budget and to partition the total budget into natural (e.g., wetlands) and anthropogenic (e.g., livestock, waste, and natural gas) sources for the period June 2016 to September 2017. Aerodynamic flux observations indicated that the landscape was a CH(4) source with a mean annual CH(4) flux of +13.7 ± 0.34 nmol m(−2) s(−1) and was rarely a net sink. The scale factor Bayesian inversion analyses revealed a mean annual source of +12.3 ± 2.1 nmol m(−2) s(−1). Flux partitioning revealed that the anthropogenic source (7.8 ± 1.6 Tg CH(4) yr(−1)) was 1.5 times greater than the bottom-up gridded United States Environmental Protection Agency inventory, in which livestock and oil/gas sources were underestimated by 1.8-fold and 1.3-fold, respectively. Wetland emissions (4.0 ± 1.2 Tg CH(4) yr(−1)) were the second largest source, accounting for 34% of the total budget. The temporal variability of total CH(4) emissions was dominated by wetlands with peak emissions occurring in August. In contrast, emissions from oil/gas and other anthropogenic sources showed relatively weak seasonality.

The ECOsystem Space Thermal Radiometer Experiment on the Space Station (ECOSTRESS) was launched to the International Space Station on June 29, 2018 by the National Aeronautics and Space Administration (NASA). The primary scientific focus of ECOSTRESS is on evapotranspiration (ET), which occurs as Level 3 (L3) latent heat flux (LE) data products. This data is generated from the Level 2 Earth Surface Temperature and Emissivity Product (L2_LSTE), along with the atmospheric and ancillary surface data. Here, we provide the first validation (Stage 1, preliminary) of the global product ECOSTRESS clear - sky ET (L3_ET_PT - JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against site measurements (instant clear sky / flyover time: r 2 = 0.88; overall bias = 8%; normalized root mean square error, RMSE = 6%) . ET uncertainty was generally constant across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), although temperate sites are over-represented. ECOSTRESS 70 m high spatial resolution improved correlations by 85% and RMSE by 62%, relative to 1 km pixels. This document serves as a reference for the accuracy of ECOSTRESS L3 ET and the Stage 1 validation status for subsequent science that continues to use this data. Fil: Fisher, Joshua B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Lee, Brian. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Purdy, Adam J. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Halverson, Gregory H. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Dohlen, Matthew B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Cawse - Nicholson, Kerry. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Wang, Audrey. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Anderson, Ray G. U.S. Department of Agriculture; Estados Unidos Fil: Aragon, Bruno. King Abdullah University of Science and Technology. Division of Biological and Environmental Science and Engineering. Hydrology, Agriculture and Land Observation Group (HALO); Arabia Saudita Fil: Arain, M. Alfat. McMaster University. School of Geography and Earth Sciences; Canadá Fil: Baldocchi, Dennis D. University of California, Berkeley. Department of Environmental Science, Policy and Management; Estados Unidos Fil: Baker, John M. U.S. Department of Agriculture; Estados Unidos Fil: Barral, Helene. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Bernacchi, Carl J. University of Illinois Urbana‐Champaign. Institute for Sustainability, Energy, and Environment and Carl R. Woese Institute for Genomic Biology. Center for Advanced Bioenergy and Bioproducts Innovation; Estados Unidos. U.S. Department of Agriculture, Global Change and Photosynthesis Research Unit; Estados Unidos Fil: Bernhofer, Christian. Technische Universität Dresden, Institute of Hydrology and Meteorology; Alemania Fil: Biraud, Sebastien C. Lawrence Berkeley National Laboratory; Estados Unidos Fil: Bohrer, Gil. Ohio State University. Department of Civil, Environmental and Geodetic Engineering; Estados Unidos Fil: Brunsell, Nathaniel. University of Kansas. Department of Geography and Atmospheric Science; Estados Unidos Fil: Cappelaere, Bernard. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Castro - Contreras, Saulo. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Chum, Junghwa. National Institute of Forest Science; Corea del Sur Fil: Conrad, Bryan. University of Kansas. Department of Geography and Atmospheric Science; Estados Unidos Fil: Cremonese, Edoardo. Environmental Protection Agency of Aosta Valley; Italia Fil: Demarty, Jerome. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Desai, Ankur R. University of Wisconsin‐Madison. Department of Atmospheric and Oceanic Sciences; Estados Unidos Fil: De Ligne, Anne. University of Liege. TERRA Teaching and Research Centre. Gembloux Agro‐Bio Tech; Bélgica Fil: Foltynova, Lenka. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Goulden, Michael L. University of California Irvine. Department of Earth System Science; Estados Unidos Fil: Griffis, Timothy J. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos Fil: Grunwald, Thomas. Technische Universität Dresden, Institute of Hydrology and Meteorology; Alemania Fil: Johnson, Mark S. University of British Columbia. Department of Earth, Ocean, and Atmospheric Sciences; Canadá Fil: Kang, Minseok. National Center for AgroMeteorology; Corea del Sur Fil: Kelbe, Dave. Xerra Earth Observation Institute; Nueva Zelanda Fil: Kowalska, Natalia. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Jong - Hwan, Lim. National Institute of Forest Science; Corea del Sur Fil: Mainassara, Ibrahim. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: McCabe, Matthew F. King Abdullah University of Science and Technology. Division of Biological and Environmental Science and Engineering. Hydrology, Agriculture and Land Observation Group (HALO); Arabia Saudita Fil: Missik, Justine E.C. Washington State University. Department of Civil and Environmental Engineering. Laboratory for Atmospheric Research; Estados Unidos Fil: Mohanty, Binayak P. Texas A&M University. Texas Water Observatory; Estados Unidos Fil: Moore, Caitlin E. University of Illinois Urbana‐Champaign. Institute for Sustainability, Energy, and Environment and Carl R. Woese Institute for Genomic Biology. Center for Advanced Bioenergy and Bioproducts Innovation; Estados Unidos Fil: Morillas, Laura. University of British Columbia. Department of Earth, Ocean, and Atmospheric Sciences; Canadá Fil: Morrison, Ross. Centre for Ecology and Hydrology; Reino Unido Fil: Munger, J. Willians. Harvard University. School of Engineering and Applied Sciences; Estados Unidos Fil: Posse, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Richardson, Andrew D. Northern Arizona University Center for Ecosystem Science and Society; Estados Unidos Fil: Russell, Eric. S. Washington State University. Department of Civil and Environmental Engineering. Laboratory for Atmospheric Research; Estados Unidos Fil: Ryu, Youngryel. Seoul National University . Department of Landscape Architecture and Rural Systems Engineering; Corea del Sur Fil: Sanchez - Azofeifa, Arturo. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Schmidt, Marius. IInstitute of Bio‐ and Geosciences: Agrosphere (IBG‐3) Forschungszentrum Jülich IBG‐3; Alemania Fil: Schwartz, Efrat. Weizmann Institute of Science. Department of Earth and Planetary Sciences, ; Israel Fil: Sharp, Iain. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Sigut, Ladislav. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Tang, Yao. Georgia Institute of Technology. School of Civil and Environmental Engineering; Estados Unidos Fil: Hulley, Glynn. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Anderson, Martha. U.S. Department of Agriculture‐Agricultural Research Service; Estados Unidos Fil: Hain, Christopher. NASA Marshall Space Flight Center; Estados Unidos Fil: French, Andrew. U.S. Department of Agriculture; Estados Unidos Fil: Wood, Eric. Princeton University. Department of Civil and Environmental Engineering; Estados Unidos Fil: Hook, Simón. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos

Zone tillage is a reduced-tillage approach that attempts to capture both the environmental advantages of year-round ground cover and the agronomic benefits of in-row tillage. This study was conducted to determine the effect of differing levels of zone tillage intensity on soil carbon and nitrogen cycling in a corn-kura clover cropping system (Zea maize-Trifolium ambiguum). Research took place in Rosemount, MN in 2015 and 2016 in an established kura clover stand. Soils and kura clover biomass were each sampled three times in crop rows per year in four treatments that varied by intensity: NT (spray-down no-till), ST (shank-till, traditional strip till unit), RZT (zone-till, PTO-driven rotary zone tiller), and DT (double-till, ST + RZT). Samples were analyzed for microbial biomass (MB), soil inorganic nitrogen, and permanganate oxidizable carbon (POXC). Additionally, potentially mineralizable nitrogen (PMN) was measured for 2016 post-spring tillage soils. Greater spring kura clover biomass in 2016 (2449 kg ha−1) relative to 2015 (187 kg ha−1) influenced overall differences in soil quality between years. The double-till (DT) treatment had greater post-till soil inorganic N than the no-till (NT) treatment in 2016, and by corn harvest, both zone-till (RZT) and double-till (DT) had higher soil inorganic N than NT, indicating that the addition of kura clover biomass contributed to in-row, plant-available nitrogen. Double-till was also more effective in reducing kura clover encroachment into crop rows than NT. No effect of tillage intensity on PMN, MB, or POXC was observed at any sampling time, although trends of decreasing POXC paired with increasing MB over the 2016 growing season suggest that the quantity of incorporated kura clover biomass may have governed belowground nutrient cycling and soil fertility.

Aerodynamic canopy height (h(a)) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate h(a) from data are limited. This synthesis evaluates the applicability and robustness of the calculation of h(a) from eddy covariance momentum-flux data. At 69 forest sites, annual h(a) robustly predicted site-to-site and year-to-year differences in canopy heights (R-2=0.88, 111site-years). At 23 cropland/grassland sites, weekly h(a) successfully captured the dynamics of vegetation canopies over growing seasons (R-2>0.70 in 74site-years). Our results demonstrate the potential of flux-derived h(a) determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying h(a) derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. Plain Language Summary Vegetation canopy height is a key descriptor of the Earth surface and is in use by many modeling and conservation applications. However, large-scale and time-varying data of canopy heights are often unavailable. This synthesis evaluates the applicability and robustness of the calculation of canopy heights from the momentum flux data measured at eddy covariance flux tower sites (i.e., meteorological observation towers with high frequency measurements of wind speed and surface fluxes). We show that the aerodynamic estimation of annual canopy heights robustly predicts the site-to-site and year-to-year differences in canopy heights across a wide variety of forests. The weekly aerodynamic canopy heights successfully capture the dynamics of vegetation canopies over growing seasons at cropland and grassland sites. Our results demonstrate the potential of aerodynamic canopy heights for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. Given the amount of data collected and the diversity of vegetation covered by the global networks of eddy covariance flux tower sites, the flux-derived canopy height has great potential for providing a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. U.S. Department of Energy's Office of ScienceUnited States Department of Energy (DOE) [DE-SC0012456, DE-AC02-05CH11231] This study is supported by FLUXNET and AmeriFlux projects, sponsored by U.S. Department of Energy's Office of Science (DE-SC0012456 and DE-AC02-05CH11231). We thank the supports from AmeriFlux Data Team: Gilberto Pastorello, Deb Agarwal, Danielle Christianson, You-Wei Cheah, Norman Beekwilder, Tom Boden, Bai Yang, and Dario Papale, and Berkeley Biomet Lab: Siyan Ma, Joseph Verfaillie, Elke Eichelmann, and Sara Knox. This work uses eddy covariance and BADM data acquired and shared by the investigators involved in the AmeriFlux and Fluxnet-Canada Research Network. The site list and corresponding references are provided in the supporting information. We thank Claudia Wagner-Riddle, Andy Suyker, David Cook, Asko Noormets, Paul Stoy, and Brian Amiro for providing additional data. All actual canopy height data can be downloaded from AmeriFlux BADM. The R codes and aerodynamic canopy height data can be accessed at http://github.com/chuhousen/aerodynamic_canopy_height. Public domain – authored by a U.S. government employee

Nutrient management on US dairy farms must balance an array of priorities, some of which conflict. To illustrate nutrient management challenges and opportunities across the US dairy industry, the USDA Agricultural Research Service Dairy Agroecosystems Working Group (DAWG) modeled 8 confinement and 2 grazing operations in the 7 largest US dairy-producing states using the Integrated Farm System Model (IFSM). Opportunities existed across all of the dairies studied to increase on-farm feed production and lower purchased feed bills, most notably on large dairies (>1,000 cows) with the highest herd densities. Purchased feed accounted for 18 to 44% of large dairies' total operating costs compared with 7 to 14% on small dairies (

In-field estimation of alfalfa (Medicago sativa L.) yield and nutritive value can inform management decisions to optimize forage quality and production. However, acquisition of timely information at the field scale is limited using traditional measurements such as destructive sampling and assessment of plant maturity. Remote sensing technologies (e.g., measurement of canopy reflectance) have the potential to enable rapid measurements at the field scale. Canopy reflectance (350–2500 nm) and Light Detection and Ranging (LiDAR)-estimated canopy height were measured in conjunction with destructive sampling of alfalfa across a range of maturities at Rosemount, MN in 2014 and 2015. Sets of specific spectral wavebands were determined via stepwise regression to predict alfalfa yield and nutritive value and models were reduced by spectral range to improve utility. Cumulative growing degree units (GDUs) and canopy height were tested as model covariates. An alternative GDU calculation (GDUALT) using a temporally graduating base temperature was also tested against the traditional static base temperature. The inclusion of GDUALT increased prediction accuracy for all response variables by 9–17%. Models using a common set of seven wavebands, combined with GDUALT, explained 81–90% of the variability in yield, crude protein (CP), neutral detergent fiber (NDF), and NDF digestibility (NDFd; 48-h in-vitro), respectively. This research establishes potential for remote sensing measurements to be integrated with air temperature information to achieve rapid and accurate predictions of alfalfa yield and nutritive value at the field scale for optimized harvest management.

Improvement of process-based crop models is needed to achieve high fidelity forecasts of regional energy, water, and carbon exchanges. However, most state-of-the-art Land Surface Models (LSMs) assessed in the fifth phase of the Coupled Model Inter-comparison project (CMIP5) simulated crops as unmanaged C3 or C4 grasses. This study evaluated the crop-enabled version of one of the most widely used LSMs, the Community Land Model (CLM4-Crop), for simulating corn and soybean agro-ecosystems at relatively long-time scales (up to 11 years) using 54 site-years of data. We found that CLM4-Crop had a biased phenology during the early growing season and that carbon emissions from corn and soybean were underestimated. The model adopts universal physiological parameters for all crop types neglecting the fact that different crops have different specific leaf area, leaf nitrogen content and vcmax25, etc. As a result, model performance varied considerably according to crop type. Overall, the energy and carbon exchange of corn systems were better simulated than soybean systems. Long-term simulations at multiple sites showed that gross primary production (GPP) was consistently over-estimated at soybean sites leading to very large short and long-term biases. A modified model, CLM4-CropM’, with optimized phenology and calibrated crop physiological parameters yielded significantly better simulations of gross primary production (GPP), ecosystem respiration (ER) and leaf area index (LAI) at both short (hourly) and long-term (annual to decadal) timescales for both soybean and corn.

Indirect nitrous oxide (N(2)O) emissions from drainage ditches and headwater streams are poorly constrained. Few studies have monitored stream N(2)O emissions and fewer modeling studies have been conducted to simulate stream N(2)O emissions. In this study, we developed direct and indirect N(2)O emission modules and a corresponding calibration module for use in the Soil and Water Assessment Tool (SWAT) model, and implemented the expanded SWAT model (termed SWAT‐N(2)O) to a representative fourth‐stream‐order catchment (210 km2) and six first‐order stream catchments (0.22–1.83 km2) in southeastern Minnesota. We simulated the spatial and temporal fluctuations of the indirect emissions from streams, identified emission “hot spots” and “hot moments,” and diagnosed the correlations between direct and indirect emissions. We showed that zero‐order streams and first‐order streams could contribute 0.034–0.066 and 0.011 nmol N(2)O m(−2) s(−1) (expressed on the basis of unit catchment area) to the total surface emissions, respectively. Emissions from zero‐order and first‐order streams equal 24–41% of direct emissions from soil, which may explain the emission gap between calculations using top‐down and bottom‐up methods. Clear spatial patterns were identified for both direct and indirect emissions and their spatial variations were negatively correlated. Our results suggest that the IPCC N(2)O emission factor for streams in the Corn Belt should be increased by 3.2–5.7 times. Increasing precipitation and streamflow in the Corn Belt may potentially increase frequencies of soil anoxic conditions and nitrate leaching to streams, and subsequently increase N(2)O emissions from both soils and streams.

Dairy farms in the United States are diverse and although regional dairy production and farm strategy has been evaluated for environmental impact, a comprehensive national assessment is important to define national priorities for sustainable intensification. We estimated important environmental footprints of dairy production using process-level simulation and cradle-to-farm gate life cycle assessment. Dairy farms representing the sizes and management practices found in six regions were simulated with the Integrated Farm System Model (IFSM). Regional and national environmental footprints were determined as an average of all simulated farms weighted by the portion of milk contributed by each to the total. Nationally, dairy farms were found to emit 99,000 ± 8480 Gg CO2e of greenhouse gas (GHG), equivalent to 1.5% of the estimated U.S. total GHG emission, with a commodity-based intensity of 1.01 ± 0.09 kg CO2e/kg of fat and protein corrected milk (FPCM) produced. Fossil energy use was 242,700 ± 38,400 TJ, 0.3% of the U.S. total, or 2.48 ± 0.39 MJ/kg FPCM. Blue (non-precipitation) water use was 11,600 ± 2480 Tg, roughly 3.0% of the estimated U.S. total freshwater withdraw, with an intensity of 119 ± 25 kg/kg FPCM. While these environmental footprints represent a small portion of the respective national inventories, the dairy industry's contribution to reactive nitrogen (N) losses appears to be considerably greater. Losses of reactive N were estimated at 970 ± 133 Gg, with an intensity of 9.92 ± 1.36 g/kg FPCM where 66% of the total was in the form of ammonia (NH3). Although there are no national estimates of total reactive N loss, dairy farms were found to contribute 19–24% of national inventories of NH3 emissions. While strategies are available to reduce NH3 emissions, finding economical and sustainable solutions that do not result in pollution swapping remains a challenge for the dairy industry.

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.

Farm management strategies for alternatives to nitrogen application can reduce greenhouse gas emissions, improve air quality, and increase crop yields in China.

Agriculture and waste are thought to account for half or more of the U.S. anthropogenic methane source. However, current bottom-up inventories contain inherent uncertainties from extrapolating limited in situ measurements to larger scales. Here, we employ new airborne methane measurements over the U.S. Corn Belt and Upper Midwest, among the most intensive agricultural regions in the world, to quantify emissions from an array of key agriculture and waste point sources. Nine of the largest concentrated animal feeding operations in the region and two sugar processing plants were measured, with multiple revisits during summer (August 2017), winter (January 2018), and spring (May-June 2018). We compare the top-down fluxes with state-of-science bottom-up estimates informed by U.S. Environmental Protection Agency methodology and site-level animal population and management practices. Top-down point source emissions are consistent with bottom-up estimates for beef concentrated animal feeding operations but moderately lower for dairies (by 37% on average) and significantly lower for sugar plants (by 80% on average). Swine facility results are more variable. The assumed bottom-up seasonality for manure methane emissions is not apparent in the aircraft measurements, which may be due to on-site management factors that are difficult to capture accurately in national-scale inventories. If not properly accounted for, such seasonal disparities could lead to source misattribution in top-down assessments of methane fluxes.

Kura clover living mulch (KCLM) systems have been previously investigated for their incorporation into upper Midwestern row crop rotations to provide ecosystem services through continuous living cover. Reductions in soil erosion and nitrate loss to surface and groundwater have been reported, but factors affecting agronomic performance and nutrient management are not well defined. To achieve realized environmental benefits, research must develop agronomic management techniques, determine economic opportunities, and provide management recommendations for row crop production in KCLM systems. Two experiments were conducted in 2017 and 2018 to determine the response to N fertilizer application for maize production in KCLM. The first-year maize experiment followed forage management, and the second-year maize experiment followed maize after forage management. Eight fertilizer N treatments ranging from 0&ndash, 250 kg N ha&minus, 1 were applied to each experiment and grain and stover yields were compared to conventionally managed maize hybrid trials that were conducted nearby. First-year maize did not need fertilizer N to maximize yield and profitability in either growing season, and second-year maize required a fertilizer N rate near local University guidelines for maize following soybean. The net economic return from maize grain and stover in the KCLM averaged over first and second-year maize experiments and 2017 and 2018 growing seasons were $138 ha&minus, 1 greater than the conventional comparison.

Anthropogenic emissions of nitrous oxide (N 2 O), a trace gas with severe environmental costs, are greatest from agricultural soils amended with nitrogen (N) fertilizer. However, accurate N 2 O emission estimates at fine spatial scales are made difficult by their high variability, which represents a critical challenge for the management of N 2 O emissions. Here, static chamber measurements ( n = 60) and soil samples ( n = 129) were collected at approximately weekly intervals ( n = 6) for 42-d immediately following the application of N in a southern Minnesota cornfield (15.6-ha), typical of the systems prevalent throughout the U.S. Corn Belt. These data were integrated into a geostatistical model that resolved N 2 O emissions at a high spatial resolution (1-m). Field-scale N 2 O emissions exhibited a high degree of spatial variability, and were partitioned into three classes of emission strength: hotspots, intermediate, and coldspots. Rates of emission from hotspots were 2-fold greater than non-hotspot locations. Consequently, 36% of the field-scale emissions could be attributed to hotspots, despite representing only 21% of the total field area. Variations in elevation caused hotspots to develop in predictable locations, which were prone to nutrient and moisture accumulation caused by terrain focusing. Because these features are relatively static, our data and analyses indicate that targeted management of hotspots could efficiently reduce field-scale emissions by as much 17%, a significant benefit considering the deleterious effects of atmospheric N 2 O.

Nitrous oxide (NO), produced primarily in agricultural soils, is a potent greenhouse gas and is the dominant ozone-depleting substance. Efforts to reduce NO emissions are underway, but mitigation results have been inconsistent. The leguminous perennial kura clover ( M. Bieb.) (KC) can grow side-by-side with cash crops in rotational corn ( L.)-soybean ( L.) systems. With biological nitrogen fixation, KC provides land managers an opportunity to reduce external fertilizer inputs, which may diminish problematic NO emissions. To investigate the effect of a KC living mulch on NO emissions, automated soil chambers coupled to a NO analyzer were used to measure hourly fluxes from April through October in a 2-yr corn-soybean (CS) rotation. Emissions from the KC treatment were significantly greater than those from the conventional CS treatment despite the fact that the KC treatment received substantially less inorganic nitrogen fertilizer. A seasonal tradeoff was observed with the KC treatment wherein emissions before strip-tillage were reduced but were surpassed by high losses after strip-tillage and postanthesis. These results represent the first reported measurements of NO emissions from a KC-based living mulch. The findings cast doubt on the efficacy of KC for mitigating NO loss in CS systems. However, if KC reduces nitrate leaching losses, as has been reported elsewhere, it may result in lower indirect (offsite) NO emissions.

Nitrous oxide (N2O) emissions within the US Corn Belt have been previously estimated to be 200–900% larger than predictions from emission inventories, implying that one or more source categories in bottom-up approaches are underestimated. Here we interpret hourly N2O concentrations measured during 2010 and 2011 at a tall tower using a time-inverted transport model and a scale factor Bayesian inverse method to simultaneously constrain direct and indirect agricultural emissions. The optimization revealed that both agricultural source categories were underestimated by the Intergovernmental Panel on Climate Change (IPCC) inventory approach. However, the magnitude of the discrepancies differed substantially, ranging from 42 to 58% and from 200 to 525% for direct and indirect components, respectively. Optimized agricultural N2O budgets for the Corn Belt were 319 ± 184 (total), 188 ± 66 (direct), and 131 ± 118 Gg N yr−1 (indirect) in 2010, versus 471 ± 326, 198 ± 80, and 273 ± 246 Gg N yr−1 in 2011. We attribute the interannual differences to varying moisture conditions, with increased precipitation in 2011 amplifying emissions. We found that indirect emissions represented 41–58% of the total agricultural budget, a considerably larger portion than the 25–30% predicted in bottom-up inventories, further highlighting the need for improved constraints on this source category. These findings further support the hypothesis that indirect emissions are presently underestimated in bottom-up inventories. Based on our results, we suggest an indirect emission factor for runoff and leaching ranging from 0.014 to 0.035 for the Corn Belt, which represents an upward adjustment of 1.9–4.6 times relative to the IPCC and is in agreement with recent bottom-up field studies.

The U.S. Corn Belt is one of the most intensive agricultural regions of the world and is drained by the Upper Mississippi River (UMR), which forms one of the largest drainage basins in the U.S. While the effects of agricultural nitrate (NO3−) on water quality in the UMR have been well documented, its impact on the production of nitrous oxide (N2O) has not been reported. Using a novel equilibration technique, we present the largest data set of freshwater dissolved N2O concentrations (0.7 to 6 times saturation) and examine the controls on its variability over a 350 km reach of the UMR. Driven by a supersaturated water column, the UMR was an important atmospheric N2O source (+68 mg N2O N m−2 yr−1) that varies nonlinearly with the NO3− concentration. Our analyses indicated that a projected doubling of the NO3− concentration by 2050 would cause dissolved N2O concentrations and emissions to increase by about 40%.

Tropical peatlands are a major, but understudied, biophysical feedback factor on the atmospheric greenhouse effect. The largest expanses of tropical peatlands are located in lowland areas of Southeast Asia and the Amazon basin. The Loreto Region of Amazonian Peru contains ~63,000 km2 of peatlands. However, little is known about the biogeochemistry of these peatlands, and in particular, the cycling of carbon dioxide (CO2) and methane (CH4), and their responses to hydrometeorological forcings. To address these knowledge gaps, we established an eddy covariance (EC) flux tower in a natural palm (Mauritia flexuosa L.f.) swamp peatland near Iquitos, Peru. Here, we report ecosystem-scale CO2 and CH4 flux observations for this Amazonian palm swamp peatland over a two-year period in relation to hydrometeorological forcings. Seasonal and short-term variations in hydrometeorological forcing had a strong effect on CO2 and CH4 fluxes. High air temperature and vapor pressure deficit (VPD) exerted an important limitation on photosynthesis during the dry season, while latent heat flux appeared to be insensitive to these climate drivers. Evidence from light-response analyses and flux partitioning support that photosynthetic activity was downregulated during dry conditions, while ecosystem respiration (RE) was either inhibited or enhanced depending on water table position. The cumulative net ecosystem CO2 exchange indicated that the peatland was a significant CO2 sink ranging from −465 (−279 to −651) g C m−2 y−1 in 2018 to −462 (−277 to −647) g C m−2 y−1 in 2019. The forest was a CH4 source of 22 (20 to 24) g C m−2 y−1, similar in magnitude to other tropical peatlands and larger than boreal and arctic peatlands. Thus, the annual carbon budget of this Amazonian palm swamp peatland appears to be a major carbon sink under current hydrometeorological conditions.

Kura clover (Trifolium ambiguum) is a perennial living mulch species that can be used in conjunction with zone tillage to reduce nitrogen pollution, maintain ground cover, and provide nitrogen to crops. In such systems, kura clover is maintained between crop rows by limiting tillage only to within-row areas. However, the effect of zone-tilled living mulches on soil quality and nutrient cycling in these distinct regions is relatively unexplored. We examined three pools of labile soil organic matter (SOM): microbial biomass, particulate organic matter (POM), and permanganate oxidizable carbon (POXC). Soil samples were collected from both within-row and between-row locations of a zone-tilled kura clover living mulch at three time points per year: before spring zone tillage, approximately ten days after spring zone tillage and corn (Zea mays) planting, and at corn harvest in 2015 and 2016. In 2016, POM and POXC decreased within rows relative to between-row regions after tillage, suggesting that zone till management stimulated decomposition of readily available SOM to effectively localize nutrient cycling in this region and slow mineralization between rows where living kura clover remained. This work shows that zone-tilled living mulches may be a promising avenue for enhancing the synchrony of nutrient mineralization specifically within crop rows, while maintaining year-round ground cover between rows.

Nutrient recycling is fundamental to sustainable agricultural systems, but few mechanisms exist to ensure that surplus manure nutrients from animal feeding operations are transported for use on nutrient-deficient croplands. As a result, manure nutrients concentrate in locations where they can threaten environmental health and devalue manure as a fertilizer resource. This study advances the concept of the “manureshed” – the lands surrounding animal feeding operations onto which manure nutrients can be redistributed to meet environmental, production, and economic goals. Manuresheds can be managed at multiple scales, for example, on farms with both animals and crops, among animal farms and crop farms within a county, or even among animal farms and crop farms in distant counties. With a focus on redistribution among counties, we classified the 3109 counties of the contiguous United States by their capacity to either supply manure phosphorus (P) and nitrogen (N) from confined livestock production (“sources”) or to assimilate and remove excess P and N via crops (“sinks”). Manure nutrient source counties were identified in 40 of the 48 states, with a substantial concentration in the southern US. Source counties for manure P greatly outnumbered source counties for manure N (390 vs. 100), and 99 of the 100 manure N source counties were also source counties for manure P. Conversely, sink counties for manure N outnumbered sink counties for manure P (2766 vs. 2317). We used the P balances of the source and sink counties to delineate four manuresheds dominated by various combinations of confined hog, poultry, dairy, and beef industries. The four manuresheds differed in the transport distances needed to assimilate excess manure P from their respective source areas (from 147 ± 51 km for a beef dominated manureshed to 368 ± 140 km for a poultry dominated manureshed), highlighting the need for systems-level strategies to promote manure nutrient recycling that operate across local, county, regional, and national scales.

Leaching of nitrate (NO3-N) from manure-applied cropping systems can represent a substantial N-loss to the environment for dairy farms, particularly in fields with artificial subsurface drainage. In this on-farm study, we used a Before/After analysis to assess the effectiveness of summer fertigation with reduced manure rates (years 2010 – 2015) versus fall injection (2007 – 2009) of dairy slurry in terms of subsequent corn silage yield, corn N removal, soil NO3-N distribution, and NO3-N losses in subsurface tile drainage from a 65-ha field in Minnesota, USA. Yield was similar between periods (average of 18.8 Mg ha-1), but crop %N, N removal, and manurial N-use efficiency were 15, 12, and 126% greater during the fertigation than injection period. Fertigation reduced spring soil NO3-N concentrations to 60-cm depth by an average of 53% relative to injection, except in the 15 to 30 cm increment, where no difference was found. Similarly, fall soil NO3-N concentrations from 30 to 90 cm were 48% lower, on average, under fertigation than injection. Weekly flow-weighted mean NO3-N concentration in tile drainage was lower during fertigation (47.7 mg L-1) than injection (56.8 mg L-1), although mean weekly drainage depth was greater during fertigation (2.3 versus 1.1 mm). This resulted in similar weekly loads between periods (mean of 0.96 kg NO3-N ha-1). For non-snowmelt flow, relationships between drainage and NO3-N load showed log–log slopes of near 1.0 for injection and 0.97 for fertigation, indicating dilution of concentrations with increased flow during fertigation, but not during injection. Differing intercepts indicated a treatment effect of fertigation independent of flow effects, and corresponded to loads of 5.9 kg NO3-N ha-1 for injection and 4.7 kg NO3-N ha-1 for fertigation, a reduction of 20% at a 10 mm weekly flow depth. The magnitude of the reduction in load increased to 22% at a 25 mm weekly flow depth. Results suggest that summer fertigation with attendant reduction in application rate is a viable method for reducing drainage NO3-N losses without impacting yield of irrigated silage corn in the U.S. Midwest.

Improving water quantity and quality impacts of corn ( L.)- and soybean [ (L.) Merr.]-based cropping systems is a key challenge for agriculture in the US Midwest. Long-term field experiments are important for documenting those effects and exploring possible solutions. This study examines differences in soil water dynamics and nitrate-nitrogen (N) leaching among cropping systems and N fertilizer sources in a long-term experiment in southeastern Minnesota. Drainage and leachate concentrations were measured for 4 yr using automated equilibrium tension lysimeters installed below the root zone in replicated, large plots on a well-drained silt loam soil. Soil water storage was monitored using water content reflectometers. Corn–soybean and continuous corn cropping systems exhibited similar soil water dynamics, drainage rates (145–202 mm yr), leachate nitrate N concentrations (21.3–25.6 mg L), and nitrate N leaching loads (30–75 kg ha yr). Nitrate-N concentrations in the leachate were similar whether N was added as urea (21.2 mg L) or anhydrous ammonia (25.7 mg L). A perennial kura clover ( M. Bieb)-based cropping system with no N fertilizer significantly altered soil water dynamics and resulted in lower ( < 0.10) drainage rates (53 mm yr), nitrate N concentrations (7.1 mg L), and nitrate N leaching loads (2–5 kg ha yr) compared with corn–soybean or continuous corn, but also reduced corn grain yields. These impacts are generally consistent with a growing body of literature showing substantial environmental benefits of a kura clover living mulch system for corn production, but the economic viability of such a system is not yet proven.

One of the most serious environmental problems associated with agriculture is excessive nitrate N in waters leaving fields. It is a health hazard in drinking water and a primary cause of hypoxia in ocean waters receiving drainage from agricultural regions. Recent mitigation efforts have focused on techniques that promote denitrification—conversion of excess agricultural nitrate to N₂. This seems inherently wasteful since industrial production of nitrate fertilizer from N₂ requires a substantial input of energy and is a major source of greenhouse gas emissions. Thus, it is desirable to develop methods to recycle nitrate, keeping it in a form suitable for reuse as fertilizer. One possibility is electrodialysis, in which direct current is passed through alternating cation- and anion-permeable membranes, creating separate streams of dilute and concentrated water. We tested the concept under controlled conditions in a greenhouse and in a field setting on a contaminated trout stream with nitrate N concentrations consistently above 20 mg L⁻¹. The solar-powered field system removed 42% of the nitrate from water passing through it and concentrated it in a tank for subsequent application as fertilizer. The upper limit of concentration was approximately 520 mg L⁻¹, above which precipitation of calcite limited operation. Economic analysis indicates that in comparison to denitrification methods such as bioreactors, electrodialysis is likely to be more expensive per unit of nitrate removed. The approach will be most feasible for situations in which nitrate concentrations are well above environmental standards for extended periods, to maximize operating time and nitrate removal rate.

The intensification of global agriculture has led to a decline in arable land. Globally, agriculture intensification has not only degraded the soil quality but also contributed to increasing the greenhouse gas (GHG) levels. These concerns attract the interest of environmental scientists and academicians to find ways to sequester more carbon (C) in the agricultural soils. Tillage is one method that can affect biological C sequestration and effects the GHG production. The components of GHGs are produced slowly from the soil through the reactions taking place between C and nutrients (nitrogen in particular), which remain present in the soil. An understanding of biological C sequestration processes in agricultural production systems can lead to potentially cost-effective strategies able to mitigate global warming. Globally, the shift in tillage practice from conventional tillage to no-tillage is effectively protecting soils under cropping, improving their quality—or reducing their rate of soil organic matter decline—as well as enhancing the resilience of cropping systems. This review summarizes the current knowledge about no-till technology and its impacts on soil properties related to carbon dynamics and explores the potential role of tillage practices in mitigating climate change.

All-black thermopile pyranometers are commonly used to measure solar radiation. Ensuring that the sensors are stable and free of drift is critical to accurately measure small variations in global solar irradiance at the Earth’s surface (K↓), which is a potential driver of changes in surface temperature. We demonstrate that the decreased responsivities of Eppley PSP pyranometers of −1.5% y−1, or −0.38% (GJ m−2)−1, were accompanied by a change in its spectral response owing to a discoloration of the sensing element. These observations motivated further work to develop routines to detect probable pyranometer drift in historical time-series. The temporal trends in the following ratios were used to detect pyranometer sensor drift: photosynthetically active radiation (PAR) to K↓, K↓ to KEX (extraterrestrial radiation at the top of the atmosphere) and PAR to KEX. Data from 8 AmeriFlux sites spanning latitudes from ∼32 to 54°N were examined in this analysis. Probable drift in either a pyranometer or PAR sensor was identified at 5 of the 8 sites. The magnitude of the drift represented changes of 0.15–0.85% y−1, which is sufficient to obscure actual trends in K↓, although these should be considered conservative low end drift estimates, given that we were not making comparisons to co-located higher grade instruments. Deployment exposure errors caused by sensor shading were also discovered by comparing the daily correlations between (i) K↓ and KEX and (ii) PAR and KEX. Sensors drifting at rates similar to our defective PSP over a 5 year period would contribute to an underestimation of available energy of ∼70 W m−2, which is non-trivial in the context of assessing eddy covariance energy balance closure, employing Penman-Monteith or Bowen ratio methods or calculating albedo radiative forcings. Given that probable drift was identified at multiple AmeriFlux sites, we recommend enhancing network access to calibration services that are traceable to a high quality gold standard.

A reasonable representation of crop phenology and biophysical processes in land surface models is necessary to accurately simulate energy, water, and carbon budgets at the field, regional, and global scales. However, the evaluation of crop models that can be coupled to Earth system models is relatively rare. Here we evaluated two such models (CLM4-Crop and CLM3.5-CornSoy), both implemented within the Community Land Model (CLM) framework, at two AmeriFlux corn-soybean sites to assess their ability to simulate phenology, energy, and carbon fluxes. Our results indicated that the accuracy of net ecosystem exchange and gross primary production simulations was intimately connected to the phenology simulations. The CLM4-Crop model consistently overestimated early growing season leaf area index, causing an overestimation of gross primary production, to such an extent that the model simulated a carbon sink instead of the measured carbon source for corn. The CLM3.5-CornSoy-simulated leaf area index (LAI), energy, and carbon fluxes showed stronger correlations with observations compared to CLM4-Crop. Net radiation was biased high in both models and was especially pronounced for soybeans. This was primarily caused by the positive LAI bias, which led to a positive net long-wave radiation bias. CLM4-Crop underestimated soil water content during midgrowing season in all soil layers at the two sites, which caused unrealistic water stress, especially for soybean. Future work regarding the mechanisms that drive early growing season phenology and soil water dynamics is needed to better represent crops including their net radiation balance, energy partitioning, and carbon cycle processes.

Nitrous oxide (N2O) has a global warming potential that is 300 times that of carbon dioxide on a 100-y timescale, and is of major importance for stratospheric ozone depletion. The climate sensitivity of N2O emissions is poorly known, which makes it difficult to project how changing fertilizer use and climate will impact radiative forcing and the ozone layer. Analysis of 6 y of hourly N2O mixing ratios from a very tall tower within the US Corn Belt-one of the most intensive agricultural regions of the world-combined with inverse modeling, shows large interannual variability in N2O emissions (316 Gg N2O-N⋅y-1 to 585 Gg N2O-N⋅y-1). This implies that the regional emission factor is highly sensitive to climate. In the warmest year and spring (2012) of the observational period, the emission factor was 7.5%, nearly double that of previous reports. Indirect emissions associated with runoff and leaching dominated the interannual variability of total emissions. Under current trends in climate and anthropogenic N use, we project a strong positive feedback to warmer and wetter conditions and unabated growth of regional N2O emissions that will exceed 600 Gg N2O-N⋅y-1, on average, by 2050. This increasing emission trend in the US Corn Belt may represent a harbinger of intensifying N2O emissions from other agricultural regions. Such feedbacks will pose a major challenge to the Paris Agreement, which requires large N2O emission mitigation efforts to achieve its goals.

Solar induced fluorescence (SIF) has shown great promise for probing spatiotemporal variations in terrestrial gross primary production (GPP), the largest component flux of the global carbon cycle. However, scale mismatches between SIF and ground-based GPP have posed challenges towards fully exploiting these data. We used SIF obtained at high spatial sampling rates and resolution by NASA's Orbiting Carbon Observatory (OCO-2) satellite to elucidate GPP-SIF relationships across space and time in the US Corn Belt. Strong linear scaling functions (R2 ≥ 0.79) that were consistent across instantaneous to monthly timescales were obtained for corn ecosystems, and for a heterogeneous landscape based on tall tower observations. Although the slope of the corn function was ~56% higher than for the landscape, SIF was similar for corn (C4) and soybean (C3). Taken together, there is strong observational evidence showing robust linear GPP-SIF scaling that is sensitive to plant physiology but insensitive to the spatial or temporal scale.

In the United States, corn (Zea mays L.) stover has been targeted for second generation fuel production and other bio-products. Our objective was to characterize sugar and structural composition as a function of vertical distribution of corn stover (leaves and stalk) that was sampled at physiological maturity and about three weeks later from multiple USA locations. A small subset of samples was assessed for thermochemical composition. Concentrations of lignin, glucan, and xylan were about 10% greater at grain harvest than at physiological maturity, but harvestable biomass was about 25% less due to stalk breakage. Gross heating density above the ear averaged 16.3 ± 0.40 MJ kg−1, but with an alkalinity measure of 0.83 g MJ−1, slagging is likely to occur during gasification. Assuming a stover harvest height of 10 cm, the estimated ethanol yield would be &gt, 2500 L ha−1, but it would be only 1000 L ha−1 if stover harvest was restricted to the material from above the primary ear. Vertical composition of corn stover is relatively uniform, thus, decision on cutting height may be driven by agronomic, economic and environmental considerations.

Quantification of regional greenhouse gas (GHG) fluxes is essential for establishing mitigation strategies and evaluating their effectiveness. Here, we used multiple top-down approaches and multiple trace gas observations at a tall tower to estimate regional-scale GHG fluxes and evaluate the GHG fluxes derived from bottom-up approaches. We first applied the eddy covariance, equilibrium, inverse modeling (CarbonTracker), and flux aggregation methods using 3 years of carbon dioxide (CO2) measurements on a 244 m tall tower in the upper Midwest, USA. We then applied the equilibrium method for estimating CH4 and N2O fluxes with 1-month high-frequency CH4 and N2O gradient measurements on the tall tower and 1-year concentration measurements on a nearby tall tower, and evaluated the uncertainties of this application. The results indicate that (1) the flux aggregation, eddy covariance, the equilibrium method, and the CarbonTracker product all gave similar seasonal patterns of the regional CO2 flux (105−106 km2, but that the equilibrium method underestimated the July CO2 flux by 52–69%. (2) The annual budget varied among these methods from −54 to −131 g C–CO2 m−2 yr−1, indicating a large uncertainty in the annual CO2 flux estimation. (3) The regional CH4 and N2O emissions according to a top-down method were at least 6 and 2 times higher than the emissions from a bottom-up inventory (Emission Database for Global Atmospheric Research), respectively. (4) The global warming potentials of the CH4 and N2O emissions were equal in magnitude to the cooling benefit of the regional CO2 uptake. The regional GHG budget, including both biological and anthropogenic origins, is estimated at 7 ± 160 g CO2 equivalent m−2 yr−1.

This study seeks to quantify the roles of soybean and corn plants and the cropland ecosystem in the regional N2O budget of the Upper Midwest, USA. The N2O flux was measured at three scales (plant, the soil-plant ecosystem, and region) using newly designed steady-state flow-through plant chambers, a flux-gradient micrometeorological tower, and continuous tall-tower observatories. Results indicate that the following. (1) N2O fluxes from unfertilized soybean (0.03 ± 0.05 nmol m(-2) s(-1)) and fertilized corn plants (-0.01 ± 0.04 nmol m(-2) s(-1)) were about one magnitude lower than N2O emissions from the soil-plant ecosystem (0.26 nmol m(-2) s(-1) for soybean and 0.95 nmol m(-2) s(-1) for corn), confirming that cropland N2O emissions were mainly from the soil. (2) Fertilization increased the corn plant flux for a short period (about 20 days), and late-season fertilization dramatically increased the soybean plant emissions. (3) The direct N2O emission from cropland accounted for less than 20 % of the regional flux, suggesting a significant influence by other sources and indirect emissions, in the regional N2O budget.

I ncorporating cover crops into the two-year corn ( Zea mays L.)–soybean ( Glycine max L.) rotation can reduce soil erosion, increase soil organic matter, improve soil structure (Snapp et al. 2005), and reduce nitrate (NO3) leaching (Strock et al. 2004; Fisher et al. 2011). However, it is often difficult to establish winter cover crops in the cooler climate and shorter growing season of the northern Corn Belt. Miguez and Bollero (2005) reported that grass cover crops in the north central United States would only provide marginal benefits due to low biomass production. Through growth simulations, Baker and Griffis (2009) found that the main limitations are degree days and photosynthetically active radiation. Strock et al. (2004) suggested that based on average weather patterns in southwestern Minnesota, winter rye ( Secale cereal L.) would only be a successful cover crop in one out of four years. In these studies, however, temperatures were already cool when the cover crop was planted following harvest of the preceding crop. As another option, Frye et al. (1988) suggested that broadcasting seed into a standing crop can result in earlier crop growth than drilling the seed after harvest. Through growth simulations based on field experiments, Feyereisen et al. (2006) recommended…

In-field measurements of direct soil greenhouse gas (GHG) emissions provide critical data for quantifying the net energy efficiency and economic feasibility of crop residue-based bioenergy production systems. A major challenge to such assessments has been the paucity of field studies addressing the effects of crop residue removal and associated best practices for soil management (i.e., conservation tillage) on soil emissions of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4). This regional survey summarizes soil GHG emissions from nine maize production systems evaluating different levels of corn stover removal under conventional or conservation tillage management across the US Corn Belt. Cumulative growing season soil emissions of CO2, N2O, and/or CH4 were measured for 2–5 years (2008–2012) at these various sites using a standardized static vented chamber technique as part of the USDA-ARS’s Resilient Economic Agricultural Practices (REAP) regional partnership. Cumulative soil GHG emissions during the growing season varied widely across sites, by management, and by year. Overall, corn stover removal decreased soil total CO2 and N2O emissions by -4 and -7 %, respectively, relative to no removal. No management treatments affected soil CH4 fluxes. When aggregated to total GHG emissions (Mg CO2 eq ha−1) across all sites and years, corn stover removal decreased growing season soil emissions by −5 ± 1 % (mean ± se) and ranged from -36 % to 54 % (n = 50). Lower GHG emissions in stover removal treatments were attributed to decreased C and N inputs into soils, as well as possible microclimatic differences associated with changes in soil cover. High levels of spatial and temporal variabilities in direct GHG emissions highlighted the importance of site-specific management and environmental conditions on the dynamics of GHG emissions from agricultural soils.

Corn stover removal, whether for silage, bedding, or bioenergy production, could have a variety of environmental consequences through its effect on soil processes, particularly N2O production and soil respiration. Because these effects may be episodic in nature, weekly snapshots with static chambers may not provide a complete picture. We adapted commercially available automated soil respiration chambers by incorporating a portable N2O analyzer, allowing us to measure both CO2 and N2O fluxes on an hourly basis through two growing seasons in a corn field in southern Minnesota, from spring 2010 to spring 2012. This site was part of a USDA multilocation research project for five growing seasons, 2008–2012, with three levels of stover removal: zero, full, and intermediate. Initially in spring 2010, two chambers were placed in each of the treatments, but following planting in 2011, the configuration was changed, with four chambers installed on zero removal plots and four on full removal plots. The cumulative data revealed no significant difference in N2O emission as a function of stover removal. CO2 loss from the full removal plots was slightly lower than that from the zero removal plots, but the difference between treatments was much smaller than the amount of C removed in the residue, implying loss of soil carbon from the full removal plots. This is consistent with soil sampling data, which showed that in five of six sampled blocks, the SOC change in the full removal treatments was negative relative to the zero removal plots. We conclude that (a) full stover removal may have little impact on N2O production, and (b) while it will reduce soil CO2 production, the reduction will not be commensurate with the decrease in fresh carbon inputs and, thus, will result in SOC loss.

Corn’s (Zea mays L.) stover is a potential nonfood, herbaceous bioenergy feedstock. A vital aspect of utilizing stover for bioenergy production is to establish sustainable harvest criteria that avoid exacerbating soil erosion or degrading soil organic carbon (SOC) levels. Our goal is to empirically estimate the minimum residue return rate required to sustain SOC levels at numerous locations and to identify which macroscale factors affect empirical estimates. Minimum residue return rate is conceptually useful, but only if the study is of long enough duration and a relationship between the rate of residue returned and the change in SOC can be measured. About one third of the Corn Stover Regional Partnership team (Team) sites met these criteria with a minimum residue return rate of 3.9 ± 2.18 Mg stover ha−1 yr−1, n = 6. Based on the Team and published corn-based data (n = 35), minimum residue return rate was 6.38 ± 2.19 Mg stover ha−1 yr−1, while including data from other cropping systems (n = 49), the rate averaged 5.74 ± 2.36 Mg residue ha−1 yr−1. In broad general terms, keeping about 6 Mg residue ha−1 yr−1 maybe a useful generic rate as a point of discussion; however, these analyses refute that a generic rate represents a universal target on which to base harvest recommendations at a given site. Empirical data are needed to calibrate, validate, and refine process-based models so that valid sustainable harvest rate guidelines are provided to producers, industry, and action agencies.

Wetlands represent the dominant natural source of methane (CH(4)) to the atmosphere. Thus, substantial effort has been spent examining the CH(4) budgets of global wetlands via continuous ecosystem-scale measurements using the eddy covariance (EC) technique. Robust error characterization for such measurements, however, remains a major challenge. Here, we quantify systematic, random and gap-filling errors and the resulting uncertainty in CH(4) fluxes using a 3.5 year time series of simultaneous open- and closed path CH(4) flux measurements over a sub-boreal wetland. After correcting for high- and low frequency flux attenuation, the magnitude of systematic frequency response errors were negligible relative to other uncertainties. Based on three different random flux error estimations, we found that errors of the CH(4) flux measurement systems were smaller in magnitude than errors associated with the turbulent transport and flux footprint heterogeneity. Errors on individual half-hourly CH(4) fluxes were typically 6%–41%, but not normally distributed (leptokurtic), and thus need to be appropriately characterized when fluxes are compared to chamber-derived or modeled CH(4) fluxes. Integrated annual fluxes were only moderately sensitive to gap-filling, based on an evaluation of 4 different methods. Calculated budgets agreed on average to within 7% (≤ 1.5 g − CH(4) m(−2) yr(−1)). Marginal distribution sampling using open source code was among the best-performing of all the evaluated gap-filling approaches and it is therefore recommended given its transparency and reproducibility. Overall, estimates of annual CH(4) emissions for both EC systems were in excellent agreement (within 0.6 g − CH(4) m(−2) yr(−1)) and averaged 18 g − CH(4) m(−2) yr(−1). Total uncertainties on the annual fluxes were larger than the uncertainty of the flux measurement systems and estimated between 7–17%. Identifying trends and differences among sites or site years requires that the observed variability exceeds these uncertainties.

Establishing cover crops in a corn (L.)–soybean (L.) rotation in northern climates can be difficult due to the short time between harvest and freezing temperatures. Aerial seeding into standing crops is one way to increase the time for germination and growth. Field studies were conducted to characterize the physical and chemical properties that affect winter rye (L.) establishment in corn and soybean, while a germination experiment was designed to determine optimal temperature and surface soil moisture content needed for successful germination. In the field study, 31 field-scale sites (22 corn and nine soybean) were aerially seeded in southeastern Minnesota during late August to early September 2009, 2010, and 2011. Aboveground biomass was collected before the ground froze, and multiple regression analysis was used to relate biomass to multiple soil and weather conditions. Total N uptake also was determined. Overall, precipitation the week after seeding was the most important factor in determining rye establishment, although our model accounted for only 43% of the variation in biomass. The germination study characterized winter rye germination on the surface of three different soils equilibrated to –50, –200, and –500 kPa water potential placed in three low-temperature incubators at 10, 18, and 25°C. Total germination was decreased by decreasing water potential in the sandy loam but not the clay or silt loam, suggesting that moisture content may be more important than water potential at the soil surface. Generally, germination was drastically reduced below a moisture content of 0.083 g g.

Increased corn (Zea mays L.) silage and manure production accompanying the proliferation of large dairies has prompted concern regarding their environmental impacts. The objectives of this on-farm, field-scale study were (1) to quantify environmental impacts, e.g., soil chemical properties and offsite nutrient transport, of corn silage production with dairy manure application on artificially drained soils and (2) to assess the environmental benefits of and agronomic constraints on the adoption of winter rye (Secale cereale L.) cover cropping by a large dairy in west central Minnesota. From 2007 to 2009, corn for silage was grown on two adjacent 65 ha (160 ac) fields, with rye planted after corn on one field in 2007. Liquid manure was fall applied annually at average total nitrogen (N) and phosphorus (P) rates of 410 and 98 kg ha−1 (365 and 87 lb ac−1), respectively. Soil nitrate nitrogen (NO3-N) and Olsen P accumulation did not occur with the studied cropping systems, but average annual NO3-N and dissolved reactive P (DRP) subsurface drainage loads were 52 and 0.8 kg ha−1 y−1 (46 and 0.7 lb ac−1 yr−1), respectively. Soil organic carbon (C) concentration was maintained on the field without rye and increased 15% to a depth of 15 cm (6 in) on the field with rye, but C additions with manure likely contributed to the increase. Rye reduced spring soil NO3-N by 46% and increased ground cover an average of fourfold compared with winter fallow. Subsurface drainage NO3-N concentration was reduced from 53 mg L−1 (53 ppm) without rye to 39 mg L−1 (39 ppm) with rye, but rye had no impact on DRP concentration. Rye aboveground dry matter yield was 2 Mg ha−1 (0.9 tn ac−1). Corn dry matter yield was 16%, or 2.7 Mg ha−1 (1.2 tn ac−1), lower after rye than after winter fallow. This reduced yield and the persistence of high NO3-N and DRP concentrations in subsurface drainage with rye indicate alternative conservation practices are warranted at this site. In general, cover cropping with winter rye provided environmental benefits over corn silage alone but also increased economic risks.

[1] Nitrous oxide (N2O) is a greenhouse gas with a large global warming potential and is a major cause of stratospheric ozone depletion. Croplands are the dominant source of N2O, but mitigation strategies have been limited by the large uncertainties in both direct and indirect emission factors (EFs) implemented in “bottom-up” emission inventories. The Intergovernmental Panel on Climate Change (IPCC) recommends EFs ranging from 0.75% to 2% of the anthropogenic nitrogen (N) input for the various N2O pathways in croplands. Consideration of the global N budget yields a much higher EF ranging between 3.8% and 5.1% of the anthropogenic N input. Here we use 2 years of hourly high-precision N2O concentration measurements on a very tall tower to evaluate the IPCC bottom-up and global “top-down” EFs for a large representative subsection of the United States Corn Belt, a vast region spanning the U.S. Midwest that is dominated by intensive N inputs to support corn cultivation. Scaling up these results indicates that agricultural sources in the Corn Belt released 420±50 Gg N (mean ±1 standard deviation; 1 Gg =109 g) in 2010, in close agreement with the top-down estimate of 350±50 Gg N and 80% larger than the bottom-up estimate based on the IPCC EFs (230 ± 180 Gg N). The large difference between the tall tower measurement and the bottom-up estimate implies the existence of N2O emission hot spots or missing sources within the landscape that are not fully accounted for in the IPCC and other bottom-up emission inventories. Reconciling these differences is an important step toward developing a practical mitigation strategy for N2O.