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The specialization and intensification of agriculture have produced incredible gains in productivity, quality, and availability of agricultural commodities but have resulted in the separation of crop and animal production. A by-product of this separation has been the accumulation of manure regions where animal production is concentrated. Enter the "manureshed," an organizing framework for integrating animal and crop production where budgeting of manure nutrients is used to strategically guide their recycling and reuse in agricultural production systems where manure resources are of highest value. To move beyond regional nutrient balance analyses into the transformational realm required to mitigate "wicked" manure problems, manureshed management requires recognition of the challenges to systematically reorganizing resource flows. In better integrating crop and livestock systems, manureshed management must account for the unique nature of managing manure nutrients within individual livestock industries, anticipate trade-offs in substituting manure for commercial fertilizer, promote technologies to refine manure, and engage extensive social networks across scales that range from the farmgate to nation and beyond.Manuresheds offer a system-level strategy for recovering manure's fertilizer value. Manuresheds address nutrient imbalances and environmental and socioeconomic outcomes. Manuresheds scale from single operations to a “mega-manureshed” transecting the southeastern United States. Manureshed management supports the strategic alignment of technologies, markets, and networks.

Changing precipitation has the potential to alter nitrous oxide (N

The manureshed represents cropland needed to safely assimilate manure nutrients from an animal feeding operation. Dairy manuresheds can be contained on-farm but may need to involve additional farms that can assimilate excess nutrients. We present case studies reviewing challenges and opportunities to manureshed management in four major dairy-producing states using available information on local manuresheds. Additionally, geographic information system software was used with data from regulated Minnesota dairies to assess cropland assimilative capacities and transport needs surrounding large dairies. Manureshed requirements vary across regions, but increased import of feed and soil phosphorus accumulation constrain on-farm manure utilization across the United States. In Minnesota, a growing proportion of Jersey cattle and differences in continuous corn (Zea mays L.) vs. corn-alfafa (Medicago sativa L.) rotations contribute to the amount of land needed to absorb dairy manure nutrients. Farm-gate budgets reveal that N-based manuresheds can be contained within Idaho dairies, but P-based manuresheds extend beyond the farm. In New Mexico, relocation of surplus manure nutrients off the farm is common via informal networks, but incentives to strengthen these networks could ensure sustainable manureshed management. Evaluation of manureshed requirements in Pennsylvania is often complicated by the need for additional nutrient management planning and greater understanding of nutrient balances on the preponderance of small dairies. Nutrient imbalances with highly concentrated dairy production often lead to the need for manure transport off-farm. However, advances in herd and cropland management offer opportunities to improve on-farm nutrient efficiencies, and emerging networks and technologies promise to facilitate manure export when needed.

The proliferation of telemedicine spurred by the COVID-19 pandemic has come with a variety of human factors challenges. Such challenges include mitigating potential risks associated with the quick transition to virtual care. We identify challenges and solutions related to telemedicine security, and analyze our results using Schlarman’s People, Policy, Technology framework (2001). Our systematic literature review synthesizes gray literature (white papers, news articles, and blog posts) in addition to formal (published) literature. This methodology closes the gap between academic research and professional practice and aids in providing timely, practical insights related to cybersecurity and safety in virtual care environments. As the transition from traditional care continues to develop, we seek to better understand emerging vulnerabilities, identify crucial cyber hygiene practices, and provide insights on how to improve the safety of patient data in virtual care. Telemedicine is here to stay, and lessons learned from the pandemic are likely to remain useful.

BACKGROUND Adverse pregnancy outcomes are more common in women with hyperglycaemia. Many women have suboptimal uptake of HbA1c testing postdelivery. AIMS To compare pregnancy outcomes among multi-ethnic women with different degrees of hyperglycaemia during pregnancy, and their association with postnatal HbA1c uptake after the introduction of email reminders. MATERIALS AND METHODS A retrospective and prospective single-centre study was conducted in South Auckland in 2639 women with early gestational diabetes mellitus (GDM) (diagnosed

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

Background Type 2 Diabetes (T2DM) affects different populations disproportionately including in New Zealand (NZ), where long-term temporal trends in cause-specific clinical outcomes between Māori, European and Pacific people remain unclear. Methods Data from patients with T2DM, aged 35-84 years enrolled 1994-2018 in a NZ primary care audit programme (the Diabetes Care Support Service) were linked with national death registration, hospitalisation, pharmaceutical claims and primary care databases. Cause-specific death and hospitalisation rates were adjusted for gender, age, smoking, obesity, social-economic status and time periods by age-period-cohort models. Results Overall, 79,912 (50.6% female, mean-age 56±15 years, median follow-up 9.7 years) patients with T2DM were enrolled. For Europeans vs Māori, adjusted incidence rates ratio (IRR) and absolute risk difference /1000 person-years were 1.96 (95% CI: 1.80- 2.14) and 22.85 (19.93-25.77) for all-cause mortality, 1.93 (1.63-2.29) and 6.97 (5.14-8.80) for cardiovascular (CVD) mortality, 1.64 (1.40-1.93) and 3.08 (2.25-3.92) for cancer mortality, 1.26 (1.25-1.28) and 42.70 (41.32-44.08) for CVD hospitalisation, 1.31 (1.28-1.34) and 44.76 (42.37-47.15) for cancer hospitalisation, 2.05 (1.96-2.14) and 31.44 (29.67-33.21) for end-stage renal disease (ESRD) hospitalisation. Pacific rates were significantly less than Māori, but higher than Europeans for ESRD (IRR:1.59 (1.52-1.67)) and CVD (1.09 (1.07-1.10)) hospitalisation. Conclusions Poorer health outcomes have persisted among Māori and Pacific people with T2DM for >20 years. New policies supporting more intensive management of T2DM are urgently needed. Differences in outcomes between Māori and Pacific people warrant further research. Key messages Outcome disparities have persisted among Māori and Pacific people with T2DM for >20 years.

Perennial cover crops, also known as living mulches, have the capacity to improve soil quality, yet their effects on nitrogen (N) cycling and provisioning in organic systems are not well understood. We evaluated soil N contributions of kura clover (Trifolium ambiguum) between and within crop rows for four zone tillage approaches of varying intensity for corn (Zea mays). In 2015 and 2016, an established kura clover field was subjected to tillage treatments including no-till, traditional shank till, also known as strip-till (ST), novel, PTO-driven rotary zone till (ZT), and a combination of ST and ZT (DT; double till) in Rosemount, MN, followed by corn. An earlier planting date in 2015 (May 5, 2015 vs. May 18, 2016) contributed to a substantially lower rate of kura clover biomass at corn planting in 2015 (518 kg ha−1) compared to 2016 (3035 kg ha−1). The substantial difference in kura clover biomass contributions at tillage and planting between years appeared to govern N cycling indicators. For instance, soil inorganic N differed by tillage treatments only in 2016. After tillage, within row soil inorganic N was 68% and 106% greater than between rows for ST and DT treatments, respectively. At harvest, DT within row soil inorganic N was approximately double that of ST. We conclude that the N benefit from a legume living mulch depends on both the intensity of tillage and the amount of biomass present, and thus there may be advantages to delayed planting, particularly when used for organic production.

Kura clover (Trifolium ambiguum Bieb.) perennial living mulch is a farming practice designed to pair water quality services and row crop production. In this system, rows are mechanically or chemically killed within a perennial kura clover stand to create a suitable environment for planting a crop. However, yields are often reduced relative to conventional, fully-tilled systems. This hypothesis was tested by using a novel rotary zone tillage unit (RZT) that creates 45 cm wide tilled strips with a depth of 8 cm for each row, with rows spaced 76 cm apart. We compared RZT to three row preparation strategies that have been commonly used in living mulch systems: herbicide band kill (BK), and shank tillage (ST), also known as strip tillage. Shank tillage produced bands that were 40 cm wide and 5 cm deep. We monitored kura clover health, soil moisture & temperature, corn (Zea mays L.) emergence, corn development, and corn yield in all three row preparation strategies over two growing seasons. In 2015, corn grown in RZT plots emerged and developed faster than corn grown in ST plots, but this did not lead to a difference in grain or stover yield. However, in 2016, corn grown in RZT plots not only emerged and developed faster, but also produced 4.0 Mg ha−1 more grain and 3.5 Mg ha−1 more stover biomass than corn grown in ST and BK plots. Kura clover biomass was not affected by treatment in either year. We conclude that rotary zone tillage is a promising row preparation strategy in kura clover living mulch for corn production with minimal herbicide use.

Hospitalization has been higher among New Zealand (NZ) Māori and Pasifika than Europeans with type 2 diabetes (T2DM) for >20 years. We compared their metabolic profiles as possible drivers behind the worse outcomes. Methods: We identified four 5-year cohorts incorporating 15498 Europeans, 6445 Māori 10294 Pasifika with T2DM enrolled in 1994, 1999, 2004, 2009, to a primary care audit program. Systolic blood pressure (SBP), body mass index (BMI), HbA1c, albumin creatinine ratio (ACR), total cholesterol (TC), and triglyceride were measured at baseline, 1, 2, 3, 4 and 5-years. Mean and mean-difference (reference= European) were estimated at each time-point, with adjustment for age, gender, smoking, SE status, diabetes duration, key meds and the other measures. Multiple imputation with chained equation tackled missing values. Multivariable mixed effects modelling was used to model the repeated measurements. Results: Compared with Europeans, Māori (black) and Pasifika (grey) had higher HbA1c, ACR, and lower SBP at each time-point and within each cohort. Fig 1 shows the adjusted mean (95%CI) differences. Conclusions: NZ Māori/Pasifika under primary care management have better SBP and lipids, but worse glycemia than Europeans. This could partly explain the worse Māori/Pasifika outcomes and suggests that glycemic management is more challenging than BP/lipid management for primary care. Disclosure D. Simmons: None. D. Yu: None. R. G. Cutfield: None. B. J. Orr-walker: None. Z. Zhao: None. Y. Cai: None. C. Hotu: None. J. Baker: None. U. L. Osuagwu: None. Funding Counties Manukau Health; Middlemore Foundation

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.

Background: Angiopoietin-like protein 3 (ANGPTL3) regulates triglyceride (TG) and lipoprotein (LP) metabolism by inhibiting liver and endothelial LP lipases and reduces plasma LDL-C. In Phase 1 Study AROANG1001 (NCT03747224), single and multiple doses of RNA interference therapeutic ARO-ANG3 (100, 200, or 300 mg; n=36) in healthy volunteers substantially reduced ANGPTL3, LDL-C, and other LPs (AHA 2019) compared with placebo (n=16). Purpose: We report preliminary results following repeat doses (days 1 and 29) of ARO-ANG3 in patients with heterozygous familial hypercholesterolemia (FH) with elevated LDL-C despite statin therapy and average LDL-C of 130 mg/dL. An additional group (non-FH patients) had LDL-C > 70 mg/dL despite statin therapy. Methods: Seventeen FH patients received open-label, subcutaneous, ARO-ANG3 100 mg (n=6), 200 mg (n=6), or 300 mg (n=5). Nine non-FH, high risk patients with elevated LDL-C not at goal received either 200 mg ARO-ANG3 (n=6) or placebo (n=3) using a randomized double-blind design. Pharmacodynamic markers included serum ANGPTL3, LDL-C, TG, and others. Results: Results are reported as of 04 May 2020. In FH patients, ARO-ANG3 significantly reduced mean ANGPTL3 levels between 62-92% at week 16 in a dose-dependent manner (Table). LDL-C (23-37%) and TG (25-43%) were consistently reduced at all doses (Table). The mean percent reductions in non-FH patients for ANGPTL3 (85%), LDL-C (28%), and TG (29%) were comparable to those in FH patients, despite their initially lower LDL-C at baseline. As of 15 May 2020, there were no drug-related serious or severe adverse events (AEs) or discontinuations and most AEs were mild. The most common AEs reported in subjects receiving ARO-ANG3 were respiratory tract infection (30% of subjects) and injection site AEs (13% of subjects). Conclusions: In FH and non-FH patients, repeat doses of ARO-ANG3 significantly reduced ANGPTL3, LDL-C, and TG, with favorable safety.

Background: Hypertriglyceridemia (HTG) increases the risk of acute pancreatitis and atherosclerosis. In a Phase 1 study (NCT03783377), single subcutaneous doses of investigational RNA interference (RNAi) therapeutic ARO-APOC3 (10, 25, 50, and 100 mg; N=24) demonstrated deep and prolonged reductions in apolipoprotein C3 (APOC3) and triglycerides (TG) and increases in HDL-C in healthy volunteers with good tolerability, compared with placebo (N=16). Purpose: We report initial results of the effects of ARO-APOC3 in patients with HTG (fasting TG ≥ 300 mg/dL) or multifactorial chylomicronemia (MCM; fasting TG ≥ 880 mg/dL). Methods: Up to 40 subjects with HTG and 20 subjects with MCM will receive ARO-APOC3 or placebo on days 1 and 29. Pharmacodynamic responses include serum APOC3, TG, and other lipid parameters reported up to week 4 prior to the 2 nd dose. Results: At the data cutoff (16 March 2020), the first 4 enrolled patients with HTG and 6 enrolled patients with MCM were administered ARO-APOC3 50 mg. ARO-APOC3 substantially reduced mean (range) APOC3 levels by 96% (88-99%) in both patient groups at Week 4 (Table). ARO-APOC3 substantially reduced mean (range) TG by 78% (67-87%) in HTG patients and by 92% (90-95%) in MCM patients at Week 4. Three of 4 HTG patients and 3 of 6 MCM patients had TG levels below 150 mg/dL. All MCM patients had TG ≤ 500 mg/dL. To date, ARO-APOC3 has been generally well tolerated with no reports of treatment-related serious or severe adverse events. Two of the 6 unblinded MCM patients experienced a transient ALT elevation to >3X ULN that returned to approximate pre-dose baseline by Day 113. Conclusions: Preliminary results indicate that a single dose of ARO-APOC3 reduces APOC3 levels by >90% and TG by ~80% 4 weeks after treatment in patients with HTG and MCM. The magnitude of treatment effect was similar in both populations and ARO-APOC3 had a favorable safety profile. Using RNAi to silence expression of APOC3 appears promising for treating patients with HTG and MCM.

Background: Incidents that threaten service user and staff safety occur frequently in adult mental health inpatient settings, often resulting in restrictive practices such as restraint and seclusion. These carry significant risks, including physical and psychological harms to service users and staff, as well as costs to the NHS. Numerous complex interventions have been developed which aim to reduce the use of restrictive practices. Aims: The aims were to identify, standardise and report the effectiveness of components of interventions that seek to reduce restrictive practices in adult mental health inpatient settings, using the Behaviour Change Technique taxonomy. Methods: A systematic mapping review of literature identified in health and social care research databases and unpublished sources (including social media) was undertaken. Records were quality appraised using the MMAT. Records of interventions to reduce any form of restrictive practice used with adults in mental health services were included. The resulting dataset for extraction was guided by WIDER, Cochrane and theory coding guidelines. The BCT taxonomy was systematically applied to each identified intervention.Results: The final dataset comprised 175 records reporting 150 interventions, 109 of which had been formally evaluated. The most common intervention targets were seclusion and/or restraint reduction. The most common evaluation approach was a non-randomised design. There were only six randomised controlled trials. The number of BCTs identified per intervention ranged from 1-33 (mean:8). The most common strategy was staff training. BCTs from 14 of a possible 16 clusters were detected. Over two thirds of the BCTs mapped onto four of the 14 clusters: ‘Goals and planning’; ‘Antecedents’; ‘Shaping knowledge’; ‘Feedback and monitoring’. Those BCTs which were found in all the interventions were similar to those found in those interventions which demonstrated statistically significant effects. Conclusions: Studies of interventions to reduce restrictive practices appear to be diverse quality. Interventions tended to contain multiple components delivered in multiple ways. Further research could enhance the evidence base prior to future commissioning decisions. Separate testing of individual procedures, for example, audit and feedback, could ascertain the more effective intervention components and improve understanding of content and delivery. Registration: The study is registered as PROSPERO 2018 CRD42018086985 Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42018086985

Background\ud Type 2 diabetes affects Indigenous and non-European populations disproportionately, including in New Zealand, where long-term temporal trends in cause-specific clinical outcomes between Māori, Pacific, and European people remain unclear. We aimed to compare the rates of mortality and hospital admission between Māori, Pacific, and European patients with type 2 diabetes in Auckland, New Zealand, over a period of 24 years.\ud Methods\ud In this retrospective, population-based, longitudinal cohort study, we identified a cohort of patients (aged 35–84 years) with type 2 diabetes enrolled between Jan 1, 1994, and July 31, 2018, to the primary care audit programme, the Diabetes Care Support Service (DCSS) in Auckland, New Zealand. Patients with type 1 diabetes, prediabetes, and gestational diabetes were excluded. We linked data from the DCSS with national death registration, hospital admission, pharmaceutical claim, and socioeconomic status databases. Patients were followed up until death or July 31, 2018 (date of last enrolment to the DCSS). Incident clinical events (all-cause mortality, cardiovascular mortality, cancer mortality, cardiovascular hospital admission, cancer hospital admission, and end-stage renal disease hospital admission) were identified. Event rates were stratified by ethnic group, age group, sex, socioeconomic status, and time period (

Aims: Despite current treatment strategies, gestational diabetes mellitus (GDM) remains a major risk factor for pregnancy complications. We examined whether the HbA1c measured at the time of oral glucose tolerance test (OGTT) predicts residual risk of adverse outcomes in women with treated GDM. Methods: Women with GDM (defined using the New Zealand criteria) enrolled in the Diabetes in Pregnancy Registry in South Auckland, New Zealand at ≥ 20 weeks gestation were included. Glycaemic targets used were fasting ≤5.0 mmol/l and 2-hour post-meal ≤6.7 mmol/l. Results: Of the 1403 women enrolled, 304 (21.7%) had an HbA1c 41-49 mmol/mol (5.9-6.6%). Women with higher HbA1c were significantly older, with higher BMI and fasting and 2-hour OGTT values. They were more likely to be multiparous, of Pacific ethnicity, and have a family history of diabetes. After adjusting for known risk factors, higher HbA1c was associated with increased risk of large for gestational age (LGA) babies (odds ratio (OR) 2.08 (1.47-2.93)) and preeclampsia (OR 2.09 (1.34-3.29)). The OGTT fasting glucose was predictive of LGA (OR 1.61 (1.17-2.21)), but not the 2-hour value (OR 1.12 (0.98-1.28)). The areas under the receiver operating characteristic curves for predicting LGA and preeclampsia by HbA1c, OGTT fasting, OGTT 2-hour, and 1-hour 50g polycose test were: LGA, 0.58 (0.51-0.65), 0.66 (0.59-0.73), 0.45 (0.37-0.52), and 0.59 (0.51-0.66) respectively; preeclampsia, 0.66 (0.57-0.75), 0.58(0.48-0.67), 0.46 (0.35-0.56), and 0.52 (0.42-0.62) respectively. Conclusions: HbA1c, fasting, and 1-hour glucose at GDM diagnosis predict residual adverse outcomes in treated women with late GDM. Studies are needed to test whether earlier treatment, or targeting the 1-hour post-prandial glucose can reduce this residual risk. Disclosure D. Simmons: None. J. Immanuel: None. C. Eagleton: None. J. Baker: None.

This paper compares legislation on clinical research conducted on patients subject to coercion in the Scandinavian countries and the UK, examines it from a human rights perspective, and problematizes the Danish legal model as the only one employing a total ban on this kind of research. Reference is made to the consequences to evidence-based psychiatric care improvements and international ethical principle statements generally entitling psychiatric patients to treatment under similar ethical and scientific conditions as patients with other illnesses, given the absolute premise that the patient does not object to research participation and always retains the right to withdraw.

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

The broad variability of Cucumis melo (melon, Cucurbitaceae) presents a challenge to conventional classification and organization within the species. To shed further light on the infraspecific relationships within C. melo, we compared genotypic and metabolomic similarities among 44 accessions representative of most of the cultivar-groups. Genotyping-by-sequencing (GBS) provided over 20,000 single-nucleotide polymorphisms (SNPs). Metabolomics data of the mature fruit flesh and rind provided over 80,000 metabolomic and elemental features via an orchestra of six complementary metabolomic platforms. These technologies probed polar, semi-polar, and non-polar metabolite fractions as well as a set of mineral elements and included both flavor-and taste-relevant volatile and non-volatile metabolites. Together these results enabled an estimate of “metabolomic/elemental distance” and its correlation with the genetic GBS distance of melon accessions. This study indicates that extensive and non-targeted metabolomics/elemental characterization produced classifications that strongly, but not completely, reflect the current and extensive genetic classification. Certain melon Groups, such as Inodorous, clustered in parallel with the genetic classifications while other genome to metabolome/element associations proved less clear. We suggest that the combined genomic, metabolic, and element data reflect the extensive sexual compatibility among melon accessions and the breeding history that has, for example, targeted metabolic quality traits, such as taste and flavor. Fil: Moing, Annick. Universite de Bordeaux; Francia Fil: William Allwood, J.. The James Hutton Institute; Reino Unido Fil: Aharoni, Asaph. Weizmann Institute Of Science Israel; Israel Fil: Baker, John. Rothamsted Research; Reino Unido Fil: Beale, Michael H.. Rothamsted Research; Reino Unido Fil: Ben-Dor, Shifra. Weizmann Institute Of Science Israel; Israel Fil: Biais, Benoît. Universite de Bordeaux; Francia Fil: Brigante, Federico Iván. Max Planck Institute Of Molecular Plant Physiology; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; Argentina Fil: Burger, Yosef. Agricultural Research Organization Of Israel; Israel Fil: Deborde, Catherine. Universite de Bordeaux; Francia Fil: Erban, Alexander. Max Planck Institute Of Molecular Plant Physiology; Alemania Fil: Faigenboim, Adi. Agricultural Research Organization Of Israel; Israel Fil: Gur, Amit. Agricultural Research Organization Of Israel; Israel Fil: Goodacre, Royston. University of Liverpool; Reino Unido Fil: Hansen, Thomas H.. Universidad de Copenhagen; Dinamarca Fil: Jacob, Daniel. Universite de Bordeaux; Francia Fil: Katzir, Nurit. Agricultural Research Organization Of Israel; Israel Fil: Kopka, Joachim. Max Planck Institute Of Molecular Plant Physiology; Alemania Fil: Lewinsohn, Efraim. Agricultural Research Organization Of Israel; Israel Fil: Maucourt, Mickael. Universite de Bordeaux; Francia Fil: Meir, Sagit. Weizmann Institute Of Science Israel; Israel Fil: Miller, Sonia. Rothamsted Research; Reino Unido Fil: Mumm, Roland. Wageningen University & Países Bajos Fil: Oren, Elad. Agricultural Research Organization Of Israel; Israel Fil: Paris, Harry S.. Agricultural Research Organization Of Israel; Israel Fil: Rogachev, Ilana. Weizmann Institute Of Science Israel; Israel Fil: Rolin, Dominique. Universite de Bordeaux; Francia Fil: Saar, Uzi. Agricultural Research Organization Of Israel; Israel Fil: Schjoerring, Jan K.. Universidad de Copenhagen; Dinamarca Fil: Tadmor, Yaakov. Agricultural Research Organization Of Israel; Israel Fil: Tzuri, Galil. Agricultural Research Organization Of Israel; Israel Fil: de Vos, Ric C. H.. Wageningen University & Países Bajos Fil: Ward, Jane L.. Rothamsted Research; Reino Unido Fil: Yeselson, Elena. Agricultural Research Organization Of Israel; Israel Fil: Hall, Robert D.. Wageningen University & Países Bajos Fil: Schaffer, Arthur A.. Agricultural Research Organization Of Israel; Israel

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.

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

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.