Artificial (tile) drainage systems are extensively implemented across the U.S. Midwest to enhance crop production in poorly drained soils; however, they also pose environmental challenges by significantly altering nitrogen fluxes within agricultural landscapes. In response, sustainable intensification strategies seek to increase agricultural productivity while reducing environmental impacts, often through improved management practices such as cover cropping and conservation tillage. Effectively evaluating the trade-offs and synergies of agricultural management practices demands advanced modeling tools capable of representing coupled biogeochemical and hydrological processes across diverse spatial and temporal scales. This study presents the first application of an enhanced version of the Soil and Water Assessment Tool (SWAT), integrated with Century/DayCent-based biogeochemical modules, to simulate both nitrate (NO3-) loss and nitrous oxide (N2O) fluxes in a tile-drained corn-soybean system. The model was applied to long-term field data (2004-2010) from an Iowa site with two treatments: with and without winter rye cover crops. With careful calibration, the model reproduced tile discharge and crop yields well and captured the direction and magnitude of cover-crop reductions in NO3- losses. However, interannual variability in NO3- export and event-scale N2O peaks remained difficult to reproduce, likely due to limited sampling frequency and structural constraints in soil hydrology, solute transport, and vertical resolution. The model simulated a similar to 41 % reduction in NO3- leaching with cover crops, close to the observed similar to 50 %. In contrast, effects on average daily N2O flux varied by year and conditions, ranging from -30-67 % (observed: -24-28 %). These results support the model's use for assessing long-term nitrogen-loss responses to cover crops in tile-drained systems, while highlighting priorities for improving event-scale biogeochemical simulations.

Cereal rye (Secale cereale L.) as winter cover crop can reduce nitrate (NO3) loss through subsurface tile drainage under corn (Zea mays L.)-soybean (Glycine max L.) production system. The Decision Support System for Agrotechnology Transfer (DSSAT) model can simulate processes of subsurface drainage flow and NO3 loss to artificial subsurface drainage, but few model evaluations with field-measured data are available. The objective of this study was to evaluate the DSSAT model for simulating crop yield and flow and NO3 losses to tile drainage in a corn-soybean rotation with (CC) and without (NCC) winter rye cover crop in Central Iowa during the 2002-2010 growing seasons. Simulations successfully reproduced the cumulative (9 years) subsurface drainage flow, observed and predicted values were 331 cm and 309 cm for NCC and, 323 cm and 284 cm for CC. Similarly, for cumulative NO3 loss in tile flow, observed and predicted values were 444 kg N ha-1 and 459 kg N ha-1 for NCC and 187 kg N ha-1 and 196 kg N ha-1 for CC; simulated and observed indicated CC treatment could reduce NO3 in drainage by 57 %. Early (-10 d) and late (+ 10 d) termination did not influence main crop yield and tile NO3 loss. Simulation of the long-term (23-years) influence of CC suggest that tile flow and NO3 load could be reduced by 15 % and 73 %, respectively for a corn-soybean production system in central Iowa.

Agroecosystems comprise environmental, economic, and social components with complex interactions that affect systemwide performance. Attempts to describe or predict how agroecosystems respond to management must account for these interconnected components, so approaches that are limited to a single discipline cannot capture the complexities necessary for a holistic understanding of performance. The goal of this research is to develop a system dynamics (SD) modeling framework that can provide quantitative measures of consequences of management on each component of an agroecosystem. A SD framework is proposed with a description of model components, as well as an illustration of methodological steps to evaluate model performance through calibration, validation, and sensitivity testing. The model structure is based on a complex web of (i) stocks that describe the system's state, (ii) flows that represent the direction and rate of change, and (iii) auxiliary parameters that assign quantitative values to each component. The capacity of the model to adequately evaluate agroecosystem response is demonstrated using a case study investigating environmental, economic, and social indicators while manipulating multiple management practices, including cover crops, tillage, and integration of crop and livestock operations. Importantly, the SD model identified tradeoffs in the three indicators that accurately reflect producer experiences when making management decisions. For example, the integration of cash crops, cover crops, and livestock clearly improves economic and environmental endpoints while negatively impacting social quality with reduction in leisure time. These findings suggest the SD modeling framework provides a viable approach for the quantitative evaluation of management interventions that can be adapted to a range of complex agroecosystems.

The inclusion of a harvested winter cereal before soybean [ Glycine max (L.) Merr.] can increase productivity and sustainability of a cereal‐soybean rotation. Still, literature disagrees on proper seeding and fertilizer rates of the winter cereal for efficient production of both crops in the rotation. This study aimed to evaluate rye ( Secale cereale L.) spring green ground cover, biomass production, and nitrogen (N) accumulation in a rye‐soybean rotation, using three seeding rates (20, 40, and 60 kg ha −1 ) and three N rates (0, 30, and 60 kg N ha −1 ) from 2021 to 2023 in central Iowa. Remote sensing was used to assess rye growth. Green ground cover was up to 42% higher in the highest seeding rate (60 kg ha −1 ). Conversely, rye biomass production was not affected by seeding or N rates and averaged 3.0 ± 1.1 and 4.9 ± 1.3 Mg ha −1 in the first and second growing seasons, respectively. Rye N accumulation increased 0.13 and 0.51 kg N ha −1 for each kg N applied in the first and second growing seasons, respectively. Soybean yield was similar among treatments but 19%–38% lower than the county average production, especially in the second growing season due to limited precipitation. This study provides new evidence that rye biomass production can be optimized with low inputs, whereas higher seeding rates increase spring green ground cover. However, because of reduced soybean yields, further studies are needed to evaluate rye harvest time and alternative soybean varieties to optimize soybean production after rye for central Iowa conditions.

Total dissolved nitrogen (TDN) is composed of dissolved inorganic nitrogen (DIN) and dissolved organic nitrogen (DON). DON is the N-containing component of dissolved organic matter (DOM) and part of the biologically reactive N pool in aquatic ecosystems that can degrade water quality in N-sensitive waters. Evidence suggests that DON may be important in triggering harmful algal blooms, particularly the DON from synthetic urea fertilizers. TDN measurements therefore contribute to an estimate of the N most available to phytoplankton. DIN export from agroecosystems is reasonably well characterized, but the factors that regulate spatial and temporal patterns of DON are not as well understood. Although the export of DON into groundwater has received recognition for more than 100 years and the contribution of DON to total nitrogen (TN) is often significant, leaching losses of N from agricultural systems are often assumed to be dominated by DIN and uninfluenced by DON. The most widely recognized N digestion method is total Kjeldahl N (TKN), whereby organic N is converted to ammonia-N, followed by titrimetric or colorimetric detection. The recommended measurement of TDN at moderate to high concentrations (i.e., >0.5 mg N/L) uses the high-temperature combustion and chemilumniscent detection method.

Snow plays an important role in the hydrological and energy cycles. In agroecosystems, snow may be a beneficial source of plant-available water, a harmful source of flooding, a source of irrigation water supply (i.e., mountain snowpack filling reservoirs), and a determinant of seasonal timing, such as the onset of the planting or growing seasons. Key snow metrics include snowfall (precipitation amount), snow water equivalent (SWE), and snow depth. Depending on the application, we may be interested in the snowfall rate of a particular storm event (e.g., 60 mm of water equivalent fell overnight, and the weight damaged crop trees) or the total amount over a season (e.g., 400 mm of total winter snowfall will provide moist spring soil). Snowfall measurement is in some ways similar to rainfall measurement, to quantify the rate (e.g., per hour or day) of precipitation through a horizontal plane (opening of a precipitation gauge). However, it is usually necessary to melt the snow within the gauge. Snowfall measurement is also susceptible to the effects of wind, which can accelerate snow laterally past the gauge opening, resulting in “undercatch.” Snow depth is the most readily observable property, requiring only a graduated stake or other simple measurement devices. However, depth does not directly convey the water content. Snow depth may increase because of new snowfall or deposition by wind. Snow depth at a point may decrease because of settling over time (often within hours), compaction by overlying snow, melting, sublimation (evaporation of ice crystals), or scouring by wind. In addition to weather, these processes are regulated by local physiographic factors, including topography (slope and aspect with regard to sun and wind), and by trees, crops, or other vegetation. Since these factors may result in high variability of snow depth over short distances, snow depth measurements in many locations at a given time point are often desirable to assess conditions in a watershed, field, or plot. Snow water equivalent is usually considered the most important metric of snowpack since it represents the water available upon melting. SWE is the product of depth and density. Density is affected by similar factors as snow depth as well as age. Freshly fallen snow often has low density that increases with time on the ground as snow crystals lose their fine edges through friction, compaction, and partial melting. This protocol describes the measurement of: ●Snow depth ●Snow water equivalent ●Snowfall ●Remote sensing and other long-term/large-scale snow products

Agricultural systems evolve from the interactions of climate, crops, soils, management practices (e.g., tillage, cover crops, nutrient management), and economic risks and rewards. Alternatives to the corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] (C-S) cropping systems that dominate in the US Midwest may provide more sustainable use of resources, reduce the documented environmental impacts of current C-S systems, and improve production efficiency and ecosystem services. Innovative management practices are needed to offer producers options to increase farm resilience to variable weather conditions and offset negative environmental impacts. In response to this need, the Upper Mississippi River Basin Long-Term Agroecosystem Research network site at Ames, IA, established a cropland experiment in 2016 to investigate an alternative crop management system that includes reduced tillage, cover crops, and right source, right rate, right time, and right place (4R) nitrogen (N) management. The experimental site is located on the Iowa State University Kelley Research Farm in Boone County, IA. Crop, soil, air, and tile drainage water measurements are made throughout the year using published methods for each agronomic and environmental metric. Our goal is to provide quantitative information to farmers, consultants, agribusiness partners, and state and federal agencies to help guide decisions on the effective use of alternative management practices. Future changes in experimental treatments will adopt a knowledge co-production approach whereby researchers and stakeholders will work collaboratively to identify problems, implement research protocols, and interpret results.

The agricultural sector is responsible for substantial amounts of greenhouse gas emissions that exacerbate climate change. Such greenhouse gas emissions from upland crops are difficult to abate because they are dominated by nitrous oxide (N2O) production from soil processes. Strategies to reduce these emissions focus on N fertilizer management, and there is a widespread assumption that legume crops, which do not receive N fertilizer, emit little N2O. Here we show that this assumption is incorrect; approximately 40% of N2O emissions from the most extensive cropping system in North America-the maize-soybean rotation-occur during the soybean phase. Yet, due to the lack of N fertilizer input, opportunities for emissions abatement from the soybean phase are unclear. Using models of cropping systems, we developed a strategy that combines cover-crop management and earlier planting of extended growth soybean varieties to reduce emissions from soybean production by 33%. These practices, which complement N fertilizer management in maize, are widely accessible and represent an immediate, climate-smart strategy to reduce nitrous oxide emissions from soybean production, thus not only contributing to climate-change mitigation but also maintaining productivity while adapting to changing weather patterns. Soil processes involved in agricultural practices emit considerable levels of nitrous oxide, which detrimentally contribute to climate change. This study explores strategies to reduce nitrous oxide emissions while maintaining crop productivity in the US maize-soybean rotational cropping system.

Agricultural systems evolve from the interactions of climate, crops, soils, management practices (e.g., tillage, cover crops, nutrient management), and economic risks and rewards. Alternatives to the corn ( Zea mays L.)–soybean [ Glycine max (L.) Merr.] (C–S) cropping systems that dominate in the US Midwest may provide more sustainable use of resources, reduce the documented environmental impacts of current C–S systems, and improve production efficiency and ecosystem services. Innovative management practices are needed to offer producers options to increase farm resilience to variable weather conditions and offset negative environmental impacts. In response to this need, the Upper Mississippi River Basin Long-Term Agroecosystem Research network site at Ames, IA, established a cropland experiment in 2016 to investigate an alternative crop management system that includes reduced tillage, cover crops, and right source, right rate, right time, and right place (4R) nitrogen (N) management. The experimental site is located on the Iowa State University Kelley Research Farm in Boone County, IA. Crop, soil, air, and tile drainage water measurements are made throughout the year using published methods for each agronomic and environmental metric. Our goal is to provide quantitative information to farmers, consultants, agribusiness partners, and state and federal agencies to help guide decisions on the effective use of alternative management practices. Future changes in experimental treatments will adopt a knowledge co-production approach whereby researchers and stakeholders will work collaboratively to identify problems, implement research protocols, and interpret results.

Nitrate-N losses from artificially drained agricultural fields lead to an acceleration of eutrophication and hypoxia in aquatic ecosystems. Adoption of conservation practices, such as cover crops and woodchip bioreactors, can significantly reduce nitrate losses and improve water quality. However, the long-term performance of these conservation practices and their effect on water quality has not been sufficiently quantified. A replicated plot experiment was initiated to quantify the long-term effectiveness of such conservation practices on nitrate-N removal rates from subsurface tile drains. Maize (Zea mays L.) and soybean (Glycine max L. Merr.) were grown with three different treatments: 1) Control: no-till crop production, 2) no-till with a winter rye (Secale cereale L.) cover crop (RC), and 3) no-till with an in-situ woodchip denitrification wall (DW) where trenches were excavated parallel to the tile on both sides and filled with woodchips to serve as additional carbon sources to increase denitrification. During a period of 19 years (2002-2020), all three treatments received the same annual N fertilization in maize years with rates ranging from 168 to 247 kg N/ha, depending on the production year. Averaged across the 19 years, the RC and DW treatments reduced N leaching by 59% and 58%, respectively, compared with the Control. Both conservation practices were effective for the duration of the study, and both were affected by annual rainfall. Effectiveness of RC increased in dry years, while effectiveness of DW increased in wet years. Overall, treatment and annual precipitation had the greatest effects on annual N loss in drainage. This suggests that the unpredictability of rainfall may make it difficult to consistently reduce nitrate losses in drainage, but it does not diminish the effectiveness of conservation practices. Minimal or no yield penalty was observed following adoption of cover crop or in-situ woodchip bioreactor conservation practices, which is important for their wider acceptance by the agriculture community.

Highlights Spring wheat yields increase with high temperatures and the minimal impact of increased CO 2 . At high temperatures and increased CO2, spring barley yields increase; yields decrease at only high temperatures. Potato and sugarbeet yields decrease with climate change. Climate change had little impact in soil nitrogen processes. Abstract. Agricultural crops grown in the irrigated semi-arid region of southern Idaho account for almost two-thirds of the median household income in the region. The impacts of climate change on cropping systems and the availability of water for irrigation would be a serious challenge for the state's economic dependence on agriculture. The objective of the study was to simulate the future impact of climate change on a crop rotation of spring wheat-potato-spring barley-sugarbeet grown in the semi-arid region of southern Idaho using conventional management practices and a high dairy manure application. The Root Zone Water Quality Model (RZWQM2) simulations used bias-corrected and spatially disaggregated projections from the World Climate Research Program’s coupled model inter-comparison project phase 5 to generate 40 GCM projections for the time from 2071-2099. The 28-yr scenarios were designed to simulate the impact of temperature and CO2 regimes on crop production, soil nitrogen mineralization, nitrogen seepage, deep seepage of water, and nitrous oxide emissions. Data from a field experiment in southern Idaho with conventional fertilizer practices and annual applications of 52 Mg ha-1 dairy manure with a crop rotation of spring wheat-potato-spring barley-sugarbeet were used in the RZWQM2 simulations. Results were compared to a baseline scenario of conventional management practices, historical weather data, and ambient CO2. Spring wheat yield increased by 22% and 16% for manure and fertilizer treatments, respectively, compared to the baseline scenario. Using the same comparison, potato tuber yield decreased by 65% and 60% in the manure and fertilizer treatments, respectively, for the highest temperature and CO2 increase scenarios. Spring barley produced a 33% higher yield with increased temperature and CO2. However, yield decreased when temperature increased, but CO2 remained unchanged. Sugarbeet yields decreased by 16% and 18% for manure and fertilizer treatments, respectively, compared to the baseline scenario. Nitrogen mineralization, N seepage from the profile, and nitrous oxide emissions were strongly influenced by the manure applications, and there was little simulated impact of climate change on these processes. These simulation results indicate that genetic enhancements or alternative management will be needed to maintain potato and sugar beet production levels in semi-arid areas, while spring barley and wheat yields may increase, assuming adequate irrigation water supplies are available. Keywords: Nitrogen Mineralization, Potato, RZWQM2, Spring Barley, Spring Wheat, Sugarbeet.

Highlights Saturated buffers redistribute tile drainage water below riparian buffers to reduce nitrate-nitrogen loading. NRCS Conservation Practice Standard 604 guides saturated buffer design in the USA. Annual edge-of-field nitrate-nitrogen loss reductions averaged 46 ± 24% and 9.4 ± 5.9 kg N/ha/y. Further research on design, siting, and mechanisms will enhance performance. Abstract. It is a pivotal time in the development of saturated buffers as a conservation drainage practice. Field data have demonstrated that this practice can effectively reduce nitrate loads in subsurface drainage. The compilation and assessment of current knowledge for this relatively new practice is timely to help identify future opportunities. This review summarizes the state of the science for saturated buffers in the US within the context of this special collection’s emphasis on performance and cost. Suggested research areas are identified to improve understanding of saturated buffer function and performance and to refine design processes and criteria to accelerate adoption. As currently designed, saturated buffers removed an average of 46 ± 24% (mean ± sd) of the N load that would have otherwise entered receiving waters (9.4 ± 5.9 kg N removed/ha-y; n = 30 site-years). Cost efficiencies, which generally trended around $3 to $5/kg N removed per year, were considered relatively efficient compared to similar nitrate removal practices (range: $1.20 to $9.20/kg N/y), with planning level costs between $25 and $66/ha treated/y. As adoption is scaled, engineering design costs need to be considered unless the design model can be simplified. Future research should refine design processes, management, and siting criteria to facilitate scaled adoption for water quality goals. Additional studies on nutrient cycling within saturated buffers are needed to fill gaps about nitrogen and phosphorus dynamics and the role of buffer vegetation. Saturated buffers have significant nitrate reduction potential for tile-drained landscapes, but design adaptations may be needed to facilitate adoption in varied landscapes. Keywords: Denitrification, Edge-of-Field, Nitrate, Nonpoint-source pollution, Saturated riparian buffer, Subsurface drainage, Tile drainage, Water quality.

Agriculture is a major source of nitrous oxide (N2O) emissions into the atmosphere. However, assessing the impacts of agricultural conservation practices, land use change, and climate adaptation measures on N2O emissions at a large scale is a challenge for process-based model applications. Here, we integrated six N2O emission algorithms for the nitrification processes and seven N2O emission algorithms for the denitrification process into the Soil and Water Assessment Tool-Carbon (SWAT-C). We evaluated the different combinations of methods in simulating N2O emissions under corn (Zea mays L.) production systems with various conservation practices, including fertilization, tillage, and crop rotation (represented by 14 experimental treatments and 83 treatment-years) at five experimental sites across the U.S. Midwest. The SWAT-C model exhibited wide variability in simulating daily average N2O emissions across treatment-years with different method configurations, as indicated by the ranges of R2, NSE, and BIAS (0.04-0.68, -1.78-0.60, and -0.94-0.001, respectively). Our results indicate that the denitrification process has a stronger impact on N2O emissions than the nitrification process. The best performing N2O emission algorithms are those rooted in the CENTURY model, which considers soil pH and respiration effects that were overlooked by other algorithms. The optimal N2O emission algorithm explained about 63% of the variability of annual average N2O emissions, with NSE and BIAS of 0.60 and -0.033, respectively. The model can reasonably represent the impacts of agricultural conservation practices on N2O emissions. We anticipate that the improved SWAT-C model, with its flexible configurations and robust modeling and assessment capabilities, will provide a valuable tool for studying and managing N2O emissions from agroecosystems.

Cover crops (CCs) can reduce nitrogen (N) loss to subsurface drainage and can be reimagined as bioenergy crops for renewable natural gas production and carbon (C) benefits (fossil fuel substitution and C storage). Little information is available on the large-scale adoption of winter rye for these purposes. To investigate the impacts in the North Central US, we used the Root Zone Water Quality Model to simulate corn-soybean rotations with and without winter rye across 40 sites. The simulations were interpolated across a five-state area (IA, IL, IN, MN, and OH) with counties in the Mississippi River basin, which consists of ∼8 million ha with potential for rye CCs on artificially drained corn-soybean fields (more than 63 million ha total). Harvesting fertilized rye CCs before soybean planting in this area can reduce N loads to the Gulf of Mexico by 27% relative to no CCs, and provide 18 million Mg yr ^−1 of biomass-equivalent to 0.21 EJ yr ^−1 of biogas energy content or 3.5 times the 2022 US cellulosic biofuel production. Capturing the CO _2 in biogas from digesting rye in the region and sequestering it in underground geologic reservoirs could mitigate 7.5 million Mg CO _2 yr ^−1 . Nine clusters of counties (hotspots) were identified as an example of implementing rye as an energy CC on an industrial scale where 400 Gg yr ^−1 of rye could be sourced within a 121 km radius. Hotspots consisted of roughly 20% of the region’s area and could provide ∼50% of both the N loss reduction and rye biomass. These results suggest that large-scale energy CC adoption would substantially contribute to the goals of reducing N loads to the Gulf of Mexico, increasing bioenergy production, and providing C benefits.

Corn (Zea mays L.) stover is an abundant biomass source with multiple end-uses including cellulosic biofuel production. However, stover removal may increase soil compaction by reducing organic matter inputs and increasing vehicle loads during harvest. While numerous studies have reported stover removal impacts on soil physical quality, few have assessed the role played by traffic compaction. Our objective was to quantify subsurface soil compaction after 13 years of chisel plow versus no-till management and no, moderate (3.5 +/- 1.1 Mg ha(-1) year(-1)), or high (5.0 +/- 1.7 Mg ha(-1) year(-1)) stover harvest rates. Penetration resistance was measured in most- and least-trafficked interrow spaces. Chisel plowed plots with moderate and high levels of stover removal had higher penetration resistance in trafficked areas relative to least-trafficked areas, whereas there was no evidence of traffic compaction when stover was retained. Traffic compaction did not negatively impact yields, which were greater with high levels of stover removal compared to no removal. The no-till practice led to very small increases in penetration resistance with wheel traffic and had no evidence of increased compaction with residue removal. This lack of traffic compaction indicated soils under no-till practice have a higher load-bearing capacity than soils under chisel plow practice. Overall, there were no yield-limiting effects of tillage practice or stover removal, and no evidence of soil compaction below the plow layer, suggesting stover removal with both tillage practices can be effectively employed without detrimental effects on plant or soil health.

A shortcoming of the RZ-SHAW model (A hybrid version of Root Zone Water Quality Model and The Simultaneous Heat and Water Model) is that it cannot simulate the plastic mulching technology which is widely used in arid areas. Our objectives in this study were to develop RZ-SHAW to include a new plastic module, and to evaluate the model's performance over three years of maize (Zea mays L.) production in China. A new plastic module was added to compute changes in the shortwave and longwave radiation transfer, turbulent heat and vapor transfer from the surface, and the energy and water balances in the system associated with a plastic mulch layer. The modified RZ-SHAW model can adequately simulate soil water (0.017 cm(3) cm(-3) <= RMSE <= 0.030 cm(3) cm(3)) and capture the evaporation reduction and transpiration increase under plastic mulch. The model over-estimated the increased soil temperatures under plastic mulch (2.3. over the 100-cm profile) compared to the measured data (1.4.). Overall, the revised RZ-SHAW model adequately simulated soil water and heat exchange under plastic mulch conditions. The modified RZ-SHAW model can be used as an effective decision tool for management optimization in plastic mulched cropland.

Abstract Double-cropping winter rye cover crops (CC) with soybean in the North Central US could help with the global effort to sustainably intensify agriculture. Studies addressing the management of these systems are limited. Therefore, a field study was conducted from 2017 to 2019 in Central Iowa, US to evaluate winter rye CC biomass production, aboveground N accumulation, estimated economics, estimated within-field energy balance and estimated greenhouse gas (GHG) emissions under three N application rates (0, 60, 120 kg N ha−1) and three planting methods (pre- and post-harvest broadcast and post-harvest drilling). Averaged over N rates, all planting methods resulted in >5.0 Mg ha−1 year−1 rye aboveground biomass dry matter. Averaged over the 2-year study and compared with unfertilized treatments, applying 60 kg N ha−1 produced 1.1 Mg ha−1 more aboveground biomass (6.1 vs 5.0 Mg ha−1), accumulated 30 kg ha−1 more N in aboveground biomass (88 vs 58 kg N ha−1), and led to 20 GJ ha−1 more net energy. Biomass production was not significantly higher with 120 kg N ha−1 compared with the 60 kg N ha−1 rate. Even when accounting for an estimated 0.75 Mg ha−1 of above ground rye biomass left in the field after harvesting, more N was removed than applied at the 60 kg N ha−1 rate. The minimum rye prices over the 2-year study needed for double-cropping winter rye CC to be profitable (breakeven prices) averaged $117 and $104 Mg−1 for the 0 and 60 kg N ha−1 rates, which factors in estimated soybean yield reductions in 2019 compared with local averages but not off-site transportation. GHG emissions were estimated to increase approximately threefold between the unfertilized and 60 kg N ha−1 rates without considering bioenergy offsets. While environmental tradeoffs need further study, results suggest harvesting fertilized rye CC biomass before planting soybean is a promising practice for the North Central US to maximize total crop and net energy production.

Sustainable intensification strategies seek to increase production while decreasing the environmental footprint of agricultural systems. In the Upper Mississippi River Basin, relay cropping of a winter oilseed crop between corn and soybean has gained interest for its potential to increase total yields and revenue while providing the environmental benefits of winter cover. In a six-year field study in central Iowa, a basic corn-soybean rotation was compared with a corn-winter camelina-soybean relay cropping system for crop yields, nitrate losses in drainage, and nitrous oxide (N2O) emissions from soil. Despite filling a niche as an overwintering crop with the potential to assimilate soil nitrogen, nitrate loads in drainage were not reduced in the camelina relay cropping system. Over the course of the study, management changes to support the camelina crop tripled cumulative N2O emissions during the camelina-soybean phase, from 3.57 kg N2O-N ha-1 in the basic corn-soybean rotation to 12.2 kg N2O-N ha-1 in the camelina relay system. Most of the increased emissions in the camelina system were associated with peak emissions events following tillage and starter fertilizer application in the fall and during the spring thaw, which may point to risks of exacerbating greenhouse gas emissions during fall management of a relay crop. Corn and soybean yields were decreased in the relay cropping system by 9.8 % and 23.3 %, respectively, as a result of management changes to the system and interspecific competition. However, combined grain dry weight of soybean and the camelina oilseed crop were similar to the soybean yield in the basic corn-soybean rotation. These findings highlight the need for careful evaluation and optimization of sustainable intensification systems to ensure environmental and production goals are met.