In this paper, we advanced the concept of nitrogen-use efficiency (NUE) of cropping systems by linking current crop- and soil-based approaches into a system NUE. We compared this new index to ...traditional metrics, and show how its application can yield insights about N cycling dynamics and tradeoffs.
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•Developed a novel systems NUE (sNUE) by synthesizing crop and soil-based approaches.•The maize-soybean rotation removed 87% of N inputs in grains.•45% of the N losses were due to inefficient N input use; the rest to poor N retention.•Balancing production-environmental tradeoffs resulted on a yield penalty of 5–7%.•sNUE was relatively more stable and less correlated to other metrics.
Increasing nitrogen (N)-use efficiency (NUE) is key to improving crop production while mitigating ecologically-damaging environmental N losses. Traditional approaches to assess NUE are principally focused on evaluating crop responses to N inputs, often consider only what happens during the growing season, and ignore other means to improve system efficiency, such as by tightening the cycling of soil N (e.g. with N scavenging cover crops). As the goals of improving production and environmental quality converge, new metrics that can simultaneously capture multiple aspects of system performance are needed. To fill this gap, we developed a theoretical framework that links both crop- and soil-based approaches to derive a system N-use efficiency (sNUE) index. This easily interpretable metric succinctly characterizes N cycling and facilitates comparison of systems that differ in biophysical controls on N dynamics. We demonstrated the application of this new approach and compared it to traditional NUE metrics using data generated with a process-based model (APSIM), trained and tested with experimental datasets (Iowa, USA). Modeling of maize-soybean rotations indicated that despite their high crop NUE, only 45% of N losses could be attributed to the inefficient use of N inputs, whereas the rest originated from the release of native soil N into the environment, due to the asynchrony between soil mineralization and crop uptake. Additionally, sNUE produced estimates of system efficiency that were more stable across weather years and less correlated to other metrics across distinct crop sequences and N fertilizer input levels. We also showed how sNUE allows for the examination of tradeoffs between N cycling and production performance, and thus has the potential to aid in the design of systems that better balance production and environmental outcomes.
The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge‐of‐field water, nutrient, and sediment transport and is used to assess the environmental impacts of ...management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site‐specific soil, weather, event flow, and water quality data. The analysis was conducted using 12 datasets at four locations representing poorly drained soils and row‐crop production under different tillage systems. Model performance was based on the Nash–Sutcliffe efficiency (NSE), the coefficient of determination (r2) and the regression slope between simulated and measured annualized loads across all site years. Although the BPJ model performance for flow was acceptable (NSE = 0.7) at the annual time step, calibration improved it (NSE = 0.9). Acceptable simulation of sediment and total phosphorus transport (NSE = 0.5 and 0.9, respectively) was obtained only after full calibration at each site. Given the unacceptable performance of the BPJ approach, uncalibrated use of APEX for planning or management purposes may be misleading. Model calibration with water quality data prior to using APEX for simulating sediment and total phosphorus loss is essential.
Core Ideas
Uncalibrated, APEX produced unacceptable site‐specific sediment and TP estimates.
Acceptable runoff estimates do not translate to acceptable water quality estimates.
Distributions of successfully calibrated performance indicator values were normal.
Calibration of the APEX model with water quality data remains an essential step.
Phosphorus (P) Index assessment requires independent estimates of long‐term average annual P loss from fields, representing multiple climatic scenarios, management practices, and landscape positions. ...Because currently available measured data are insufficient to evaluate P Index performance, calibrated and validated process‐based models have been proposed as tools to generate the required data. The objectives of this research were to develop a regional parameterization for the Agricultural Policy Environmental eXtender (APEX) model to estimate edge‐of‐field runoff, sediment, and P losses in restricted‐layer soils of Missouri and Kansas and to assess the performance of this parameterization using monitoring data from multiple sites in this region. Five site‐specific calibrated models (SSCM) from within the region were used to develop a regionally calibrated model (RCM), which was further calibrated and validated with measured data. Performance of the RCM was similar to that of the SSCMs for runoff simulation and had Nash–Sutcliffe efficiency (NSE) > 0.72 and absolute percent bias (|PBIAS|) < 18% for both calibration and validation. The RCM could not simulate sediment loss (NSE < 0, |PBIAS| > 90%) and was particularly ineffective at simulating sediment loss from locations with small sediment loads. The RCM had acceptable performance for simulation of total P loss (NSE > 0.74, |PBIAS| < 30%) but underperformed the SSCMs. Total P‐loss estimates should be used with caution due to poor simulation of sediment loss. Although we did not attain our goal of a robust regional parameterization of APEX for estimating sediment and total P losses, runoff estimates with the RCM were acceptable for P Index evaluation.
Core Ideas
Regionally calibrated APEX produced very good estimates of site‐specific runoff.
Regionally calibrated APEX failed to adequately estimate sediment loss.
Regionally calibrated APEX P‐loss estimates were worse than site‐specific models.
APEX runoff estimates are adequate for rigorous evaluation of P Index runoff components.
APEX sediment loss estimates are unsuitable for evaluation of P Index.
As global populations and affluence rise, there is increasing demand for energy, animal protein, and construction materials. In many cases, available resource pools are insufficient to meet growing ...market demands, resulting in increased prices and competition for limited resources. This study evaluates key construction resources needed to build different types and scales of Iowa swine production facilities. Two types of facilities — conventional confinement and hoop barn-based — within farrow-to-finish pig production systems scaled to produce either 5,200 or 15,600 market pigs annually are examined. Conventional confinement facilities are typical of pork industry practice in the United States and are characterized by individual gestation stalls and 1,200 head grow-finish buildings with slatted concrete floors and liquid manure systems. The hoop barn-based alternative uses bedded group pens in hoop barns for gestation and finishing. Five building materials: concrete, steel, lumber, thermoplastics, insulation, as well as crushed rock and diesel fuel used for building site preparation are considered. Land surface area required for buildings and pig production infrastructure are also compared. Relative market costs of newly constructed swine facilities are compared under several material price scenarios. Using hoop barns for grow-finish and gestation results in lower construction costs. Increasing the scale of pig production results in lower construction costs per pig space, however the construction costs per pig space for a 5,200 head hoop barn-based complex is less than the construction costs per pig space for a 15,600 head conventional confinement system. In terms of construction resource use and cost, hoop barns for swine are a viable alternative that are less dependent on the scale of production than conventional confinement facilities.
Loss of biodiversity and degradation of ecosystem services from agricultural lands remain important challenges in the United States despite decades of spending on natural resource management. To ...date, conservation investment has emphasized engineering practices or vegetative strategies centered on monocultural plantings of nonnative plants, largely excluding native species from cropland. In a catchment-scale experiment, we quantified the multiple effects of integrating strips of native prairie species amid corn and soybean crops, with prairie strips arranged to arrest run-off on slopes. Replacing 10% of cropland with prairie strips increased biodiversity and ecosystem services with minimal impacts on crop production. Compared with catchments containing only crops, integrating prairie strips into cropland led to greater catchment-level insect taxa richness (2.6-fold), pollinator abundance (3.5-fold), native bird species richness (2.1-fold), and abundance of bird species of greatest conservation need (2.1-fold). Use of prairie strips also reduced total water runoff from catchments by 37%, resulting in retention of 20 times more soil and 4.3 times more phosphorus. Corn and soybean yields for catchments with prairie strips decreased only by the amount of the area taken out of crop production. Social survey results indicated demand among both farming and nonfarming populations for the environmental outcomes produced by prairie strips. If federal and state policies were aligned to promote prairie strips, the practice would be applicable to 3.9 million ha of cropland in Iowa alone.
We used the Agricultural Production Systems sIMulator (APSIM) to predict and explain maize and soybean yields, phenology, and soil water and nitrogen (N) dynamics during the growing season in Iowa, ...USA. Historical, current and forecasted weather data were used to drive simulations, which were released in public four weeks after planting. In this paper, we (1) describe the methodology used to perform forecasts; (2) evaluate model prediction accuracy against data collected from 10 locations over four years; and (3) identify inputs that are key in forecasting yields and soil N dynamics. We found that the predicted median yield at planting was a very good indicator of end‐of‐season yields (relative root mean square error RRMSE of ∼20%). For reference, the prediction at maturity, when all the weather was known, had a RRMSE of 14%. The good prediction at planting time was explained by the existence of shallow water tables, which decreased model sensitivity to unknown summer precipitation by 50–64%. Model initial conditions and management information accounted for one‐fourth of the variation in maize yield. End of season model evaluations indicated that the model simulated well crop phenology (R2 = 0.88), root depth (R2 = 0.83), biomass production (R2 = 0.93), grain yield (R2 = 0.90), plant N uptake (R2 = 0.87), soil moisture (R2 = 0.42), soil temperature (R2 = 0.93), soil nitrate (R2 = 0.77), and water table depth (R2 = 0.41). We concluded that model set‐up by the user (e.g. inclusion of water table), initial conditions, and early season measurements are very important for accurate predictions of soil water, N and crop yields in this environment.
We compare subsurface‐drainage NO3–N and total reactive phosphorus (TRP) concentrations and yields of select bioenergy cropping systems and their rotational phases. Cropping systems evaluated were ...grain‐harvested corn–soybean rotations, grain‐ and stover‐harvested continuous corn systems with and without a cover crop, and annually harvested reconstructed prairies with and without the addition of N fertilizer in an Iowa field. Drainage was monitored when soils were unfrozen during 2010 through 2013. The corn–soybean rotations without residue removal and continuous corn with residue removal produced similar mean annual flow‐weighted NO3–N concentrations, ranging from 6 to 18.5 mg N L−1 during the 4‐yr study. In contrast, continuous corn with residue removal and with a cover crop had significantly lower NO3–N concentrations of 5.6 mg N L−1 when mean annual flow‐weighted values were averaged across the 4 yr. Prairies systems with or without N fertilization produced significantly lower concentrations below <1 mg NO3–N L−1 than all the row crop systems throughout the study. Mean annual flow‐weighted TRP concentrations and annual yields were generally low, with values <0.04 mg TRP L−1 and <0.14 kg TRP ha−1, and were not significantly affected by any cropping systems or their rotational phases. Bioenergy‐based prairies with or without N fertilization and continuous corn with stover removal and a cover crop have the potential to supply bioenergy feedstocks while minimizing NO3–N losses to drainage waters. However, subsurface drainage TRP concentrations and yields in bioenergy systems will need further evaluation in areas prone to higher levels of P losses.
Core Ideas
Bioenergy prairies limited NO3–N losses in subsurface drainage even when N fertilizer was applied.
Bioenergy continuous corn with cover crop can supply feedstocks while minimizing NO3–N losses.
Drainage TRP concentrations in bioenergy systems need evaluation in areas with high P losses.
Given widespread biodiversity declines, a growing global human population, and demands to improve water quality, there is an immediate need to explore land management solutions that support multiple ...ecosystem services. Agricultural water quality wetlands designed to provide both water quality benefits and wetland and grassland habitat are an emerging restoration solution that may reverse habitat declines in intensive agricultural areas. Installation of water quality wetlands in the Upper Midwest, USA, when considered alongside the repair and modification of aging agricultural tile drainage infrastructure, is a likely scenario that may mitigate nutrient pollution exported from agricultural systems and improve crop yields. The capacity of water quality wetlands to provide habitat within the wetland pool and the surrounding grassland is not well-studied, particularly with respect to potential habitat changes resulting from drainage infrastructure upgrades. For the current study, we produced spatially explicit models of 37 catchments distributed throughout an important region for agriculture and biodiversity, the Des Moines Lobe of Iowa. Four scenarios were considered - with and without improved drainage and with and without water quality wetlands - to estimate the net potential habitat implications of these scenarios for amphibians, grassland birds, and wild bees. Model results indicate that drainage modification alone will likely result in moderate direct losses of suitable amphibian habitat and large declines in overall habitat quality. However, inclusion of water quality wetlands at the catchment scale may mitigate these amphibian habitat losses while also increasing grassland bird and pollinator habitat. The impacts of water quality wetlands and drainage modernization on waterfowl in the region require additional study.
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•Management solutions that optimize crop yields and increase habitat are needed.•We modeled habitat impact of drainage modernization and water quality wetlands (WQW).•Modeled WQW and buffers provided amphibian, grassland bird, and wild bee habitat.•Modeled WQW habitat gains mitigated modeled losses from drainage modernization.•The impacts of drainage modernization on waterfowl require additional study.
Agriculture in the US Corn Belt is under increasing pressure to produce greater quantities of food, feed and fuel, while better protecting environmental quality. Key environmental problems in this ...region include water contamination by nutrients and herbicides emitted from cropland, a lack of non-agricultural habitat to support diverse communities of native plants and animals, and a high level of dependence on petrochemical energy in the dominant cropping systems. In addition, projected changes in climate for this region, which include increases in the proportion of precipitation coming from extreme events could make soil and water conservation in existing cropping systems more difficult. To address these challenges we have conducted three cropping systems projects in central Iowa: the Marsden Farm Cropping Systems experiment, the Science-based Trials of Row-crops Integrated with Prairies (STRIPs) experiment, and the Comparison of Biofuel Systems (COBS) experiment. Results from these experiments indicate that (1) diversification of the dominant corn–soybean rotation with small grains and forage legumes can permit substantial reductions in agrichemical and fossil hydrocarbon use without compromising yields or profitability; (2) conversion of small amounts of cropland to prairie buffer strips can provide disproportionately large improvements in soil and water conservation, nutrient retention, and densities of native plants and birds; and (3) native perennial species can generate large amounts of biofuel feedstocks and offer environmental benefits relative to corn- and soybean-based systems, including greater carbon inputs to soil and large reductions in nitrogen emissions to drainage water. Increasing biodiversity through the strategic integration of perennial plant species can be a viable strategy for reducing reliance on purchased inputs and for increasing agroecosystem health and resilience in the US Corn Belt.
Aims
Root distributions determine crop nutrient access and soil carbon input patterns. To date, root distribution data are rare but needed to improve knowledge and prediction of cropping system ...sustainability. In this study, we sought to (i) quantify variation in maize (
Zea mays
) and soybean (
Glycine max
) roots by depth and environment across Iowa, USA and (ii) identify environmental factors explaining the most variation.
Methodology
Over three years we collected soil cores from 0 to 210 cm in 16 maize and 12 soybean field experiments at grain filling. Root mass, length, carbon (C) and nitrogen (N) were determined at 30 cm increments, coupled with crop, soil, management, and weather-related measurements.
Results
Percentage of root mass located in the top 30 cm varied from 52 to 94% in maize and 54–84% in soybean. Variation in maize root distributions was strongly associated with depth to water tables, variation in soybean with soil physical attributes. Root C:N ratios were highly variable with no depth-pattern, averaging 20 and 30 for soybean and maize, respectively. In both crops, specific root lengths increased with depth to 60 cm, and thereafter remained constant.
Conclusions
Field studies of roots should consider depth to water tables and soil moisture measurements, as they influence vertical root distributions.
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