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Background: Climate-smart agriculture (CSA) addresses the challenge of meeting the growing demand for food, fibre and fuel, despite the changing climate and fewer opportunities for agricultural expansion on additional lands. CSA focuses on contributing to economic development, poverty reduction and food security; maintaining and enhancing the productivity and resilience of natural and agricultural ecosystem functions, thus building natural capital; and reducing trade-offs involved in meeting these goals. Current gaps in knowledge, work within CSA, and agendas for interdisciplinary research and science-based actions identified at the 2013 Global Science Conference on Climate-Smart Agriculture (Davis, CA, USA) are described here within three themes: (1) farm and food systems, (2) landscape and regional issues and (3) institutional and policy aspects. The first two themes comprise crop physiology and genetics, mitigation and adaptation for livestock and agriculture, barriers to adoption of CSA practices, climate risk management and energy and biofuels (theme 1); and modelling adaptation and uncertainty, achieving multifunctionality, food and fishery systems, forest biodiversity and ecosystem services, rural migration from climate change and metrics (theme 2). Theme 3 comprises designing research that bridges disciplines, integrating stakeholder input to directly link science, action and governance. Outcomes: In addition to interdisciplinary research among these themes, imperatives include developing (1) models that include adaptation and transformation at either the farm or landscape level; (2) capacity approaches to examine multifunctional solutions for agronomic, ecological and socioeconomic challenges; (3) scenarios that are validated by direct evidence and metrics to support behaviours that foster resilience and natural capital; (4) reductions in the risk that can present formidable barriers for farmers during adoption of new technology and practices; and (5) an understanding of how climate affects the rural labour force, land tenure and cultural integrity, and thus the stability of food production. Effective work in CSA will involve stakeholders, address governance issues, examine uncertainties, incorporate social benefits with technological change, and establish climate finance within a green development framework. Here, the socioecological approach is intended to reduce development controversies associated with CSA and to identify technologies, policies and approaches leading to sustainable food production and consumption patterns in a changing climate.

For maize (Zea mays L.), nitrogen (N) fertilizer use is often summarized from field to global scales using average N use efficiency (NUE). But expressing NUE as averages is misleading because grain increase to added N diminishes near optimal yield. Thus, environmental risks increase as economic benefits decrease. Here, we use empirical datasets obtained in North America of maize grain yield response to N fertilizer (n = 189) to create and interpret incremental NUE (iNUE), or the change in NUE with change in N fertilization. We show for those last units of N applied to reach economic optimal N rate (EONR) iNUE for N removed with the grain is only about 6%. Conversely stated, for those last units of N applied over 90% is either lost to the environment during the growing season, remains as inorganic soil N that too may be lost after the growing season, or has been captured within maize stover and roots or soil organic matter pools. Results also showed iNUE decrease averaged 0.63% for medium-textured soils and 0.37% for fine-textured soils, attributable to fine-textured soils being more predisposed to denitrification and/or lower mineralization. Further analysis demonstrated the critical nature growing season water amount and distribution has on iNUE. Conditions with too much rainfall and/or uneven rainfall produced low iNUE. Producers realize this from experience, and it is uncertain weather that largely drives insurance fertilizer additions. Nitrogen fertilization creating low iNUE is environmentally problematic. Our results show that with modest sub-EONR fertilization and minor forgone profit, average NUE improvements of ~10% can be realized. Further, examining iNUE creates unique perspective and ideas for how to improve N fertilizer management tools, educational programs, and public policies and regulations., Competing Interests: The authors have declared that no competing interests exist.

Increasing temperatures in the US Midwest are projected to reduce maize yields because warmer temperatures hasten reproductive development and, as a result, shorten the grain fill period. However, there is widespread expectation that farmers will mitigate projected yield losses by planting longer season hybrids that lengthen the grain fill period. Here, we ask: (a) how current hybrid maturity length relates to thermal availability of the local climate, and (b) if farmers are shifting to longer season hybrids in response to a warming climate. To address these questions, we used county-level Pioneer brand hybrid sales (Corteva Agriscience) across 17 years and 650 counties in 10 Midwest states (IA, IL, IN, MI, MN, MO, ND, OH, SD, and WI). Northern counties were shown to select hybrid maturities with growing degree day (GDD°C) requirements more closely related to the environmentally available GDD compared to central and southern counties. This measure, termed "thermal overlap," ranged from complete 106% in northern counties to a mere 63% in southern counties. The relationship between thermal overlap and latitude was fit using split-line regression and a breakpoint of 42.8°N was identified. Over the 17-years, hybrid maturities shortened across the majority of the Midwest with only a minority of counties lengthening in select northern and southern areas. The annual change in maturity ranged from -5.4 to 4.1 GDD year -1 with a median of -0.9 GDD year -1 . The shortening of hybrid maturity contrasts with widespread expectations of hybrid maturity aligning with magnitude of warming. Factors other than thermal availability appear to more strongly impact farmer decision-making such as the benefit of shorter maturity hybrids on grain drying costs, direct delivery to ethanol biorefineries, field operability, labor constraints, and crop genetics availability. Prediction of hybrid choice under future climate scenarios must include climatic factors, physiological-genetic attributes, socio-economic, and operational constraints., (© 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Although the scientific community has reached a consensus that anthropogenic climate change is a severe and pressing issue, climate change remains a contentious debate with the United States public. Through a survey ( N  = 273), we explored climate professionals' perspectives on their role and responsibility to promote climate change adaptation/mitigation strategies related to agroecosystems. They believed that climate professionals have a social responsibility to provide scientific input to both policymakers and the public. There was strong agreement that media, political, and public support is necessary for development, and near unanimous agreement for implementation, of climate change mitigation/adaptation strategies. This study highlights the climate professionals' perceptions of their responsibility to provide scientific input, but also demonstrates that they believe the responsibility does not rest solely on their shoulders. Further research should explore scientists' perceptions of their and others' policy roles and scientists' interactions with different influencers of adaptation/mitigation policy.

The Wheat Initiative (WI) and the WI Expert Working Group (EWG) for Agronomy (www.wheatinitiative.org) were formed with a collective goal to "coordinate global wheat research efforts to increase wheat production, quality, and sustainability to advance food security and safety under changing climate conditions." The Agronomy EWG is responsive to the WI's research need, "A knowledge exchange strategy to ensure uptake of innovations on farm and to update scientists on changing field realities." The Agronomy EWG aims to consolidate global expertise for agronomy with a focus on wheat production systems. The overarching approach is to develop and adopt a systems-agronomy framework relevant to any wheat production system. It first establishes the scale of current yield gaps, identifies defensible benchmarks, and takes a holistic approach to understand and overcome exploitable yield gaps to complement genetic increases in potential yield. New opportunities to increase productivity will be sought by exploiting future Genotype × Environment × Management synergies in different wheat systems. To identify research gaps and opportunities for collaboration among different wheat producing regions, the EWG compiled a comprehensive database of currently funded wheat agronomy research ( n = 782) in countries representing a large proportion of the wheat grown in the world. The yield gap analysis and research database positions the EWG to influence priorities for wheat agronomy research in member countries that would facilitate collaborations, minimize duplication, and maximize the global impact on wheat production systems. This paper outlines a vision for a global WI agronomic research strategy and discusses activities to date. The focus of the WI-EWG is to transform the agronomic research approach in wheat cropping systems, which will be applicable to other crop species., (Copyright © 2020 Beres, Hatfield, Kirkegaard, Eigenbrode, Pan, Lollato, Hunt, Strydhorst, Porker, Lyon, Ransom and Wiersma.)

Wheat production is required to supply food for the world's population, and increases in production will be necessary to feed the expanding population. Estimates show that production must increase by 1 billion metric tons to meet this demand. One method to meet future demand is to increase wheat yields by reducing the gap between actual and potential yields. Potential yields represent an optimum set of conditions, and a more realistic metric would be to compare actual yields with attainable yields, where these yields represent years in the record where there is no obvious limitation. This study was conducted to evaluate the yield trends, attainable yields, and yield gaps for the 10 largest wheat producing countries in the world and more localized yield statistics at the state or county level. These data were assembled from available government sources. Attainable yield was determined using an upper quantile analysis to define the upper frontier of yields over the period of record and yield gaps calculated as the difference between attainable yield and actual yield for each year and expressed as a percentage of the attainable yield. In all countries, attainable yield increase over time was larger than the yield trend indicating the technological advances in genetics and agronomic practices were increasing attainable yield. Yield gaps have not shown a decrease over time and reflect that weather during the growing season remains the primary limitation to production. Yield gap closure will require that local producers adopt practices that increase their climate resilience in wheat production systems., (Copyright © 2019 Hatfield and Beres.)

A delayed harvest of maize and soybean crops is associated with yield or revenue losses, whereas a premature harvest requires additional costs for artificial grain drying. Accurately predicting the ideal harvest date can increase profitability of US Midwest farms, but today's predictive capacity is low. To fill this gap, we collected and analyzed time-series grain moisture datasets from field experiments in Iowa, Minnesota and North Dakota, US with various maize (n = 102) and soybean (n = 36) genotype-by-environment treatments. Our goal was to examine factors driving the post-maturity grain drying process, and develop scalable algorithms for decision-making. The algorithms evaluated are driven by changes in the grain equilibrium moisture content (function of air relative humidity and temperature) and require three input parameters: moisture content at physiological maturity, a drying coefficient and a power constant. Across independent genotypes and environments, the calibrated algorithms accurately predicted grain dry-down of maize (r 2  = 0.79; root mean square error, RMSE = 1.8% grain moisture) and soybean field crops (r 2  = 0.72; RMSE = 6.7% grain moisture). Evaluation of variance components and treatment effects revealed that genotypes, weather-years, and planting dates had little influence on the post-maturity drying coefficient, but significantly influenced grain moisture content at physiological maturity. Therefore, accurate implementation of the algorithms across environments would require estimating the initial grain moisture content, via modeling approaches or in-field measurements. Our work contributes new insights to understand the post-maturity grain dry-down and provides a robust and scalable predictive algorithm to forecast grain dry-down and ideal harvest dates across environments in the US Corn Belt.

Harvesting corn stover removes N from the fields, but its effect on subsurface drainage and other N losses is uncertain. We used the Root Zone Water Quality Model (RZWQM) to examine N losses with 0 (NRR) or 50% (RR) corn residue removal within a corn and soybean rotation over a 10-yr period. In general, all simulations used the same pre-plant or post-emergence N fertilizer rate (200 kg ha -1  yr -1 ). Simulated annual corn yields averaged 10.7 Mg ha -1 for the post emergence applications (NRRpost and RRpost), and 9.5 and 9.4 Mg ha -1  yr -1 for NRRpre and RRpre. Average total N input during corn years was 19.3 kg N ha -1 greater for NRRpre compared to RRpre due to additional N in surface residues, but drainage N loss was only 1.1 kg N ha -1  yr -1 greater for NRRpre. Post-emergence N application with no residue removal (NRRpost) reduced average drainage N loss by 16.5 kg ha -1  yr -1 compared to pre-plant N fertilization (NRRpre). The farm-gate net energy ratio was greatest for RRpost and lowest for NRRpre (14.1 and 10.4 MJ output per MJ input) while greenhouse gas intensity was lowest for RRpost and highest for NRRpre (11.7 and 17.3 g CO 2 -eq. MJ -1 output). Similar to published studies, the simulations showed little difference in N 2 O emissions between scenarios, decreased microbial immobilization for RR compared to NRR, and small soil carbon changes over the 10-yr simulation. In contrast to several previous modeling studies, the crop yield and N lost to drain flow were nearly the same between NRR and RR without supplemental N applied to replace N removed with corn stover. These results are important to optimizing the energy and nitrogen budgets associated with corn stover harvest and for developing a sustainable bioenergy industry., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Water use efficiency (WUE) is defined as the amount of carbon assimilated as biomass or grain produced per unit of water used by the crop. One of the primary questions being asked is how plants will respond to a changing climate with changes in temperature, precipitation, and carbon dioxide (CO 2 ) that affect their WUE At the leaf level, increasing CO 2 increases WUE until the leaf is exposed to temperatures exceeded the optimum for growth (i.e., heat stress) and then WUE begins to decline. Leaves subjected to water deficits (i.e., drought stress) show varying responses in WUE. The response of WUE at the leaf level is directly related to the physiological processes controlling the gradients of CO 2 and H 2 O, e.g., leaf:air vapor pressure deficits, between the leaf and air surrounding the leaf. There a variety of methods available to screen genetic material for enhanced WUE under scenarios of climate change. When we extend from the leaf to the canopy, then the dynamics of crop water use and biomass accumulation have to consider soil water evaporation rate, transpiration from the leaves, and the growth pattern of the crop. Enhancing WUE at the canopy level can be achieved by adopting practices that reduce the soil water evaporation component and divert more water into transpiration which can be through crop residue management, mulching, row spacing, and irrigation. Climate change will affect plant growth, but we have opportunities to enhance WUE through crop selection and cultural practices to offset the impact of a changing climate.

Virtuosity in music performance is often associated with fast, precise, and efficient sound-producing movements. The generation of such highly skilled movements involves complex joint and muscle control by the central nervous system, and depends on the ability to anticipate, segment, and coarticulate motor elements, all within the biomechanical constraints of the human body. When successful, such motor skill should lead to what we characterize as fluency in musical performance. Detecting typical features of fluency could be very useful for technology-enhanced learning systems, assisting and supporting students during their individual practice sessions by giving feedback and helping them to adopt sustainable movement patterns. In this study, we propose to assess fluency in musical performance as the ability to smoothly and efficiently coordinate while accurately performing slow, transitionary, and rapid movements. To this end, the movements of three cello players and three drummers at different levels of skill were recorded with an optical motion capture system, while a wireless electromyography (EMG) system recorded the corresponding muscle activity from relevant landmarks. We analyzed the kinematic and coarticulation characteristics of these recordings separately and then propose a combined model of fluency in musical performance predicting music sophistication. Results suggest that expert performers' movements are characterized by consistently smooth strokes and scaling of muscle phasic coactivation. The explored model of fluency as a function of movement smoothness and coarticulation patterns was shown to be limited by the sample size, but it serves as a proof of concept. Results from this study show the potential of a technology-enhanced objective measure of fluency in musical performance, which could lead to improved practices for aspiring musicians, instructors, and researchers.

Anthropogenic perturbation of the global nitrogen cycle and its effects on the environment such as hypoxia in coastal regions and increased N 2 O emissions is of increasing, multi-disciplinary, worldwide concern, and agricultural production is a major contributor. Only limited studies, however, have simultaneously investigated NO 3 - losses to subsurface drain flow and N 2 O emissions under corn-soybean production. We used the Root Zone Water Quality Model (RZWQM) to evaluate NO 3 - losses to drain flow and N 2 O emissions in a corn-soybean system with a winter rye cover crop (CC) in central Iowa over a nine year period. The observed and simulated average drain flow N concentration reductions from CC were 60% and 54% compared to the no cover crop system (NCC). Average annual April through October cumulative observed and simulated N 2 O emissions (2004-2010) were 6.7 and 6.0kgN 2 O-Nha -1 yr -1 for NCC, and 6.2 and 7.2kgNha -1 for CC. In contrast to previous research, monthly N 2 O emissions were generally greatest when N loss to leaching were greatest, mostly because relatively high rainfall occurred during the months fertilizer was applied. N 2 O emission factors of 0.032 and 0.041 were estimated for NCC and CC using the tested model, which are similar to field results in the region. A local sensitivity analysis suggests that lower soil field capacity affects RZWQM simulations, which includes increased drain flow nitrate concentrations, increased N mineralization, and reduced soil water content. The results suggest that 1) RZWQM is a promising tool to estimate N 2 O emissions from subsurface drained corn-soybean rotations and to estimate the relative effects of a winter rye cover crop over a nine year period on nitrate loss to drain flow and 2) soil field capacity is an important parameter to model N mineralization and N loss to drain flow., (Published by Elsevier B.V.)

Cereal production around the world is critical to the food supply for the human population. Crop productivity is primarily determined by a combination of temperature and precipitation because temperatures have to be in the range for plant growth and precipitation has to supply crop water requirements for a given environment. The question is often asked about the changes in productivity and what we can expect in the future and we evaluated the causes for variation in historical annual statewide wheat grain yields in Oklahoma, Kansas, and North Dakota across the Great Plains of United States. Wheat ( Triticum aestivum L.) is adapted to this area and we focused on production in these states from 1950 to 2016. This analysis used a framework for annual yields using yield gaps between attainable and actual yields and found the primary cause of the variation among years were attributable to inadequate precipitation during the grain-filling period. In Oklahoma, wheat yields were reduced when April and May precipitation was limited ( r 2 = 0.70), while in Kansas, May precipitation was the dominant factor ( r 2 = 0.78), and in North Dakota June-July precipitation was the factor explaining yield variation ( r 2 = 0.65). Temperature varied among seasons and at the statewide level did not explain a significant portion of the yield variation. The pattern of increased variation in precipitation will cause further variation in wheat production across the Great Plains. Reducing yield variation among years will require adaptation practices that increase water availability to the crop coupled with the positive impact derived from other management practices, e.g., cultivars, fertilizer management, etc.

The purpose of the present mixed method study was to investigate personal benefits, perceptions, and the effect of a 15-week sport psychological skills training program adapted for musicians. The program was individually tailored for six music performance students with the objective of facilitating the participants' instrumental practice and performance. The participants learnt techniques such as goal setting, attentional focus, arousal regulation, imagery, and acceptance training/self-talk. Zimmerman's (1989) cyclical model of self-regulated learning was applied as a theoretical frame for the intervention. The present study's mixed-method approach (i.e., quan+ QUAL) included effect size, semi-structured interviews, a research log, and practice diaries of the participants (Creswell, 2009). Thematic analysis revealed that participants had little or no experience concerning planning and goal setting in regard to instrumental practice. Concentration, volition, and physical pain were additional issues that the participants struggled with at the time of pre-intervention. The study found that psychological skills training (with special emphasis on planning and goal setting) facilitated cyclical self-regulated learning patterns in the participants. In essence, the intervention was found to facilitate the participants' concentration, self-observation, self-efficacy, and coping in the face of failure. The appliance of practice journals facilitated the participants' self-observation, self-evaluation, and awareness of instrumental practice. Finally, the psychological skills intervention reduced participants' worry and anxiety in performance situations. An 8-month follow up interview revealed that the participants were still actively applying psychological skills.

The goals of the present study are to evaluate, implement, and adapt psychological skills used in the realm of sports into music performance. This research project also aims to build foundations on how to implement future interventions to guide music students on how to optimize practice toward performance. A 2-month psychological skills intervention was provided to two students from the national music academy's bachelor program in music performance to better understand how to adapt and construct psychological skills training programs for performing music students. The program evaluated multiple intervention tools including the use of questionnaires, performance profiling, iPads, electronic practice logs, recording the perceived value of individual and combined work, as well as the effectiveness of different communication forms. Perceived effects of the intervention were collected through semi-structured interviews, observations, and logs.

The U.S. Corn Belt area has the capacity to generate high nitrous oxide (NO) emissions due to medium to high annual precipitation, medium- to heavy-textured soils rich in organic matter, and high nitrogen (N) application rates. The purpose of this work was to estimate NO emissions from cornfields in Iowa at the county level using the DeNitrification-DeComposition (DNDC) model and to compare the DNDC NO emission estimates with available results from field experiments. All data were acquired for 2007 to 2011. Weather Underground Network and the Iowa State University Iowa Soil Properties and Interpretation Database 7.3 were the data sources for DNDC inputs and for computing county soil parameters. The National Agriculture Statistic Service 5-yr averages for corn yield data were used to establish ex post fertilizer N input at the county level. The DNDC output suggested county-wide NO emissions in Iowa ranged from 2.2 kg NO-N ha yr in south-central to 4.6 to 4.7 kg NO-N ha yr in north-central and eastern Iowa counties. In northern districts, the average direct NO emissions were 3.2, 4.4, and 3.6 kg NO-N ha yr for west, central, and east, respectively. In central districts, average NO emissions were 3.5, 3.9, and 3.4 kg NO-N ha yr for west, central, and east, respectively. For southern districts, NO emissions were 3.5, 2.6, and 3.1 kg NO-N ha yr for west, central, and east, respectively. Direct NO emissions estimated by the DNDC model were 1.93% of N fertilizer input to corn fields in Iowa, with values ranging from 1.66% in the northwest cropping district to 2.25% in the north-central cropping district. These values are higher than the average 1% loss rate used in the IPCC Tier 1 approach., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models., (© 2014 John Wiley & Sons Ltd.)

Soil preparation for agricultural crops produces aerosols that may significantly contribute to seasonal atmospheric particulate matter (PM). Efforts to reduce PM emissions from tillage through a variety of conservation management practices (CMPs) have been made, but the reductions from many of these practices have not been measured in the field. A study was conducted in California's San Joaquin Valley to quantify emissions reductions from fall tillage CMP. Emissions were measured from conventional tillage methods and from a "combined operations" CMP, which combines several implements to reduce tractor passes. Measurements were made of soil moisture, bulk density, meteorological profiles, filter-based total suspended PM (TSP), concentrations of PM with an equivalent aerodynamic diameter ≤10 μm (PM) and PM with an equivalent aerodynamic diameter ≤2.5 μm (PM), and aerosol size distribution. A mass-calibrated, scanning, three-wavelength light detection and ranging (LIDAR) procedure estimated PM through a series of algorithms. Emissions were calculated via inverse modeling with mass concentration measurements and applying a mass balance to LIDAR data. Inverse modeling emission estimates were higher, often with statistically significant differences. Derived PM emissions for conventional operations generally agree with literature values. Sampling irregularities with a few filter-based samples prevented calculation of a complete set of emissions through inverse modeling; however, the LIDAR-based emissions dataset was complete. The CMP control effectiveness was calculated based on LIDAR-derived emissions to be 29 ± 2%, 60 ± 1%, and 25 ± 1% for PM, PM, and TSP size fractions, respectively. Implementation of this CMP provides an effective method for the reduction of PM emissions., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

Two common variants (rs1387153, rs10830963) in MTNR1B have been reported to have independent effects on fasting blood glucose (FBG) levels with increased risk to type 2 diabetes (T2D) in recent genome-wide association studies (GWAS). In this investigation, we report the association of these two variants, and an additional variant (rs1374645) within the GWAS locus of MTNR1B with FBG, 2h glucose, insulin resistance (HOMA IR), β-cell function (HOMA B), and T2D in our sample of Asian Sikhs from India. Our cohort comprised 2222 subjects [1201 T2D, 1021 controls]. None of these SNPs was associated with T2D in this cohort. Our data also could not confirm association of rs1387153 and rs10830963 with FBG phenotype. However, upon stratifying data according to body mass index (BMI) (low ≤ 25 kg/m(2) and high > 25 kg/m(2)) in normoglycemic subjects (n = 1021), the rs1374645 revealed a strong association with low FBG levels in low BMI group (β = -0.073, p = 0.002, Bonferroni p = 0.01) compared to the high BMI group (β = 0.015, p = 0.50). We also detected a strong evidence of interaction between rs1374645 and BMI with respect to FBG levels (p = 0.002). Our data provide new information about the significant impact of another MTNR1B variant on FBG levels that appears to be modulated by BMI. Future confirmation on independent datasets and functional studies will be required to define the role of this variant in fasting glucose variation., (Published by Elsevier B.V.)

The Raccoon River Watershed in Iowa has received considerable attention in the recent past due to frequent detections of nitrate concentrations above the federal drinking water standard. This paper econometrically investigates the determinants of variation of nitrate concentrations in the Raccoon River. The analysis relies on a generalized autoregressive conditional heteroscedastic process to model the serial dependence of volatility of the monthly nitrate concentrations in the Raccoon River. Monthly nitrate concentration data from Des Moines Water Works at Van Meter from 1992 to 2008 are used in the study. We found no statistically significant increasing trend in nitrate concentrations over the study period. There are substantial intra-annual variations in nitrate concentrations, and we noted a very strong seasonal pattern. Variations in rainfall and temperature contribute more to the monthly variation in nitrate concentration than do the changes in nitrogen application rates., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

An 8-yr study was conducted to better understand factors influencing year-to-year variability in field-scale herbicide volatilization and surface runoff losses. The 21-ha research site is located at the USDA-ARS Beltsville Agricultural Research Center in Beltsville, MD. Site location, herbicide formulations, and agricultural management practices remained unchanged throughout the duration of the study. Metolachlor [2-chloro--(2-ethyl-6-methylphenyl)--(2-methoxy-1-methylethyl) acetamide] and atrazine [6-chloro--ethyl--(1-methylethyl)-1,3,5-triazine-2,4-diamine] were coapplied as a surface broadcast spray. Herbicide runoff was monitored from a month before application through harvest. A flux gradient technique was used to compute volatilization fluxes for the first 5 d after application using herbicide concentration profiles and turbulent fluxes of heat and water vapor as determined from eddy covariance measurements. Results demonstrated that volatilization losses for these two herbicides were significantly greater than runoff losses ( < 0.007), even though both have relatively low vapor pressures. The largest annual runoff loss for metolachlor never exceeded 2.5%, whereas atrazine runoff never exceeded 3% of that applied. On the other hand, herbicide cumulative volatilization losses after 5 d ranged from about 5 to 63% of that applied for metolachlor and about 2 to 12% of that applied for atrazine. Additionally, daytime herbicide volatilization losses were significantly greater than nighttime vapor losses ( < 0.05). This research confirmed that vapor losses for some commonly used herbicides frequently exceeds runoff losses and herbicide vapor losses on the same site and with the same management practices can vary significantly year to year depending on local environmental conditions., (by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

Sinking agricultural botanical and soil residues to the deep seafloor may not be a viable option for long-term carbon sequestration.

A 3-yr study was conducted to focus on the impact of surface soil water content on metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl) acetamide) volatilization from a field with different surface soil water regimes created by subsurface water flow paths. Metolachlor vapor fluxes were measured at two locations within the field where local meteorological and soil conditions were relatively constant, except for surface soil water content, which differed significantly. Surface soil water content at the two sites differed in response to the presence of subsurface flow pathways. Detailed soil moisture observations over the duration of the study showed that for the first 2 yr (2004 and 2005), surface soil water contents at the dry location (V1) were nearly half those at the wetter location (V2). Cumulative metolachlor vapor fluxes during 2004 and 2005 at V1 were also about half that at V2. In the third year (2006), early-season drought conditions rendered the soil water content at the two locations to be nearly identical, resulting in similar metolachlor volatilization losses. Analysis of infrared soil surface temperatures suggests a correlation between surface soil temperatures and metolachlor volatilization when soils are wet (2004 and 2005) but not when the soils are dry (2006). Field-averaged metolachlor volatilization losses were highly correlated with increasing surface soil water contents (r(2) = 0.995).

Accurate assessment of N(2)O emission from soil requires continuous year-round and spatially extensive monitoring or the use of simulation that accurately and precisely predict N(2)O fluxes based on climatic, soil, and agricultural system input data. DAYCENT is an ecosystem model that simulates, among other processes, N(2)O emissions from soils. The purpose of the study was to compare N(2)O fluxes predicted by the DAYCENT model to measured N(2)O fluxes from an experimental corn field in central Iowa. Soil water content temperature and inorganic N, simulated by DAYCENT were compared to measured values of these variables. Field N(2)O emissions were measured using four replicated automated chambers at 6-h intervals, from day of year (DOY) 42 through DOY 254 of 2006. We observed that DAYCENT generally accurately predicted soil temperature, with the exception of winter when predicted temperatures tended to be lower than measured values. Volumetric water contents predicted by DAYCENT were generally lower than measured values during most of the experimental period. Daily N(2)O emissions simulated by DAYCENT were significantly correlated to field measured fluxes; however, time series analyses indicate that the simulated fluxes were out of phase with the measured fluxes. Cumulative N(2)O emission calculated from the simulations (3.29 kg N(2)O-N ha(-1)) was in range of the measured cumulative N(2)O emission (4.26 +/- 1.09 kg N(2)O-N ha(-1)).

The interactive effects of soil texture and type of N fertility (i.e., manure vs. commercial N fertilizer) on N(2)O and CH(4) emissions have not been well established. This study was conducted to assess the impact of soil type and N fertility on greenhouse gas fluxes (N(2)O, CH(4), and CO(2)) from the soil surface. The soils used were a sandy loam (789 g kg(-1) sand and 138 g kg(-1) clay) and a clay soil (216 g kg(-1) sand, and 415 g kg(-1) clay). Chamber experiments were conducted using plastic buckets as the experimental units. The treatments applied to each soil type were: (i) control (no added N), (ii) urea-ammonium nitrate (UAN), and (iii) liquid swine manure slurry. Greenhouse gas fluxes were measured over 8 weeks. Within the UAN and swine manure treatments both N(2)O and CH(4) emissions were greater in the sandy loam than in the clay soil. In the sandy loam soil N(2)O emissions were significantly different among all N treatments, but in the clay soil only the manure treatment had significantly higher N(2)O emissions. It is thought that the major differences between the two soils controlling both N(2)O and CH(4) emissions were cation exchange capacity (CEC) and percent water-filled pore space (%WFPS). We speculate that the higher CEC in the clay soil reduced N availability through increased adsorption of NH(4)(+) compared to the sandy loam soil. In addition the higher average %WFPS in the sandy loam may have favored higher denitrification and CH(4) production than in the clay soil.

Depending on management, soil organic carbon (SOC) is a potential source or sink for atmospheric CO(2). We used the EPIC model to study impacts of soil and crop management on SOC in corn (Zea mays L.) and soybean (Glycine max L. Merr.) croplands of Iowa. The National Agricultural Statistics Service crops classification maps were used to identify corn-soybean areas. Soil properties were obtained from a combination of SSURGO and STATSGO databases. Daily weather variables were obtained from first order meteorological stations in Iowa and neighboring states. Data on crop management, fertilizer application and tillage were obtained from publicly available databases maintained by the NRCS, USDA-Economic Research Service (ERS), and Conservation Technology Information Center. The EPIC model accurately simulated state averages of crop yields during 1970-2005 (R(2) = 0.87). Simulated SOC explained 75% of the variation in measured SOC. With current trends in conservation tillage adoption, total stock of SOC (0-20 cm) is predicted to reach 506 Tg by 2019, representing an increase of 28 Tg with respect to 1980. In contrast, when the whole soil profile was considered, EPIC estimated a decrease of SOC stocks with time, from 1835 Tg in 1980 to 1771 Tg in 2019. Hence, soil depth considered for calculations is an important factor that needs further investigation. Soil organic C sequestration rates (0-20 cm) were estimated at 0.50 to 0.63 Mg ha(-1) yr(-1) depending on climate and soil conditions. Overall, combining land use maps with EPIC proved valid for predicting impacts of management practices on SOC. However, more data on spatial and temporal variation in SOC are needed to improve model calibration and validation.

Prolonged retained placenta causing a delayed postpartum hemorrhage is a relatively common occurrence. However, there is a dearth of medical literature describing fertility-preserving treatments when standard therapy fails. We present two cases in which protracted retained placenta due to placenta accreta was successfully treated by hysteroscopic resection. Two nulliparous women had spontaneous vaginal deliveries requiring manual placental extraction. Both experienced delayed postpartum hemorrhage and underwent suction curettage with ultrasound guidance. Both patients were found to have persistent products of conception with imaging consistent with placenta accreta. Both patients failed expectant management and subsequently underwent hysteroscopic resection with complete resolution of their symptoms. We conclude that hysteroscopic resection is a conservative therapeutic option for placenta accreta in stable patients.

Pesticide volatilization is a significant loss pathway that may have unintended consequences in nontarget environments. Field-scale pesticide volatilization involves the interaction of a number of complex variables. There is a need to acquire pesticide volatilization fluxes from a location where several of these variables can be held constant. Accordingly, soil properties, tillage practices, surface residue management, and pesticide formulations were held constant while fundamental information regarding metolachlor volatilization (a pre-emergent pesticide) was monitored over a five-year period as influenced by meteorological variables and soil water content. Metolachlor vapor concentrations were measured continuously for 120 h after each application using polyurethane foam plugs in a logarithmic profile above the soil surface. A flux gradient technique was used to compute volatilization fluxes from metolachlor concentration profiles and turbulent fluxes of heat and water vapor (as determined from eddy covariance measurements). Differences in meteorological conditions and surface soil water contents resulted in variability of the volatilization losses over the years studied. The peak volatilization losses for each year occurred during the first 24 h after application with a maximum flux rate in 2001 (1500 ng m(-2) s(-1)) associated with wet surface soil conditions combined with warm temperatures. The cumulative volatilization losses for the 120-hour period following metolachlor application varied over the years from 5 to 25% of the applied active ingredient, with approximately 87% of the losses occurring during the first 72 h. In all of the years studied, volatilization occurred diurnally and accounted for between 43 and 86% during the day and 14 and 57% during the night of the total measured loss. The results suggest that metolachlor volatilization is influenced by multiple factors involving meteorological, surface soil, and chemical factors.

This study was designed to evaluate the improved version of the Root Zone Water Quality Model (RZWQM) using 6 yr (1992-1997) of field-measured data from a field within Walnut Creek watershed located in central Iowa. Measured data included subsurface drainage flows, NO3-N concentrations and loads in subsurface drainage water, and corn (Zea mays L.) and soybean [Glycine mar (L.) Merr.] yields. The dominant soil within this field was Webster (fine-loamy, mixed, superactive, mesic Typic Endoaquolls) and cropping system was corn-soybean rotation. The model was calibrated with 1992 data and was validated with 1993 to 1997 data. Simulations of subsurface drainage flow closely matched observed data showing model efficiency of 99% (EF = 0.99), and difference (D) of 1% between measured and predicted data. The model simulated NO3-N losses with subsurface drainage water reasonably well with EF = 0.8 and D = 13%. The simulated corn grain yields were in close agreement with measured data with D < 10%. Nitrogen-scenario simulations demonstrated that corn yield response function reached a plateau when N-application rate exceeded 90 kg ha(-1). Fraction of applied N lost with subsurface drainage water varied from 7 to 16% when N-application rate varied from 30 to 180 kg ha(-1) after accounting for the nitrate loss with no-fertilizer application. These results indicate that the RZWQM has the potential to simulate the impact of N application rates on corn yields and NO3-N losses with subsurface drainage flows for agricultural fields in central Iowa.

Nitrate N fluxes from tile-drained watersheds have been implicated in water quality studies of the Mississippi River basin, but actual NO3-N loads from small watersheds during long periods are poorly documented. We evaluated discharge and NO3-N fluxes passing the outlet of an Iowa watershed (5134 ha) and two of its tile-drained subbasins (493 and 863 ha) from mid-1992 through 2000. The cumulative NO3-N load from the catchment was 168 kg ha(-1), and 176 and 229 kg ha(-1) from the subbasins. The outlet had greater total discharge (1831 mm) and smaller flow-weighted mean NO3-N concentration (9.2 mg L(-1)) than the subbasins, while the larger subbasin had greater discharge (1712 vs. 1559 mm) and mean NO3-N concentration (13.4 vs. 11.3 mg L(-1)) than the smaller subbasin. Concentrations exceeding 10 mg L(-1) were common, but least frequent at the outlet. Nitrate N was generally not diluted by large flows, except during 1993 flooding. The outlet showed smaller NO3-N concentrations at low flows. Relationships between discharge and NO3-N flux showed log-log slopes near 1.0 for the subbasins, and 1.2 for the outlet, considering autocorrelation and measurement-error effects. We estimated denitrification of subbasin NO3-N fluxes in a hypothetical wetland using published data. Assuming that temperature and NO3-N supply could limit denitrification, then about 20% of the NO3-N would have been denitrified by a wetland constructed to meet USDA-approved criteria. The low efficiency results from the seasonal timing and NO3-N content of large flows. Therefore, agricultural and wetland best management practices (BMPs) are needed to achieve water quality goals in tile-drained watersheds.

Nitrogen (N) loss from agricultural systems raises concerns about the potential impact of farming practices on environmental quality. N is a critical input to agricultural production. However, there is little understanding of the interactions among crop water use, N application rates, and soil types. This study was designed to quantify these interactions in corn ( Zea mays L.) grown in production-size fields in central Iowa on the Clarion-Nicollet-Webster soil association. Seasonal water use varied by soil type and N application rate. Yield varied with N application rate, with the highest average yield obtained at 100 kg ha(-1). N use efficiency (NUE) decreased with increasing N application rates, having values around 50%. Water use efficiency (WUE) decreased as N fertilizer rates increased. Analysis of plant growth patterns showed that in the low organic matter soils (lower water-holding capacities), potential yield was not achieved because of water deficits during the grain-filling period. Using precipitation data coupled with daily water use throughout the season, lower organic matter soils showed these soils began to drain earlier in the spring and continued to drain more water throughout the season. The low NUE in these soils together with increased drainage lead to greater N loss from these soils. Improved management decisions have shown that it is possible to couple water use patterns with N application to increase both WUE and NUE.

Nitrogen (N) is applied worldwide to produce food. It is in the atmosphere, soil, and water and is essential to all life. N for agriculture includes fertilizer, biologically fixed, manure, recycled crop residue, and soil-mineralized N. Presently, fertilizer N is a major source of N, and animal manure N is inefficiently used. Potential environmental impacts of N excreted by humans are increasing rapidly with increasing world populations. Where needed, N must be efficiently used because N can be transported immense distances and transformed into soluble and/or gaseous forms that pollute water resources and cause greenhouse effects. Unfortunately, increased amounts of gaseous N enter the environment as N2O to cause greenhouse warming and as NH3 to shift ecological balances of natural ecosystems. Large amounts of N are displaced with eroding sediments in surface waters. Soluble N in runoff or leachate water enters streams, rivers, and groundwater. High-nitrate drinking water can cause methemoglobinemia, while nitrosamines are associated with various human cancers. We describe the benefits, but also how N in the wrong form or place results in harmful effects on humans and animals, as well as to ecological and environmental systems.

The purpose of this research was to determine the efficiency of a polymer biocover for the abatement of H2S and NH3 emissions from an east-central Missouri swine lagoon with a total surface area of 7800 m2. The flux rate of NH3, H2S, and CH4 was monitored continuously from two adjacent, circular (d = 66 m) control and treatment plots using a nonintrusive, micrometeorological method during three independent sampling periods that ranged between 52 and 149 hr. Abatement rates were observed to undergo a temporal acclimation event in which NH3 abatement efficiency improved from 17 to 54% (p = < 0.0001 to 0.0005) and H2S abatement efficiency improved from 23 to 58% (p < 0.0001) over a 3-month period. The increase in abatement efficiency for NH3 and H2S over the sampling period was correlated with the development of a stable anaerobic floc layer on the bottom surface of the biocover that reduced mass transfer of NH3 and H2S across the surface. Analysis of methanogenesis activity showed that the biocover enhanced the rate of anaerobic digestion by 25% when compared with the control. The biocover-enhanced anaerobic digestion process was shown to represent an effective mechanism to counteract the accumulation of methanogenic substrates in the biocovered lagoon.

Direct multicomponent analysis of malodorous volatile organic compounds (VOCs) present in ambient air samples from 29 swine (Sus scrofa) production facilities was used to develop a 19-component artificial swine odor solution that simulated olfactory properties of swine effluent. Analyses employing either a human panel consisting of 14 subjects or gas chromatography were performed on the air stream from an emission chamber to assess human olfactory responses or odorant concentration, respectively. Analysis of the olfactory responses using Fisher's LSD statistics showed that the subjects were sensitive to changes in air concentration of the VOC standard across dilutions differing by approximately 16%. The effect of chemical synergisms and antagonisms on human olfactory response magnitudes was assessed by altering the individual concentration of nine compounds in artificial swine odor over a twofold concentration range while maintaining the other 18 components at a constant concentration. A synergistic olfactory response was observed when the air concentration of acetic acid was increased relative to the concentration of other VOC odorants in the standard. An antagonistic olfactory response was observed when the air concentration of 4-ethyl phenol was increased relative to the other VOC odorants in the standard. The collective odorant responses for nine major VOCs associated with swine odor were used to develop an olfactory prediction model to estimate human odor response magnitudes to swine manure odorants through measured air concentrations of indicator VOCs. The results of this study show that direct multicomponent analysis of VOCs emitted from swine effluent can be applied toward estimating perceived odor intensity.

Gaseous emissions from swine (Sus scrofa) manure storage systems represent a concern to air quality due to the potential effects of hydrogen sulfide, ammonia, methane, and volatile organic compounds on environmental quality and human health. The lack of knowledge concerning functional aspects of swine manure management systems has been a major obstacle in the development and optimization of emission abatement technologies for these point sources. In this study, a classification system based on gas emission characteristics and effluent concentrations of total phosphorus (P) and total sulfur (S) was devised and tested on 29 swine manure management systems in Iowa, Oklahoma, and North Carolina in an effort to elucidate functional characteristics of these systems. Four swine manure management system classes were identified that differed in effluent concentrations of P and S, methane (CH4) emission rate, odor intensity, and air concentration of volatile organic compounds (VOCs). Odor intensity and the concentration of VOCs in air emitted from swine manure management systems were strongly correlated (r2 = 0.88). The concentration of VOC in air samples was highest with outdoor swine manure management systems that received a high input of volatile solids (Type 2). These systems were also shown to have the highest odor intensity levels. The emission rate for VOCs and the odor intensity associated with swine manure management systems were inversely correlated with CH4 and ammonia (NH3) emission rates. The emission rates of CH4, NH3, and VOCs were found to be dependent upon manure loading rate and were indirectly influenced by animal numbers.

Cotton (Gossypium hirsutum L.) plants grown under field water deficits exhibited an 80 to 85% reduction in leaf area index, plant height, and dry matter accumulation compared with irrigated controls. Midday photosynthetic rates of dryland plants decreased 2-fold, and canopy temperatures increased to 40 degrees C at 80 days after planting compared with canopy temperatures of 30 degrees C for irrigated plants. Leaves from dryland plants which had exhibited canopy temperatures of 40 degrees C for several weeks accumulated stainable levels of polypeptides with apparent molecular weights of 100, 94, 89, 75, 60, 58, 37, and 21 kilodaltons. These polypeptides did not accumulate in leaves from irrigated plants.Addition of [(35)S]methionine to leaves of growth chamber-grown cotton plants and subsequent incubation at 40 degrees C for 3 hours radiolabeled polypeptides with molecular weights similar to those that accumulate in dryland cotton leaves. These data suggest that the proteins which accumulate in water-stressed cotton leaves at elevated temperatures (40 degrees C) are heat shock proteins and that these proteins can accumulate to substantial levels in field-stressed plants.

The effects of water deficits on plant morphology and biochemistry were analyzed in two photoperiodic strains of field-grown cotton (Gossypium hirsutum L.). Plants grown under dryland conditions exhibited a 40 to 85% decrease in leaf number, leaf area index, leaf size, plant height, and total weight per plant. Gross photosynthesis decreased from 0.81 to 0.47 milligram CO(2) fixed per meter per second and the average midday water, osmotic, and turgor potentials decreased to -2.1, -2.4, and 0.3 megapascals, respectively.There was a progressive increase in glutathione reductase activity and in the cellular antioxidant system in the leaves of stressed plants compared to the irrigated controls. The stress-induced increases in enzyme activity occurred at all canopy positions analyzed.Irrigation of the dryland plots following severe water stress resulted in a 50% increase in leaf area per gram fresh weight in newly expanded leaves of both strains over the leaves which had expanded under the dryland conditions. Paraquat resistance (a relative measure of the cellular antioxidant system) decreased in the strain T25 following irrigation. Glutathione reductase activities remained elevated in the T25 and T185 leaves which were expanded fully prior to irrigation and in the leaves which expanded following the irrigation treatment.

Activity of glutathione reductase has been related to stress tolerance; however, these enzyme assays are generally conducted at 25 degrees C. Foliage temperature varies greatly in the field in response to soil water availability and ambient conditions and this may affect enzyme response. This study was conducted to determine the effect of changing foliage temperature on glutathione reductase activity of wheat under field conditions. Wheat leaf glutathione reductase was purified and the temperature response of the enzyme was determined at 2.5 degrees C intervals between 12.5 and 45 degrees C. These data, in conjunction with continuous measurements of field-grown wheat foliage temperatures, were used to compare the temperature-related changes in potential glutathione reductase activities in water stressed and control plants. Assuming saturating substrate levels, the results indicate that early in the season the daily potential enzyme activity of the irrigated and stressed plants could never have reached the daily activity predicted from the 25 degrees C (room temperature) measurements. Later in the season, the daily potential activity of the irrigated plants was lower, and the daily potential activity of the stressed plants was higher, than the activities predicted from the 25 degrees C determinations. These results suggest that a better understanding of the regulation of plant metabolism will be obtained by linking continuous temperature measurements of plant foliage with enzyme responses to temperature.