Economic and environmental nitrate leaching consequences of 4R nitrogen management practices including use of inhibitors for corn production in Ontario.

Nitrate (NO3-) leaching has negative human and environmental health consequences that can be attributed to and mitigated by agricultural decision making. The purpose of this study is to examine the economic and environmental nitrogen (N) leaching reduction from 4R (Right Rate, Right Source, Right Time, Right Placement) agricultural management practices, including application methods, timing and rates, and the use of nitrification and urease inhibitors, for Ontario corn production. This study employed an integrated biophysical and economic GIS-based simulation model considering corn yields, prices, and production costs, and environmental losses, under historical weather scenarios, with NO3- leaching constraints. Reducing N application from historical to model optimized agronomic rates sharply lowered corn NO3- leaching from 75.3 to 24.9 kt N per year. Increasing model restrictions on corn NO3- leaching increased the use of broadcast and sidedress application methods compared to injection and lower overall production. They also increased the use of nitrification and urease inhibitors, which increased N use efficiency, because they allowed lower leaching from corn production, for a price. Leaching decreases from restrictions trade-off with ammonia (NH3) volatilization increases, but there was no trade-off with nitrous oxide (N2O) emissions. This highlighted the importance of considering net N losses and production trade-offs by policy decision-makers when developing N loss reduction strategies.

Modifying fertilizer rate and application method reduces environmental nitrogen losses and increases corn yield in Ontario.

Nitrogen (N) use in corn production is an important driver of nitrous oxide (N2O) emissions and 4R (Right source, Right rate, Right time and Right place) fertilizer practices have been proposed to mitigate emissions. However, combined 4R practices have not been assessed for their potential to reduce N2O emissions at the provincial-scale while also considering trade-offs with other N losses such as leaching or ammonia (NH3) volatilization. The objectives of this study were to develop, validate, and apply a Denitrification-Decomposition model framework at 270 distinct soil-climate regions in Ontario to simulate corn yield and N2O emissions across eleven fertilizer management scenarios during 1986-2015. The results show that broadcasting fertilizer at the surface without incorporation had the highest environmental N loss which was primarily caused by NH3 volatilization. When injected at planting or at sidedress, the NH3 loss was reduced considerably. However, because more N was left in the soil, injection and sidedressing induced more losses by nitrate leaching and N2O emissions. Reduction of N rate as proposed by the DNDC model did not affect crop yield but decreased leaching and N2O emissions. Addition of inhibitors promoted a further reduction in N2O emission (11-16%) although lesser than the reduction in N rate. Overall, our results emphasize that N rate adjustment following improvements in placement, use of inhibitors, and application timings can mitigate N2O emissions by 42-57% and result in 3-4% greater yields compared to baseline scenario in Ontario corn production.

Simulating nitrogen management impacts on maize production in the U.S. Midwest.

Nutrient loss reduction strategies have recently been developed in the U.S. Midwest to decrease the environmental footprint associated with nitrogen (N) fertilizer use. Although these strategies generally suggest decreasing N rates and shifting the timing of N application from fall to spring, the spatiotemporal impacts of these practices on maize yield and fertilizer N use efficiency (NUE, kg grain yield increase per kg N applied) have not been assessed at the watershed scale using crop simulation models. We simulated the effects of N fertilizer rate (0, 168, 190, 224 kg N ha-1) and application timing [fall-applied N (FN): 100% N applied on 1 December; spring-applied N (SN): 100% N applied 10 days before planting; split N: 66% N applied on 1 December + 34% N applied 10 days before planting] on maize grain yield (GY) across 3042 points in Illinois during 2011-2015 using the DSSAT-CERES-Maize model. When simulations were scaled up to the watershed level, results suggest that increases in average maize GY for SN compared to FN occurred in years with higher than average winter rainfall (2011, 2013), whereas yields were similar (+/- 4%) in 2012, 2014, and 2015. Accordingly, differences in NUE for SN compared to FN were small (0.0-1.4 kg GY/kg N) when cumulative winter rainfall was < 300 mm, but increased to 0.1-9.2 kg GY/kg N when winter rainfall was > 500 mm at both 168 kg N ha-1 and 224 kg N ha-1. The combined practice of reducing N fertilizer amounts from 224 kg N ha-1 to 190 kg N ha-1 and shifting from FN to SN resulted in a wide range of yield responses during 2011-2015, with the probability of increasing yields varying from <10% to >70% of simulation points within a watershed. Positive impacts on both GY and NUE occurred in only 60% of simulations for this scenario, highlighting the challenge of simultaneously improving yield and NUE with a 15% N rate reduction in this region.

A Vision for Incorporating Environmental Effects into Nitrogen Management Decision Support Tools for U.S. Maize Production.

Meeting crop nitrogen (N) demand while minimizing N losses to the environment has proven difficult despite significant field research and modeling efforts. To improve N management, several real-time N management tools have been developed with a primary focus on enhancing crop production. However, no coordinated effort exists to simultaneously address sustainability concerns related to N losses at field- and regional-scales. In this perspective, we highlight the opportunity for incorporating environmental effects into N management decision support tools for United States maize production systems by integrating publicly available crop models with grower-entered management information and gridded soil and climate data in a geospatial framework specifically designed to quantify environmental and crop production tradeoffs. To facilitate advances in this area, we assess the capability of existing crop models to provide in-season N recommendations while estimating N leaching and nitrous oxide emissions, discuss several considerations for initial framework development, and highlight important challenges related to improving the accuracy of crop model predictions. Such a framework would benefit the development of regional sustainable intensification strategies by enabling the identification of N loss hotspots which could be used to implement spatially explicit mitigation efforts in relation to current environmental quality goals and real-time weather conditions. Nevertheless, we argue that this long-term vision can only be realized by leveraging a variety of existing research efforts to overcome challenges related to improving model structure, accessing field data to enhance model performance, and addressing the numerous social difficulties in delivery and adoption of such tool by stakeholders.

Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models: Current status and future directions.

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO2) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-long (1901-2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project and two observation-based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 1015 g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr-1 with a median value of 51 Pg C yr-1 during 2001-2010. The largest uncertainty in SOC stocks exists in the 40-65°N latitude whereas the largest cross-model divergence in Rh are in the tropics. The modeled SOC change during 1901-2010 ranges from -70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble-estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO2 and nitrogen deposition over intact ecosystems increased SOC stocks-even though the responses varied significantly among models. Model representations of temperature and moisture sensitivity, nutrient limitation, and land use partially explain the divergent estimates of global SOC stocks and soil C fluxes in this study. In addition, a major source of systematic error in model estimations relates to nonmodeled SOC storage in wetlands and peatlands, as well as to old C storage in deep soil layers.

Complex spatiotemporal responses of global terrestrial primary production to climate change and increasing atmospheric CO2 in the 21st century.

Quantitative information on the response of global terrestrial net primary production (NPP) to climate change and increasing atmospheric CO2 is essential for climate change adaptation and mitigation in the 21st century. Using a process-based ecosystem model (the Dynamic Land Ecosystem Model, DLEM), we quantified the magnitude and spatiotemporal variations of contemporary (2000s) global NPP, and projected its potential responses to climate and CO2 changes in the 21st century under the Special Report on Emission Scenarios (SRES) A2 and B1 of Intergovernmental Panel on Climate Change (IPCC). We estimated a global terrestrial NPP of 54.6 (52.8-56.4) PgC yr(-1) as a result of multiple factors during 2000-2009. Climate change would either reduce global NPP (4.6%) under the A2 scenario or slightly enhance NPP (2.2%) under the B1 scenario during 2010-2099. In response to climate change, global NPP would first increase until surface air temperature increases by 1.5 °C (until the 2030s) and then level-off or decline after it increases by more than 1.5 °C (after the 2030s). This result supports the Copenhagen Accord Acknowledgement, which states that staying below 2 °C may not be sufficient and the need to potentially aim for staying below 1.5 °C. The CO2 fertilization effect would result in a 12%-13.9% increase in global NPP during the 21st century. The relative CO2 fertilization effect, i.e. change in NPP on per CO2 (ppm) bases, is projected to first increase quickly then level off in the 2070s and even decline by the end of the 2080s, possibly due to CO2 saturation and nutrient limitation. Terrestrial NPP responses to climate change and elevated atmospheric CO2 largely varied among biomes, with the largest increases in the tundra and boreal needleleaf deciduous forest. Compared to the low emission scenario (B1), the high emission scenario (A2) would lead to larger spatiotemporal variations in NPP, and more dramatic and counteracting impacts from climate and increasing atmospheric CO2.

Arsenic contamination in soil-water-plant (rice, Oryza sativa L.) continuum in central and sub-mountainous Punjab, India.

In the present study, Arsenic (As) concentrations in underground water, soil, and plants (rice) and their inter-relationships in central and sub-mountainous Punjab, India were studied. Approximately, 32% of the tubewell water samples had As concentrations greater than the maximum permissible limit (10 µg As L(-1)) set by the World Health Organization (WHO) whereas in hand pump waters, As concentrations were within the safe range (i.e. <10 µg As L(-1)). As concentrations in tubewell waters were significantly correlated with As concentrations in surface soil (r = 0.57; P < 0.05) and plant samples (r = 0.27-0.82; P < 0.05) in central and sub-mountainous Punjab. The estimated daily intake of As through human consumption in rural and urban population was 0.016 and 0.012 µg day(-1) kg(-1) body weight respectively.

Do nitrogen fertilizers stimulate or inhibit methane emissions from rice fields?

In rice cultivation, there are controversial reports on net impacts of nitrogen (N) fertilizers on methane (CH 4 ) emissions. Nitrogen fertilizers increase crop growth as well as alter CH 4 producing (Methanogens) and consuming (Methanotrophs) microbes, and thereby produce complex effects on CH 4 emissions. Objectives of this study were to determine net impact of N fertilizers on CH 4 emissions and to identify their underlying mechanisms in the rice soils. Database was obtained from 33 published papers that contained CH 4 emissions observations from N fertilizer (28-406 kg N ha-1 ) treatment and its control. Results have indicated that N fertilizers increased CH 4 emissions in 98 of 155 data pairs in rice soils. Response of CH 4 emissions per kg N fertilizer was significantly (P < 0.05) greater at < 140 kg N ha-1 than > 140 kg N ha-1 indicating that substrate switch from CH 4 to ammonia by Methanotrophs may not be a dominant mechanism for increased CH 4 emissions. On the contrary, decreased CH 4 emission in intermittent drainage by N fertilizers has suggested the stimulation of Methanotrophs in rice soils. Effects of N fertilizer stimulated Methanotrophs in reducing CH 4 emissions were modified by the continuous flood irrigation due to limitation of oxygen to Methanotrophs. Greater response of CH 4 emissions per kg N fertilizer in urea than ammonia sulfate probably indicated the interference of sulfate in the CH 4 production process. Overall, response of CH 4 emissions to N fertilizers was correlated with N-induced crop yield (r = +0.39; P < 0.01), probably due to increased carbon substrates for Methanogens. Using CH 4 emission observations, this meta-analysis has identified dominant microbial processes that control net effects of N fertilizers on CH 4 emissions in rice soils. Finally, we have provided a conceptual model that included microbial processes and controlling factors to predict effects of N fertilizers on CH 4 emissions in rice soils.