Simulating Long‐Term and Residual Effects of Nitrogen Fertilization on Corn Yields, Soil Carbon Sequestration, and Soil Nitrogen Dynamics

He, Xiaoliang; Izaurralde, R. C.; Vanotti, Matías B.; Williams, J. R.; Thomson, Allison M.

doi:10.2134/jeq2005.0259

Cited by 28 publications

(13 citation statements)

References 52 publications

(58 reference statements)

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“…However, there is a clear decreasing trend under the control and mineral applications during the last ten years. There is evidence that N application can increase grain yields and biomass (He et al, 2006). In this study, the N application shows a significant effect on carbon biomass during the third five-year period (i.e., from the 11th to 15th years of fertilization in Fig.…”

Section: Above-ground Carbon Biomass and Carbon Inputmentioning

confidence: 50%

Soil organic carbon dynamics under long-term fertilizations in arable land of northern China

et al. 2010

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Abstract. Soil carbon sequestration is a complex process influenced by agricultural practices, climate and soil conditions. This paper reports a study of long-term fertilization impacts on soil organic carbon (SOC) dynamic from six long-term experiments. The experiment sites are located from warm-temperate zone with a double-cropping system of corn (Zea mays L.) -wheat (Triticum Aestivium L.) rotation, to mild-temperate zones with mono-cropping systems of continuous corn, or a three-year rotation of corn-wheatwheat. Mineral fertilizer applications result in an increasing trend in SOC except in the arid and semi-arid areas with the mono-cropping systems. Additional manure application is important to maintain SOC level in the arid and semi-arid areas. Carbon conversion rate is significant lower in the warmtemperate zone with double cropping system (6.8%-7.7%) than that in the mild-temperate areas with mono-cropping systems (15.8%-31.0%). The conversion rate is significantly correlated with annual precipitation and active accumulative temperature, i.e., higher conversion rate under lower precipitation and/or temperature conditions. Moreover, soil high in clay content has higher conversion rate than soils low in clay content. Soil carbon sequestration rate ranges from 0.07 to 1.461 t ha −1 year −1 in the upland of northern China. There is significantly linear correlation between soil carbon sequestration and carbon input at most sites, indicating that these soils are not carbon-saturated thus have potential to migrate more CO 2 from atmosphere.

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Section: Above-ground Carbon Biomass and Carbon Inputmentioning

confidence: 50%

Soil organic carbon dynamics under long-term fertilizations in arable land of northern China

et al. 2010

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“…EPIC was designed, in principle, to explore the impacts of soil erosion on crop productivity [49], and evolved with continued refinements to approach carbon and nutrient cycling via submodels; also, additional capacity was introduced to predict water quality and the response of crops to atmospheric CO 2 [50]. EPIC and the models which have evolved from it have been applied extensively to a variety of soils and cropping systems worldwide [51].…”

Section: Model Simulationmentioning

confidence: 99%

Assessing Nitrogen Use Efficiency and Nitrogen Loss in a Forage-Based System Using a Modeling Approach

Piccini¹,

Bene²,

Farina³

et al. 2016

Agronomy

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Abstract:In intensive agriculture, N supply often exceeds crop requirements, even in nitrate vulnerable zones (NVZ). In farmland, the N surplus gives rise to NO 3´l eaching and consequent groundwater pollution. The present study aimed at proposing measures to reduce N leaching and hence improve N efficiency in a buffalo livestock farm located in the NVZ of Latina plain (Central Italy). The farm was cultivated with forage crops in a double annual crop rotation: Italian ryegrass (Lolium multiflorum Lam.) in winter and silage corn (Zea mays L.) in summer. Mineral and organic fertilizers were supplied to both crops. The annual N budget and soil solution NO 3 -N concentrations were evaluated using a modeling approach. The performance of the WinEPIC model in simulating the response of the NO 3 -N concentration in percolation to the N application rate was assessed and validated by field measurements of the NO 3 -N concentration in the soil solution. Three scenarios were proposed to identify the best practice to minimize the environmental impact of N application without significant yield loss. Also, recommendations of best practices in N fertilization and animal manure spreading were given. This study thus provides useful preliminary information for decision-making in agriculture/environmental policies.

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“…The model has evolved continuously since 1985, with continued refinements to the carbon and nutrient cycling submodels, and additional capacity introduced related to water quality and the response of crops to atmospheric CO 2 (Gassman et al 2005). EPIC, and the models that have evolved from it such as APEX, have been applied extensively to cropping systems worldwide on a variety of soils and cropping systems (see He et al 2006 for a review), and a number of validation studies have been performed to explore its handling of nutrient cycling and nutrient loss (Gassman et al 2005), including tile drainage (e.g., Chung et al 2001). …”

Section: Epicmentioning

confidence: 99%

Modeling denitrification in a tile-drained, corn and soybean agroecosystem of Illinois, USA

et al. 2008

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Denitrification is known as an important pathway for nitrate loss in agroecosystems. It is important to estimate denitrification fluxes to close field and watershed N mass balances, determine greenhouse gas emissions (N 2 O), and help constrain estimates of other major N fluxes (e.g., nitrate leaching, mineralization, nitrification). We compared predicted denitrification estimates for a typical corn and soybean agroecosystem on a tile drained Mollisol from five models (DAYCENT, SWAT, EPIC, DRAINMOD-N II and two versions of DNDC, 82a and 82h), after first calibrating each model to crop yields, water flux, and nitrate leaching. Known annual crop yields and daily flux values (water, nitrate-N) for 1993-2006 were provided, along with daily environmental variables (air temperature, precipitation) and soil characteristics. Measured denitrification fluxes were not available. Model output for 1997-2006 was then compared for a range of annual, monthly and daily fluxes. Each model was able to estimate corn and soybean yields accurately, and most did well in estimating riverine water and nitrate-N fluxes (1997-2006 mean measured nitrate-N loss 28 kg N ha -1 year -1 , model range 21-28 kg N ha -1 year -1 ). Monthly patterns in observed riverine nitrate-N flux were generally reflected in model output (r 2 values ranged from 0.51 to 0.76). Nitrogen fluxes that did not have corresponding measurements were quite variable across the models, including 10-year average denitrification estimates, ranging from 3.8 to 21 kg N ha -1 year -1 and substantial variability in simulated soybean N 2 fixation, N harvest, and the change in soil organic N pools. DNDC82a and DAYCENT gave comparatively low estimates of total denitrification flux (3.8 and 5.6 kg N ha -1 year -1 , respectively) with similar patterns controlled primarily by moisture. DNDC82h predicted similar fluxes until 2003, when estimates were abruptly much greater. SWAT and DRAINMOD predicted larger denitrification fluxes (about 17-18 kg N ha -1 year -1 ) with monthly values that were similar. EPIC denitrification was intermediate between all models (11 kg N ha -1 year -1 ). Predicted daily fluxes during a high precipitation year (2002) varied considerably among models regardless of whether the models had comparable annual fluxes for the years. Some models predicted large denitrification fluxes for a few days, whereas others predicted large fluxes persisting for several weeks to months. Modeled denitrification fluxes were controlled mainly by soil moisture status and nitrate available to be denitrified, and the way denitrification in each model responded to moisture status greatly determined the flux. Because denitrification is dependent on the amount of nitrate available at any given time, modeled differences in other components of the N cycle (e.g., N 2 fixation, N harvest, change in soil N storage) no doubt led to differences in predicted denitrification. Model comparisons suggest our ability to accurately predict denitrification fluxes (without known values) from the dominant...

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Simulating Long‐Term and Residual Effects of Nitrogen Fertilization on Corn Yields, Soil Carbon Sequestration, and Soil Nitrogen Dynamics

Cited by 28 publications

References 52 publications

Soil organic carbon dynamics under long-term fertilizations in arable land of northern China

Soil organic carbon dynamics under long-term fertilizations in arable land of northern China

Assessing Nitrogen Use Efficiency and Nitrogen Loss in a Forage-Based System Using a Modeling Approach

Modeling denitrification in a tile-drained, corn and soybean agroecosystem of Illinois, USA

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