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1.
Front Plant Sci ; 9: 436, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29706974

RESUMO

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha-1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3% lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost.

2.
Glob Chang Biol ; 24(1): e303-e317, 2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-28805279

RESUMO

The frequency and intensity of extreme weather years, characterized by abnormal precipitation and temperature, are increasing. In isolation, these years have disproportionately large effects on environmental N losses. However, the sequence of extreme weather years (e.g., wet-dry vs. dry-wet) may affect cumulative N losses. We calibrated and validated the DAYCENT ecosystem process model with a comprehensive set of biogeophysical measurements from a corn-soybean rotation managed at three N fertilizer inputs with and without a winter cover crop in Iowa, USA. Our objectives were to determine: (i) how 2-year sequences of extreme weather affect 2-year cumulative N losses across the crop rotation, and (ii) if N fertilizer management and the inclusion of a winter cover crop between corn and soybean mitigate the effect of extreme weather on N losses. Using historical weather (1951-2013), we created nine 2-year scenarios with all possible combinations of the driest ("dry"), wettest ("wet"), and average ("normal") weather years. We analyzed the effects of these scenarios following several consecutive years of relatively normal weather. Compared with the normal-normal 2-year weather scenario, 2-year extreme weather scenarios affected 2-year cumulative NO3- leaching (range: -93 to +290%) more than N2 O emissions (range: -49 to +18%). The 2-year weather scenarios had nonadditive effects on N losses: compared with the normal-normal scenario, the dry-wet sequence decreased 2-year cumulative N2 O emissions while the wet-dry sequence increased 2-year cumulative N2 O emissions. Although dry weather decreased NO3- leaching and N2 O emissions in isolation, 2-year cumulative N losses from the wet-dry scenario were greater than the dry-wet scenario. Cover crops reduced the effects of extreme weather on NO3- leaching but had a lesser effect on N2 O emissions. As the frequency of extreme weather is expected to increase, these data suggest that the sequence of interannual weather patterns can be used to develop short-term mitigation strategies that manipulate N fertilizer and crop rotation to maximize crop N uptake while reducing environmental N losses.


Assuntos
Ecossistema , Nitrogênio/química , Tempo (Meteorologia) , Agricultura/métodos , Simulação por Computador , Produtos Agrícolas , Fertilizantes/análise , Iowa , Modelos Teóricos , Estações do Ano , Solo
3.
PLoS One ; 12(3): e0172293, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28249014

RESUMO

Nitrogen fertilization is critical to optimize short-term crop yield, but its long-term effect on soil organic C (SOC) is uncertain. Here, we clarify the impact of N fertilization on SOC in typical maize-based (Zea mays L.) Midwest U.S. cropping systems by accounting for site-to-site variability in maize yield response to N fertilization. Within continuous maize and maize-soybean [Glycine max (L.) Merr.] systems at four Iowa locations, we evaluated changes in surface SOC over 14 to 16 years across a range of N fertilizer rates empirically determined to be insufficient, optimum, or excessive for maximum maize yield. Soil organic C balances were negative where no N was applied but neutral (maize-soybean) or positive (continuous maize) at the agronomic optimum N rate (AONR). For continuous maize, the rate of SOC storage increased with increasing N rate, reaching a maximum at the AONR and decreasing above the AONR. Greater SOC storage in the optimally fertilized continuous maize system than in the optimally fertilized maize-soybean system was attributed to greater crop residue production and greater SOC storage efficiency in the continuous maize system. Mean annual crop residue production at the AONR was 22% greater in the continuous maize system than in the maize-soybean system and the rate of SOC storage per unit residue C input was 58% greater in the monocrop system. Our results demonstrate that agronomic optimum N fertilization is critical to maintain or increase SOC of Midwest U.S. cropland.


Assuntos
Carbono , Produção Agrícola/métodos , Glycine max/crescimento & desenvolvimento , Nitrogênio , Solo , Zea mays/crescimento & desenvolvimento , Fertilizantes , Meio-Oeste dos Estados Unidos
4.
Front Plant Sci ; 7: 1630, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-27891133

RESUMO

Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR's were within the historical N rate error range (40-50 kg N ha-1). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward agronomic, economic, and environmental sustainability.

5.
Glob Chang Biol ; 21(9): 3200-9, 2015 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-25990618

RESUMO

Labile, 'high-quality', plant litters are hypothesized to promote soil organic matter (SOM) stabilization in mineral soil fractions that are physicochemically protected from rapid mineralization. However, the effect of litter quality on SOM stabilization is inconsistent. High-quality litters, characterized by high N concentrations, low C/N ratios, and low phenol/lignin concentrations, are not consistently stabilized in SOM with greater efficiency than 'low-quality' litters characterized by low N concentrations, high C/N ratios, and high phenol/lignin concentrations. Here, we attempt to resolve these inconsistent results by developing a new conceptual model that links litter quality to the soil C saturation concept. Our model builds on the Microbial Efficiency-Matrix Stabilization framework (Cotrufo et al., 2013) by suggesting the effect of litter quality on SOM stabilization is modulated by the extent of soil C saturation such that high-quality litters are not always stabilized in SOM with greater efficiency than low-quality litters.


Assuntos
Ciclo do Carbono , Compostos Orgânicos/química , Fenômenos Fisiológicos Vegetais , Solo/química , Ecossistema , Modelos Biológicos
6.
J Environ Qual ; 44(3): 711-9, 2015 May.
Artigo em Inglês | MEDLINE | ID: mdl-26024252

RESUMO

Little information exists on the potential for N fertilizer application to corn ( L.) to affect NO emissions during subsequent unfertilized crops in a rotation. To determine if N fertilizer application to corn affects NO emissions during subsequent crops in rotation, we measured NO emissions for 3 yr (2011-2013) in an Iowa, corn-soybean [ (L.) Merr.] rotation with three N fertilizer rates applied to corn (0 kg N ha, the recommended rate of 135 kg N ha, and a high rate of 225 kg N ha); soybean received no N fertilizer. We further investigated the potential for a winter cereal rye ( L.) cover crop to interact with N fertilizer rate to affect NO emissions from both crops. The cover crop did not consistently affect NO emissions. Across all years and irrespective of cover crop, N fertilizer application above the recommended rate resulted in a 16% increase in mean NO flux rate during the corn phase of the rotation. In 2 of the 3 yr, N fertilizer application to corn (0-225 kg N ha) did not affect mean NO flux rates from the subsequent unfertilized soybean crop. However, in 1 yr after a drought, mean NO flux rates from the soybean crops that received 135 and 225 kg N ha N application in the corn year were 35 and 70% higher than those from the soybean crop that received no N application in the corn year. Our results are consistent with previous studies demonstrating that cover crop effects on NO emissions are not easily generalizable. When N fertilizer affects NO emissions during a subsequent unfertilized crop, it will be important to determine if total fertilizer-induced NO emissions are altered or only spread across a greater period of time.

7.
Glob Chang Biol ; 20(4): 1339-50, 2014 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-24395533

RESUMO

Global maize production alters an enormous soil organic C (SOC) stock, ultimately affecting greenhouse gas concentrations and the capacity of agroecosystems to buffer climate variability. Inorganic N fertilizer is perhaps the most important factor affecting SOC within maize-based systems due to its effects on crop residue production and SOC mineralization. Using a continuous maize cropping system with a 13 year N fertilizer gradient (0-269 kg N ha(-1) yr(-1)) that created a large range in crop residue inputs (3.60-9.94 Mg dry matter ha(-1) yr(-1)), we provide the first agronomic assessment of long-term N fertilizer effects on SOC with direct reference to N rates that are empirically determined to be insufficient, optimum, and excessive. Across the N fertilizer gradient, SOC in physico-chemically protected pools was not affected by N fertilizer rate or residue inputs. However, unprotected particulate organic matter (POM) fractions increased with residue inputs. Although N fertilizer was negatively linearly correlated with POM C/N ratios, the slope of this relationship decreased from the least decomposed POM pools (coarse POM) to the most decomposed POM pools (fine intra-aggregate POM). Moreover, C/N ratios of protected pools did not vary across N rates, suggesting little effect of N fertilizer on soil organic matter (SOM) after decomposition of POM. Comparing a N rate within 4% of agronomic optimum (208 kg N ha(-1) yr(-1)) and an excessive N rate (269 kg N ha(-1) yr(-1)), there were no differences between SOC amount, SOM C/N ratios, or microbial biomass and composition. These data suggest that excessive N fertilizer had little effect on SOM and they complement agronomic assessments of environmental N losses, that demonstrate N2 O and NO3 emissions exponentially increase when agronomic optimum N is surpassed.


Assuntos
Agricultura/métodos , Fertilizantes , Nitrogênio , Solo/química , Zea mays , Biomassa , Carbono/análise , Produtos Agrícolas , Iowa , Nitrogênio/análise , Microbiologia do Solo
8.
J Environ Qual ; 37(2): 325-32, 2008.
Artigo em Inglês | MEDLINE | ID: mdl-18268294

RESUMO

Nitrogen application can have a significant effect on soil carbon (C) pools, plant biomass production, and microbial biomass C processing. The focus of this study was to investigate the short-term effect of N fertilization on soil CO(2) emission and microbial biomass C. The study was conducted from 2001 to 2003 at four field sites in Iowa representing major soil associations and with a corn (Zea mays L.)-soybean (Glycine max L. Merr.) rotation. The experimental design was a randomized complete block with four replications of four N rates (0, 90, 180, and 225 kg ha(-1)). In the corn year, season-long cumulative soil CO(2) emission was greatest with the zero N application. There was no effect of N applied in the prior year on CO(2) emission in the soybean year, except at one of three sites, where greater applied N decreased CO(2) emission. Soil microbial biomass C (MBC) and net mineralization in soil collected during the corn year was not significantly increased with increase in N rate in two out of three sites. At all sites, soil CO(2) emission from aerobically incubated soil showed a more consistent declining trend with increase in N rate than found in the field. Nitrogen fertilization of corn reduced the soil CO(2) emission rate and seasonal cumulative loss in two out of three sites, and increased MBC at only one site with the highest N rate. Nitrogen application resulted in a reduction of both emission rate and season-long cumulative emission of CO(2)-C from soil.


Assuntos
Agricultura/métodos , Poluentes Atmosféricos/análise , Dióxido de Carbono/análise , Fertilizantes , Nitrogênio , Microbiologia do Solo , Monitoramento Ambiental , Iowa , Glycine max , Zea mays
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