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Author |
Perego, A.; Sanna, M.; Giussani, A.; Chiodini, M.E.; Fumagalli, M.; Pilu, S.R.; Bindi, M.; Moriondo, M.; Acutis, M. |
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Title |
Designing a high-yielding maize ideotype for a changing climate in Lombardy plain northern Italy |
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Journal Article |
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Year |
2014 |
Publication |
Science of the Total Environment |
Abbreviated Journal |
Science of the Total Environment |
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Volume  |
499 |
Issue |
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Pages |
497-509 |
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Keywords |
Agriculture/*methods/standards; *Climate Change; Droughts; Italy; Nitrogen/analysis; Soil; Water Supply/statistics & numerical data; Zea mays/*growth & development/standards; Climate change; Crop model; Maize; Water use adaptation |
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Abstract |
• ARMOSA model simulated a maize ideotype with drought adaptation under climate change. • The ideotype needs less water for higher yield compared to current hybrids. • Higher production involves more crop residues that enhance soil C sequestration. • Soil organic C may generally decrease and N leaching will increase in sandy soil. The expected climate change will affect the maize yields in view of air temperature increase and scarce water availability. The application of biophysical models offers the chance to design a drought-resistant ideotype and to assist plant breeders and agronomists in the assessment of its suitability in future scenarios. The aim of the present work was to perform a model-based estimation of the yields of two hybrids, current vs ideotype, under future climate scenarios (2030–2060 and 2070–2100) in Lombardy (northern Italy), testing two options of irrigation (small amount at fixed dates vs optimal water supply), nitrogen (N) fertilization (300 vs 400 kg N ha− 1), and crop cycle durations (current vs extended). For the designing of the ideotype we set several parameters of the ARMOSA process-based crop model: the root elongation rate and maximum depth, stomatal resistance, four stage-specific crop coefficients for the actual transpiration estimation, and drought tolerance factor. The work findings indicated that the current hybrid ensures good production only with high irrigation amount (245–565 mm y− 1). With respect to the current hybrid, the ideotype will require less irrigation water (− 13%, p < 0.01) and it resulted in significantly higher yield under water stress condition (+ 15%, p < 0.01) and optimal water supply (+ 2%, p < 0.05). The elongated cycle has a positive effect on yield under any combination of options. Moreover, higher yields projected for the ideotype implicate more crop residues to be incorporated into the soil, which are positively correlated with the SOC sequestration and negatively with N leaching. The crop N uptake is expected to be adequate in view of higher rate of soil mineralization; the N fertilization rate of 400 kg N ha− 1 will involve significant increasing of grain yield, and it is expected to involve a higher rate of SOC sequestration. |
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0048-9697 |
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CropM |
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MA @ admin @ |
Serial |
4633 |
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Author |
Sanz-Cobena, A.; García-Marco, S.; Quemada, M.; Gabriel, J.L.; Almendros, P.; Vallejo, A. |
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Title |
Do cover crops enhance N2O, CO2 or CH4 emissions from soil in Mediterranean arable systems? |
Type |
Journal Article |
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Year |
2014 |
Publication |
Science of the Total Environment |
Abbreviated Journal |
Science of the Total Environment |
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Volume |
466-467 |
Issue |
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Pages |
164-174 |
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Keywords |
Agriculture/*methods; Air Pollutants/*metabolism; Brassica napus/growth & development/metabolism; Crops, Agricultural/growth & development/*metabolism; Gases/metabolism; Greenhouse Effect; Hordeum/growth & development/metabolism; Manure/*analysis; Nitrogen/metabolism; Nitrogen Dioxide/metabolism; Spain; Vicia/growth & development/metabolism; Zea mays/growth & development; Cover crops; GHG emissions; Green manure; Irrigation; Maize |
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This study evaluates the effect of planting three cover crops (CCs) (barley, Hordeum vulgare L.; vetch, Vicia villosa L.; rape, Brassica napus L.) on the direct emission of N(2)O, CO(2) and CH(4) in the intercrop period and the impact of incorporating these CCs on the emission of greenhouse gas (GHG) from the forthcoming irrigated maize (Zea mays L.) crop. Vetch and barley were the CCs with the highest N(2)O and CO(2) losses (75 and 47% increase compared with the control, respectively) in the fallow period. In all cases, fluxes of N(2)O were increased through N fertilization and the incorporation of barley and rape residues (40 and 17% increase, respectively). The combination of a high C:N ratio with the addition of an external source of mineral N increased the fluxes of N(2)O compared with -Ba and -Rp. The direct emissions of N(2)O were lower than expected for a fertilized crop (0.10% emission factor, EF) compared with other studies and the IPCC EF. These results are believed to be associated with a decreased NO(3)(-) pool due to highly denitrifying conditions and increased drainage. The fluxes of CO(2) were in the range of other fertilized crops (i.e., 1118.71-1736.52 kg CO(2)-Cha(-1)). The incorporation of CC residues enhanced soil respiration in the range of 21-28% for barley and rape although no significant differences between treatments were detected. Negative CH(4) fluxes were measured and displayed an overall sink effect for all incorporated CC (mean values of -0.12 and -0.10 kg CH(4)-Cha(-1) for plots with and without incorporated CCs, respectively). |
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0048-9697 |
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CropM |
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MA @ admin @ |
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4639 |
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Author |
Kraus, D.; Weller, S.; Klatt, S.; Haas, E.; Wassmann, R.; Kiese, R.; Butterbach-Bahl, K. |
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A new LandscapeDNDC biogeochemical module to predict CH4 and N2O emissions from lowland rice and upland cropping systems |
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Journal Article |
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Year |
2015 |
Publication |
Plant and Soil |
Abbreviated Journal |
Plant Soil |
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386 |
Issue |
1-2 |
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125-149 |
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Keywords |
methane; nitrous oxide; paddy rice; maize; model; nitrous-oxide emissions; process-based model; methane transport capacity; process-oriented model; pnet-n-dndc; forest soils; paddy soils; sensitivity-analysis; residue management; organic-matter |
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Replacing paddy rice by upland systems such as maize cultivation is an on-going trend in SE Asia caused by increasing water scarcity and higher demand for meat. How such land management changes will feedback on soil C and N cycles and soil greenhouse gas emissions is not well understood at present. A new LandscapeDNDC biogeochemical module was developed that allows the effect of land management changes on soil C and N cycle to be simulated. The new module is applied in combination with further modules simulating microclimate and crop growth and evaluated against observations from field experiments. The model simulations agree well with observed dynamics of CH (4) emissions in paddy rice depending on changes in climatic conditions and agricultural management. Magnitude and peak emission periods of N (2) O from maize cultivation are simulated correctly, though there are still deficits in reproducing day-to-day dynamics. These shortcomings are most likely related to simulated soil hydrology and may only be resolved if LandscapeDNDC is coupled to more complex hydrological models. LandscapeDNDC allows for simulation of changing land management practices in SE Asia. The possibility to couple LandscapeDNDC to more complex hydrological models is a feature needed to better understand related effects on soil-atmosphere-hydrosphere interactions. |
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0032-079x |
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CropM, ft_macsur |
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MA @ admin @ |
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4530 |
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Klosterhalfen, A.; Herbst, M.; Weihermueller, L.; Graf, A.; Schmidt, M.; Stadler, A.; Schneider, K.; Subke, J.-A.; Huisman, J.A.; Vereecken, H. |
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Title |
Multi-site calibration and validation of a net ecosystem carbon exchange model for croplands |
Type |
Journal Article |
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Year |
2017 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
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Volume |
363 |
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137-156 |
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Keywords |
AgroC; Soil respiration; Carbon balance; Winter wheat; Grassland; NEE; LOLIUM-PERENNE L; SOIL HETEROTROPHIC RESPIRATION; LAND-SURFACE MODELS; EDDY-COVARIANCE; WINTER-WHEAT; CARBOHYDRATE CONTENT; TURNOVER MODEL; ROTHC MODEL; ROOT RATIOS; CO2 EFFLUX |
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Croplands play an important role in the carbon budget of many regions. However, the estimation of their carbon balance remains difficult due to diversity and complexity of the processes involved. We report the coupling of a one-dimensional soil water, heat, and CO2 flux model (SOILCO2), a pool concept of soil carbon turnover (RothC), and a crop growth module (SUCROS) to predict the net ecosystem exchange (NEE) of carbon. The coupled model, further referred to as AgroC, was extended with routines for managed grassland as well as for root exudation and root decay. In a first step, the coupled model was applied to two winter wheat sites and one upland grassland site in Germany. The model was calibrated based on soil water content, soil temperature, biometric, and soil respiration measurements for each site, and validated in terms of hourly NEE measured with the eddy covariance technique. The overall model performance of AgroC was sufficient with a model efficiency above 0.78 and a correlation coefficient above 0.91 for NEE. In a second step, AgroC was optimized with eddy covariance NEE measurements to examine the effect of different objective functions, constraints, and data-transformations on estimated NEE. It was found that NEE showed a distinct sensitivity to the choice of objective function and the inclusion of soil respiration data in the optimization process. In particular, both positive and negative day- and nighttime fluxes were found to be sensitive to the selected optimization strategy. Additional consideration of soil respiration measurements improved the simulation of small positive fluxes remarkably. Even though the model performance of the selected optimization strategies did not diverge substantially, the resulting cumulative NEE over simulation time period differed substantially. Therefore, it is concluded that data transformations, definitions of objective functions, and data sources have to be considered cautiously when a terrestrial ecosystem model is used to determine NEE by means of eddy covariance measurements. (C) 2017 Elsevier B.V. All rights reserved. |
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2017-11-09 |
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0304-3800 |
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CropM, ft_MACSUR |
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MA @ admin @ |
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5216 |
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Author |
Hjelkrem, A.-G.R.; Höglind, M.; van Oijen, M.; Schellberg, J.; Gaiser, T.; Ewert, F. |
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Sensitivity analysis and Bayesian calibration for testing robustness of the BASGRA model in different environments |
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Journal Article |
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Year |
2017 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
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359 |
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80-91 |
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Keywords |
Metropolis-hasting; Morris method; Reducing complexity; Robustness |
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Highlights • The parameters to be fixed were consistent across sites. • Model calibration must be performed separately for each specific case. • Possible to reduce model parameters from 66 to 45. • Strong model reductions must be avoided. • The error term for the training data were characterised by timing (phase shift). Abstract Proper parameterisation and quantification of model uncertainty are two essential tasks in improvement and assessment of model performance. Bayesian calibration is a method that combines both tasks by quantifying probability distributions for model parameters and outputs. However, the method is rarely applied to complex models because of its high computational demand when used with high-dimensional parameter spaces. We therefore combined Bayesian calibration with sensitivity analysis, using the screening method by Morris (1991), in order to reduce model complexity by fixing parameters to which model output was only weakly sensitive to a nominal value. Further, the robustness of the model with respect to reduction in the number of free parameters were examined according to model discrepancy and output uncertainty. The process-based grassland model BASGRA was examined in the present study on two sites in Norway and in Germany, for two grass species (Phleum pratense and Arrhenatherum elatius). According to this study, a reduction of free model parameters from 66 to 45 was possible. The sensitivity analysis showed that the parameters to be fixed were consistent across sites (which differed in climate and soil conditions), while model calibration had to be performed separately for each combination of site and species. The output uncertainty decreased slightly, but still covered the field observations of aboveground biomass. Considering the training data, the mean square error for both the 66 and the 45 parameter model was dominated by errors in timing (phase shift), whereas no general pattern was found in errors when using the validation data. Stronger model reduction should be avoided, as the error term increased and output uncertainty was underestimated. |
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0304-3800 |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
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5010 |
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