| Records |
| Author |
Kraus, D.; Weller, S.; Klatt, S.; Haas, E.; Wassmann, R.; Kiese, R.; Butterbach-Bahl, K. |
| Title |
A new LandscapeDNDC biogeochemical module to predict CH4 and N2O emissions from lowland rice and upland cropping systems |
Type |
Journal Article |
| Year |
2015 |
Publication |
Plant and Soil |
Abbreviated Journal |
Plant Soil |
| Volume |
386 |
Issue |
1-2 |
Pages |
125-149 |
| 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 |
| Abstract |
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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| Language |
English |
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| ISSN |
0032-079x |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4530 |
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| Author |
Bulak, P.; Walkiewicz, A.; Brzezińska, M. |
| Title |
Plant growth regulators-assisted phytoextraction |
Type |
Journal Article |
| Year |
2014 |
Publication |
Biologia Plantarum |
Abbreviated Journal |
Biol. Plant. |
| Volume |
58 |
Issue |
1 |
Pages |
1-8 |
| Keywords |
auxins; cytokinins; gibberelins; heavy metals; phytoremediation; pollutants; Zea-mays l.; heavy-metals; Pteris-vittata; organic-acids; molecular-mechanisms; contaminated soils; Sedum-alfredii; lead uptake; hyperaccumulation; phytoremediation |
| Abstract |
Plant growth regulators (PRG)-assisted phytoremediation is a technique that could enhance the yield of heavy metal accumulation in plant tissues. So far, a small number of experiments have helped identify three groups of plant hormones that may be useful for this purpose: auxins, cytokinins, and gibberellins. Studies have shown that these hormones positively affect the degree of accumulation of metallic impurities and improve the growth and stress resistance of plants. This review summarizes the present knowledge about PGRs’ impact on phytoextraction yield. |
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English |
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0006-3134 |
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Medium |
Review |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4515 |
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| Author |
Yang, H.; Dobbie, S.; Ramirez-Villegas, J.; Feng, K.; Challinor, A.J.; Chen, B.; Gao, Y.; Lee, L.; Yin, Y.; Sun, L.; Watson, J.; Koehler, A.-K.; Fan, T.; Ghosh, S. |
| Title |
Potential negative consequences of geoengineering on crop production: A study of Indian groundnut |
Type |
Journal Article |
| Year |
2016 |
Publication |
Geophysical Research Letters |
Abbreviated Journal |
Geophys. Res. Let. |
| Volume |
43 |
Issue |
22 |
Pages |
11786-11795 |
| Keywords |
Mangrove Tidal Creek; Land-Ocean Boundary; Carbon-Dioxide; Organic-Matter; River Estuary; European Estuaries; CO2 Fluxes; NE Coast; Water; Bay; fCO(2) (water); air-water CO2 flux; Hugli Estuary; Matla Estuary; Blue Carbon; source of CO2 |
| Abstract |
Geoengineering has been proposed to stabilize global temperature, but its impacts on crop production and stability are not fully understood. A few case studies suggest that certain crops are likely to benefit from solar dimming geoengineering, yet we show that geoengineering is projected to have detrimental effects for groundnut. Using an ensemble of crop-climate model simulations, we illustrate that groundnut yields in India undergo a statistically significant decrease of up to 20% as a result of solar dimming geoengineering relative to RCP4.5. It is somewhat reassuring, however, to find that after a sustained period of 50 years of geoengineering crop yields return to the nongeoengineered values within a few years once the intervention is ceased. |
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2017-01-20 |
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English |
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| ISSN |
0094-8276 |
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Article |
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| Notes |
CropM, ft_MACSUR |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4936 |
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| Author |
Grosz, B.; Dechow, R.; Gebbert, S.; Hoffmann, H.; Zhao, G.; Constantin, J.; Raynal, H.; Wallach, D.; Coucheney, E.; Lewan, E.; Eckersten, H.; Specka, X.; Kersebaum, K.-C.; Nendel, C.; Kuhnert, M.; Yeluripati, J.; Haas, E.; Teixeira, E.; Bindi, M.; Trombi, G.; Moriondo, M.; Doro, L.; Roggero, P.P.; Zhao, Z.; Wang, E.; Tao, F.; Roetter, R.; Kassie, B.; Cammarano, D.; Asseng, S.; Weihermueller, L.; Siebert, S.; Gaiser, T.; Ewert, F. |
| Title |
The implication of input data aggregation on up-scaling soil organic carbon changes |
Type |
Journal Article |
| Year |
2017 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
96 |
Issue |
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Pages |
361-377 |
| Keywords |
Biogeochemical model; Data aggregation; Up-scaling error; Soil organic carbon; DIFFERENT SPATIAL SCALES; NITROUS-OXIDE EMISSIONS; MODELING SYSTEM; DATA; RESOLUTION; CROP MODELS; CLIMATE; LONG; PRODUCTIVITY; CROPLANDS; DAYCENT |
| Abstract |
In up-scaling studies, model input data aggregation is a common method to cope with deficient data availability and limit the computational effort. We analyzed model errors due to soil data aggregation for modeled SOC trends. For a region in North West Germany, gridded soil data of spatial resolutions between 1 km and 100 km has been derived by majority selection. This data was used to simulate changes in SOC for a period of 30 years by 7 biogeochemical models. Soil data aggregation strongly affected modeled SOC trends. Prediction errors of simulated SOC changes decreased with increasing spatial resolution of model output. Output data aggregation only marginally reduced differences of model outputs between models indicating that errors caused by deficient model structure are likely to persist even if requirements on the spatial resolution of model outputs are low. (C)2017 Elsevier Ltd. All rights reserved. |
| Address |
2017-09-14 |
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English |
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Edition |
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| ISSN |
1364-8152 |
ISBN |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5176 |
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| Author |
Sandor, R.; Ehrhardt, F.; Grace, P.; Recous, S.; Smith, P.; Snow, V.; Soussana, J.-F.; Basso, B.; Bhatia, A.; Brilli, L.; Doltra, J.; Dorich, C.D.; Doro, L.; Fitton, N.; Grant, B.; Harrison, M.T.; Kirschbaum, M.U.F.; Klumpp, K.; Laville, P.; Leonard, J.; Martin, R.; Massad, R.-S.; Moore, A.; Myrgiotis, V.; Pattey, E.; Rolinski, S.; Sharp, J.; Skiba, U.; Smith, W.; Wu, L.; Zhang, Q.; Bellocchi, G. |
| Title |
Ensemble modelling of carbon fluxes in grasslands and croplands |
Type |
Journal Article |
| Year |
2020 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
252 |
Issue |
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Pages |
107791 |
| Keywords |
C fluxes; croplands; grasslands; multi-model ensemble; multi-model; median (mmm); soil organic-carbon; greenhouse-gas emissions; climate-change impacts; crop model; data aggregation; use efficiency; n2o emissions; maize; yield; wheat; productivity |
| Abstract |
Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs – C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are available for model calibration. The further development of crop/grassland ensemble modelling will hinge upon the interpretation of results in light of the way models represent the processes underlying C fluxes in complex agricultural systems (grassland and crop rotations including fallow periods). |
| Address |
2020-06-08 |
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LiveM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5230 |
| Permanent link to this record |
