| Records |
| Author |
De Sanctis, G.; Roggero, P.P.; Seddaiu, G.; Orsini, R.; Porter, C.H.; Jones, J.W. |
| Title |
Long-term no tillage increased soil organic carbon content of rain-fed cereal systems in a Mediterranean area |
Type |
Journal Article |
| Year |
2012 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
40 |
Issue |
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Pages |
18-27 |
| Keywords |
N fertilization; C dynamics; DSSAT; Wheat; Maize; Weed fallow; sandy loam soil; cropping systems; agricultural systems; climate-change; winter-wheat; sequestration; matter; model; fertilization; dynamics |
| Abstract |
The differential impact on soil organic carbon (SOC) of applying no tillage (NT) compared to conventional tillage (CT, i.e. mouldboard ploughing), along with three rates of nitrogen (N) fertilizer application (0,90 and 180 kg ha(-1) y(-1)), was studied under rain-fed Mediterranean conditions in a long-term experiment based on a durum wheat-maize rotation, in which crop residues were left on the soil (NT) or incorporated (CT). Observed SOC content following 8 and 12 years of continuous treatment application was significantly higher in the top 10 cm of the soil under NT than CT, but it was similar in the 10-40 cm layer. NT grain yields for both maize and durum wheat were below those attained under CT (on average 32% and 14% lower respectively) at a given rate of N fertilizer application. Soil, climate and crop data over 5 years were used to calibrate DSSAT model in order to simulate the impact of the different management practices over a 50-year period. Good agreement was obtained between observed and simulated values for crops grain yield, above-ground biomass and observed SOC values. Results from the simulations showed that under NT the weeds growing during the intercrop fallow period made a significant contribution to the observed SOC increase. When the contribution of the weed fallow was considered, NT significantly increased SOC in the top 40 cm of the soil at an average rate of 0.43, 0.31 and 0.03 t ha(-1) per year, respectively for 180,90 and 0 kg N ha(-1) year(-1), within the simulated 50 years. Under CT, a significant SOC increase was simulated under N180 and a significant decrease when no fertilizer was supplied. |
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English |
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1161-0301 |
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article |
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CropM |
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MA @ admin @ |
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4469 |
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Rötter, R.P.; Appiah, M.; Fichtler, E.; Kersebaum, K.C.; Trnka, M.; Hoffmann, M.P. |
| Title |
Linking modelling and experimentation to better capture crop impacts of agroclimatic extremes-A review |
Type |
Journal Article |
| Year |
2018 |
Publication |
Field Crops Research |
Abbreviated Journal |
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| Volume |
221 |
Issue |
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Pages |
142-156 |
| Keywords |
ft_macsur; Agroclimatic extremes; Crop model; Heat; Drought; Heavy rain; Anthropogenic Climate-Change; Head-Emergence Frost; Weather Extremes; Wheat Yields; Temperature Variability; Induced Sterility; Food Security; Soil-Moisture; Plant-Growth; Winter-Wheat |
| Abstract |
Climate change implies higher frequency and magnitude of agroclimatic extremes threatening plant production and the provision of other ecosystem services. This review is motivated by a mismatch between advances made regarding deeper understanding of abiotic stress physiology and its incorporation into ecophysiological models in order to more accurately quantifying the impacts of extreme events at crop system or higher aggregation levels. Adverse agroclimatic extremes considered most detrimental to crop production include drought, heat, heavy rains/hail and storm, flooding and frost, and, in particular, combinations of them. Our core question is: How have and could empirical data be exploited to improve the capability of widely used crop simulation models in assessing crop impacts of key agroclimatic extremes for the globally most important grain crops? To date there is no comprehensive review synthesizing available knowledge for a broad range of extremes, grain crops and crop models as a basis for identifying research gaps and prospects. To address these issues, we selected eight major grain crops and performed three systematic reviews using SCOPUS for period 1995-2016. Furthermore, we amended/complemented the reviews manually and performed an in-depth analysis using a sub-sample of papers. Results show that by far the majority of empirical studies (1631 out of 1772) concentrate on the three agroclimatic extremes drought, heat and heavy rain and on the three major staples wheat, maize and rice (1259 out of 1772); the concentration on just a few has increased over time. With respect to modelling studies two model families, i.e. CERES-DSSAT and APSIM, are dearly dominating for wheat and maize; for rice, ORYZA2000 and CERES-Rice predominate and are equally strong. For crops other than maize and wheat the number of studies is small. Empirical and modelling papers don’t differ much in the proportions the various extreme events are dealt with drought and heat stress together account for approx. 80% of the studies. There has been a dramatic increase in the number of papers, especially after 2010. As a way forward, we suggest to have very targeted and well-designed experiments on the specific crop impacts of a given extreme as well as of combinations of them. This in particular refers to extremes addressed with insufficient specificity (e.g. drought) or being under-researched in relation to their economic importance (heavy rains/storm and flooding). Furthermore, we strongly recommend extending research to crops other than wheat, maize and rice. |
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MA @ admin @ |
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5199 |
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Sándor, R.; Barcza, Z.; Acutis, M.; Doro, L.; Hidy, D.; Köchy, M.; Minet, J.; Lellei-Kovács, E.; Ma, S.; Perego, A.; Rolinski, S.; Ruget, F.; Sanna, M.; Seddaiu, G.; Wu, L.; Bellocchi, G. |
| Title |
Multi-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: Uncertainties and ensemble performance |
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Journal Article |
| Year |
2016 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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Biomass; Grasslands; Modelling; Multi-model ensemble; Soil processes |
| Abstract |
• We simulate biomass, soil water content (SWC) and temperature (ST) in grasslands. • We compare nine models to the multi-model median (MMM) at nine sites. • With model calibration, we obtain satisfactory estimates of ST, less of SWC and biomass. • We observe discrepancies across models in the simulation of grassland processes. • We improve performance with multi-model approach. This study presents results from a major grassland model intercomparison exercise, and highlights the main challenges faced in the implementation of a multi-model ensemble prediction system in grasslands. Nine, independently developed simulation models linking climate, soil, vegetation and management to grassland biogeochemical cycles and production were compared in a simulation of soil water content (SWC) and soil temperature (ST) in the topsoil, and of biomass production. The results were assessed against SWC and ST data from five observational grassland sites representing a range of conditions – Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland – and against yield measurements from the same sites and other experimental grassland sites in Europe and Israel. We present a comparison of model estimates from individual models to the multi-model ensemble (represented by multi-model median: MMM). With calibration (seven out of nine models), the performances were acceptable for weekly-aggregated ST (R² > 0.7 with individual models and >0.8–0.9 with MMM), but less satisfactory with SWC (R² < 0.6 with individual models and < ∼ 0.5 with MMM) and biomass (R² < ∼0.3 with both individual models and MMM). With individual models, maximum biases of about −5 °C for ST, −0.3 m3 m−3 for SWC and 360 g DM m−2 for yield, as well as negative modelling efficiencies and some high relative root mean square errors indicate low model performance, especially for biomass. We also found substantial discrepancies across different models, indicating considerable uncertainties regarding the simulation of grassland processes. The multi-model approach allowed for improved performance, but further progress is strongly needed in the way models represent processes in managed grassland systems. |
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1161-0301 |
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LiveM |
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MA @ admin @ |
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4768 |
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