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Author |
Olesen, J.E.; Jabloun, M.; Schelde, K. |
Title |
Reconciling estimates of climate change effects on nitrate leaching from agricultural crops |
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Conference Article |
Year |
2014 |
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Nitrate leaching from agricultural systems constitutes a severe environmental effect in regions with valuable groundwater resources and vulnerable aquatic ecosystems. Therefore cropping systems should in many parts of Europe reduce the amount of nitrate leached from the root zone. Since soil nitrogen transformation and loss processes are highly influenced by climate, including temperature and precipitation, estimates of climate change effects on nitrate leaching is in high demand for evaluating future groundwater and surface water protection policies. Modelling studies using both the FASSET and Daisy models for cereal crops as well as arable crop rotations in Denmark have shown increased nitrate leaching under projected climate change. Sensitivity analyses using these models have shown a higher response to changes in temperature than to precipitation, although in particular precipitation responses differ between soil types. Simulations for crop rotations show that current catch crop management may not be sufficient to maintain low nitrate leaching levels in future. These effects of temperature and precipitation as well as crop management are confirmed in an empirical analysis of nitrate leaching from a long-term cropping system experiment in Denmark. The main uncertainties on climate change effects on future nitrate leaching appears to be related to effects of climate change on soil organic matter and thus on the amount of soil total N available for mineralization as well as the effects of enhanced atmospheric CO2 concentration on crop residue quality and N mineralization. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
Serial |
5118 |
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Author |
Sharif, B.; Olesen, J.E.; Schelde, K. |
Title |
Statistical learning approach for modelling the effects of climate change on oilseed rape yield |
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Conference Article |
Year |
2014 |
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Statistical learning is a fairly new term referring to a set of supervised and unsupervised modelling and prediction techniques. It is based on traditional statistics but has been highly enhanced inspired by developments in machine learning and data mining. The main focus of statistical learning is to estimate the functions that quantify relations between several parameters and observed responses. These functions are further used for prediction, inference or a combination of both. For a particular case of quantitative responses, regularization techniques in regression are developed to overcome the weaknesses of ordinary least square (OLS) regression in prediction. These new shrinkage methods outperform OLS for prediction, especially in large datasets. In this study, a large dataset of field experiments on winter oilseed rape in Denmark for 22 years (1992 to 2013) was collected. Biweekly climatic data along with sowing date, harvest date, soil type and previous crop are considered as the explanatory variables. Yield of winter oilseed rape is considered as response variable. LASSO and Elastic Nets are the regularization techniques used to estimate the functions. Hold-one-out cross validation method for testing the prediction power reveals that these techniques are much useful in both prediction and inference. Since these techniques are included in recent versions of some software packages (e.g. R), they can be easily implemented by users at any level. The estimated function (model) is further used to predict the oilseed rape yield responses to climate change for several scenarios using representative weather data produced by a weather generator. |
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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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MA @ admin @ |
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5129 |
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Author |
Yin, X.; Olesen, J.E.; Li, W.; Wang, M.; Zhang, H. |
Title |
Contributions of climatic, technological and social factors to maize yield in the northeast farming region of China during 1985 to 2009 |
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Manuscript |
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2015 |
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CropM |
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MA @ admin @ |
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2912 |
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Doltra, J.; Olesen, J.E.; Báez, D.; Louro, A.; Chirinda, N. |
Title |
Modeling nitrous oxide emissions from organic and conventional cereal-based cropping systems under different management, soil and climate factors |
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Journal Article |
Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
Volume |
66 |
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Pages |
8-20 |
Keywords |
greenhouse gas emissions; nitrogen losses; fasset process-based model; mitigation; crop management; n2o emissions; agricultural soils; cover crops; simulation; matter; wheat; uncertainty; variability; fertilizer; rotation |
Abstract |
Mitigation of greenhouse gas emissions from agriculture should be assessed across cropping systems and agroclimatic regions. In this study, we investigate the ability of the FASSET model to analyze differences in the magnitude of N2O emissions due to soil, climate and management factors in cereal-based cropping systems. Forage maize was grown in a conventional dairy system at Mabegondo (NW Spain) and wheat and barley in organic and conventional crop rotations at Foulum (NW Denmark). These two European sites represent agricultural areas with high and low to moderate emission levels, respectively. Field trials included plots with and without catch crops that were fertilized with either mineral N fertilizer, cattle slurry, pig slurry or digested manure. Non-fertilized treatments were also included. Measurements of N2O fluxes during the growing cycle of all the crops at both sites were performed with the static chamber method with more frequent measurements post-fertilization and biweekly measurements when high fluxes were not expected. All cropping systems were simulated with the FASSET version 2.5 simulation model. Cumulative soil seasonal N2O emissions were about ten-fold higher at Mabegondo than at Foulum when averaged across systems and treatments (8.99 and 0.71 kg N2O-N ha(-1), respectively). The average simulated cumulative soil N2O emissions were 9.03 and 1.71 kg N2O-N ha(-1) at Mabegondo and at Foulum, respectively. Fertilization, catch crops and cropping systems had lower influence on the seasonal soil N2O fluxes than the environmental factors. Overall, in its current version FASSET reproduced the effects of the different factors investigated on the cumulative seasonal soil N2O emissions but temporally it overestimated emissions from nitrification and denitrification on particular days when soil operations, ploughing or fertilization, took place. The errors associated with simulated daily soil N2O fluxes increased with the magnitude of the emissions. For resolving causes of differences in simulated and measured fluxes more intensive and temporally detailed measurements of N2O fluxes and soil C and N dynamics would be needed. (C) 2015 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4748 |
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Author |
Trnka, M.; Kersebaum, K.; Christian,; Olesen, J.E. |
Title |
Description of the compiled experimental data available in the MACSUR CropM database |
Type |
Report |
Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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Volume |
6 |
Issue |
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Pages |
D-C2.1 |
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Abstract |
The input data necessary for crop model simulations and data for their calibration/validation (and thus requirements for observations and measurements in suitable experiments) have been collected through out the project together with data for additional analysis of abiotic factors influencing yields. A list of possible dataset was collated in the first year of project however very few of the existing datasets were found usable for the crop model simulation as they fell short of the requirements defined in the part 2.3. However database has been populated as planned with the results of the ongoing MACSUR studies and will serve in the same way for the MACSUR 2 duration. No Label |
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MA @ admin @ |
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2090 |
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