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Author |
Makowski, D. |
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Title |
A simple Bayesian method for adjusting ensemble of crop model outputs to yield observations |
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Journal Article |
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Year |
2017 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
Europ. J. Agron. |
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Volume |
88 |
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Pages |
76-83 |
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Keywords |
Bayesian method; Climate change; Ensemble modelling; Uncertainty; Yield; Linear-Approach; Climate-Change; CO2 |
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Abstract  |
Multi-model forecasting has drawn some attention in crop science for evaluating effect of climate change on crop yields. The principle is to run several individual process-based crop models under several climate scenarios in order to generate ensembles of output values. This paper describes a simple Bayesian method – called Bayes linear method- for updating ensemble of crop model outputs using yield observations. The principle is to summarize the ensemble of crop model outputs by its mean and variance, and then to adjust these two quantities to yield observations in order to reduce uncertainty. The adjusted mean and variance combine two sources of information, i.e., the ensemble of crop model outputs and the observations. Interestingly, with this method, observations collected under a given climate scenario can be used to adjust mean and variance of the model ensemble under a different scenario. Another advantage of the proposed method is that it does not rely on a separate calibration of each individual crop model. The uncertainty reduction resulting from the adjustment of an ensemble of crop models to observations was assessed in a numerical application. The implementation of the Bayes linear method systematically reduced uncertainty, but the results showed the effectiveness of this method varied in function of several factors, especially the accuracy of the yield observation, and the covariance between the crop model output and the observation. (C) 2015 Elsevier B.V. All rights reserved. |
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2017-08-07 |
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English |
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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 |
5171 |
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Author |
Waha, K.; Müller, C.; Bondeau, A.; Dietrich, J.P.; Kurukulasuriya, P.; Heinke, J.; Lotze-Campen, H. |
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Title |
Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa |
Type |
Journal Article |
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Year |
2013 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
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Volume |
23 |
Issue |
1 |
Pages |
130-143 |
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Keywords |
multiple cropping; sequential cropping systems; crop modelling; agricultural management; adaptation options; global vegetation model; future food-production; rainy-season; west-africa; agriculture; yield; maize; soil; variability; heat |
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Abstract |
Multiple cropping systems provide more harvest security for farmers, allow for crop intensification and furthermore influence ground cover, soil erosion, albedo, soil chemical properties, pest infestation and the carbon sequestration potential. We identify the traditional sequential cropping systems in ten sub-Saharan African countries from a survey dataset of more than 8600 households. We find that at least one sequential cropping system is traditionally used in 35% of all administrative units in the dataset, mainly including maize or groundnuts. We compare six different management scenarios and test their susceptibility as adaptation measure to climate change using the dynamic global vegetation model for managed land LPJmL. Aggregated mean crop yields in sub-Saharan Africa decrease by 6-24% due to climate change depending on the climate scenario and the management strategy. As an exception, some traditional sequential cropping systems in Kenya and South Africa gain by at least 25%. The crop yield decrease is typically weakest in sequential cropping systems and if farmers adapt the sowing date to changing climatic conditions. Crop calorific yields in single cropping systems only reach 40-55% of crop calorific yields obtained in sequential cropping systems at the end of the 21st century. The farmers’ choice of adequate crops, cropping systems and sowing dates can be an important adaptation strategy to climate change and these management options should be considered in climate change impact studies on agriculture. (C) 2012 Elsevier Ltd. All rights reserved. |
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2016-10-31 |
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0959-3780 |
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CropM |
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MA @ admin @ |
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4823 |
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Author |
Jayet, P.; Petsakos, A. |
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Title |
Evaluating the efficiency of a uniform N-input tax under different policy scenarios at different scales |
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Journal Article |
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Year |
2013 |
Publication |
Environmental Modelling & Assessment |
Abbreviated Journal |
Environmental Modelling & Assessment |
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Volume |
18 |
Issue |
1 |
Pages |
57-72 |
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Keywords |
Bioeconomic model; Mathematical; programming; Nitrogen response curves; Nitrate emissions; Nitrogen tax |
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Abstract |
Nitrate pollution from agriculture is an important environmental externality, caused by the excessive use of fertilizers. The internalization of this problem, via a tax on mineral nitrogen, could lead to a second best solution, reducing nitrate emissions. Several authors suggest that a reduction in agricultural support could produce similar results. In this paper, we examine the effects of different levels of a uniformly implemented nitrogen tax in France under two policy scenarios, corresponding to post Agenda 2000 and 2003 Luxembourg reforms of European Union ’ s Common Agricultural Policy, in order to reveal the synergies and conflicts between the tax and the policy scenarios in terms of nitrate emissions abatement. The analysis is performed at different geographical scales, from the national to the regional and is based on a bioeconomic approach that involves the coupling of the economic model AROPAj with the crop model STICS. Results show that the efficiency of the N-tax varies according to the geographical scale of the analysis and the type of farming. Furthermore, we prove that a uniform implementation may lead to perverse effects that should always be taken into account when introducing second-best instruments. |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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4605 |
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Author |
Eza, U.; Shtiliyanova, A.; Borras, D.; Bellocchi, G.; Carrère, P.; Martin, R. |
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Title |
An open platform to assess vulnerabilities to climate change: An application to agricultural systems |
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Journal Article |
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Year |
2015 |
Publication |
Ecological Informatics |
Abbreviated Journal |
Ecological Informatics |
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30 |
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Pages |
389-396 |
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Keywords |
climate change; grasslands; modeling platform; vulnerability assessment; pasture simulation-model; software component; solar-radiation; crop production; change impacts; adaptation; indicator; makers |
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Abstract |
Numerous climate futures are now available from global climate models. Translation of climate data such as precipitation and temperatures into ecologically meaningful outputs for managers and planners is the next frontier. We describe a model-based open platform to assess vulnerabilities of agricultural systems to climate change on pixel-wise data. The platform includes a simulation modeling engine and is suited to work with NetCDF format of input and output files. In a case study covering a region (Auvergne) in the Massif Central of France, the platform is configured to characterize climate (occurrence of arid conditions in historical and projected climate records), soils and human management, and is then used to assess the vulnerability to climate change of grassland productivity (downscaled to a fine scale). We demonstrate how using climate time series, and process-based simulations vulnerabilities can be defined at fine spatial scales relevant to farmers and land managers, and can be incorporated into management frameworks. (C) 2015 Elsevier B.V. All rights reserved. |
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ISSN |
1574-9541 |
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Notes |
CropM LiveM, ft_macsur |
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Call Number |
MA @ admin @ |
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4708 |
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Author |
Dass, P.; Müller, C.; Brovkin, V.; Cramer, W. |
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Title |
Can bioenergy cropping compensate high carbon emissions from large-scale deforestation of high latitudes |
Type |
Journal Article |
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Year |
2013 |
Publication |
Earth System Dynamics |
Abbreviated Journal |
Earth System Dynamics |
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Volume |
4 |
Issue |
2 |
Pages |
409-424 |
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Keywords |
land-use change; global vegetation model; soil carbon; climate-change; surface albedo; cover changes; snow cover; remind-r; forest; productivity |
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Abstract |
Numerous studies have concluded that deforestation of the high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance, however, may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely theoretical in order to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. For realistic assumptions of land suitability, the total emissions computed in this study are higher than that of previous studies assessing the effects of boreal deforestation. The warming due to biogeochemical effects ranges from 0.12 to 0.32 degrees C, depending on the climate sensitivity. Using LPJmL to assess the mitigation potential of bioenergy plantations in the suitable areas of the deforested region, we find that the global biophysical bioenergy potential is 68.1 +/- 5.6 EJ yr(-1) of primary energy at the end of the 21st century in the most plausible scenario. The avoided combustion of fossil fuels over the time frame of this experiment would lead to further cooling. However, since the carbon debt caused by the cumulative emissions is not repaid by the end of the 21st century, the global temperatures would increase by 0.04 to 0.11 degrees C. The carbon dynamics in the high latitudes especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth’s carbon and energy budget. |
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2190-4987 |
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CropM |
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MA @ admin @ |
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4486 |
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