|   | 
Details
   web
Records
Author Semenov, M.A.; Mitchell, R.A.C.; Whitmore, A.P.; Hawkesford, M.J.; Parry, M.A.J.; Shewry, P.R.
Title Shortcomings in wheat yield predictions Type Journal Article
Year 2012 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change
Volume 2 Issue 6 Pages (down) 380-382
Keywords winter-wheat; elevated CO2; temperature; growth
Abstract Predictions of a 40–140% increase in wheat yield by 2050, reported in the UK Climate Change Risk Assessment, are based on a simplistic approach that ignores key factors affecting yields and hence are seriously misleading.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1758-678x 1758-6798 ISBN Medium Commentary
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4504
Permanent link to this record
 

 
Author Dumont, B.; Vancutsem, F.; Seutin, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F.
Title Simulation de la croissance du blé à l’aide de modèles écophysiologiques: Synthèse bibliographique des méthodes, potentialités et limitations Type Journal Article
Year 2012 Publication Biotechnologie, Agronomie, Société et Environnement Abbreviated Journal Biotechnologie, Agronomie, Société et Environnement
Volume 163 Issue Pages (down) 376-386
Keywords crops; growth; soil; Triticum; wheats; calibration; optimization methods
Abstract Crop models describe the growth and development of a crop interacting with its surrounding agro-environmental conditions (soil, climate and the close conditions of the plant). However, the implementation of such models remains difficult because of the high number of explanatory variables and parameters. It often happens that important discrepancies appear between measured and simulated values. This article aims to highlight the different sources of uncertainty related to the use of crop models, as well as the actual methods that allow a compensation for or, at least, a consideration of these sources of error during analysis of the model results. This article presents a literature review, which firstly synthesises the general mathematical structure of crop models. The main criteria for evaluating crop models are then described. Finally, several methods used for improving models are given. Parameter estimation methods, including frequentist and Bayesian approaches, are presented and data assimilation methods are reviewed.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language French Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4584
Permanent link to this record
 

 
Author Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F.
Title Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions Type Journal Article
Year 2015 Publication Precision Agriculture Abbreviated Journal Precision Agric.
Volume 16 Issue 4 Pages (down) 361-384
Keywords nitrogen management; climatic variability; lars-wg weather generator; stics soil-crop model; pearson system; probability risk assessment; crop model stics; fertilizer nitrogen; generic model; wheat yield; maize; simulation; skewness; field; agriculture; scenarios
Abstract At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1385-2256 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4519
Permanent link to this record
 

 
Author Rodriguez, A.; Ruiz-Ramos, M.; Palosuo, T.; Carter, T.R.; Fronzek, S.; Lorite, I.J.; Ferrise, R.; Pirttioja, N.; Bindi, M.; Baranowski, P.; Buis, S.; Cammarano, D.; Chen, Y.; Dumont, B.; Ewert, F.; Gaiser, T.; Hlavinka, P.; Hoffmann, H.; Hohn, J.G.; Jurecka, F.; Kersebaum, K.C.; Krzyszczak, J.; Lana, M.; Mechiche-Alami, A.; Minet, J.; Montesino, M.; Nendel, C.; Porter, J.R.; Ruget, F.; Semenov, M.A.; Steinmetz, Z.; Stratonovitch, P.; Supit, I.; Tao, F.; Trnka, M.; de Wit, A.; Roetter, R.P.
Title Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations Type Journal Article
Year 2019 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 264 Issue Pages (down) 351-362
Keywords Wheat adaptation; Uncertainty; Climate change; Decision support; Response surface; Outcome confidence; Climate-Change Impacts; Response Surfaces; Wheat; Uncertainty; Yield; Simulation; 21St-Century; Productivity; Temperature; Projections
Abstract unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivwn L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.
Address 2019-01-07
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1923 ISBN Medium
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5214
Permanent link to this record
 

 
Author Refsgaard, J.C.; Arnbjerg-Nielsen, K.; Drews, M.; Halsnaes, K.; Jeppesen, E.; Madsen, H.; Markandya, A.; Olesen, J.E.; Porter, J.R.; Christensen, J.H.
Title The role of uncertainty in climate change adaptation strategies – a Danish water management example Type Journal Article
Year 2013 Publication Mitigation and Adaptation Strategies for Global Change Abbreviated Journal Mitig. Adapt. Strateg. Glob. Change
Volume 18 Issue 3 Pages (down) 337-359
Keywords Climate change; Adaptation; Uncertainty; Risk; Water sectors; Multi-disciplinary; change impacts; global change; winter-wheat; models; scenarios; ensembles; denmark; vulnerability; community; knowledge
Abstract We propose a generic framework to characterize climate change adaptation uncertainty according to three dimensions: level, source and nature. Our framework is different, and in this respect more comprehensive, than the present UN Intergovernmental Panel on Climate Change (IPCC) approach and could be used to address concerns that the IPCC approach is oversimplified. We have studied the role of uncertainty in climate change adaptation planning using examples from four Danish water related sectors. The dominating sources of uncertainty differ greatly among issues; most uncertainties on impacts are epistemic (reducible) by nature but uncertainties on adaptation measures are complex, with ambiguity often being added to impact uncertainties. Strategies to deal with uncertainty in climate change adaptation should reflect the nature of the uncertainty sources and how they interact with risk level and decision making: (i) epistemic uncertainties can be reduced by gaining more knowledge; (ii) uncertainties related to ambiguity can be reduced by dialogue and knowledge sharing between the different stakeholders; and (iii) aleatory uncertainty is, by its nature, non-reducible. The uncertainty cascade includes many sources and their propagation through technical and socio-economic models may add substantially to prediction uncertainties, but they may also cancel each other. Thus, even large uncertainties may have small consequences for decision making, because multiple sources of information provide sufficient knowledge to justify action in climate change adaptation.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1381-2386 1573-1596 ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur Approved no
Call Number MA @ admin @ Serial 4613
Permanent link to this record