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	Author	Pirttioja, N.; Carter, T.R.; Fronzek, S.; Bindi, M.; Hoffmann, H.; Palosuo, T.; Ruiz-Ramos, M.; Tao, F.; Trnka, M.; Acutis, M.; Asseng, S.; Baranowski, P.; Basso, B.; Bodin, P.; Buis, S.; Cammarano, D.; Deligios, P.; Destain, M.F.; Dumont, B.; Ewert, F.; Ferrise, R.; François, L.; Gaiser, T.; Hlavinka, P.; Jacquemin, I.; Kersebaum, K.C.; Kollas, C.; Krzyszczak, J.; Lorite, I.J.; Minet, J.; Minguez, M.I.; Montesino-San Martin, M.; Moriondo, M.; Müller, C.; Nendel, C.; Öztürk, I.; Perego, A.; Rodríguez, A.; Ruane, A.C.; Ruget, F.; Sanna, M.; Semenov, M.A.; Slawinski, C.; Stratonovitch, P.; Supit, I.; Waha, K.; Wang, E.; Wu, L.; Zhao, Z.; Rötter, R.P.
	Title	Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces			Type	Journal Article
	Year	2015	Publication	Climate Research	Abbreviated Journal	Clim. Res.
	Volume	65	Issue		Pages	87-105
	Keywords	climate; crop model; impact response surface; IRS; sensitivity analysis; wheat; yield; climate-change impacts; uncertainty; 21st-century; projections; simulation; growth; region
	Abstract	This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development.
	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	0936-577x 1616-1572	ISBN		Medium	Article
	Area		Expedition		Conference
	Notes	CropM, ft_macsur			Approved	no
	Call Number	MA @ admin @			Serial	4662
Permanent link to this record



	Author	Nendel, C.; Thorburn, P.; Melzer, D.; Cerri, C.E.P.; Claessens, L.; Aggarwal, P.K.; Adam, M.; Angulo, C.; Asseng, S.; Baron, C.; Basso, B.; Bassu, S.; Bertuzzi, P.; Biernath, C.; Boogaard, H.; Boote, K.J.; Brisson, N.; Cammarano, D.; Conijn, S.; Corbeels, M.; Deryng, D.; Sanctis, G.D.; Doltra, J.; Durand, J.L.; Ewert, F.; Gayler, S.; Goldberg, R.; Grant, R.; Grassini, P.; Heng, L.; Hoek, S.B.; Hooker, J.A.U.-, L.A.H.; Ingwersen, J.; Izaurralde, C.; Jongschaap, R.; Kemanian, A.; Kersebaum, K.C.; Lizaso, J.; Makowski, D.; Martre, P.; Müller, C.; Kim, S.H.; Kumar, S.N.; O’Leary, G.; Olesen, J.E.; Osborne, T.; Palosuo, T.; Pravia, M.V.; Priesack, E.; Ripoche, D.A.U.-, R.P.R.; Sau, F.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.L.; Teixeira, E.; Timlin, D.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Wolf, J.
	Title	Soil nitrogen mineralisation simulated by crop models across different environments and the consequences for model improvement			Type	Conference Article
	Year	2016	Publication		Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication	Berlin (Germany)	Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany
	Notes				Approved	no
	Call Number	MA @ admin @			Serial	4903
Permanent link to this record



	Author	Nendel, C.; Ewert, F.; Rötter, R.P.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Asseng, S.; Ruane, A.C.; Banse, M.; Tiffin, R.; Brouwer, F.; Sinabell, F.; Scollan, N.; Meijs, J.; Angulo, C.; Antle, J.M.; Baigorria, G.; Basso, B.; Bindi, M.; Boote, K.J.; Gaiser, T.; Janssen, S.; Kersebaum, K.C.; Nelson, G.; Olesen, J.E.; Palosuo, T.; Porter, C.H.; Porter, J.R.; Rivington, M.; Semenov, M.; Stewart, D.; Thorburn, P.; Trnka, M.; van Ittersum, M.K.; Verhagen, J.; Wallach, D.; Winter, J.M.
	Title	Addressing challenges and uncertainties for, the use of agro-ecosystem models to, assess climate change impact and food security across scales			Type	Conference Article
	Year	2013	Publication		Abbreviated Journal
	Volume		Issue		Pages
	Keywords	CropM
	Abstract
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	Climate Change and Regional Responses Conference, Dresden, 2013-05-27 to 2013-05-27
	Notes				Approved	no
	Call Number	MA @ admin @			Serial	2679
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	Author	Martre, P.; Wallach, D.; Asseng, S.; Ewert, F.; Jones, J.W.; Rötter, R.P.; Boote, K.J.; Ruane, A.C.; Thorburn, P.J.; Cammarano, D.; Hatfield, J.L.; Rosenzweig, C.; Aggarwal, P.K.; Angulo, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Brisson, N.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.F.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Müller, C.; Kumar, S.N.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; White, J.W.; Wolf, J.
	Title	Multimodel ensembles of wheat growth: many models are better than one			Type	Journal Article
	Year	2015	Publication	Global Change Biology	Abbreviated Journal	Glob. Chang. Biol.
	Volume	21	Issue	2	Pages	911-925
	Keywords	Climate; Climate Change; Environment; Models, Biological; Seasons; Triticum/growth & development; ecophysiological model; ensemble modeling; model intercomparison; process-based model; uncertainty; wheat (Triticum aestivum L.)
	Abstract	Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.
	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	1354-1013	ISBN		Medium	Article
	Area		Expedition		Conference
	Notes	CropM, ftnotmacsur			Approved	no
	Call Number	MA @ admin @			Serial	4665
Permanent link to this record



	Author	Martre, P.; He, J.; Le Gouis, J.; Semenov, M.A.
	Title	In silico system analysis of physiological traits determining grain yield and protein concentration for wheat as influenced by climate and crop management			Type	Journal Article
	Year	2015	Publication	Journal of Experimental Botany	Abbreviated Journal	J. Experim. Bot.
	Volume	66	Issue	12	Pages	3581-3598
	Keywords	Climate; Computer Simulation; Crops, Agricultural/growth & development/physiology; Edible Grain/growth & development; Models, Biological; Nitrogen/metabolism; Plant Proteins/metabolism; Plant Transpiration; Probability; Quantitative Trait, Heritable; Soil/chemistry; Triticum/growth & development/metabolism/physiology; Water/chemistry; Crop growth model; genetic adaptation; grain protein concentration; grain yield; interannual variability; sensitivity analysis; wheat (Triticum aestivum L.); yield stability
	Abstract	Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work.
	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	1460-2431 (Electronic) 0022-0957 (Linking)	ISBN		Medium	Article
	Area		Expedition		Conference
	Notes	CropM, ftnotmacsur			Approved	no
	Call Number	MA @ admin @			Serial	4567
Permanent link to this record