Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations

Autor: Yi Chen, Davide Cammarano, Thomas Gaiser, Jukka Höhn, Kurt Christian Kersebaum, Mikhail A. Semenov, Miroslav Trnka, Altaaf Mechiche-Alami, Benjamin Dumont, Roberto Ferrise, Fulu Tao, Timothy R. Carter, Alfredo Rodríguez, Stefan Fronzek, C. Nendel, Julien Minet, Holger Hoffmann, F. Ewert, John R. Porter, Jaromir Krzyszczak, Pierre Stratonovitch, Marco Bindi, Zacharias Steinmetz, Samuel Buis, A.J.W. de Wit, Iwan Supit, Reimund P. Rötter, Ignacio J. Lorite, František Jurečka, Marcos Lana, Manuel Montesino, Piotr Baranowski, Taru Palosuo, Margarita Ruiz-Ramos, Nina Pirttioja, P. Hlavinka, Françoise Ruget
Přispěvatelé: Universidad Politécnica de Madrid (UPM), Universidad de Castilla-La Mancha (UCLM), Natural Resources Institute Finland (LUKE), Finnish Environment Institute (SYKE), Instituto Andaluz de Investigación y Formación Agraria y Pesquera (IFAPA), Universtiy of Florence, Institute of Agrophysics, Polska Akademia Nauk = Polish Academy of Sciences (PAN), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), The James Hutton Institute, Université de Liège, Rheinische Friedrich-Wilhelms-Universität Bonn, Institute of Agrosystems and Bioclimatology, Mendel University in Brno (MENDELU), Global Change Research Institute CAS, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), Department of Physical Geography and Ecosystem Science, Lund University, University of Copenhagen = Københavns Universitet (KU), Rothamsted Research, RIFCON GmbH, Wageningen University and Research Centre (WUR), TROPAGS, Department of Crop Sciences, Georg-August-University [Göttingen], MACSUR01-UPM ERA73-SUSTAG-UPM ERA73-SUSTAG-IFAPA, MACSUR02-APCIN2016-00050-00-00 MULCLIVAR-CGL2012-38923-C02-02, MACSUR-D.M.24064/7303/15, PLUMES-277276 PLUMES-277403 PLUMES-292836 NORFASYS-268277 NORFASYS-292944, SustES-C2.02.1.01/0.0/0.0/16_019/0000797, LCAgri-BIOSTRATEG1/271322/3/NCBR/2015 GyroScan-BIOSTRATEG2/298782/11/NCBR/2016, SPACES-01LL1304A IMPAC<^>3-FKZ 031A351A MACSUR-031B0039C, BB/P016855/1, European Project: 603416,EC:FP7:ENV,FP7-ENV-2013-two-stage,IMPRESSIONS(2013), Universidad de Castilla-La Mancha = University of Castilla-La Mancha (UCLM), Università degli Studi di Firenze = University of Florence (UniFI), Global Change Research Centre (CzechGlobe), Lund University [Lund], University of Copenhagen = Københavns Universitet (UCPH), Biotechnology and Biological Sciences Research Council (BBSRC), Georg-August-University = Georg-August-Universität Göttingen
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Agricultural and Forest Meteorology
Agricultural and Forest Meteorology, Elsevier Masson, 2019, 264, pp.351-362. ⟨10.1016/j.agrformet.2018.09.018⟩
Agricultural and Forest Meteorology, 2019, 264, pp.351-362. ⟨10.1016/j.agrformet.2018.09.018⟩
Agricultural and Forest Meteorology, 264, 351-362
Rodríguez, 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, Höhn, 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 & Rötter, R P 2019, ' Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations ', Agricultural and Forest Meteorology, vol. 264, pp. 351-362 . https://doi.org/10.1016/j.agrformet.2018.09.018
Agricultural and Forest Meteorology 264 (2019)
ISSN: 0168-1923
DOI: 10.1016/j.agrformet.2018.09.018
Popis: International audience; Abstract Climate change is expected to severely affect cropping systems and food production in many parts of the world 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 aestivum 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.
Databáze: OpenAIRE
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