globalchange  > 气候减缓与适应
DOI: 10.1016/j.agrformet.2018.09.018
WOS ID: WOS:000452931700029
Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations
Author: Rodriguez, A.1,2; Ruiz-Ramos, M.1; Palosuo, T.3; Carter, T. R.4; Fronzek, S.4; Lorite, I. J.5; Ferrise, R.6; Pirttioja, N.4; Bindi, M.6; Baranowski, P.7; Buis, S.8; Cammarano, D.9; Chen, Y.3; Dumont, B.10; Ewert, F.11; Gaiser, T.11; Hlavinka, P.12,13; Hoffmann, H.11; Hohn, J. G.3; Jurecka, F.12,13; Kersebaum, K. C.14; Krzyszczak, J.7; Lana, M.14,15; Mechiche-Alami, A.16; Minet, J.17; Montesino, M.18; Nendel, C.14; Porter, J. R.18; Ruget, F.8; Semenov, M. A.19; Steinmetz, Z.20; Stratonovitch, P.19; Supit, I.21; Tao, F.3; Trnka, M.12,13; de Wit, A.21; Roetter, R. P.22,23
Corresponding Author: Rodriguez, A.
ISSN: 0168-1923
EISSN: 1873-2240
Publishing Year: 2019
Volume: 264, Pages:351-362
Language: 英语
Keyword: Wheat adaptation ; Uncertainty ; Climate change ; Decision support ; Response surface ; Outcome confidence
WOS Category: Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS Research Area: Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
English 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.

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Document Type: 期刊论文
Appears in Collections:气候减缓与适应

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Affiliation: 1.Univ Politecn Madrid, CEIGRAM, E-28040 Madrid, Spain
2.Univ Castilla La Mancha, Dept Econ Anal & Finances, Toledo 45071, Spain
3.Nat Resources Inst Finland Luke, Helsinki 00790, Finland
4.Finnish Environm Inst SYKE, Helsinki 00251, Finland
5.IFAPA Junta Andalucia, Cordoba 14004, Spain
6.Univ Florence, I-50144 Florence, Italy
7.Polish Acad Sci, Inst Agrophys, Doswiadczaina 4, PL-20290 Lublin, Poland
8.INRA, UMR EMMAH 1114, F-84914 Avignon, France
9.James Hutton Inst, Dundee DD2 5DA, Scotland
10.ULgGembloux Agrobio Tech, Crop Sci Unii, Dept AgroBioChem& Terra, B-5030 Gembloux, Belgium
11.Univ Bonn, INRES, D-53115 Bonn, Germany
12.Mendel Univ Brno, Inst Agrosyst & Bioclimatol, Brno 61300, Czech Republic
13.Czech Acad Sci, Global Change Res Inst, Brno 60300, Czech Republic
14.Lelbniz Ctr Agr Landscape Res ZALF, D-15374 Muncheberg, Germany
15.Swedish Univ Agr Sci, Dept Crop Prod Ecol, Ulls Vag 16, S-75007 Uppsala, Sweden
16.Lund Univ, Dept Phys Geog & Ecosyst Sci, S-22362 Lund, Sweden
17.Univ Liege, Arlon Campus Environm, B-6700 Arlon, Belgium
18.Univ Copenhagen, DK-2630 Taastrup, Denmark
19.Rothamsted Res, Harpenden AL5 2JQ, Herts, England
20.RIFCON GmbH, D-69493 Hirschberg, Germany
21.Wageningen Univ, NL-6700 AA Wageningen, Netherlands
22.Georg August Univ Gottingen, Dept Crop Sci, TROPAGS, Grisebachstr 6, D-37077 Gottingen, Germany
23.Georg August Univ Gottingen, Ctr Biodivers & Land Use CBL, Busgenweg 1, D-37077 Gottingen, Germany

Recommended Citation:
Rodriguez, A.,Ruiz-Ramos, M.,Palosuo, T.,et al. Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations[J]. AGRICULTURAL AND FOREST METEOROLOGY,2019-01-01,264:351-362
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