Temperature and precipitation effects on wheat yield across a European transect: A crop model ensemble analysis using impact response surfaces

Climate Research

Volumn 65, Issue , 2015, Pages 87-105

  Pirttioja, N ^a   Carter, T R ^a   Fronzek, S ^a   Bindi, M ^b   Hoffmann, H ^c   Palosuo, T ^d   Ruiz Ramos, M ^e   Tao, F ^d   Trnka, M ^f,g   Acutis, M ^h   Asseng, S ⁱ   Baranowski, P ^j   Basso, B ^k   Bodin, P ^l   Buis, S ^m   Cammarano, D ⁿ   Deligios, P ^o   Destain, M F ^p   Dumont, B ^p   Ewert, F ^c   Ferrise, R ^b   Francois L ^p   Gaiser, T ^c   Hlavinka, P ^f,g   Jacquemin, I ^p   Kersebaum, K C ^q   Kollas, C ^q   Krzyszczak, J ^j   Lorite, I J ^r   Minet, J ^p   Minguez, M I ^e   Montesino, M ^s   Moriondo, M ^t   Muller C ^u   Nendel, C ^q   Ozturk I ^v   Perego, A ^h   Rodriguez A ^e   Ruane, A C ^w,x   Ruget, F ^m   Sanna, M ^h   Semenov, M A ^y   Slawinski, C ^j   Stratonovitch, P ^y   Supit, I ^z   Waha, K ^u,aa   Wang, E ^aa   Wu, L ^y   Zhao, Z ^aa,ab   Rotter R P ^d   more..

^a FINNISH ENVIRONMENT INSTITUTE   (Finland)

^b UNIVERSITY OF FLORENCE   (Italy)

^c UNIVERSITY OF BONN   (Germany)

^d FINNISH FOREST RESEARCH INSTITUTE   (Finland)

^e UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

^f MENDEL UNIVERSITY IN BRNO   (Czech Republic)

^g Global Change Research Centre AS CR   (Czech Republic)

^h UNIVERSITY OF MILAN   (Italy)

ⁱ UNIVERSITY OF FLORIDA   (United States)

^j INSTITUTE OF AGROPHYSICS   (Poland)

^k MICHIGAN STATE UNIVERSITY   (United States)

^l LUND UNIVERSITY   (Sweden)

^m UAPV   (France)

ⁿ SCOTTISH CROP RESEARCH INSTITUTE   (United Kingdom)

^o UNIVERSITY OF SASSARI   (Italy)

^p UNIVERSITY OF LIÈGE   (Belgium)

^q LEIBNIZ CENTRE FOR AGRICULTURAL LANDSCAPE RESEARCH ZALF   (Germany)

^r JUNTA DE ANDALUCÍA   (Spain)

^s UNIVERSITY OF COPENHAGEN   (Denmark)

^t CNR   (Italy)

^u POTSDAM INSTITUTE FOR CLIMATE IMPACT RESEARCH   (Germany)

^v AARHUS UNIVERSITY   (Denmark)

^w NASA GODDARD INSTITUTE FOR SPACE STUDIES   (United States)

^x NASA Goddard Institute for Space Studies   (United States)

^y ROTHAMSTED RESEARCH   (United Kingdom)

^z WAGENINGEN UNIVERSITY   (Netherlands)

^aa CSIRO   (Australia)

^ab CHINA AGRICULTURAL UNIVERSITY   (China)

more..

Author keywords

Climate; Crop model; Impact response surface; IRS; Sensitivity analysis; Wheat; Yield

Indexed keywords

ANNUAL VARIATION; BASELINE CONDITIONS; CLIMATE CHANGE; CROP YIELD; PRECIPITATION (CLIMATOLOGY); TRANSECT;

FINLAND; GERMANY; SPAIN;

TRITICUM AESTIVUM;

EID: 84940558272     PISSN: 0936577X     EISSN: 16161572     Source Type: Journal    
DOI: 10.3354/cr01322     Document Type: Article

References (57)

1. Abeledo LG, Savin R, Slafer GA (2008) Wheat productivity in the Mediterranean Ebro Valley: analyzing the gap between attainable and potential yield with a simulation model. Eur J Agron 28: 541-550
2. Alderman P, Quilligan E, Asseng S, Ewert F, Reynolds M (2014) Proc Workshop Model Wheat Response High Temp. CIMMYT, El Batán, Mexico, 19-21 June 2013
3. Angulo C, Rötter R, Lock R, Enders A, Fronzek S, Ewert F (2013) Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe. Agric For Meteorol 170: 32-46
4. Asseng S, Ewert F, Rosenzweig C, Jones JW and others (2013) Uncertainty in simulating wheat yields under climate change. Nat Clim Change 3: 827-832
5. Asseng S, Ewert F, Martre P, Rötter RP and others (2014) Rising temperatures reduce global wheat production. Nat Clim Change 5: 143-147
6. Becker R, Chambers J, Wilks A (1988) The new S language. Wadsworth & Brooks/Cole, Pacific Grove, CA
7. Børgesen CD, Olesen JE (2011) A probabilistic assessment of climate change impacts on yield and nitrogen leaching from winter wheat in Denmark. Nat Hazards Earth Syst Sci 11: 2541-2553
8. Cartelle J, Pedró A, Savin R, Slafer GA (2006) Grain weight responses to post-anthesis spikelet-trimming in an old and a modern wheat under Mediterranean conditions. Eur J Agron 25: 365-371
9. Challinor A, Wheeler T, Craufurd P, Slingo J (2005) Simulation of the impact of high temperature stress on annual crop yields. Agric For Meteorol 135: 180-189
10. Challinor AJ, Simelton ES, Fraser ED, Hemming D, Collins M (2010) Increased crop failure due to climate change: assessing adaptation options using models and socioeconomic data for wheat in China. Environ Res Lett 5: 034012
11. Challinor A, Martre P, Asseng S, Thornton P, Ewert F (2014a) Making the most of climate impacts ensembles. Nat Clim Change 4: 77-80
12. Challinor AJ, Watson J, Lobell DB, Howden SM, Smith DR, Chhetri N (2014b) A meta-analysis of crop yield under climate change and adaptation. Nat Clim Change 4: 287-291
13. Cleveland WS (1993) Visualizing data. Hobart Press, Summit, NJ
14. Craufurd PQ, Vadez V, Krishna Jagadish SV, Vara Prasad PV, Zaman-AllahM(2013) Crop science experiments de signed to inform crop modeling. Agric For Meteorol 170: 8-18
15. Diaz-Nieto J, Wilby RL (2005) A comparison of statistical downscaling and climate change factor methods: im pacts on low flows in the River Thames, United Kingdom. Clim Change 69: 245-268
16. Easterling WE, Aggarwal PK, Batima P, Brander KM and others (2007) Food, fibre and forest products. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (eds) Climate change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, p 273-313
17. Ewert F, Rötter R, Bindi M, Webber H and others (2014) Crop modelling for integrated assessment of risk to food production from climate change. Environ Model Softw, doi: 10.1016/j.envsoft.2014.12.003
18. Ferrise R, Moriondo M, Bindi M (2011) Probabilistic assessments of climate change impacts on durum wheat in the Mediterranean region. Nat Hazards Earth Syst Sci 11: 1293-1302
19. Fronzek S (2013) Climate change and the future distribution of palsa mires: ensemble modelling, probabilities and uncertainties. Monogr Boreal Environ Res No. 44, http://hdl.handle.net/10138/40184
20. Fronzek S, Carter TR, Raisanen J, Ruokolainen L, Luoto M (2010) Applying probabilistic projections of climate change with impact models: a case study for sub-arctic palsa mires in Fennoscandia. Clim Change 99: 515-534
21. Fronzek S, Carter TR, Luoto M (2011) Evaluating sources of uncertainty in modelling the impact of probabilistic climate change on sub-arctic palsa mires. Nat Hazards Earth Syst Sci 11: 2981-2995
22. Gitay H, Brown S, Easterling W, Jallow B and others (2001) Ecosystems and their goods and services. In: McCarthy JJ, Canziani OF, Leary NA, Dokken DJ, White KS (eds) Climate change 2001: impacts, adaptation, and vulnerability. Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, p 235-242
23. Hanasaki N, Masutomi Y, Takahashi K, Hijioka Y, Harasawa H, Matsuoka Y (2007) Development of a global water resources scheme for climate change policy support models. Environmental systems research. Jpn Soc Civ Eng 35: 367-374 (in Japanese)
24. Harris GR, Collins M, Sexton DMH, Murphy JM, Booth BBB (2010) Probabilistic projections for 21st century European climate. Nat Hazards Earth Syst Sci 10: 2009-2020
25. Iizumi T, Yokozawa M, Nishimori M (2011) Probabilistic evaluation of climate change impacts on paddy rice productivity in Japan. Clim Change 107: 391-415
26. IPCC (2013a) Annex I: Atlas of global and regional climate projections [van Oldenborgh GI and others]. In: Stocker TF, Quin D, Plattner GK, Tignor M and others (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, p 1311-1393
27. IPCC (2013b) Annex II: Climate system scenario tables [Prather M and others]. In: Stocker TF, Quin D, Plattner GK, Tignor M and others (eds) Climate change 2013: the physical science basis contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, p 1395-1445
28. Jamieson PD, Porter JR, Goudriaan J, Ritchie JT, van Keulen H, Stol W (1998) A comparison of the models AFRCWHEAT2, CERES-Wheat, Sirius, SUCROS2 and SWHEAT with measurements from wheat grown under drought. Field Crops Res 55: 23-44
29. Jones RJA, Thomasson AJ (1985) An agroclimatic databank for England and Wales. Tech Monogr No. 16, Soil survey of England and Wales, Harpenden
30. Lobell DB, Field CB (2007) Global scale climate-crop yield relationships and the impacts of recent warming. Environ Res Lett 2: 014002
31. Luo Q, Bellotti W, Williams M, Cooper I, Bryan B (2007) Risk analysis of possible impacts of climate change on South Australian wheat production. Clim Change 85: 89-101
32. Makowski D, Wallach D, Tremblay M (2002) Using a Bayesian approach to parameter estimation; comparison of the GLUE and MCMC methods. Agronomie 22: 191-203
33. Metzger M, Bunce R, Jongman R, Mücher C, Watkins J (2005) A climatic stratification of the environment of Europe. Glob Ecol Biogeogr 14: 549-563
34. Monfreda C, Ramankutty N, Foley JA (2008) Farming the planet. 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biogeochem Cycles 22: GB1022, doi: 10.1029/2007GB002947
35. Palosuo T, Kersebaum KC, Angulo C, Hlavinka P and others (2011) Simulation of winter wheat yield and its variability in different climates of Europe: a comparison of eight crop growth models. Eur J Agron 35: 103-114
36. Peltonen-Sainio P, Jauhiainen L, Hakala K (2011) Crop responses to temperature and precipitation according to long-term multi-location trials at high-latitude conditions. J Agric Sci 149: 49-62
37. Porter J (1993) AFRCWHEAT2: a model of the growth and development of wheat incorporating responses to water and nitrogen. Eur J Agron 2: 69-82
38. Porter JR, Gawith M (1999) Temperatures and the growth and development of wheat: a review. Eur J Agron 10: 23-26
39. Porter JR, Xie L, Challinor A, Cochrane K and others (2014) Food security and food production systems. In: Field CB and others (eds) Climate change 2014: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, p 485-533
40. R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. www.R-project.org/
41. Rosenzweig C, Jones JW, Hatfield JL, Ruane AC and others (2013) The agricultural model intercomparison and improvement project (AgMIP): protocols and pilot studies. Agric For Meteorol 170: 166-182
42. Rosenzweig C, Elliott J, Deryng D, Ruane AC and others (2014) Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc Natl Acad Sci USA 111: 3268-3273
43. Rötter RP (2014) Agricultural impacts: robust uncertainty. Nat Clim Change 4: 251-252
44. Rötter RP, Carter TR, Olesen JE, Porter JR (2011) Crop- climate models need an overhaul. Nat Clim Change 1: 175-177
45. Rötter RP, Ewert F, Palosuo T, Bindi M and others (2013) Challenges for agro-ecosystem modelling in climate change risk assessment for major European crops and farming systems. Proc Impacts World 2013 Conf, Potsdam, 27-30 May 2013, p 555-564
46. Ruane AC, McDermid S, Rosenzweig C, Baigorria GA and others (2014) Carbon-temperature-water change analysis for peanut production under climate change: a prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). Glob Chang Biol 20: 394-407
47. Trnka M, Rötter RP, Ruiz-Ramos M, Kersebaum KC and others (2014) Adverse weather conditions for European wheat production will become more frequent with climate change. Nat Clim Change 4: 637-643
48. van Ittersum M, Rabbinge R (1997) Concepts in production ecology for analysis and quantification of agricultural input-output combinations. Field Crops Res 52: 197-208
49. van Ittersum MK, Leffelaar PA, Van Keulen H, Kropff MJ, Bastiaans L, Goudriaan J (2003) On approaches and applications of the Wageningen crop models. Eur J Agron 18: 201-234
50. van Keulen H, Wolf J (1986) Modelling of agricultural production: weather, soils and crops. PUDOC, Wageningen
51. Wallach D, Makowski D, Jones JW, Brun F (2013) Working with dynamic crop models: methods, tools and examples for agriculture and environment. Academic Press, London
52. Watson J, Challinor AJ, Fricker TE, Ferro CA (2014) Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model. Clim Change, doi: 10.1007/s10584-014-1264-3014-1264-3
53. Wetterhall F, Graham LP, Andreasson J, Rosberg J, Yang W (2011) Using ensemble climate projections to assess probabilistic hydrological change in the Nordic region. Nat Hazards Earth Syst Sci 11: 2295-2306
54. White JW, Hoogenboom G, Kimball BA, Wall GW (2011) Methodologies for simulating impacts of climate change on crop production. Field Crops Res 124: 357-368
55. Wilby RL, Dawson CW, Murphy C, O'Connor P, Hawkins E (2014) The Statistical DownScaling Model-Decision Centric (SDSM-DC): conceptual basis and applications. Clim Res 61: 259-276
56. Wu L, Kersebaum KC (2008) Modeling water and nitrogen interaction responses and their consequences in crop models. In: Ahuja LR, Reddy VR, Saseendran SA, Yu Q (eds) Response of crops to limited water: understanding and modeling water stress effects on plant growth processes. ASA-CSSA-SSSA, Madison, WI, p 215-249
57. Zadoks JC, Chang TT, Konzak CF (1974) A decimal code for the growth stages of cereals. Weed Res 14: 415-421