Climate change and global wheat grain protein

Transcription

1 Climate change and global wheat grain protein Senthold Asseng P. Martre, A. Maiorano, R.P. Rötter, G. O Leary, G. Fitzgerald, C. Girousse, M.A. Baber, M.P. Reynolds, F. Giunta, R. Motzo, A.M.S. Kheir, P.J. Thorburn, K. Waha, A.C. Ruane, P.K. Aggarwal, M. Ahmed, J. Balkovic, B. Basso, C. Biernath, M. Bindi, D. Cammarano, A.J. Challinor, G. De Sanctis, B. Dumont, E. Eyshi Rezaei, E. Fereres, R. Ferrise, M. Garcia-Vila, Y. Gao, S. Gayler, G. Hoogenboom, R.C. Izaurralde, M. Jabloun, C.D. Jones, B.T. Kassie, K.C. Kersebaum, C. Klein, A.K. Koehler, B. Liu, S. Minoli, M. Montesino San Martin, C. Müller, S. Naresh Kumar, C. Nendel, J.E. Olesen, T. Palosuo, J.R. Porter, E. Priesack, D. Ripoche, M.A. Semenov, C. Stöckle, P. Stratonovitch, T. Streck, I. Supit, F. Tao, M. Van der Velde, D. Wallach, E. Wang, H. Webber, J. Wolf, P. Woli, Z. Zhang, and Y. Zhu, F. Ewert

2 Outline 1. Agricultural challenge 2. AgMIP 3. Estimates of climate change impact on yield 4. Climate change impact on grain protein

3 The Agricultural Challenge Climate Change Food Security - Increased demand Increase nutritional value Reduce environmental impact Temperature increased by 1.0 o C By 2050: Atmospheric CO 2 >500ppm By 2100: More extremes (heat, droughts, rainfall). Temperature +2 to 4 o C

4 Modeling (Wheat) Cropping Systems Ozone CO 2 Light Temperature Rainfall/Irrigation Breeding Cultivar Agronomy Crop Management Carter 2013 Soil Time

5 AgMIP - Multi-model ensembles 12 Grain yield (t/ha) Bruce Kimball Season mean temperature ( C) Asseng et al Nature CC

6 AgMIP - Multi-model ensembles Multi-model ensemble median is a better predictor than any single model! Wheat yields --- Asseng et al Nature CC Wheat yields (heat stress) --- Asseng et al Nature CC Wheat variables --- Martre et al GCB Maize yields --- Bassu et al GCB Rice yields --- Li et al GCB Potato yields --- Fleisher et al GCB

7 Improved models increase accuracy of simulations Growing season mean T: Total biomass (t/ha) Observed = symbols Maiorano et al FCR Multi-model simulation = shades (red shade = improved models) Multi-model simulation medians = lines

8 Multi-model ensembles to reduce uncertainty Model improvements reduce required number of models in multi-model ensembles Maiorano et al FCR Wang et al Nature Plants

9 AgMIP - Wheat yield decline with increasing temperature 30 model ensemble median (& mean of 30 years) +2 o C Wheat producing area 6% decline in global wheat production for each degree in global warming Asseng et al Nature CC

10 Different methods to estimate climate change impacts E s rainfall max & min temperature solar radiation Phenology E p CO 2 Assimilation C Harvest TUE Shoot + Leaf C N Grain C,N runoff C,N C N Root N Crop Residues (surface) CO 2 Denitrification Fertiliser 1 2 Residues (roots) 3 n LL DUL SAT FOM carbohydartes cellulose lignin CO 2 Mineralisation Immobilisation Mineral-N NH 4 NO 3 urea NH 4 Drainage BIOM C:N CO 2 US wheat yields Water CO 2 HUM C:N Soil Leaching Multi-model points Global-gridded Impact

11 Consistent impact estimates of global temperature increase on global yield, using 4 methods Yield impact with 1 o C increase in global temperature (%) Impacts of 1 o C (For wheat: Liu et al Nature CC) Zhao et al PNAS

12 Climate change impact on grain protein Region-specific (local climate, projected change, soil, cultivar, crop management, adaptation) Grain protein (%) high rainfall & high N The impact of climate change on grain protein is highly variable depending on local conditions together with specific changes in temperature, rainfall, atmospheric CO 2 concentration and possible adaptations. low rainfall faster fill rate Grain yield (t/ha) elevated CO 2 Asseng et al EJA