Abstract
To better understand how climate change might influence global canola production, scientists from six countries have completed the first inter-comparison of eight crop models for simulating growth and seed yield of canola, based on experimental data from six sites across five countries. A sensitivity analysis was conducted with a combination of five levels of atmospheric CO2 concentrations, seven temperature changes, five precipitation changes, together with five nitrogen application rates. Our results were in several aspects different from those of previous model inter-comparison studies for wheat, maize, rice, and potato crops. A partial model calibration only on phenology led to very poor simulation of aboveground biomass and seed yield of canola, even from the ensemble median or mean. A full calibration with additional data of leaf area index, biomass, and yield from one treatment at each site reduced simulation error of seed yield from 43.8 to 18.0%, but the uncertainty in simulation results remained large. Such calibration (with data from one treatment) was not able to constrain model parameters to reduce simulation uncertainty across the wide range of environments. Using a multi-model ensemble mean or median reduced the uncertainty of yield simulations, but the simulation error remained much larger than observation errors, indicating no guarantee that the ensemble mean/median would predict the correct responses. Using multi-model ensemble median, canola yield was projected to decline with rising temperature (2.5–5.7% per °C), but to increase with increasing CO2 concentration (4.6–8.3% per 100-ppm), rainfall (2.1–6.1% per 10% increase), and nitrogen rates (1.3–6.0% per 10% increase) depending on locations. Due to the large uncertainty, these results need to be treated with caution. We further discuss the need to collect new data to improve modelling of several key physiological processes of canola for increased confidence in future climate impact assessments.
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Acknowledgements
We thank Dr. Susie Sprague and Dr. John Kirkegaard for provision of the experimental data from Young which was funded by CSIRO and the Australian Grains Research and Development Corporation (Project CSP00085). We thank Penny Riffkin for provision of the experimental data from Hamilton which was funded by the Department of Jobs, Precincts and Regions Victoria and the Australian Grains Research and Development Corporation (Project DAV00141). We thank Prof. Anthony Whitbread (previously University of Goettingen, now ICRISAT) for his support in collating the data from the Rosdorf site.
Funding
DH received support from the Natural Science Foundation of China (Grant No. 41905103). WS and BG received funding from Agriculture and Agri-Food Canada’s Growing Forward 2 policy framework program. MPH received “Limpopo Living Landscapes” project (SPACES program, grant number 01LL1304A) funded by the German Federal Ministry of Education 544 and Research (http://www.bmbf.de/en/). PD and LL received support from the Sardinia Region through a co-financed scholarship under the 2007–2013 ESF POR SARDINIA (7/2007RL) “Scientific Research and Technological Innovation Promotion in Sardinia” program. EW, DH, and JML received financial support from CSIRO to conduct this research.
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Wang, E., He, D., Wang, J. et al. How reliable are current crop models for simulating growth and seed yield of canola across global sites and under future climate change?. Climatic Change 172, 20 (2022). https://doi.org/10.1007/s10584-022-03375-2
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DOI: https://doi.org/10.1007/s10584-022-03375-2