Abstract
The relationships between crop productivity and climate variability drivers are often assumed to be stationary over time. However, this may not be true in a warming climate. Here we use a crop model and a machine learning algorithm to demonstrate the changing impacts of climate drivers on wheat productivity in Australia. We find that, from the end of the nineteenth century to the 1980s, wheat productivity was mainly subject to the impacts of the El Niño Southern Oscillation. Since the 1990s, the impacts from the El Niño Southern Oscillation have been decreasing, but those from the Indian Ocean Dipole have been increasing. The warming climate has brought more occurrences of positive Indian Ocean Dipole events, resulting in severe yield reductions in recent decades. Our findings highlight the need to adapt seasonal forecasting to the changing impacts of climate variability to inform the management of climate-induced yield losses.
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Data availability
The climate, soil and climate drivers indices data are publicly available from the following sources: the SILO climate data are at https://www.longpaddock.qld.gov.au/silo, the soil data are at https://www.apsim.info/apsim-model/apsoil/ and the climate drivers indices data are at https://psl.noaa.gov/. The detailed wheat yield data simulated by the APSIM crop model and the raw data of the figures are available at Puyu Feng’s Github homepage https://github.com/PuyuFeng/NF_Paper.git. Source data are provided with this paper.
Code availability
The detailed R code for data processing and illustration is available at Puyu Feng’s Github homepage https://github.com/PuyuFeng/NF_Paper.git.
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Acknowledgements
This work was part of a study investigating the impacts of and adaptation to our changing climate in Australia and China. This work is supported by the 2115 Talent Development Program of China Agricultural University (grant no. 1191-00109011), the Fundamental Research Funds for the Central Universities (grant no. 2022TC110), National Key R&D Program of China (grant no. 2020YFA0608004) and National Natural Science Foundation of China (grant no. 42088101).
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B.W., P.F. and Q.Y. designed the research. P.F. and D.L.L. collected climate and soil data. P.F. ran machine learning and crop models. P.F. drew the figures. P.F. and B.W. wrote the draft manuscript. I.M., A.S.T., N.J.A., J.-J.L, A.D.K., Y.C., Y.L., D.L.L., Q.Y. and K.H. contributed to writing the manuscript.
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Feng, P., Wang, B., Macadam, I. et al. Increasing dominance of Indian Ocean variability impacts Australian wheat yields. Nat Food 3, 862–870 (2022). https://doi.org/10.1038/s43016-022-00613-9
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DOI: https://doi.org/10.1038/s43016-022-00613-9
