Effects of climate change and agronomic practice on changes in wheat phenology
Phenological changes in crops affect efficient agricultural production and can be used as important biological indicators of local and regional climate change. Although crop phenological changes and their responses to climate change, especially temperature, have been investigated, the impact of agronomic practice such as cultivar shifts and planted date changes on crop phenology remains unclear. Here, we used a long-term dataset (1981–2010) of wheat phenology and associated local weather data from 48 agro-meteorological stations in four temperature zones in China to analyze phenological changes of spring and winter wheat. Trend analysis method was used to estimate changes in the date of growth stages and the duration of growth phases, while sensitivity analysis method was used to qualify the response of growth phase duration to mean temperature (Tmean), total precipitation (PRE), and total sunshine duration (SSD). Using the Crop Environment Resource Synthesis-wheat model, we isolated the impacts of climate change, cultivar selection, and sowing date on phenological change of wheat. Results show that phenological changes were greatest in the warm-temperate zone. Sensitivity analysis indicates that growth phase duration was generally negatively related to Tmean and positively related to PRE and SSD. The positive sensitivity response to Tmean occurred in the tillering to jointing and sowing to maturity growth periods in the warmer temperature zones, suggesting that warmer temperatures during the overwintering period hampered effective vernalization in winter wheat. Modeling results further indicate that reductions in wheat growth duration caused by climate change could be offset by the introduction of new cultivars with high thermal requirements and accelerated with delayed sowing date.
This work was supported by Strategic Priority Research Program of the Chinese Academy of Sciences, [Grant No. XDA19040103], National Natural Science Foundation of China [Grant No. 41671037], Youth Innovation Promotion Association, CAS [Grant No. 2016049], and Program for “Kezhen” Excellent Talents in IGSNRR, CAS, [Grant No. 2017RC101]. We also thank the China Meteorological Administration for providing data support.
- China Yearbook Press (2015) The People’s Republic of China Yearbook 2015. People’s Publishing House, BeijingGoogle Scholar
- Hoogenboom G, Jones JW, Wilkens PW et al (2015) Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.6 (www.DSSAT.net). In: D. Foundation (Editor). Prosser, Washington
- Iglesias A (2009) Use of DSSAT models for climate change impact assessment: calibration and validation of CERES-wheat and CERES-maize in Spain. Climate Variability. http://unfccc.int/files/national_reports/non-annex_i_natcom/cge/application/pdf/agriculture.dssatvalidation.pdf
- IPCC (2013) Summary for policymakers. In: Stocker TF et al (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, pp 3–29Google Scholar