Your browser doesn't support javascript.
loading
Heat stress may cause a significant reduction of rice yield in China under future climate scenarios.
Sun, Qing; Zhao, Yanxia; Zhang, Yi; Chen, Sining; Ying, Qing; Lv, Zunfu; Che, Xianghong; Wang, Delong.
Afiliación
  • Sun Q; State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences, Beijing 100081, China.
  • Zhao Y; State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences, Beijing 100081, China. Electronic address: zhaoyanxia@cma.gov.cn.
  • Zhang Y; State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences, Beijing 100081, China.
  • Chen S; Tianjin Climate Center, Tianjin 300074, China.
  • Ying Q; Department of Geosciences, Texas Tech University, Lubbock, TX 79430, USA.
  • Lv Z; College of Agriculture & Food Science and the Key Laboratory for Quality Improvement of Agricultural Products of Zhejiang Province, Zhejiang A & F University, Lin'an 311300, Zhejiang, China.
  • Che X; Chinese Academy of Surveying & Mapping, Beijing 100830, China.
  • Wang D; Beijing Institute of Applied Meteorology, Beijing 100029, China.
Sci Total Environ ; 818: 151746, 2022 Apr 20.
Article en En | MEDLINE | ID: mdl-34801492
ABSTRACT
Extreme heat events have become more frequent and severe under climate change and seriously threaten rice growth. Most existing crop models tend to underestimate the impacts of heat stress on rice yields. Heat stress modules in crop models have not been extensively explored, particularly on a large scale. This study modeled rice growth under heat stress at the flowering and filling stages through two heat stress models which coupled into the CERES-Rice model. We evaluated the advanced model with provincial statistics and Gridded Observed Rice Yield. Our improved CERES-Rice model produced more accurate estimates on rice yield than the original model evidenced by an increased correlation coefficient (R) of 12.72% and d-index of 0.02%. The RMSE and MAE decreased by 5.94% and 6.01%, respectively. Most pseudo positive correlations between rice yield and the number of heat days were corrected to the negative ones by the improved model. The future projections from the improved model signifies multi-model ensemble yield projection without CO2 effect (MME-I-NOCO2) has an apparent fall from 2020 to 2099 under RCP4.5, RCP6.0 and RCP8.5 with the decreasing percentages of 6%, 14%, and 37%, respectively, whereas the decreasing trend (12%) only occurs under RCP8.5 with CO2 effect (MME-I-CO2). The apparently decreasing trends of yield projection from MME-I-NOCO2 will occur in most rice-planted regions of China with the decreasing rate < 50 kg/ha/a especially in the central-south and southern cropping regions, and this decreasing trend will be slowed down for MME-I-CO2. Relative to rice yield of historical period, rice yield variations of MME-I-NOCO2 for different growing seasons show a downward trend with the decrease of approximately 54%, 60%, and 43%, respectively. Our study highlights the importance of modeling crop yields under heat stress to food security, agricultural adaptation and mitigation to climate change.
Asunto(s)
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Oryza Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: Sci Total Environ Año: 2022 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Oryza Tipo de estudio: Prognostic_studies País/Región como asunto: Asia Idioma: En Revista: Sci Total Environ Año: 2022 Tipo del documento: Article