Optimized rice adaptations in response to heat and cold stress under climate change in southern China

Zhang, Lei; Huo, Zhiguo; Amou, Martial; Xiao, Jingjing; Cao, Yun; Gou, Peng; Li, Sen

doi:10.1007/s10113-022-02010-1

Cited by 6 publications

(4 citation statements)

References 50 publications

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“…Specifically, to cope with increasing heatwaves in eastern and southern regions, more efforts of measures like bioclimatic design of buildings, multifunctionality of spaces, circular use of materials, renewable energy services and so forth are needed to ensure human health and society security (IPCC, 2022; van Ruijven et al, 2019). Besides, climate‐smart agriculture programme, for example, adjustment in cultivation and improvement in heat resistance variety (Ding et al, 2020; Zhang et al, 2023) can help farmers adapt to future risks. It should be emphasized that frost is likely to occur on some days across some parts where need adaptations like heating services, although there is a general decrease.…”

Section: Discussionmentioning

confidence: 99%

Regional features of future warming using high‐resolution downscaled multimodel climate scenarios in mainland China

Zhang¹,

Zhao³

et al. 2023

Intl Journal of Climatology

Self Cite

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The frequency and magnitude of global warming events varies greatly across different regions and countries. The climatic diversity for China and future warming features are projected across 12 climatic zones based on the ensemble of the five well‐performing high‐resolution downscaled climate models for each zone. There are warming patterns for the mean near‐surface air temperature (Tm), maximum near‐surface air temperature (Tmax), minimum near‐surface air temperature (Tmin) as well as heatwave and frost events. Under RCP4.5 and RCP8.5 scenarios, the three indices (i.e., Tm, Tmax and Tmin) countrywide are likely to increase at respective rates of 0.30–0.31 and 0.64–0.67°C·decade−1. The extent of frost event (FE) are projected to decrease at a rate of −1912 and −4442 day·km−2·decade−1 while the extent of heatwave event (HE) increase at a rate of 1116 and 3557 day·km−2·decade−1 under RCP4.5 and RCP8.5 scenarios, respectively. A higher increment in temperatures, a decreasing trend in diurnal temperature range (DTR), frost days and FE are highlighted in the western and northern zones, while these trends are opposite in southern zones. The warming is likely to get faster in the current colder zones (western and northern zones) while heatwave is more intense and severe in Jianghuai, Jianghan, the south Yangzi River, South China and Xinjiang. These potential changes indicate that adaption and mitigation strategies are necessary in response to future warming.

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Section: Discussionmentioning

confidence: 99%

Regional features of future warming using high‐resolution downscaled multimodel climate scenarios in mainland China

Zhang¹,

Zhao³

et al. 2023

Intl Journal of Climatology

Self Cite

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“…In our experiment, cold stress often occurred in SD3 and SD4, but did not occur in SD1 and SD2. In the future, climate change is most likely towards increasing heat stress and decreasing cold stress [24], cold stress could be reduced to a small intensity but heat stress would be getting severer [28]. Therefore, adaptations are urgently needed to minimize the latent negative effects of rice heat stress in central China.…”

Section: Discussionmentioning

confidence: 99%

Optimizing Rice Sowing Dates for High Yield and Climate Adaptation in Central China

Liu,

Song,

et al. 2023

Agronomy

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Optimizing the sowing date of rice can change the seasonal patterns and distributions of climate factors during the crop growing season, making it one of the most effective ways to adapt to climate change and achieve high yield. A four–year field experiment (2018–2021) was conducted at Jingzhou Agricultural Meteorological Experiment Station, central China, with four different sowing dates (SD) each year, late April (SD1), early May (SD2), mid–May (SD3) and late May (SD4). Dry matter accumulation, grain yield and climate conditions were observed across sowing dates. Our findings revealed that delaying the sowing date from early May to mid or late May could increase grain yield by 5.6% to 8.6%. However, sowing too early could increase heat stress, decrease the net effective accumulated temperature, inhibit rice growth, and reduce grain yield. On the other hand, sowing too late could increase the risk of low temperatures after flowering. From the perspective of increasing net effective accumulated temperature, reducing heat stress and low temperature after flowering, mid to late May was the most favorable sowing date to ensure high yield. It is suggested that optimizing rice sowing dates can effectively avoid the threat of heat stress and better match thermal resources, thereby increasing rice productivity.

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“…However, long-term waterlogging caused by excessive precipitation can damage crop growth and reduce crop yields (Wang et al 2023;Li et al 2019). Therefore, given that extreme climate events can lead to severe agricultural disasters, understanding trends in the frequency and intensity of agroclimatic extreme events is critical to ensuring food security in a warming climate environment (Zhang et al 2023;Xiao et al 2022;Bai et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Assessment of extreme climate stress across China’s maize harvest region in CMIP6 simulations

Xiao,

Shi,

Chen

et al. 2024

Preprint

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Climate change is expected to increase the frequency and severity of climate extremes, which will negatively impact crop production. As one of the main food and feed crops, maize is also vulnerable to extreme climate events. In order to accurately and comprehensively assess the future climate risk to maize, it is urgent to project and evaluate the stress of extreme climate related maize production under future climate scenarios. In this study, we comprehensively evaluated the spatio-temporal changes in the frequency and intensity of six extreme climate indices (ECIs) across China’s maize harvest region by using a multi-model ensemble method, and examined the capability of the Coupled Model Intercomparison Project Phase 6 (CMIP6) to capture these variations. We found that the Independence Weight Mean (IWM) ensemble results calculated by multiple Global Change Models (GCMs) with bias correction could better reproduce each ECI. The results indicated that heat stress for maize showed consistent increase trends under four future climate scenarios in the 21st century. The intensity and frequency of the three extreme temperature indices in 2080s were significantly higher than these in 2040s, and in the high emission scenario were significantly higher than these in the low emission scenario. The three extreme precipitation indices changed slightly in the future, but the spatial changes were relatively prominent. Overall, the temporal characteristics and trends of extreme temperature events were consistent, while the spatial heterogeneity of extreme precipitation events was more significant.

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Optimized rice adaptations in response to heat and cold stress under climate change in southern China

Cited by 6 publications

References 50 publications

Regional features of future warming using high‐resolution downscaled multimodel climate scenarios in mainland China

Regional features of future warming using high‐resolution downscaled multimodel climate scenarios in mainland China

Optimizing Rice Sowing Dates for High Yield and Climate Adaptation in Central China

Assessment of extreme climate stress across China’s maize harvest region in CMIP6 simulations

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