Literature DB >> 27991912

Plausible rice yield losses under future climate warming.

Chuang Zhao1, Shilong Piao1,2,3, Xuhui Wang1, Yao Huang4, Philippe Ciais5, Joshua Elliott6, Mengtian Huang1, Ivan A Janssens7, Tao Li8, Xu Lian1, Yongwen Liu1, Christoph Müller9, Shushi Peng1, Tao Wang2,3, Zhenzhong Zeng1, Josep Peñuelas10,11.   

Abstract

Rice is the staple food for more than 50% of the world's population1-3. Reliable prediction of changes in rice yield is thus central for maintaining global food security. This is an extraordinary challenge. Here, we compare the sensitivity of rice yield to temperature increase derived from field warming experiments and three modelling approaches: statistical models, local crop models and global gridded crop models. Field warming experiments produce a substantial rice yield loss under warming, with an average temperature sensitivity of -5.2 ± 1.4% K-1. Local crop models give a similar sensitivity (-6.3 ± 0.4% K-1), but statistical and global gridded crop models both suggest less negative impacts of warming on yields (-0.8 ± 0.3% and -2.4 ± 3.7% K-1, respectively). Using data from field warming experiments, we further propose a conditional probability approach to constrain the large range of global gridded crop model results for the future yield changes in response to warming by the end of the century (from -1.3% to -9.3% K-1). The constraint implies a more negative response to warming (-8.3 ± 1.4% K-1) and reduces the spread of the model ensemble by 33%. This yield reduction exceeds that estimated by the International Food Policy Research Institute assessment (-4.2 to -6.4% K-1) (ref. 4). Our study suggests that without CO2 fertilization, effective adaptation and genetic improvement, severe rice yield losses are plausible under intensive climate warming scenarios.

Entities:  

Year:  2016        PMID: 27991912     DOI: 10.1038/nplants.2016.202

Source DB:  PubMed          Journal:  Nat Plants        ISSN: 2055-0278            Impact factor:   15.793


  11 in total

1.  Leaf layer-based transcriptome profiling for discovery of epidermal-selective promoters in Medicago truncatula.

Authors:  Xin Cui; Ji Hyung Jun; Xiaolan Rao; Camille Bahr; Elisabeth Chapman; Stephen Temple; Richard A Dixon
Journal:  Planta       Date:  2022-07-06       Impact factor: 4.116

2.  Transcriptomics for Drought Stress Mediated by Biological Processes in-relation to Key Regulated Pathways in Gossypium darwinii.

Authors:  Cuilian Xu; Muhammad Kashif Ilyas; Richard Odongo Magwanga; Hejun Lu; M Kashif Riaz Khan; Zhongli Zhou; Yujun Li; Zhengcheng Kuang; Asif Javaid; Danish Ibrar; Abdul Ghafoor; Kunbo Wang; Fang Liu; Haodong Chen
Journal:  Mol Biol Rep       Date:  2022-07-30       Impact factor: 2.742

3.  Selection of Candidate Genes Conferring Blast Resistance and Heat Tolerance in Rice through Integration of Meta-QTLs and RNA-Seq.

Authors:  Tian Tian; Lijuan Chen; Yufang Ai; Huaqin He
Journal:  Genes (Basel)       Date:  2022-01-25       Impact factor: 4.096

4.  Recovery of metagenome-assembled genomes from the phyllosphere of 110 rice genotypes.

Authors:  Pin Su; Wisnu Adi Wicaksono; Chenggang Li; Kristina Michl; Gabriele Berg; Dan Wang; Youlun Xiao; Renyan Huang; Houxiang Kang; Deyong Zhang; Tomislav Cernava; Yong Liu
Journal:  Sci Data       Date:  2022-06-01       Impact factor: 8.501

5.  Temperature increase reduces global yields of major crops in four independent estimates.

Authors:  Chuang Zhao; Bing Liu; Shilong Piao; Xuhui Wang; David B Lobell; Yao Huang; Mengtian Huang; Yitong Yao; Simona Bassu; Philippe Ciais; Jean-Louis Durand; Joshua Elliott; Frank Ewert; Ivan A Janssens; Tao Li; Erda Lin; Qiang Liu; Pierre Martre; Christoph Müller; Shushi Peng; Josep Peñuelas; Alex C Ruane; Daniel Wallach; Tao Wang; Donghai Wu; Zhuo Liu; Yan Zhu; Zaichun Zhu; Senthold Asseng
Journal:  Proc Natl Acad Sci U S A       Date:  2017-08-15       Impact factor: 11.205

6.  A global analysis of alternative tillage and crop establishment practices for economically and environmentally efficient rice production.

Authors:  Debashis Chakraborty; Jagdish Kumar Ladha; Dharamvir Singh Rana; Mangi Lal Jat; Mahesh Kumar Gathala; Sudhir Yadav; Adusumilli Narayana Rao; Mugadoli S Ramesha; Anitha Raman
Journal:  Sci Rep       Date:  2017-08-24       Impact factor: 4.379

7.  Enhancement of vitamin B6 levels in rice expressing Arabidopsis vitamin B6 biosynthesis de novo genes.

Authors:  Nathalie Mangel; Jared B Fudge; Kuan-Te Li; Ting-Ying Wu; Takayuki Tohge; Alisdair R Fernie; Boris Szurek; Teresa B Fitzpatrick; Wilhelm Gruissem; Hervé Vanderschuren
Journal:  Plant J       Date:  2019-07-11       Impact factor: 6.417

8.  Reduction in nutritional quality and growing area suitability of common bean under climate change induced drought stress in Africa.

Authors:  Marijke Hummel; Brendan F Hallahan; Galina Brychkova; Julian Ramirez-Villegas; Veronica Guwela; Bartholomew Chataika; Edna Curley; Peter C McKeown; Liam Morrison; Elise F Talsma; Steve Beebe; Andy Jarvis; Rowland Chirwa; Charles Spillane
Journal:  Sci Rep       Date:  2018-11-01       Impact factor: 4.379

9.  Metabolome-based prediction of yield heterosis contributes to the breeding of elite rice.

Authors:  Zhiwu Dan; Yunping Chen; Weibo Zhao; Qiong Wang; Wenchao Huang
Journal:  Life Sci Alliance       Date:  2019-12-13

10.  Predicting spatial and temporal variability in crop yields: an inter-comparison of machine learning, regression and process-based models.

Authors:  Guoyong Leng; Jim W Hall
Journal:  Environ Res Lett       Date:  2020-02-28       Impact factor: 6.947

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