Author
Listed:
- Chaoyang Wu
(Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences
University of the Chinese Academy of Sciences)
- Xiaoyue Wang
(Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences
University of the Chinese Academy of Sciences)
- Huanjiong Wang
(Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences
University of the Chinese Academy of Sciences)
- Philippe Ciais
(Laboratoire des Sciences du Climat et de l’Environnement, IPSL-LSCE CEA CNRS UVSQ)
- Josep Peñuelas
(CSIC, Global Ecology Unit CREAF-CSIC-UAB
CREAF)
- Ranga B. Myneni
(Boston University)
- Ankur R. Desai
(University of Wisconsin–Madison)
- Christopher M. Gough
(Virginia Commonwealth University)
- Alemu Gonsamo
(University of Toronto)
- Andrew T. Black
(University of British Columbia)
- Rachhpal S. Jassal
(University of British Columbia)
- Weimin Ju
(Nanjing University)
- Wenping Yuan
(Sun Yat-Sen University)
- Yongshuo Fu
(Beijing Normal University)
- Miaogen Shen
(CAS Center for Excellence in Tibetan Plateau Earth Sciences)
- Shihua Li
(University of Electronic Science and Technology of China)
- Ronggao Liu
(Institute of Geographic Sciences and Natural Resources Research, CAS)
- Jing M. Chen
(University of Toronto)
- Quansheng Ge
(Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences
University of the Chinese Academy of Sciences)
Abstract
Plant phenology is a sensitive indicator of climate change1–4 and plays an important role in regulating carbon uptake by plants5–7. Previous studies have focused on spring leaf-out by daytime temperature and the onset of snow-melt time8,9, but the drivers controlling leaf senescence date (LSD) in autumn remain largely unknown10–12. Using long-term ground phenological records (14,536 time series since the 1900s) and satellite greenness observations dating back to the 1980s, we show that rising pre-season maximum daytime (Tday) and minimum night-time (Tnight) temperatures had contrasting effects on the timing of autumn LSD in the Northern Hemisphere (> 20° N). If higher Tday leads to an earlier or later LSD, an increase in Tnight systematically drives LSD to occur oppositely. Contrasting impacts of daytime and night-time warming on drought stress may be the underlying mechanism. Our LSD model considering these opposite effects improved autumn phenology modelling and predicted an overall earlier autumn LSD by the end of this century compared with traditional projections. These results challenge the notion of prolonged growth under higher autumn temperatures, suggesting instead that leaf senescence in the Northern Hemisphere will begin earlier than currently expected, causing a positive climate feedback.
Suggested Citation
Chaoyang Wu & Xiaoyue Wang & Huanjiong Wang & Philippe Ciais & Josep Peñuelas & Ranga B. Myneni & Ankur R. Desai & Christopher M. Gough & Alemu Gonsamo & Andrew T. Black & Rachhpal S. Jassal & Weimin , 2018.
"Contrasting responses of autumn-leaf senescence to daytime and night-time warming,"
Nature Climate Change, Nature, vol. 8(12), pages 1092-1096, December.
Handle:
RePEc:nat:natcli:v:8:y:2018:i:12:d:10.1038_s41558-018-0346-z
DOI: 10.1038/s41558-018-0346-z
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Cited by:
- Zhaozhe Li & Ranghui Wang & Bo Liu & Zhonghua Qian & Yongping Wu & Cheng Li, 2022.
"Responses of Vegetation Autumn Phenology to Climatic Factors in Northern China,"
Sustainability, MDPI, vol. 14(14), pages 1-13, July.
- Lwando Royimani & Onisimo Mutanga & John Odindi & Rob Slotow, 2023.
"Multi-Temporal Assessment of Remotely Sensed Autumn Grass Senescence across Climatic and Topographic Gradients,"
Land, MDPI, vol. 12(1), pages 1-14, January.
- Xianliang Zhang & Tim Rademacher & Hongyan Liu & Lu Wang & Rubén D. Manzanedo, 2023.
"Fading regulation of diurnal temperature ranges on drought-induced growth loss for drought-tolerant tree species,"
Nature Communications, Nature, vol. 14(1), pages 1-10, December.
- Liu, Guohua & Chen, Xiaoqiu & Fu, Yongshuo & Delpierre, Nicolas, 2019.
"Modelling leaf coloration dates over temperate China by considering effects of leafy season climate,"
Ecological Modelling, Elsevier, vol. 394(C), pages 34-43.
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