Huanjiong Wang

Dr. Huanjiong Wang

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Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 June 2014 in Global Change Biology
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QGQuansheng Ge
Quansheng Ge
HWHuanjiong Wang
Huanjiong Wang
TRThis Rutishauser
This Rutishauser
Junhu DaiJunhu Dai
Junhu Dai

26 November 2018 in Nature Climate Change
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CWChaoyang Wu
Chaoyang Wu
XWXiaoyue Wang
Xiaoyue Wang
HWHuanjiong Wang
Huanjiong Wang
PCPhil Ciais
Phil Ciais
Josep PenuelasJosep Penuelas
Josep Penuelas
QGQuansheng Ge
Quansheng Ge
Plant phenology is a sensitive indicator of climate change1,2,3,4 and plays an important role in regulating carbon uptake by plants5,6,7. 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 unknown10,11,12. 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.

5 September 2022 in Nature Climate Change
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CWChaoyang Wu
Chaoyang Wu
Jie PengJie Peng
Jie Peng
PCPhil Ciais
Phil Ciais
Josep PenuelasJosep Penuelas
Josep Penuelas
HWHuanjiong Wang
Huanjiong Wang
QGQuansheng Ge
Quansheng Ge

2 October 2020 in Nature Communications
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HWHuanjiong Wang
Huanjiong Wang
CWChaoyang Wu
Chaoyang Wu
PCPhil Ciais
Phil Ciais
Josep PenuelasJosep Penuelas
Josep Penuelas
JDJunhu Dai
Junhu Dai
QGQuansheng Ge
Quansheng Ge
Spring warming substantially advances leaf unfolding and flowering time for perennials. Winter warming, however, decreases chilling accumulation (CA), which increases the heat requirement (HR) and acts to delay spring phenology. Whether or not this negative CA-HR relationship is correctly interpreted in ecosystem models remains unknown. Using leaf unfolding and flowering data for 30 perennials in Europe, here we show that more than half (7 of 12) of current chilling models are invalid since they show a positive CA-HR relationship. The possible reason is that they overlook the effect of freezing temperature on dormancy release. Overestimation of the advance in spring phenology by the end of this century by these invalid chilling models could be as large as 7.6 and 20.0 days under RCPs 4.5 and 8.5, respectively. Our results highlight the need for a better representation of chilling for the correct understanding of spring phenological responses to future climate change.

4 June 2013 in International Journal of Biometeorology
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JDJunhu Dai
Junhu Dai
HWHuanjiong Wang
Huanjiong Wang
QGQuansheng Ge
Quansheng Ge

12 April 2021 in Proceedings of the National Academy of Sciences
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CWChaoyang Wu
Chaoyang Wu
JWJian Wang
Jian Wang
PCPhilippe Ciais
Philippe Ciais
Josep PenuelasJosep Penuelas
Josep Penuelas
XZXiaoyang Zhang
Xiaoyang Zhang
QGQuansheng Ge
Quansheng Ge
Significance: Decline in winds over past decades were observed over high northern latitudes (>50°), yet its influence on the date of autumn leaf senescence (DFS) remains unknown. Using ground observations, flux measurements, and remote sensing imagery, here we show that decline in winds significantly extended DFS over high latitudes at a magnitude comparable with the temperature and precipitation effects. We found that decline in winds reduces evapotranspiration, causes fewer damaging effects, and also results in decreased cooling effect. Our results therefore are of great significance for carbon cycle modeling because an improved algorithm based on these findings projected overall widespread earlier DFS by the end of this century, contributing potentially to a positive feedback to climate.