TY - JOUR
T1 - Asymmetric response of primary productivity to precipitation anomalies in Southwest China
AU - Dong, Guanyu
AU - Fan, Lei
AU - Fensholt, Rasmus
AU - Frappart, Frédéric
AU - Ciais, Philippe
AU - Xiao, Xiangming
AU - Sitch, Stephen
AU - Xing, Zanpin
AU - Yu, Ling
AU - Zhou, Zhilan
AU - Ma, Mingguo
AU - Tong, Xiaowei
AU - Xiao, Qing
AU - Wigneron, Jean-Pierre
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023
Y1 - 2023
N2 - Southwest China has been the largest terrestrial carbon sink in China over the past 30 years, but has recently experienced a succession of droughts caused by high precipitation variability, potentially threatening vegetation productivity in the region. Yet, the impact of precipitation anomalies on the vegetation primary productivity is poorly known. We used an asymmetry index (AI) to explore possible asymmetric productivity responses to precipitation anomalies in Southwest China from 2003 to 2018, using a precipitation dataset, combined with gross primary productivity (GPP), net primary productivity (NPP), and vegetation optical depth (VOD) products. Our results indicate that the vegetation primary productivity of Southwest China shows a negative asymmetry, suggesting that the increase of vegetation primary productivity during wet years exceeds the decrease during dry years. However, this negative asymmetry of vegetation primary productivity was shifted towards a positive asymmetry during the period of analysis, suggesting that the resistance of vegetation to drought, has increased with the rise in the occurrence of drought events. Among the different biomes, grassland vegetation primary productivity had the highest sensitivity to precipitation anomalies, indicating that grasslands are more flexible than other biomes and able to adjust primary productivity in response to precipitation anomalies. Furthermore, our results showed that the asymmetry of vegetation primary productivity was influenced by the effects of temperature, precipitation, solar radiation, and anthropogenic and topographic factors. These findings improve our understanding of the response of vegetation primary productivity to climate change over Southwest China.
AB - Southwest China has been the largest terrestrial carbon sink in China over the past 30 years, but has recently experienced a succession of droughts caused by high precipitation variability, potentially threatening vegetation productivity in the region. Yet, the impact of precipitation anomalies on the vegetation primary productivity is poorly known. We used an asymmetry index (AI) to explore possible asymmetric productivity responses to precipitation anomalies in Southwest China from 2003 to 2018, using a precipitation dataset, combined with gross primary productivity (GPP), net primary productivity (NPP), and vegetation optical depth (VOD) products. Our results indicate that the vegetation primary productivity of Southwest China shows a negative asymmetry, suggesting that the increase of vegetation primary productivity during wet years exceeds the decrease during dry years. However, this negative asymmetry of vegetation primary productivity was shifted towards a positive asymmetry during the period of analysis, suggesting that the resistance of vegetation to drought, has increased with the rise in the occurrence of drought events. Among the different biomes, grassland vegetation primary productivity had the highest sensitivity to precipitation anomalies, indicating that grasslands are more flexible than other biomes and able to adjust primary productivity in response to precipitation anomalies. Furthermore, our results showed that the asymmetry of vegetation primary productivity was influenced by the effects of temperature, precipitation, solar radiation, and anthropogenic and topographic factors. These findings improve our understanding of the response of vegetation primary productivity to climate change over Southwest China.
KW - Asymmetric response
KW - Precipitation anomalies
KW - Southwest China
KW - Vegetation primary productivity
U2 - 10.1016/j.agrformet.2023.109350
DO - 10.1016/j.agrformet.2023.109350
M3 - Journal article
AN - SCOPUS:85149973719
VL - 331
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
SN - 0168-1923
M1 - 109350
ER -