Vegetation drought risk assessment based on the multi-weight methods in Northwest China

Chen, Huixia; Wang, Qianfeng; Bento, Virgílio A.; Meng, Xianyong; Li, Xiaohan

doi:10.1007/s10661-023-11747-z

Cited by 5 publications

(1 citation statement)

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“…Vegetation phenology, denoting the recurrent seasonal fluctuations in vegetation growth, constitutes a crucial indicator of vegetation development with profound implications for terrestrial carbon balance and ecosystem productivity 1 – 5 . As an exceptionally responsive bio-indicator, vegetation phenology is a particularly important asset to climate change, making it an invaluable tool for monitoring ecological responses to shifting climate conditions 3 , 6 – 8 .…”

Section: Introductionmentioning

confidence: 99%

Understanding vegetation phenology responses to easily ignored climate factors in china's mid-high latitudes

Wang,

Chen,

et al. 2024

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Previous studies have primarily focused on the influence of temperature and precipitation on phenology. It is unclear if the easily ignored climate factors with drivers of vegetation growth can effect on vegetation phenology. In this research, we conducted an analysis of the start (SOS) and end (EOS) of the growing seasons in the northern region of China above 30°N from 1982 to 2014, focusing on two-season vegetation phenology. We examined the response of vegetation phenology of different vegetation types to preseason climatic factors, including relative humidity (RH), shortwave radiation (SR), maximum temperature (Tmax), and minimum temperature (Tmin). Our findings reveal that the optimal preseason influencing vegetation phenology length fell within the range of 0–60 days in most areas. Specifically, SOS exhibited a significant negative correlation with Tmax and Tmin in 44.15% and 42.25% of the areas, respectively, while EOS displayed a significant negative correlation with SR in 49.03% of the areas. Additionally, we identified that RH emerged as the dominant climatic factor influencing the phenology of savanna (SA), whereas temperature strongly controlled the SOS of deciduous needleleaf forest (DNF) and deciduous broadleaf forest (DBF). Meanwhile, the EOS of DNF was primarily influenced by Tmax. In conclusion, this study provides valuable insights into how various vegetation types adapt to climate change, offering a scientific basis for implementing effective vegetation adaptation measures.

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