In arid regions, climatic fluctuations significantly affect vegetation structure and function. Sun-induced chlorophyll fluorescence (SIF) can quantify certain physiological parameters of vegetation but has limitations in characterizing responses to climate change. This study analyzed the spatiotemporal differences in response to climate change across various ecological regions and vegetation types from 2000 to 2020 in Xinjiang. According to China's ecological zoning, R1 (Altai Mountains-Western Junggar Mountains forest-steppe) and R5 (Pamir-Kunlun Mountains-Altyn Tagh high-altitude desert grasslands) represent two ecological extremes, while R2-R4 span desert and forest-steppe ecosystems. We employed the standardized precipitation evapotranspiration index (SPEI) at different timescales to represent drought intensity and frequency in conjunction with global OCO-2 SIF products (GOSIF) and the normalized difference vegetation index (NDVI) to assess vegetation growth conditions. The results show that (1) between 2000 and 2020, the overall drought severity in Xinjiang exhibited a slight deterioration, particularly in northern regions (R1 and R2), with a gradual transition from short-term to long-term drought conditions. The R4 and R5 ecological regions in southern Xinjiang also displayed a slight deterioration trend; however, R5 remained relatively stable on the SPEI24 timescale. (2) The NDVI and SIF values across Xinjiang exhibited an upward trend. However, in densely vegetated areas (R1-R3), both NDVI and SIF declined, with a more pronounced decrease in SIF observed in natural forests. (3) Vegetation in northern Xinjiang showed a significantly stronger response to climate change than that in southern Xinjiang, with physiological parameters (SIF) being more sensitive than structural parameters (NDVI). The R1, R2, and R3 ecological regions were primarily influenced by long-term climate change, whereas the R4 and R5 regions were more affected by short-term climate change. Natural grasslands showed a significantly stronger response than forests, particularly in areas with lower vegetation cover that are more structurally impacted. This study provides an important scientific basis for ecological management and climate adaptation in Xinjiang, emphasizing the need for differentiated strategies across ecological regions to support sustainable development.
机构:Gong Qing Institute of Science and Technology,Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research
Ming Li
Yang Wang
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机构:Gong Qing Institute of Science and Technology,Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research
Yang Wang
Na Li
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机构:Gong Qing Institute of Science and Technology,Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research
Na Li
Bin Chen
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机构:Gong Qing Institute of Science and Technology,Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research
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Gong Qing Inst Sci & Technol, Nanchang 330044, Peoples R China
Jilin Acad Agr Sci, Changchun 130016, Peoples R China
Jilin Jianzhu Univ, Sch Civil & Environm Engn, Changchun, Peoples R ChinaGong Qing Inst Sci & Technol, Nanchang 330044, Peoples R China
Li, Ming
Wang, Yang
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Gong Qing Inst Sci & Technol, Nanchang 330044, Peoples R China
Space Engn Univ, Space Secur Ctr, Beijing 101416, Peoples R China
Jilin Jianzhu Univ, Sch Civil & Environm Engn, Changchun, Peoples R ChinaGong Qing Inst Sci & Technol, Nanchang 330044, Peoples R China
Wang, Yang
Li, Na
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Jilin Jianzhu Univ, Sch Civil & Environm Engn, Changchun, Peoples R ChinaGong Qing Inst Sci & Technol, Nanchang 330044, Peoples R China
Li, Na
Chen, Bin
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机构:
Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R ChinaGong Qing Inst Sci & Technol, Nanchang 330044, Peoples R China
Chen, Bin
Chou, Shuren
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Space Engn Univ, Space Secur Ctr, Beijing 101416, Peoples R ChinaGong Qing Inst Sci & Technol, Nanchang 330044, Peoples R China