Vegetation sensitivity shift from temperature to radiation dominance in Northwest China's drylands—Implications for ecosystem stability in mid-latitude drylands

Clarifying the spatiotemporal patterns and driving mechanisms of vegetation growth and sensitivity is critical for assessing ecosystem stability and formulating conservation strategies. Taking Northwest China (NWC)—the core of global mid-latitude arid regions and China's “Northern Ecological Security Barrier”—as the study area, we analyzed vegetation growth (via EVI) and sensitivity (via VSI) dynamics, and their climatic drivers (temperature, precipitation, and solar radiation) (2000−2022) using a novel EVI-VSI synergetic framework, combined with growing-season EVI data, China's national climate/vegetation zoning, and statistical methods (ANOVA, Mann-Kendall trend test, 11-year moving window). The results show that: 1) EVI showed significant zonal differences (all P < 0.001): under climate zoning, mean EVI followed “humid (0.46 ± 0.06) > semi-humid (0.31 ± 0.08) > semi-arid/arid (0.21–0.22)”; VSI (regional mean: 47.10 ± 20.01) had no zonal differences ( P > 0.05), with low spatial overlap between high-EVI and high-VSI areas. 2) EVI increased significantly (0.0021 a −1 , P < 0.01), with 88.21% of the region improving (highest in humid zones: 99.16%); VSI decreased non-significantly (−0.021 a −1 , P > 0.05), with wetlands showing a lower decline (45.56%) due to human disturbance (grazing, tourism). 3) climatic drivers exhibited distinct zoning differences, with a post-2010 trend of “weakened temperature dominance, enhanced radiation dominance”: semi-arid zones saw the proportion of radiation-dominated areas undergo a marked surge across the study period, rising from its lowest point (9.51% in 2007) to its peak (46.35% in 2017), making it the dominant driver; arid zones had 34.90% precipitation-dominated areas (significantly higher than humid zones' 12.86%); humid/semi-humid zones showed increased precipitation/radiation sensitivity but decreased temperature sensitivity. This study innovatively reveals the “radiation substitution for temperature” driving transition of vegetation sensitivity in arid/semi-arid regions, and provides scientific support for precise ecosystem conservation and climate adaptation in NWC, as well as a reference for vegetation management in global mid-latitude arid zones (e.g., Central Asia, North American Great Plains). • Post-2010 shift from MAT to RAD dominated vegetation sensitivity in NWC. • Temporal asynchrony between vegetation growth and stability enhancement. • Proposed zonal-specific strategies for ecological monitoring.

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Publication Details

Journal
Ecological Indicators
Published
2026-02-23
DOI
https://doi.org/10.1016/j.ecolind.2026.114693
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Vegetation sensitivity shift from temperature to radiation dominance in Northwest China's drylands—Implications for ecosystem stability in mid-latitude drylands

Ruide Yu, Zengkun Guo, Chunlan Li, Yuanbo Lu et al.
Ecological Indicators
Remote Sensing in Agriculture
article

Vegetation sensitivity shift from temperature to radiation dominance in Northwest China's drylands—Implications for ecosystem stability in mid-latitude drylands

Ruide Yu, Zengkun Guo, Chunlan Li, Yuanbo Lu, Lingxiao Sun, Yang Yu, Jianming Deng, Jing He
article en

Abstract

Clarifying the spatiotemporal patterns and driving mechanisms of vegetation growth and sensitivity is critical for assessing ecosystem stability and formulating conservation strategies. Taking Northwest China (NWC)—the core of global mid-latitude arid regions and China's “Northern Ecological Security Barrier”—as the study area, we analyzed vegetation growth (via EVI) and sensitivity (via VSI) dynamics, and their climatic drivers (temperature, precipitation, and solar radiation) (2000−2022) using a novel EVI-VSI synergetic framework, combined with growing-season EVI data, China's national climate/vegetation zoning, and statistical methods (ANOVA, Mann-Kendall trend test, 11-year moving window). The results show that: 1) EVI showed significant zonal differences (all P < 0.001): under climate zoning, mean EVI followed “humid (0.46 ± 0.06) > semi-humid (0.31 ± 0.08) > semi-arid/arid (0.21–0.22)”; VSI (regional mean: 47.10 ± 20.01) had no zonal differences ( P > 0.05), with low spatial overlap between high-EVI and high-VSI areas. 2) EVI increased significantly (0.0021 a −1 , P < 0.01), with 88.21% of the region improving (highest in humid zones: 99.16%); VSI decreased non-significantly (−0.021 a −1 , P > 0.05), with wetlands showing a lower decline (45.56%) due to human disturbance (grazing, tourism). 3) climatic drivers exhibited distinct zoning differences, with a post-2010 trend of “weakened temperature dominance, enhanced radiation dominance”: semi-arid zones saw the proportion of radiation-dominated areas undergo a marked surge across the study period, rising from its lowest point (9.51% in 2007) to its peak (46.35% in 2017), making it the dominant driver; arid zones had 34.90% precipitation-dominated areas (significantly higher than humid zones' 12.86%); humid/semi-humid zones showed increased precipitation/radiation sensitivity but decreased temperature sensitivity. This study innovatively reveals the “radiation substitution for temperature” driving transition of vegetation sensitivity in arid/semi-arid regions, and provides scientific support for precise ecosystem conservation and climate adaptation in NWC, as well as a reference for vegetation management in global mid-latitude arid zones (e.g., Central Asia, North American Great Plains). • Post-2010 shift from MAT to RAD dominated vegetation sensitivity in NWC. • Temporal asynchrony between vegetation growth and stability enhancement. • Proposed zonal-specific strategies for ecological monitoring.

Ecological IndicatorsVol. 184
Institute of Ecology and Geography (MD), Xinjiang Institute of Ecology and Geography (CN), University of Chinese Academy of Sciences (CN), Lanzhou University (CN)
Climate action
Openalex Percentile: Top 53%
Remote Sensing in Agriculture
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