Resistance of vegetation sensitivity to climate and human activities under short-term drought in subtropical humid region: a case study of Guangdong, China

Understanding how the changes of vegetation sensitivity to climate and human activities under drought is essential for evaluating ecosystem resistance in subtropical humid regions. This paper focused on Guangdong Province, China, and used SPEI-3 (Standardized Precipitation Evapotranspiration Index) to identify short-term drought events (< 6 months). LMG (Lindeman-Merenda-Gold method) and XGBoost (Extreme Gradient Boosting) were used to quantitatively analyze the contributions of temperature, precipitation and nighttime light (NTL) to the NDVI of evergreen forest, grassland and urban region. LMM (Linear Mixed Model) with month and year as random effects were applied. The conclusions revealed that: (1) Short-term drought significantly reduced the sensitivity of vegetation to temperature in the south of the Tropic of Cancer, while vegetation in the north of the Tropic of Cancer maintained a stable relationship with temperature. (2) Under drought, the temperature contribution to evergreen forest decreased the most (10-13%), followed by urban region (6-15%) and grassland (7-12%). The precipitation contribution to evergreen forest increased by 7-10% and 2-7% for grassland. (3) Drought weakened the positive temperature-NDVI correlation in the west located in the south of the Tropic of Cancer, while the positive temperature-NDVI correlation persisted in the north located in the north of the Tropic of Cancer. (4) Under drought, vegetation maintained a stable positive response to climate. The temperature-NDVI relationship in more than half of the cities shifted from positive to negative.

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Publication Details

Journal
Scientific Reports
Published
2026-02-21
DOI
https://doi.org/10.1038/s41598-026-40399-5
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Resistance of vegetation sensitivity to climate and human activities under short-term drought in subtropical humid region: a case study of Guangdong, China

Fan An, Yuanda Lei, Yuzhen Wu, Rumin Wu et al.
Scientific Reports
Remote Sensing in Agriculture
article

Resistance of vegetation sensitivity to climate and human activities under short-term drought in subtropical humid region: a case study of Guangdong, China

Fan An, Yuanda Lei, Yuzhen Wu, Rumin Wu, Weishi Xiao
article en

Abstract

Understanding how the changes of vegetation sensitivity to climate and human activities under drought is essential for evaluating ecosystem resistance in subtropical humid regions. This paper focused on Guangdong Province, China, and used SPEI-3 (Standardized Precipitation Evapotranspiration Index) to identify short-term drought events (< 6 months). LMG (Lindeman-Merenda-Gold method) and XGBoost (Extreme Gradient Boosting) were used to quantitatively analyze the contributions of temperature, precipitation and nighttime light (NTL) to the NDVI of evergreen forest, grassland and urban region. LMM (Linear Mixed Model) with month and year as random effects were applied. The conclusions revealed that: (1) Short-term drought significantly reduced the sensitivity of vegetation to temperature in the south of the Tropic of Cancer, while vegetation in the north of the Tropic of Cancer maintained a stable relationship with temperature. (2) Under drought, the temperature contribution to evergreen forest decreased the most (10-13%), followed by urban region (6-15%) and grassland (7-12%). The precipitation contribution to evergreen forest increased by 7-10% and 2-7% for grassland. (3) Drought weakened the positive temperature-NDVI correlation in the west located in the south of the Tropic of Cancer, while the positive temperature-NDVI correlation persisted in the north located in the north of the Tropic of Cancer. (4) Under drought, vegetation maintained a stable positive response to climate. The temperature-NDVI relationship in more than half of the cities shifted from positive to negative.

Scientific ReportsVol. 16(1)
Lingnan Normal University (CN)
National Natural Science Foundation of China, Lingnan Normal University, Basic and Applied Basic Research Foundation of Guangdong Province
Climate action
Openalex Percentile: Top 54%
Remote Sensing in Agriculture
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