Evidence map›Paper›PMID 41635693›Full record

ArticleFrontiers in plant science2025

The response and coupling coordination of soil moisture to vegetation in the Yellow River's primary tributaries: a multi-source data analysis of the Wanchuan River Basin.

Xingyu Liu, Xiaodan Li, Xiaoning Zhang, Jiali Yang, Zizhen Li, Haichao Zhang, Xuelu Liu

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Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Xingyu LiuCollege of Forestry, Gansu Agricultural University, Lanzhou, China.
Xiaodan LiCollege of Management, Gansu Agricultural University, Lanzhou, China.
Xiaoning ZhangCollege of Resources and Environment, Gansu Agricultural University, Lanzhou, China.
Jiali YangCollege of Forestry, Gansu Agricultural University, Lanzhou, China.
Zizhen LiCollege of Forestry, Gansu Agricultural University, Lanzhou, China.
Haichao ZhangSchool of Architecture, South China University of Technology, Guangzhou, China.
Xuelu LiuCollege of Forestry, Gansu Agricultural University, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Vegetation status and soil moisture play crucial roles in ecosystem supply- demand services. Understanding the spatiotemporal variations of soil moisture (SM) and vegetation conditions is essential for assessing the stability of terrestrial ecosystems. However, the long-term response mechanisms and synergistic relationships between soil moisture and vegetation in the upper Yellow River's Gansu section remain unclear, introducing uncertainties in evaluating the Loess Plateau ecosystem. Methods: Utilizing multi-source data from the Wanchuan River Basin, a major tributary of the Yellow River, an inversion model was constructed to simulate the spatiotemporal distribution of soil moisture at depths of 0-30 cm. Results and Discussion: The results reveal a distinct spatial pattern of lower moisture in the northern part and higher moisture in the southern part, with no significant variation across soil depths. A comprehensive vegetation index (VEG) integrating net primary productivity (NPP), leaf area index (LAI), and atmosphere-resistant vegetation index (ARVI) was found to be most suitable for this region. Overall vegetation conditions improved annually, with interannual variation following a normal distribution. Significant interaction between vegetation and soil moisture was observed, with the area of statistically significant positive correlation substantially exceeding that of negative correlation, indicating a synergistic relationship between the two variables. Coupling coordination analysis showed notable seasonal differences: in summer, coordination between SM and VEG was significantly divergent (coordinated in the south, uncoordinated in the north), while in other seasons, the relationship was characterized as marginally coordinated. This suggests a need for continuous structural optimization, with marginal coordination representing the predominant state of the soil moisture- vegetation system in the basin.Variable importance screening using the Giniindex- enhanced random forest algorithm identified land surface temperature and potential evapotranspiration as the dominant factors influencing the soil moisture-vegetation coupling coordination degree. These findings provide valuable data and theoretical support for understanding the synergistic mechanisms between soil, water, and vegetation in the Gansu section of the Yellow River, contributing to more effective ecosystem management strategies in the Loess Plateau region.

Indexed as

coupling coordinationrandom forestsoil moisturevegetation dynamicsWanchuan River BasinYellow River tributaries

Identifiers

PMID41635693
PMCPMC12862093

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.