Evidence map›Paper›PMID 42718725›Full record

ArticleFrontiers in public health2026

Nonlinear response of vegetation productivity to climate change and human activities in a water-source basin: implications for environmental health and water security.

Hai Liu, Yubing Wang, Tiancheng Wang, Si Chen, Yuhui Bao, Liang Zheng, Min Wang

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Hai Liu *Faculty of Resources and Environmental Science, Hubei University, Wuhan, China.
Yubing Wang *Faculty of Resources and Environmental Science, Hubei University, Wuhan, China.
Tiancheng Wang *School of Geographical Science, Hubei University, Wuhan, China.
Si Chen *Faculty of Resources and Environmental Science, Hubei University, Wuhan, China.
Yuhui BaoFaculty of Resources and Environmental Science, Hubei University, Wuhan, China.
Liang ZhengCollege of Urban and Environmental Sciences, Central China Normal University, Wuhan, China.
Min WangFaculty of Resources and Environmental Science, Hubei University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Gross primary productivity (GPP) is a key component of the global carbon cycle, and its dynamics are influenced by climate conditions and human activities. However, the nonlinear response of GPP to climate change and human activities remains unclear. The Hanjiang River Basin (HJRB), a crucial water-source region of the South-to-North Water Diversion Project in China, is vital to China's ecological security. Changes in vegetation productivity in this water-source basin may affect water conservation, soil erosion control, drought and flood regulation, and the environmental conditions to which downstream populations are exposed. In recent decades, the region has experienced significant climate change, intensified human activities, and notable increases in vegetation greenness. However, previous literature relying on the assumption of stationarity and traditional linear methods has limited capability in detecting nonlinear and gradual vegetation changes. Methods: The long-term nonlinear trend in GPP in the HJRB was analyzed using ensemble empirical mode decomposition (EEMD), and the nonlinear response relationships among climatic factors, human activities, and GPP were further quantified using the LightGBM machine-learning method. Results: From 2000 to 2020, the annual growth rate of vegetation productivity in the HJRB was 12.27 g C m Discussion: This study elucidates trends and underlying response patterns in vegetation productivity in the HJRB, reveals the driving factors behind regional vegetation productivity changes, and provides environmental evidence for vegetation monitoring, water-source ecosystem management, and climate-related health-risk prevention in the HJRB and similar water-source regions.

Indexed as

Climate ChangeEnvironmental HealthHuman ActivitiesWater InsecurityWater SupplyChinaHumansNonlinear DynamicsRiversanthropogenic activitiesclimate changeenvironmental healthgross primary productivitynonlinear responsewater security

Identifiers

PMID42718725
PMCPMC13553843

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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.