Evidence map›Paper›PMID 40781535›Full record

ArticleScientific reports2025

Investigation into the supply-demand relationship of carbon sequestration in the yellow river basin using the optimal parameter geographical detector model.

Heng Zhao, Yingying Gai, Fuqiang Wang, Lanbo Cui, Yutian Du, Heng Wang, Lei Tang, Huan Yang

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Heng ZhaoYellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Yingying GaiYellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Fuqiang WangYellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China. wangfuqiang@ncwu.edu.cn.
Lanbo CuiYellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Yutian DuYellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Heng WangYellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Lei TangYellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.
Huan YangYellow River Research Institute, North China University of Water Resources and Electric Power, Zhengzhou, 450046, China.

Funding

Agricultural Major Science and Technology Projects NK202319020506The National Natural Science Foundation of China Project U2443203
6 · The paper itself

Abstract

The carbon cycle is crucial for ecosystem regulation. Carbon sequestration services (CSS) stabilize and fix CO2 in ecosystems over the long term, which is crucial for mitigating global climate change and promoting sustainable development. This study quantified the supply and demand of CSS in the Yellow River Basin from 2001 to 2021 using the InVEST model and urban metabolism approach. Additionally, the advanced Optimal Parameter Geodetector (OPGD) model was employed to explore the carbon sequestration service demand-supply relationship (CSSDR) and its driving mechanisms. Results showed: (1) CSS supply increased to varying degrees, while demand fluctuated upwards, with higher demand in downstream and lower in upstream areas. (2) Spatial CSSDR imbalance was evident at the grid scale, with significant regional differences and a declining CSS supply-demand index at the provincial level. (3) CSS supply was mainly influenced by natural factors, while demand was driven by human activities and socio-economic development. Increasing population and GDP densities disrupted the balance, becoming key determinants of CSSDR. (4) Interactions between drivers exhibited dual-factor enhancement and non-linear amplification, with population density showing the most significant correlations (all q-values > 0.67). These findings underpin improved environmental protection and sustainable development strategies in the region.

Indexed as

Carbon sequestration servicesInVEST modelOPGDUrban metabolism approach

Identifiers

PMID40781535
PMCPMC12334652

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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.