Evidence map›Paper›PMID 42486868›Full record

ArticleScientific reports2026

Trade-offs and synergies of ecosystem services in the yellow river basin: spatial dynamics and driving factors.

Weisi Ma, Zhiwei Zhao, Jinshuo Zhang, Mengyao Xun

Abstract read
In one paragraph

Article in Scientific reports, 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

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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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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Weisi MaCollege of Management, Zhengzhou University, Zhengzhou, 450001, China.
Zhiwei ZhaoCollege of Management, Zhengzhou University, Zhengzhou, 450001, China. zhaozhiwei@zzu.edu.cn.
Jinshuo ZhangCollege of Management, Zhengzhou University, Zhengzhou, 450001, China.
Mengyao XunCollege of Management, Zhengzhou University, Zhengzhou, 450001, China.

Funding

the General Project of Humanities and Social Sciences Research in Henan Universities 2025-ZZJH-150the Philosophy and Social Science Planning Program of Henan Province [grant numbers 2025BJJ025the Soft Science Research Program of Henan Province 252400410450
6 · The paper itself

Abstract

Understanding the interactions among ecosystem services and their relationships with dominant drivers are crucial for effective ecosystem management. Previous studies have mainly focused on trade-offs and synergies between ESs, overlooking no-effect interactions. The effect of bidirectional land cover transitions on ESs remained insufficiently quantified. Additionally, driving force analyses typically focused on the overall impacts, neglecting spatial heterogeneity. In the Yellow River Basin, we used the InVEST model and spatial allocation methods to assess the spatiotemporal distributions of carbon storage (CS), soil retention (SR), water yield (WY), food production (FP), habitat quality (HQ), and landscape aesthetics (LA) from 2003 to 2023. ES changes due to land cover transitions were evaluated using a Cross-Tabulation Matrix. An improved pairwise method analyzed the spatial diversity of interactions among ES pairs, while key drivers were identified using the optimized parameter-based geographical detector (OPGD) model. Additionally, bivariate local spatial autocorrelation was used to analyze the spatial relationships between ESs and their key drivers. The results indicated that FP and WY were higher in the south and east, SR and CS were more concentrated in the center and south, while HQ and LA were predominantly distributed in the west. Seven ES pairs exhibited predominant synergies, including HQ-SR, HQ-CS, HQ-LA, SR-FP, SR-WY, CS-LA, and FP-WY, whereas five involving HQ-FP, HQ-WY, WY-LA, FP-LA, and SR-LA showed trade-offs. For CS-FP, CS-WY, and SR-CS pairs, synergy, trade-off, and no-effect relationships occupied comparable spatial area proportions. CS and HQ are primarily shaped by landscape configuration, SR by slope, vegetation, and precipitation, WY by climate and topography, and FP by socioeconomic intensity and elevation. Spatially, HH areas linking CS, SR, WY, HQ, and LA to their main drivers cluster in the upstream Loess Plateau gully region, the Sichuan Tibet alpine canyon region, and the southern Tibetan Plateau, whereas the northwestern desert region and the middle and lower reaches are dominated by LL, HL, LH, or not significant patterns. In contrast, HH hotspots for FP and its main drivers are concentrated in the middle and lower reaches, especially in the agropastoral transition zone and irrigated plains. These findings suggest that regulating key drivers, balancing vegetation restoration with regional water capacity, and protecting wetlands and other sensitive areas can help manage tradeoffs, enhance synergies, and support sustainable regional development.

Indexed as

Driving factorsEcosystem servicesInVEST modelOptimized parameter-based geographical detectorTrade-off/synergyYellow River Basin

Identifiers

PMID42486868
PMCPMC13392281

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.