Evidence map›Paper›PMID 40991622›Full record

ArticlePloS one2025

Spatial structure evolution and ecosystem service relationship changes in urban-fringe-rural areas of megacities: Evidence from Suzhou, China.

Qianhong Mao, Yasi Tian

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Qianhong MaoDepartment of Urban and Rural Planning, School of Architecture, Soochow University, Suzhou, CHINA.ORCID 0009-0006-9100-7815
Yasi TianDepartment of Urban and Rural Planning, School of Architecture, Soochow University, Suzhou, CHINA.ORCID 0000-0001-9671-2675

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The evolution of urban-fringe-rural structures profoundly impacts ecosystem services (ESs). However, the way in which trade-offs and synergies in ESs respond to changes in regional spatial structures has rarely been discussed. This knowledge gap hinders the development of spatially explicit strategies to mitigate ecological degradation while accommodating urban growth, ultimately perpetuating unsustainable landscape management practices characterized by reactive rather than preventive interventions. Such critical disconnect between structural dynamics and ES feedbacks has emerged as a major bottleneck to operationalizing landscape sustainability in metropolitan regions. This study selected Suzhou-a typical megacity in China-as an example to conduct an empirical study. The urban, urban fringe, and rural areas were firstly identified in 2010 and 2022 using Deep Neural Network (DNN) based on multi-source geographical data. Then, seven typical ESs were assessed using multiple models, and their interactions were examined through correlation analysis, coupling coordination degree model, and a self-organizing feature mapping network approach. At last, this study highlighted the complex responses of ESs relationships to dramatically changing spatial structure of urban-fringe-rural areas and proposed landscape management strategies. The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. The coupled coordination index among multiple ESs declines significantly in these areas, degrading from key coordination to key or mild trade-offs bundles. The results show ES interactions exhibit significant spatial variability under the evolution of metropolitan spatial structure, thus innovatively proposing integration of ESs synergies into urban-fringe-rural development framework to support overall landscape sustainability.

Indexed as

Conservation of Natural ResourcesEcosystemChinaCitiesHumansNeural Networks, ComputerRural PopulationUrbanization

Identifiers

PMID40991622
PMCPMC12459847

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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.