Evidence map›Paper›PMID 41253854›Full record

ArticleScientific reports2025

Comprehensive framework for optimizing ecological security and infrastructure in the Guangdong, Hong Kong, Macao Greater Bay Area.

Meng Yang, Ju He, Longyu Shi

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. 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

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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

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Meng YangCollege of Architectural Science and Engineering, Yangzhou University, Yangzhou, 225127, China.
Ju HeResearch Institute of Central Jiangsu Development, Yangzhou University, Yangzhou, 225127, China. TorchHeju@outlook.com.
Longyu ShiKey Lab of Urban Environment and Health and Key Laboratory of Urban Metabolism of Xiamen, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.

Funding

Humanities and Social Sciences Youth Foundation, Ministry of Education 23YJCZH265Jiangsu Province Higher Education Institutions Basic Science (Natural Science) Top Project 24KJD170004Jiangsu Province Social Science Applied Research Excellent Project 23SYC-047Natural Science Research of Jiangsu Higher Education Institutions of China BK20230602Technology Integration and Demonstration of Urban Ecological Infrastructure Construction in the Guangdong-Hong Kong-Macao Greater Bay Area XDA23030201
6 · The paper itself

Abstract

Urban ecological security (ES) is increasingly challenged by rapid economic development. Previous studies have primarily focused on the physical characteristics of the ecosystem, rarely analyzing the interdependencies and impacts of natural, social, and economic development on ecological security. To address this gap, we examined the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and proposed a novel comprehensive framework that includes ecological security assessment (ESA) and ecological infrastructure (EI) planning. The Driver-Pressure-State-Impact-Response-Structure (DPSIR-S) framework and obstacle degree model (ODM) were used to assess the ES level and analyze the impacts of natural, social, and economic development on it. Subsequently, leveraging natural language processing (NLP) technology and the "matrix-patch-corridor" method, we proposed an EI planning method that integrates the outcomes of the ESA and the responsive policy context to optimize urban ecological security. The results indicated that the response level was a significant factor in determining urban ES, with environmental protection investment share, GDP, population density, and GDP per capita identified as the main obstacle factors impeding ES in the GBA. Furthermore, the proposed EI network increased ecological space by 10.5%, incorporating 121 ecological nodes and 227 ecological corridors, which significantly improved the connectivity of fragmented ecological sources and optimized the urban landscape. The findings of this study contribute to the exploration of urban ES protection within the context of balanced natural, social, and economic development, providing a theoretical foundation and practical guidance for optimizing urban ES.

Indexed as

Conservation of Natural ResourcesEcologyEcosystemBaysChinaEconomic DevelopmentHong KongDPSIR-SEcological infrastructureEcological securityOptimizationThe Guangdong-Hong Kong-Macao Greater Bay Area (GBA)

Identifiers

PMID41253854
PMCPMC12627816

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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.