Spatiotemporal changes in ecological network resilience in the Shandong Peninsula urban agglomeration

Huang, Longyang; Wang, Jing; Cheng, Hongguang

doi:10.1016/j.jclepro.2022.130681

Cited by 41 publications

(9 citation statements)

References 47 publications

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Section: Introductionmentioning

confidence: 99%

“…Rapid urbanization and subsequent artificial surface expansion in cities have led to a decline in both the quantity and quality of habitats within urban areas, increasing the degree of isolation among habitat patches (Barbati et al, 2013; Huang et al, 2022; Yang et al, 2020). Habitat fragmentation alters the migration and dispersal patterns of species, restricting genetic exchange among populations (Donald & Evans, 2006; Gippet et al, 2017), consequently resulting in reduced biodiversity and an increased risk of species extinction (Wang, Li, Kuang, et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, ESPs are a comprehensive network system formed by organically connecting key areas for ecological processes through ecological corridors (Peng et al, 2017; Huang et al, 2022), making them a suitable choice as spatial ecological constraints. Moreover, using different levels of ESPs as conversion zones for different simulation scenarios would facilitate the construction of a simulation mechanism adaptable to multiple development goals (Nie et al, 2023; Nie, Xu, et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Research on the coupled mechanism of landscape connectivity simulation by integrating multi‐level ecological security patterns and multi‐scenario simulation: A case study of the main urban area of Hangzhou

Xu,

Nie,

Wang

et al. 2024

Land Degrad Dev

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In the context of rapid urbanization, protecting landscape connectivity has become an effective measure to mitigate habitat fragmentation and curb biodiversity decline. However, in the current research on simulating optimization processes, the ecological constraints often set are dispersed, isolated, and fixed. They fail to form a comprehensive protective spatial framework and struggle to align with the multifaceted objectives of future development. This study, taking the main urban area of Hangzhou, China as a case study and employing small mammals as indicator species, utilizes the PLUS model to predict the potential threats to landscape connectivity of biological habitats posed by artificial surface expansion from 2020 to 2035. It constructs a coupled mechanism that integrates multi‐level ecological security patterns (ESPs) and multi‐scenario simulation for landscape connectivity, successfully demonstrating the effectiveness of this mechanism in future landscape connectivity preservation. The results indicate that under the scenarios of business‐as‐usual (BAU), priority given to urban development (PUD), and priority given to ecological protection (PEP), the overall level of landscape connectivity in the main urban area of Hangzhou is projected to decrease by 18.42%, 7.02%, and 4.39% respectively from 2020 to 2035. The reduction in core area is estimated to be 9.08%, 7.85%, and 6.34%, respectively, while highly important patches are expected to decrease by 12.91%, 7.51%, and 5.86%, respectively. Both PEP and PUD scenarios effectively mitigate the degree of landscape connectivity disruption. This study provides valuable insights for the future optimization of landscape connectivity and contributes to biodiversity conservation efforts.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Research on the coupled mechanism of landscape connectivity simulation by integrating multi‐level ecological security patterns and multi‐scenario simulation: A case study of the main urban area of Hangzhou

Xu,

Nie,

Wang

et al. 2024

Land Degrad Dev

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“…As an important carrier of economic and social development and production and life, the countryside has a certain complexity and comprehensiveness [1][2][3]. Since the reform and opening up, the urbanization process has been accelerating, and the traditional rural society, economy, culture, and ecology have been subjected to great impacts [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Ecological Network Construction of Putian Rural Landscape Based on Geospatial Analysis

Lu,

Chen,

Cao

et al. 2024

Applied Mathematics and Nonlinear Sciences

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As the countryside continues to expand and develop, ecological issues are becoming increasingly complex and critical. The creation of environmental networks plays a vital role in ensuring ecological protection and promoting sustainable development in these areas. This study selects the Putian countryside as the focal area for research, utilizing remote sensing technology to collect pertinent data. By integrating geospatial analysis methods, we constructed a landscape ecological network. The methodology involved several key steps: employing a landscape index to delineate the spatial pattern of the rural landscape, evaluating the service function value of the established ecological network, and applying the Minimum Cumulative Resistance (MCR) model to formulate the security pattern of the network. This approach underscores the importance of structured ecological planning in rural development initiatives. The analysis found that among the four types of rural green landscapes in the study area, the regional green space occupies a dominant position, with an LSI value of 116.1734, mainly large patches with uneven spatial distribution, and based on the Putian Rural Minimum Cumulative Resistance Surface Model = 0.41*Land Use + 0.33*Slope + 0.26*Distance from Water Bodies, the Putian Rural Landscape Ecological Network with a nucleus, a belt, five axes, and multiple points has been formed. The research in this paper provides a reference basis for the development of the Putian countryside and helps revitalize the Putian countryside.

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“…The corridor retrieved by the least cumulative resistance model may determine corridor importance using the gravity model matrix; however, corridor width cannot be directly estimated. By modeling charge transportation, the circuit theory model can accurately calculate corridor width, determine corridor importance, and designate the ecological protection zones by ecological key nodes [25]. Ecological key nodes consist of ecological pinch points and ecological barrier points, in which ecological pinch points are nodes of high ecological flow located in the corridor that play an important role, and ecological barrier points are regions with a high level of resistance to biological circulation and exchange flows, and are frequently regarded as conflict zones in contemporary land development and ecological protection [26].…”

Section: Introductionmentioning

confidence: 99%

Construction of Ecological Security Pattern and Identification of Ecological Restoration Zones in the City of Changchun, China

2022

IJERPH

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Identification of crucial regions in need of ecological conservation and restoration based on ecological security patterns is of utmost importance for ecological restoration across national land space with regard to China’s promotion of ecological civilization. Using Changchun, the capital of northeast China, as an illustration, the study chooses ecological sources based on the importance of ecosystem services, builds an ecological security pattern using circuit theory, and organizes critical regions for ecological conservation and restoration. The findings reveal that the 20 ecological sources chosen based on ecosystem services are more concentrated on the eastern side of the city, whereas the western side of the city has a smaller overall area; 41 ecological corridors show a network distribution, among which the southeast is relatively densely distributed; 31 ecological pinch points and 15 ecological barrier points are also identified. Prioritized restoration zones, prioritized protection zones, key conservation zones, and general conservation zones were the four different types of ecological restoration regions identified by the study. Each district’s prioritized restoration zones in the main metropolitan area are larger than the others; Gongzhuling’s priority protection zones are the largest, and Yushu’s natural substrate is the best. According to the grading, targeted solutions are suggested, offering helpful advice for the improvement of ecological patterns and ecological restoration of the aforementioned national areas.

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Spatiotemporal changes in ecological network resilience in the Shandong Peninsula urban agglomeration

Cited by 41 publications

References 47 publications

Research on the coupled mechanism of landscape connectivity simulation by integrating multi‐level ecological security patterns and multi‐scenario simulation: A case study of the main urban area of Hangzhou

Research on the coupled mechanism of landscape connectivity simulation by integrating multi‐level ecological security patterns and multi‐scenario simulation: A case study of the main urban area of Hangzhou

Ecological Network Construction of Putian Rural Landscape Based on Geospatial Analysis

Construction of Ecological Security Pattern and Identification of Ecological Restoration Zones in the City of Changchun, China

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