Spatial resilience assessment and optimization of small watershed based on complex network theory

Zhou, Jizhe; Hou, Quanhua; Li, Weijia

doi:10.1016/j.ecolind.2022.109730

Cited by 14 publications

(9 citation statements)

References 41 publications

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“…Node structural holes reflect the relative competitive advantage of the nodes in the region. Node structural hole EC i is the degree of dependence of node e i on other nodes in the network, which is also called the network constraint coefficient 10 . The smaller the constraint coefficient of node I is, the easier the node becomes a node occupying a structural hole, the more diverse the selection of connections, and the stronger the collaboration between nodes 41 , as shown in the following formulas: where node q is the common adjacent point of node i and node j .…”

Section: Methodsmentioning

confidence: 99%

“…If all points in one of the subgraphs in the network are adjacent to at least k other points in the subgraph, such a subgraph is called a “k-core”. The higher the ratio of the k value to the k-core is, the more components that are locally stable in the network, and the higher the resilience of the network as a whole 10 .…”

Section: Methodsmentioning

confidence: 99%

“…Basin is the basic spatial unit of natural landforms and soil and water conservation management on the Loess Plateau 9 . As a sensitive and complex independent ecosystem 10 , it provides ecosystem services such as water conservation and biodiversity maintenance. Improving the quality of the ecological environment of a basin involves maintaining stable ecological space and the ability to adapt to risks when human interference occurs.…”

Section: Introductionmentioning

confidence: 99%

“…Zhang et al used node degree, betweenness, and clustering coefficient characteristic indicators to evaluate grid structure performance 20 . Zhou et al adopted node degree, structural hole, clustering coefficient, k-core and core–edge, and betweenness feature metrics to assess small watershed ecological spatial network resilience 10 . Zhang et al used a connection robustness and restore robustness assessment to study the dynamic characteristics of network efficiency and connectivity changes under malicious and random attacks 21 .…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Evaluation and optimization of ecological spatial resilience of Yanhe River Basin based on complex network theory

Hou,

Li,

Yang

et al. 2024

Sci Rep

Self Cite

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The loess hilly and gully areas have broken terrain, vertical and horizontal ravines and fragile ecological environments. Improving the resilience of the regional ecological space is conducive to improving the quality of the local ecological environment. With the ecological space of the Yanhe River Basin selected as the research object, this paper constructs a research framework of "network identification topology-resilience evaluation-spatial optimization" and uses morphological spatial pattern analysis (MSPA) and the minimum cumulative resistance model (MCR) to identify ecological spatial networks. Based on circuit theory, the ecological pinch point is identified, the ecological spatial network is optimized, and scenario simulation is performed. Through complex network theory and related indicators, the ecological spatial resilience of the basin is evaluated, and the hierarchical optimization strategy of the ecological space is confirmed. According to the ecological function of the source area and the results of the resilience evaluation, the boundaries of the protected control area, guidance development area, remediation area, and maintenance and improvement area of the basin are delineated. The importance of ecological source and corridor protection is classified, and corresponding protection strategies are proposed. The research results can provide theoretical support and practical guidance for the territorial spatial planning and ecological space construction of the Yanhe River Basin and provide a reference for the ecological restoration, resource development and environmental governance of the Yanhe River Basin.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation and optimization of ecological spatial resilience of Yanhe River Basin based on complex network theory

Hou,

Li,

Yang

et al. 2024

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…The evaluation of ecological network stability and the comparison of stability indicators pre and post optimization can provide insights into the extent to which optimization strategies have improved the resilience of the network [81]. Therefore, the stability of the ecological network may be completely assessed through the examination of global efficiency, largest subgraph size, and robustness [82]. As shown in Fig.…”

Section: A Measurement Of the Stability Of Ecological Networkmentioning

confidence: 99%

Stability of Regional Ecological Supply–Demand Is Enhanced by Complex Network Modeling: Evidence From the Xuzhou Metropolitan Area, China

Li,

Chang,

Wang

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In the era of urbanization, the imperative to safeguard ecological security and navigate towards sustainable development is paramount. The emergence of remote sensing technologies has unveiled a nuanced approach to understanding and refining regional ecological networks, which are crucial for achieving these objectives. However, in constructing regional ecological networks, the spatial integration of ecological supply and demand frequently goes unaddressed. The balance of supply and demand for ecosystem services is a complex challenge. Additionally, there is an absence of comprehensive effectiveness assessment for regional ecological networks constructed based on element evaluation. To address these challenges, this study focuses on the highly urbanized Xuzhou Metropolitan Area(XMA) in eastern China, utilizing remote sensing data to develop an ecological network focused on balancing ecological supply and demand. The study adeptly applies complex network theory to model the ecological network, analyzing its structure and function to propose thorough and specific optimization strategies. The results indicate that the ecological network in the XMA encompasses 20 ecological supply sources, 21 demand sources, and various corridors and nodes, displaying a "dense in the center, sparse on the periphery" spider web-like distribution. Post-optimization, the network integrates further stepping stones and corridors, evolving into a denser and more intricate structure. The study emphasizes the significance of constructing regional ecological networks based on ecological supply and demand, aiding the balance of ecosystem services in urbanized areas. It highlights the transformative potential of complex network models in ecological network optimization, facilitating effective ecosystem management and spatial planning.

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Ecological network resilience evaluation and ecological strategic space identification based on complex network theory: A case study of Nanjing city

Wu,

Cheng,

et al. 2024

Ecological Indicators

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Spatial resilience assessment and optimization of small watershed based on complex network theory

Cited by 14 publications

References 41 publications

Evaluation and optimization of ecological spatial resilience of Yanhe River Basin based on complex network theory

Evaluation and optimization of ecological spatial resilience of Yanhe River Basin based on complex network theory

Stability of Regional Ecological Supply–Demand Is Enhanced by Complex Network Modeling: Evidence From the Xuzhou Metropolitan Area, China

Ecological network resilience evaluation and ecological strategic space identification based on complex network theory: A case study of Nanjing city

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