Exploring habitat patch clusters based on network community detection to identify restored priority areas of ecological networks in urban areas |
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| Affiliation: | 1. School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen 518055, China;2. Key Laboratory of Earth Surface System and Human-Earth Relations of Ministry of Natural Resources of China, Shenzhen Graduate School, Peking University, Shenzhen 518055, China;3. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China;1. Department for International Scientific Cooperation in Southeast Europe – EFISEE, Croatian Forest Research Institute, Cvjetno naselje 41, 10450 Jastrebarsko, Croatia;2. Humboldt Universität zu Berlin, Rudower Chaussee 16, 12489 Berlin, Germany;3. Helmholtz Centre for Environmental Research – UFZ, Department of Computational Landscape Ecology, Permoserstraße 15, 04318 Leipzig, Germany;1. Key Laboratory of Wetland Ecology and Management, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. College of Natural Resources, University of Wisconsin-Stevens Point, 800 Reserve Street, Stevens Point, WI 54481, USA;4. Department of Human Resources Management, School of Business and Management, Jilin University, Changchun 130021, China;5. Environment and Resources College, Dalian Minzu University, Dalian 116600, China;1. State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China;2. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;3. Beijing Urban Ecosystem Research Station, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China;1. CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;2. Shenyang Arboretum, Chinese Academy of Sciences, Shenyang 110016, China;3. Tanghekou Middle School, Huairou District, Beijing 101400, China;1. Graduate School of Environment and Information Sciences, Yokohama National University, 79-7 Tokiwadai, Hodogaya, Yokohama, Kanagawa 240-8501, Japan;2. Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan.;3. Department of Earth System Science, Faculty of Science, Fukuoka University, 8-19-1, Nanakuma, Jonan-ku, Fukuoka 814-0180, Japan |
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| Abstract: | Ecological connectivity is the foundation of maintaining urban biodiversity and ecosystem health. Identifying and managing ecological (connectivity) networks can help maintain the stability of urban ecosystems. However, few studies have explored the cluster effect in the ecological network caused by the imbalance in connectivity strength between habitat patches, which is not conducive to the in-depth restoration of ecological networks. In the present study, a typical urban area, Shenzhen, was used as an example to analyze the important habitats in the city based on the focal species and to identify an ecological network. Habitat patch clusters in the ecological network were explored based on random walk network community detection. These are clusters of closely connected habitat lands. Finally, we analyzed existing urban policies for the protection of clusters and the points to be repaired in the network. The results showed that 50 ecological corridors connected 39 habitats in the study area, which further formed seven habitat patch clusters. Most of the clusters were well-protected by existing policies. Nineteen barrier points were identified between the clusters, and their restoration helped strengthen the connectivity between clusters. This study provides a reference for future urban ecological restoration. |
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| Keywords: | Ecological networks Ecological corridors Network community detection Habitat patch cluster Restored priority area Typical urban areas |
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