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Land Use Simulation and Ecological Network Construction around Poyang Lake Area in China under the Goal of Sustainable Development

Author

Listed:
  • Zhijun Luo

    (College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China)

  • Xiaofang Yang

    (College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China)

  • Songkai Luo

    (College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China)

Abstract

The pivotal aspects of enhancing regional ecosystem services and augmenting socioeconomic growth lie in optimizing the land-space development and protection strategies, coupled with the establishment of a robust ecological network (EN). This article examines the Poyang Lake area and employs the MOP model, NSGA-II, and PLUS model to determine the best sustainable land use strategy. Subsequently, the MSPA, InVEST model, circuit theory, complex network, and others are employed to construct and analyze the land-space EN across three time periods. Ultimately, the EN is optimized based on spatial protection priority, ecological obstacle areas, and ecological nodes. The results show the following: (1) From 2005 to 2035, more construction land will be developed around the Greater Nanchang area and other urban centers. In the BAU scenario, construction land will expand faster, while cultivated land, forest, grassland, and bare land will continue to decline. In the SD scenario, the alteration to comparable land is minimal, the growth rate of construction land will slow, cultivated land, forest, grassland, and bare land will all decline little, and the water area will increase slightly; (2) While the area of ecological sources is decreased and ecological corridors become longer and narrower in the BAU scenario, the spatial distribution of ENs in different periods is small, and the quantitative structure and spatial distribution of ecological sources and corridors are essentially unchanged in the SD scenario; (3) Based on the topological structure of ENs, it is found that the clustering of nodes in the SD scenario is more obvious, the importance of ecological sources is enhanced, the efficiency of information transmission is improved, and the radiation range is wider and more stable; (4) The greatest priority ecological sources in each period are concentrated around Poyang Lake. In the SD scenario, the priority of ecological sources improves, and 7025 km 2 of ecological obstacle restoration area is identified, with 41, 31, and 36 ecological breakpoints in the first, second, and third levels. The study’s findings can assist and shape theoretical and practical approaches to land governance and sustainable development in great lake areas.

Suggested Citation

  • Zhijun Luo & Xiaofang Yang & Songkai Luo, 2024. "Land Use Simulation and Ecological Network Construction around Poyang Lake Area in China under the Goal of Sustainable Development," Sustainability, MDPI, vol. 16(18), pages 1-24, September.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8146-:d:1480467
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    References listed on IDEAS

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    1. Jiang, Xue & Li, Bingxin & Zhao, Hongyu & Zhang, Qiqi & Song, Xiaoya & Zhang, Haoran, 2022. "Examining the spatial simulation and land-use reorganisation mechanism of agricultural suburban settlements using a cellular-automata and agent-based model: Six settlements in China," Land Use Policy, Elsevier, vol. 120(C).
    2. Fath, Brian D. & Scharler, Ursula M. & Ulanowicz, Robert E. & Hannon, Bruce, 2007. "Ecological network analysis: network construction," Ecological Modelling, Elsevier, vol. 208(1), pages 49-55.
    3. José M. Montoya & Stuart L. Pimm & Ricard V. Solé, 2006. "Ecological networks and their fragility," Nature, Nature, vol. 442(7100), pages 259-264, July.
    4. Inceyol, Yasar & Cay, Tayfun, 2022. "Comparison of traditional method and genetic algorithm optimization in the land reallocation stage of land consolidation," Land Use Policy, Elsevier, vol. 115(C).
    5. Gao, Jing & Gong, Jian & Li, Yao & Yang, Jianxin & Liang, Xun, 2024. "Ecological network assessment in dynamic landscapes: Multi-scenario simulation and conservation priority analysis," Land Use Policy, Elsevier, vol. 139(C).
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    Cited by:

    1. Chang Liu & Qing Liu & Xingchuan Gao, 2024. "Spatial and Temporal Evolution Characteristics of Ecosystem Service Value and Population Distribution in China’s Coastal Areas," Sustainability, MDPI, vol. 16(23), pages 1-17, November.

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