生态环境学报 ›› 2026, Vol. 35 ›› Issue (7): 1072-1082.DOI: 10.16258/j.cnki.1674-5906.2026.07.008

• 研究论文【生态学】 • 上一篇    下一篇

耦合预警与多情景模拟的生态安全格局构建——以鄱阳湖流域为例

何杰霞1,2,3,4(), 张福庆1,2,3,*(), 辛雪1,2,3   

  1. 1 东华理工大学测绘与空间信息工程学院江西 南昌 330013
    2 江西省流域生态过程与信息重点实验室江西 南昌 330013
    3 南昌市景观过程与国土空间生态修复重点实验室江西 南昌 330013
    4 自然资源部鄱阳湖流域生态保护红线野外科学观测研究站江西 南昌 330025
  • 收稿日期:2025-12-08 修回日期:2026-04-02 接受日期:2026-04-26 出版日期:2026-07-18 发布日期:2026-07-17
  • 通讯作者: *张福庆,202260001@ecut.edu.cn
  • 作者简介:何杰霞(2002年生),女,硕士研究生,主要从事土地利用与景观生态研究。E-mail: hejiexia2002@126.com
  • 基金资助:
    国家自然科学基金项目(42377472);国家自然科学基金项目(42471120);国家自然科学基金项目(42261021);自然资源部鄱阳湖流域生态保护红线野外科学观测研究站开放课题基金(JXZSZ2025003);东华理工大学研究生创新基金项目(DHYC-2025024)

Construction of Ecological Security Pattern Coupled with Early Warning and Multi-Scenario Simulation: A Case Study of the Poyang Lake Basin

He Jiexia1,2,3,4(), Zhang Fuqing1,2,3,*(), Xin Xue1,2,3   

  1. 1 School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang 330013, P. R. China
    2 Jiangxi Key Laboratory of Watershed Ecological Process and Information, Nanchang 330013, P. R. China
    3 Nanchang Key Laboratory of Landscape Process and Territorial Spatial Ecological Restoration, Nanchang 330013, P. R. China
    4 Field Scientific Observation and Research Station for Ecological Protection Red Line in Poyang Lake Basin of the Ministry of Natural Resources, Nanchang 330029, P. R. China
  • Received:2025-12-08 Revised:2026-04-02 Accepted:2026-04-26 Online:2026-07-18 Published:2026-07-17

摘要:

提升生态安全预警信号的识别精度、构建符合地域特征的生态安全格局,是保障区域可持续发展的迫切需求。以鄱阳湖流域为研究区,运用确定性系数法与CNN-LSTM模型进行生态安全预警评估,并结合MSPA与电路理论识别生态源地、廊道及关键节点。进一步耦合PLUS模型的多情景模拟结果开展空间叠加分析,从而面向未来发展趋势划定优先保护与修复区域,最终构建生态安全格局。结果表明:1)CNN-LSTM模型在生态安全预警评估中展现出良好的预测能力和较高的预测精度,预警结果呈现出“南高北低”的空间分异特征;2)共识别生态源地26405 km2、11条关键生态廊道、18条重要生态廊道、149个生态夹点与968个生态障碍点;3)基于PLUS模型模拟2030年惯性发展、经济发展优先、生态保护优先及耕地保护优先等4种情景,结合生态网络要素分布识别出优先保护区97个、优先修复区457个,最终构建“五域三带多点”的生态安全格局。研究结果可为快速变化环境下的国土空间布局提供生态风险预警与管理情景预测,支撑流域生态安全与可持续发展目标的实现。

关键词: 生态安全格局, 生态安全预警, 多情景模拟, 深度学习, 鄱阳湖流域

Abstract:

In the context of rapid global industrialization and urbanization, the high concentration of industries and populations has profoundly altered regional land use and land cover patterns. The rapid expansion of cities and the intensification of agricultural activities continue to encroach upon ecological spaces, triggering a series of ecological and environmental issues such as land degradation, habitat fragmentation, and the decline of ecosystem services. These changes exacerbate the conflict between socio-economic development and ecological conservation, posing a serious threat to regional ecological security. Against this backdrop, research on ecological security early warning has become a critical pathway for defining the baseline of sustainable development, optimizing watershed management, and supporting scientific decision-making. As the spatial foundation for regional sustainable development, the scientific construction of an ecological security pattern is an important approach to reconciling the contradiction between ecological protection and socio-economic development. Therefore, improving the accuracy of ecological security warning identification, constructing region-specific ecological security patterns, and implementing tailored ecological protection and risk management have become urgent needs for ensuring regional sustainable development. Using the Poyang Lake Basin as a case study, this research, from the perspective of dynamic ecological security warning and pattern optimization, constructed a research framework of “warning assessment-source extraction-element identification-scenario simulation-pattern construction”. First, an ecological security early warning indicator system was built across four dimensions: stress risk, spatial pattern, ecological function and dynamic process response. The coefficient of determination method was used to screen negative samples to establish spatial constraints, and the CNN-LSTM model was combined to achieve a dynamic ecological security early warning assessment. Secondly, the warning results were integrated with Morphological Spatial Pattern Analysis (MSPA) to identify ecological sources, extracting core areas with structural integrity, functional importance, and significant ecological pressure, thereby balancing conservation priority and restoration urgency. Subsequently, based on a resistance surface and circuit theory, ecological corridors, pinch points, and barrier points were identified to construct an ecological network for the Poyang Lake Basin. Finally, the Patch-generating Land Use Simulation (PLUS) model was employed to simulate land use changes in 2030 under four scenarios: inertial development, economic development priority, ecological protection priority, and cropland protection priority. By overlaying these with the spatial distribution of the ecological network elements, priority conservation and restoration areas within the basin were identified, forming a spatial governance and decision-support plan. The results indicate that: 1) the area under the Receiver Operating Characteristic (ROC) curve (AUC) for the CNN-LSTM model was 0.92, indicating that the model possesses reliable predictive capability. The ecological security warning index shows a spatial differentiation pattern of “higher in the south and lower in the north”. High-susceptibility areas are mainly distributed in hilly and mountainous regions and their interfaces with rivers and lakes. Specifically, higher and highest susceptibility areas are concentrated around the Jiuling Mountains in the northwest, the Jitai Basin in the central part, and the Poyang Lake area in the north. 2) A total of 16 ecological sources were identified, covering a total area of 26405 km2. These sources are mainly located in the Xiushui River basin, the Jitai Basin, the Jiuling Mountains in southern Jiangxi, and mountain ranges such as the Luoxiao Mountains in western Jiangxi. They possess structurally intact natural ecosystems and are key patches for maintaining regional ecological security and carrying important ecosystem services. Eleven key ecological corridors were identified, with a total length of 1132.21 km, and 18 important ecological corridors, with a total length of 860.73 km. The key ecological corridors are spatially widespread and extend over longer distances, generally running northwest-southeast across the basin. They primarily connect the mountain ranges in the northwest, northeast, and east, passing through the Xiushui, Fuhe, and Xinjiang River basins. These corridors effectively link distant ecological sources but may also increase risks and uncertainties during species migration and energy flow. The important ecological corridors are relatively concentrated and shorter in length, running north-south through the southern part of the basin and east-west through the northern part. They mainly connect the western and southern mountain ranges, passing through the Ganjiang and Raohe River basins. This layout facilitates rapid migration and exchange of species over relatively short distances but also subjects adjacent ecological sources to higher pressure from material and energy flow. A total of 149 ecological pinch points were extracted, located in areas with lower resistance that are easier for species to traverse, making them key areas for conservation to maintain ecological connectivity. In addition, 968 ecological barrier points were identified, mostly distributed at road intersections and around construction land, requiring targeted ecological restoration and landscape pattern optimization. 3) Based on the PLUS model, land use in 2030 was simulated for four different development scenarios in the Poyang Lake Basin: inertial development, economic development priority, ecological protection priority, and cropland protection priority. Combining this with the distribution of ecological network elements, 97 priority conservation areas and 457 priority restoration areas were identified. Ultimately, a security pattern of “Five Zones, Three Belts, Multiple Points” was constructed. Here, “Multiple Points” refers to the ecologically critical nodes within the basin requiring priority management, including the 97 priority conservation areas and 457 priority restoration areas. Priority conservation areas are mainly distributed at the intersections of ecological sources and corridors in counties such as Suichuan, Yongxin, and Nancheng. Priority restoration areas are concentrated in the mid-sections of corridors within cities like Dexing, Yudu, and Fenyi. The “Five Zones” includes the Northwest Jiangxi Large Ecological Corridor Connectivity Zone, the Northeast Jiangxi Abandoned Mine Ecological Restoration Zone, the West Jiangxi Industrial Green Transformation and Upgrading Zone, the Central-East Jiangxi Agricultural Land Ecological Quality Improvement Zone, and the South Jiangxi Ecological Tourism Economic Development Zone. The “Three Belts” includes the east-west Poyang Lake Ecological Corridor Construction Belt, the northwest-southeast Xiushui-Fuhe River Basin Ecological Corridor Construction Belt, and the north-south Large Contiguous Ecological Corridor Construction Belt. The findings can provide ecological risk warnings and management scenario predictions for territorial spatial planning in rapidly changing environments, supporting the achievement of ecological security and sustainable development goals in the basin.

Key words: ecological security pattern, ecological security early warning, multi-scenario simulation, deep learning, Poyang Lake Basin

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