Integrating ecosystem services and complex network theory to construct and optimize ecological security patterns: a case study of Guangdong-Hong Kong-Macao Greater Bay Area, China

The urban agglomerations' rapid expansion and population growth have led to the fragmentation of landscape patterns and the degradation of ecosystems, seriously threatening regional ecological security. Ecological security pattern (ESP) is a spatial planning approach to effectively balance the development of urbanization and ecological protection. However, previous studies have ignored the difference in the importance of ecosystem services and the spatial compactness of ecological sources. The quantitative management objectives for optimizing ESP are also rarely addressed. In this study, taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as an example, ecological sources were identified by simulating multiple ES weight assignment scenarios through GeoSOS area optimization. Ecological corridors and strategic points were extracted by LinkageMapper. The robustness analysis based on complex network theory was performed to quantify the management objectives of ESPs. The results showed that ESPs include 26,130.61km 2 ecological sources (accounting for 46.6% of the total area of GBA), 557 ecological corridors, and 112 ecological strategic points. In more detail, ecological sources are mainly distributed in the western and eastern mountainous areas, and ecological corridors primarily link peripheral edge areas of GBA in a circular radial shape. Compared with the current nature reserves, the identified ecological source areas are more compact in landscape pattern and can provide a higher level of integrated ecosystem services. According to the robustness analysis, at least 23% of the important ecological sources should be strictly restricted from development activities to maintain the ESP's ability to resist ecological risks. This study also proposed corresponding differentiated ESPs management strategies. By optimizing the existing ESPs identification method and clarifying the ESPs management objectives, this study provides a completely scientific framework for the construction and optimal management of ESPs in urban agglomerations.