Ecological spatial optimization based on complex network theory: a case study of Songhua River Basin of northeastern China

  Objective  Rapid urbanization leads to fragmentation of the landscape and destruction of ecological spatial networks, so the reasonable construction of ecological spatial networks can promote the flow of energy between ecological sources and effectively mitigate the deterioration of the ecological environment.

  Method  Taking the Songhua River Basin as the research object, present study firstly extracted the ecological source area from the land use data, and screened the ecological sources and potential ecological corridors by employing GIS spatial analysis and MCR model. Then, present research calculated the degree of ecological sources based on the complex network method, and calculated the frontier rights of potential ecological corridors in the Songhua River Basin using the gravity model, and then whereby the frontier rights and degree of ecological corridors in the complex network, the weight of the Songhua River Basin can be obtained. Finally, the robustness of the ecological space network in the Songhua River Basin was analyzed by simulating the increased edge optimization through the weight-degree correlation.

  Result  (1) The ecological space network of the Songhua River Basin was composed of 450 ecological sources and 1 019 potential ecological corridors. (2) In the ecological space network of the Songhua River Basin, the ecological source patches in Qiqihar, Daqing and Songyuan were low in aggregation and the ecological corridor structure was simple, while the patches in Hulunbeier and Mudanjiang were high in aggregation and the ecological space network was intricate and complex. Accordingly, the ecological space network in the study area was polarized, and the ecological environment needs to be optimized urgently. (3) Based on the complex network theory, 20 increased edge nodes were identified and 24 increased edges were simulated through simulating the increased edge optimization of the Songhua River Basin. Simultaneously, the network connectivity robustness had been significantly enhanced after the increased edge optimization, and the connectivity and anti-disturbance ability of the ecological space network in the Songhua River Basin had been greatly improved.

  Conclusion  The ecological space network is constructed based on the MCR model, and the complex network theory is applied to increase edge optimization of the Songhua River Basin, which improves the robustness of the ecological space network and lays a theoretical foundation for the optimization of the ecological space pattern for Songhua River Basin.