Impact of spatial structure on the functional connectivity of urban ecological corridors based on quantitative analysis

Abstract

Building urban ecological corridors (UECs) and enhancing their functional connectivity are of great significance for biodiversity conservation and the enhancement of ecosystem services in urbanised areas. However, the key spatial structural indicators that affect the functional connectivity of UECs are unclear, resulting in ineffective ecological corridor optimisation measures. Therefore, this study attempted to reveal the quantitative relationship between the spatial structure and functional connectivity of UECs, using Minhang District, Shanghai, as a representative area. It analysed the type, morphological structure, area, habitat quality, and spatial location of the ecological space, and applied the results to the selection of ecological source patches and construction of resistance surfaces. Considering the species types, this study identified the spatial boundaries of UECs with different cost-weighted distance widths based on least-cost paths to optimise the UEC identification method. It used effective conductance to measure the functional connectivity of UECs and regression modelling to identify the spatial structural factors that contributed to their variation. The results showed that three spatial indicators affected the functional connectivity of UECs: the cost-weighted distance of the least-cost path (LCD), average spatial width (SW), and shape index; of which the LCD was the most critical and negatively-correlated indicator. The functional connectivity of UECs could be enhanced by increasing the SW within a certain width range, but the enhancement rate was inconsistent, and most corridors had transition points. This study screened nine key component types that affected the functional connectivity of UECs, of which the percentage of woodland area was the most critical and positively-correlated indicator. This study provides insights for adjusting the spatial structure and setting appropriate SWs of UECs to effectively improve their functional connectivity, which will help identify specific and actionable optimisation strategies for UECs.