Identification of spatial pathways for aquatic ecological risk spread under multi-stressor synergies: A case study of the Pinglu Canal

• Multi-stressor synergy in aquatic risk was identified in China’s Pinglu Canal. • Revealed spatial relationships between stressors, receptors, and responses. • Defined conceptual relationships among 11 stressors, 4 receptors, and 6 responses. • Mapped 39 risk spatial spread pathways (RSSPs) along the canal. • Risk segments were prioritized and targeted management strategies were proposed. Multiple stressors in aquatic ecosystems can interact to amplify risks and drive their spread across space. Conventional single-stressor models overlook these dynamics, impeding the identification of risk spatial spread pathways (RSSPs) and evidence-based management. Decision-makers must identify such synergies by establishing stressor–receptor–response relationships and mapping RSSPs from stressors to receptors to develop targeted management strategies. Focusing on the Pinglu Canal, this study employs a Bayesian network (BN) to establish a stressor–receptor–response network of 11 stressors, 4 receptors and 6 responses. These responses reflect multiple stressors synergies and form the basis for generating the RSSP resistance surface. By applying the minimum cumulative resistance (MCR) model, we delineate RSSPs between main stressors and receptors, providing a spatially explicit method to inform ecosystem-based risk management. The key findings are as follows: (1) Six responses were quantitatively assessed: aquatic eutrophication, increased habitat fragmentation, decreased fish habitat suitability, increased organic pollution, increased heavy metal exposure levels, and mangrove degradation. Among these, increased habitat fragmentation was the most prominent response observed along the Pinglu Canal. (2) Thirty-nine RSSPs were identified, with two high-risk segments (K86–K101 and K115–K122) prioritized due to the co-occurrence of all 6 responses, providing guidance for targeted management. The BN-MCR model bridges multiple stressors synergy analysis and RSSP identification, offering a replicable strategy for canal ecosystems under intensive human-altered aquatic stressors.