Traditional aquatic ecological risk assessments are often constrained by a heavy reliance on extensive toxicological data and a limited consideration of interspecies interactions.To address these limitations,this stud...Traditional aquatic ecological risk assessments are often constrained by a heavy reliance on extensive toxicological data and a limited consideration of interspecies interactions.To address these limitations,this study proposes a novel framework:the“ecological node-food web”method.This approach establishes dose-response relationships between pollutants and ecosystem-level toxicity endpoints by integrating toxicological data from key“ecological node”species with food web modeling.Results demonstrate that data from a few key nodes can effectively mimic ecosystem-wide responses to pollutants.Compared to conventional methods,this approach reduces the need for extensive datasets,enhances cost-effectiveness,and elucidates risk mechanisms through changes in community structure.The method ultimately enables the derivation of scientifically robust ecological risk thresholds.展开更多
基金supported by the Major Program of National Natural Science Foundation of China(52293440,52293442).
文摘Traditional aquatic ecological risk assessments are often constrained by a heavy reliance on extensive toxicological data and a limited consideration of interspecies interactions.To address these limitations,this study proposes a novel framework:the“ecological node-food web”method.This approach establishes dose-response relationships between pollutants and ecosystem-level toxicity endpoints by integrating toxicological data from key“ecological node”species with food web modeling.Results demonstrate that data from a few key nodes can effectively mimic ecosystem-wide responses to pollutants.Compared to conventional methods,this approach reduces the need for extensive datasets,enhances cost-effectiveness,and elucidates risk mechanisms through changes in community structure.The method ultimately enables the derivation of scientifically robust ecological risk thresholds.
