Suspended sediment and fisheries: An exploration of empirical relationships

ABSTRACT Objective Sediment has an important role in aquatic ecosystems; however, excess sediment can negatively impact fish and other aquatic life. Quantifying the response of aquatic life, particularly fish, to suspended sediment is important for natural resource managers tasked with developing sediment management guidelines to protect aquatic ecosystems. Our goal was to assess the ability of established, revised, and alternate severity of ill effect (SEV) dose–response models to predict the impact of suspended sediment on fish. Methods We synthesized existing literature to develop an expansive data set that relates suspended sediment concentration and exposure duration to biological effects on fish, and we assessed the predictive ability of established and revised SEV dose–response models. We investigated potential sources of variation in biological responses to suspended sediment dose and explored two alternative approaches for assessing the effects of suspended sediment on fish: 90th quantile SEV dose–response regression models and logistic SEV dose–response models. Results We found that both established and revised linear SEV dose–response models poorly quantified fish biological response to suspended sediment. Quantile SEV dose–response regressions also performed poorly. More promising are logistic dose–response models that identify sediment thresholds where major effects of sediment on fish can be expected to occur. We demonstrate that fish biological response to suspended sediment is modulated by sediment particle size, water temperature, and dissolved oxygen levels, suggesting additional environmental and biological variables to consider when evaluating the effects of suspended sediment on fish. Conclusions We contribute revised and novel empirically derived tools for predicting the effects of suspended sediment on fish, and we demonstrate how environmental variables and life stage may modulate fish biological response. Our work illustrates challenges associated with predictive modeling and some potential sources of variation. Although empirical models integrating biological stress response to suspended sediment may help natural resource managers to capture potential impacts of this stressor, a cautious approach that considers co-acting stressors may be most effective for sediment management that is protective of fish.