Resource managers need to predict effects of pollution episodes on aquatic biota, and suspended sediment is an important variable in considerations of freshwater quality. Despite considerable research, there is little agreement on environmental effects of suspended sediment as a function of concentration and duration of exposure. More than 70 papers on the effects of inorganic suspended sediments on freshwater and marine fish and other organisms were reviewed to compile a data base on such effects. Regression analysis indicates that concentration alone is a relatively poor indicator of suspended sediment effects (r2 = 0.14, NS). The product of sediment concentration (mg/L) and duration of exposure (h) is a better indicator of effects (r2 = 0.64, P < 0.01). An index of pollution intensity (stress index) is calculated by taking the natural logarithm of the product of concentration and duration. The stress index provides a convenient tool for predicting effects for a pollution episode of known intensity. Aquatic biota respond to both the concentration of suspended sediments and duration of exposure, much as they do for other environmental contaminants. Researchers should, therefore, not only report concentration of suspended sediment but also duration of exposure of aquatic biota to suspended sediments.

Our meta‐analysis of 80 published and adequately documented reports on fish responses to suspended sediment in streams and estuaries has yielded six empirical equations that relate biological response to duration of exposure and suspended sediment concentration. These equations answer an important need in fisheries management: quantifying the response of fishes to suspended sediment pollution of streams and estuaries has been difficult historically, and the lack of a reliable metric has hindered assessment for risk and impact for fishes subjected to excess sedimentation. The six equations address various taxonomic groups of lotic, lentic, and estuarine fishes, life stages of species within those groups, and particle sizes of suspended sediments. The equations all have the form z = a + b (logex) + c(logey); z is severity of ill effect, x is duration of exposure (h), y is concentration of suspended sediment (mg SS/L), a is the intercept, and b and c are slope coefficients. The severity of ill effect (z) is delineated semiquantitatively along a 15‐point scale on which is superimposed four “decision” categories ranging from no effect through behavioral and sublethal effects to lethal consequences (a category that also includes a range of paralethal effects such as reduced growth rate, reduced fish density, reduced fish population size, and habitat damage). The study also provided best available estimates of the onset of sublethal and lethal effects, and it supported the hypothesis that susceptible individuals are affected by sediment doses (concentration × exposure duration) lower than those at which population responses can be detected. Some species and life stages show “ultrasensitivity” to suspended sediment. When tested against data not included in the analysis, the equations were robust. They demonstrate that meta‐analysis can be an important tool in habitat impact assessment.

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A new type of empirical model described here enables real time assessment of impacts caused by excessive water cloudiness as a function of (a) reduced visual clarity (excessive cloudiness) and (b) duration of exposure to cloudy conditions, in fisheries or fish life stages adapted to life in clear water ecosystems. This model takes the familiar form used in earlier suspended sediment dose effect models where z is severity of ill effect (SEV), x is duration of exposure (h), y is black disk sighting range (y BD, m)—a measure of water clarity, a is the intercept, and b and c are slope coefficients. As calibrated in this study the model is Severity of ill effect is ranked on a 15‐step scale that ranges from 0 to 14, where zero represents nil effect and 14 represents 100 percent mortality. This model, based on peer consultation and limited meta analysis of peer reviewed reports, accomplishes the following: (a) identifies the threshold of the onset of ill effects among clear water fishes; (b) postulates the rate at which serious ill effects are likely to escalate as a function of reduced visual clarity and persistence; (c) provides a context (the “visual clarity” matrix, with its cell coordinates) to share and compare information about impacts as a function of visual clarity “climate” (d) demonstrates changes in predator prey interactions at exposures greater than and less than the threshold of direct ill effects; (e) calibrates trout reactive distance (cm) as function of water clarity in the form where y represents reactive distance (cm) and x represents visual clarity (black disk sighting range, cm), and where a and b are intercept and slope respectively, such that (f) identifies black disk sighting range, in meters, and its reciprocal, beam attenuation, as preferred monitoring variables; and (g) provides two additional optical quality variables (Secchi disk extinction distance and turbidity) which, suitably calibrated as they have been in this study, expand the range of monitoring options in situations in which the preferred technology—beam attenuation equipment or black disk sighting equipment—is unavailable or impractical to use. This new model demonstrates the efficacy of peer collaboration and defines new research horizons for its refinement.

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