Salinization is of growing concern as an aquatic-life stressor in Appalachian headwater streams influenced by coal mining. Consequently, it is desirable to improve understanding of associations between salinity and biologi-cal effects. Such analyses are often conducted using temporally discrete water samples collected during seasonal benthic macroinvertebrate surveys. Because salinity is not temporally static in such streams, discrete seasonal salinity measures are often inadequate to describe life-cycle exposures. Our research compares a continuous water-quality sampling approach to traditional discrete-sampling methods as means for evaluating saliniza-tion effects on benthic macroinvertebrate community structure. We used automated dataloggers to record conductivity continuously for ~21 months in 27 headwater streams spanning a gradient of salinity (specific conduct-ance ~20 – 2,000 mS/cm) where non-salinity stressors were not evident. We found that models using salinity measures derived from continuous con-ductivity data described the salinity-biota association with greater certainty than models using discrete salinity measures as predictors of genus-level macroinvertebrate community metrics. Our results suggest that predictive models using continuous conductivity data from time periods prior to mac-roinvertebrate sampling provide more accurate predictions of biotic effects compared to models constructed using discrete conductivity data collected at the time of biological sampling.
|Title of host publication
|Society of Environmental Toxicology and Chemistry North America 34th Annual Meeting, 17-21 November 2013, Nashville, Tennessee
|Published - 2013