Toward improved assessment of freshwater salinization as a benthic macroinvertebrate stressor

Salinization of freshwaters by human activities is of growing concern globally. Salt pollution can cause adverse effects to aquatic biodiversity, ecosystem function, ecosystem services, and human health. In many regions of the world, and in coal-mining-influenced streams of the temperate forests of Appalachia USA, specific conductance (SC), a surrogate measure for the dissolved major ions composing salinity, has been linked to decreased diversity of benthic macroinvertebrates. However, assessments used to reach this conclusion have generally not accounted for temporal variability of salinity, as most studies use "snapshot" SC data collected concurrently with biological data at a single point in time. Effective management of salinization requires tools to accurately monitor and predict salinity while accounting for temporal variability. To improve those tools, I conducted analyses of 4.5 years of salinity and benthic macroinvertebrate data from 25 forested headwater streams spanning a gradient of salinity where non-salinity stressors were minimized. My objectives were to: 1) model the annual pattern of salinity, 2) determine if salinity measures derived from continuous data are more precise than snapshot SC as predictors of aquatic biology, and 3) quantify response to salinity of the benthic macroinvertebrate community. A sinusoidal model of the annual cycle of SC using daily measurements for 4.5 years revealed that salinity naturally deviated ± 20% from annual mean levels, with minimum SC occurring in late winter and maximum SC occurring in late summer. The pattern was responsive to seasonal dilution as driven by catchment evapotranspiration dynamics. Alternative discrete sampling intervals can approximate the pattern revealed by continuous SC data if sampling intervals are ≤ 30 days. Continuous SC variables did not significantly improve precision for prediction of benthic macroinvertebrate metrics (p > 0.1) as compared to snapshot SC using generalized additive mixed models.

Results suggest that snapshot SC is a capable predictor of benthic macroinvertebrate community structure if sampling is carefully timed. However, continuous SC data can quantify chronic salt exposure, which supports a hypothesis to explain how temporal variability of field-based observations of salt sensitivity of benthic macroinvertebrate taxa may be influenced by life stage. Benthic macroinvertebrate community structure diverged from reference condition as salinity increased, with stronger relationships in Spring than in Fall. Intra-seasonal variation in community structure was also revealed across sampling dates. Non-Baetidae Ephemeroptera were most sensitive to salinity, with richness and abundance lower than reference at SC > 200 =µS/cm in Spring based on snapshot SC. Equivalent effects were predicted by mean monthly SC of 250-300 µS/cm from the prior Fall. Continuous conductivity monitoring may improve assessment of salinity effects because they can describe life-cycle exposure, which may aid investigations of mechanisms driving field-based observations of benthic-macroinvertebrate community alteration.