Toward improved assessment of freshwater salinization as a benthic macroinvertebrate stressor
| dc.contributor.author | Timpano, Anthony J. | en |
| dc.contributor.committeechair | Zipper, Carl E. | en |
| dc.contributor.committeechair | Schoenholtz, Stephen H. | en |
| dc.contributor.committeemember | Brown, Bryan L. | en |
| dc.contributor.committeemember | Soucek, David J. | en |
| dc.contributor.department | Forest Resources and Environmental Conservation | en |
| dc.date.accessioned | 2017-09-28T08:00:19Z | en |
| dc.date.available | 2017-09-28T08:00:19Z | en |
| dc.date.issued | 2017-09-27 | en |
| dc.description.abstract | 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. | en |
| dc.description.abstractgeneral | Freshwater ecosystems around the world are at risk of contamination from salt pollution resulting from a variety of human activities. All natural freshwaters contain low levels of dissolved minerals, or salts, the combined concentration of which is referred to as salinity. Activities such as crop irrigation, road de-icing, and mining can cause salt pollution in streams and rivers, and excessive salinity can be toxic to many aquatic organisms. In many regions of the world, including in coal-mining-influenced streams of Appalachia USA, elevated salinity has been linked to decreased diversity of benthic macroinvertebrates, which are primarily aquatic insects, a group critical to healthy stream ecosystems. However, assessments used to reach this conclusion have generally not accounted for annual variability of salinity, as most studies use “snapshot” salinity data collected concurrently with biological data at a single point in time. Effective management of salinity impacts requires tools to accurately monitor and predict salinity while accounting for annual variability. Toward improving those tools, I conducted analyses of 4.5 years of salinity and aquatic insect data from 25 small central Appalachian mountain streams spanning a gradient of salinity. My objectives were to: 1) characterize the annual pattern of salinity using high-frequency salinity data, 2) determine if high-frequency salinity data is better than snapshot data for predicting aquatic insect diversity, and 3) measure the response to salinity of the aquatic insect community and identify salinity levels associated with insect biodiversity loss. High-frequency (daily) data revealed that salinity exhibited a predictable cyclic annual pattern with seasonal deviations of ± 20% from annual average salinity levels. Minimum salinity occurred during late winter and maximum salinity occurred in late summer. Lower-frequency salinity data can approximate the annual pattern if sampling interval is ≤ 30 days. Snapshot salinity was equally capable as high-frequency data of predicting aquatic insect diversity provided that snapshot salinity sampling is carefully timed. Diversity of many aquatic insects, especially mayflies, declined with increasing salinity, with stronger relationships in Spring than in Fall. Variation in diversity measures was also somewhat related to sample timing within seasons. Alteration of aquatic insect communities was evident at total salt concentrations levels of approximately 130 – 200 parts per million, depending on time of year. Efforts to manage salinity impacts to aquatic life may be improved by integrating knowledge of annual salinity patterns with how aquatic insects respond to salt pollution. | en |
| dc.description.degree | Ph. D. | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:12902 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/79428 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | biomonitoring | en |
| dc.subject | coal mining | en |
| dc.subject | conductivity | en |
| dc.subject | major ions | en |
| dc.subject | Water quality | en |
| dc.title | Toward improved assessment of freshwater salinization as a benthic macroinvertebrate stressor | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Forestry | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Ph. D. | en |
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