Scaling to the Organism: An Innovative Model of Dynamic Exposure Hotspots in Stream Systems

TitleScaling to the Organism: An Innovative Model of Dynamic Exposure Hotspots in Stream Systems
Publication TypeJournal Article
Year of Publication2017
AuthorsHarrigan KM, Moore PA
JournalArchives of Environmental Contamination and Toxicology
Issue2922
Date PublishedMay-09-2017
ISSN0090-4341
Abstract

In flowing systems, fluctuations in the frequency, magnitude, and duration of exposure occurs due to turbulence and geomorphology, causing spatial and temporal variations in chemical exposure at the scale of the organism. Spatial models representing toxicant distribution at the appropriate scales of stream organisms are noticeably missing from the literature. To characterize the fine scale distribution of pollutants in freshwater streams at the scale of a benthic organism, nine artificial stream habitats were created (riffle, pool, run, bend, woody debris) with either sand or gravel substrate. Dopamine was released as a chemical tracer, mimicking a groundwater source, and measurements were recorded with a microelectrode and Epsilon electrochemical recording system. Proxies for the frequency, magnitude, and duration of chemical exposure were extracted. Geographic information systems and an inverse distance weight interpolation technique were used to predict spatially the chemical distribution throughout the habitats. Spatial and temporal variations of exposure were exhibited within and across habitats, indicating that the frequency, magnitude, and duration of exposure is influenced by the organism’s location within a habitat and the habitat it resides in. The run and pool with sand substrate contained the greatest frequency, magnitude, and duration of exposure, suggesting a more detrimental exposure compared to other habitats. Differences in peak heights within and across habitats are orders of magnitude in value. Spatial and temporal fluctuations of fine scale exposure need to be considered in both ecotoxicology and water quality modeling to represent and understand the exposure of pollutants impacting benthic organisms.

URLhttp://link.springer.com/10.1007/s00244-017-0444-3http://link.springer.com/content/pdf/10.1007/s00244-017-0444-3.pdfhttp://link.springer.com/content/pdf/10.1007/s00244-017-0444-3.pdfhttp://link.springer.com/article/10.1007/s00244-017-0444-3/fulltext.html
DOI10.1007/s00244-017-0444-3
Short TitleArch Environ Contam Toxicol
Related research sites: 
UMBS Stream Research Facility