EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021

(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)

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5/20/2019  |   2:15 PM - 2:30 PM   |  CHARACTERIZING NUISANCE ALGAL RESPONSES TO ENVIRONMENTAL STRESSORS USING HIGH-THROUGHPUT SEQUENCING   |  150 DEF

CHARACTERIZING NUISANCE ALGAL RESPONSES TO ENVIRONMENTAL STRESSORS USING HIGH-THROUGHPUT SEQUENCING

Bloom-forming and toxin-producing algae can decrease ecological condition, impair drinking water, and prevent recreational use of streams and rivers. Little is known about how nuisance algae in streams respond to drought, nutrient pollution, and pesticide contamination. DNA metabarcoding offers a time- and cost-effective alternative to traditional morphological analysis to increase nuisance algal detection in stream biofilms. Predictive modeling can be used to understand how environmental stressors affect taxon presence. I present results comparing the sensitivity of morphology-based counts and 23S rRNA DNA metabarcoding in detecting key nuisance algae genera and their relationships to environmental stressors across 95 northeastern United States streams along an urban gradient. We identified the cyanobacteria Anabaena, Lyngbya, Microcystis, and Nostoc; the green algae Cladophora, Mougeotia, and Zygnema; Euglena; and the diatom Didymosphenia as potential nuisance algae in streams. For each genus, we constructed predictive models using taxon presence/absence and stream hydrology, nutrients, major ions, and pesticides to determine likelihoods of nuisance algae occurrence in impacted streams. Our results suggest DNA-based methods and predictive modeling can determine conditions in which nuisance algae affect water quality for human use.

  • Bioassessment
  • Genetics
  • Modeling

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Presenters/Authors

Nicholas Schulte (), Institute of Arctic and Alpine Research, University of Colorado Boulder, nicholas.schulte@colorado.edu;


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Daren Carlisle (), U.S. Geological Survey, dcarlisle@usgs.gov;


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Sarah Spaulding (), U.S. Geological Survey, Institute of Arctic and Alpine Research, University of Colorado Boulder, sarah.spaulding@colorado.edu;


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