2022 Early Hearing Detection & Intervention Virtual Conference
March 13 - 15, 2022
5/23/2019 | 12:00 PM - 12:15 PM | CAPTURING BENTHIC MACROINVERTEBRATE TAXA RICHNESS ACROSS A SALINITY GRADIENT IN CENTRAL APPALACHIAN HEADWATER STREAMS | 151 ABC
CAPTURING BENTHIC MACROINVERTEBRATE TAXA RICHNESS ACROSS A SALINITY GRADIENT IN CENTRAL APPALACHIAN HEADWATER STREAMS
Anthropogenic salinization is a global concern as human activities such as road de-icing, agriculture, and mining introduce increased levels of ions to freshwaters. Headwater streams draining coalfields in central Appalachia have elevated levels of sulfate and associated major ions that alter benthic macroinvertebrate community structure by decreasing diversity of salt-sensitive taxa. Less is known about how elevated salinity affects macroinvertebrate densities and their functions because quantitative sampling is less common. Taxa accumulation curves identify the sample effort (i.e. the number of samples) required to capture representative metrics. In April of 2014, three Surber samples were collected from riffles of 15 headwater streams (N=45) across a salinity gradient (~25-1500 µS/cm). The estimated number of samples needed was predicted to decrease as salinity increased because salinity negatively impacts taxa richness. Preliminary accumulation curves suggest decreases in taxa richness with increased salinity as curves level off sooner. Reference sites continue to have higher slopes that reach higher asymptote values, suggesting more than three Surber samples were required to capture taxa richness. We will present complete accumulation curves that inform future quantitative sampling efforts and functional metrics in relation to salinity.
- Invertebrate
- Biodiversity
- Bioassessment
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Presenters/Authors
Aryanna James
(), Virginia Tech, aryannaj@vt.edu;
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Rachel Pence
(), Virginia Tech, pencera@vt.edu;
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Sally Entrekin
(), Virginia Tech, sallye@vt.edu;
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Carl Zipper
(), Virginia Tech, czip@vt.edu;
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Anthony Timpano
(), Virginia Tech, atimpano@vt.edu;
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Stephen Schoenholtz
(), Virginia Tech, schoenhs@vt.edu;
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Daniel McLaughlin
(), Virginia Tech, mclaugd@vt.edu;
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