Filters: Tags: Nearshore (X) > partyWithName: Catherine A Fargen (X)
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This dataset provides results of a targeted bacterial community metagenomic analysis of surface water, groundwater, and sand samples at Jeorse Park on Lake Michigan in East Chicago, Indiana. Seventy-two samples were collected from 6 sites in 2017. Samples were analyzed for the 16S ribosomal RNA (16S rRNA) gene (the S in 16S refers to the rate of sedimentation, in Svedberg units, of the RNA molecule in a centrifugal field), and one sample was excluded because it produced too few reads. The 16S rRNA gene is the most conserved of three rRNA genes (16S, 23S, and 5S) and is considered the most reliable for identification and taxonomic classification of bacterial species (Bouchet and others, 2008). Taxonomic analysis...
Groundwater and surface-water samples were collected and analyzed for microbial source tracking markers to identify the primary sources of fecal bacteria at a Lake Michigan beach in Northwestern Indiana.
The U.S. Geological Survey (USGS), in cooperation with the Great Lakes Restoration Initiative, collected data in 2017 to study the sources and occurrences of continual detections of high Escherichia coli (E. coli) detections at urban beaches along the Lake Michigan shoreline in northwest Indiana and northeastern Illinois. High E. coli detections cause the beaches to be closed for recreational use until additional samples verify that E. coli levels have fallen below the threshold of 235 counts per 100 ml. The project used microbial source tracking (MST) and metagenomics analyses to evaluate the sources of E. coli. This data release provides the phytoplankton, mictobial source tracking, and metagenomics components...
This dataset describes the identification of phytoplankton to the lowest taxonomic level (typically species), as well as abundance (density) and biovolume from grab samples collected from Lake Michigan at Jackson Park at Hyde Park, Illinois and Lake Michigan at Jeorse Park at Gary, Indiana.
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