Title |
Optimizing fish sampling for fish–mercury bioaccumulation factors
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Published in |
Chemosphere, January 2015
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DOI | 10.1016/j.chemosphere.2014.12.068 |
Pubmed ID | |
Authors |
Barbara C. Scudder Eikenberry, Karen Riva-Murray, Christopher D. Knightes, Celeste A. Journey, Lia C. Chasar, Mark E. Brigham, Paul M. Bradley |
Abstract |
Fish Bioaccumulation Factors (BAFs; ratios of mercury (Hg) in fish (Hgfish) and water (Hgwater)) are used to develop total maximum daily load and water quality criteria for Hg-impaired waters. Both applications require representative Hgfish estimates and, thus, are sensitive to sampling and data-treatment methods. Data collected by fixed protocol from 11 streams in 5 states distributed across the US were used to assess the effects of Hgfish normalization/standardization methods and fish-sample numbers on BAF estimates. Fish length, followed by weight, was most correlated to adult top-predator Hgfish. Site-specific BAFs based on length-normalized and standardized Hgfish estimates demonstrated up to 50% less variability than those based on non-normalized Hgfish. Permutation analysis indicated that length-normalized and standardized Hgfish estimates based on at least 8 trout or 5 bass resulted in mean Hgfish coefficients of variation less than 20%. These results are intended to support regulatory mercury monitoring and load-reduction program improvements. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 1% |
Germany | 1 | 1% |
Italy | 1 | 1% |
Unknown | 83 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 20 | 23% |
Student > Bachelor | 15 | 17% |
Student > Master | 12 | 14% |
Student > Ph. D. Student | 11 | 13% |
Student > Doctoral Student | 6 | 7% |
Other | 11 | 13% |
Unknown | 11 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Environmental Science | 27 | 31% |
Agricultural and Biological Sciences | 22 | 26% |
Chemistry | 10 | 12% |
Biochemistry, Genetics and Molecular Biology | 3 | 3% |
Engineering | 3 | 3% |
Other | 4 | 5% |
Unknown | 17 | 20% |