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Optimizing fish sampling for fish–mercury bioaccumulation factors

Overview of attention for article published in Chemosphere, January 2015
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Title
Optimizing fish sampling for fish–mercury bioaccumulation factors
Published in
Chemosphere, January 2015
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

Mendeley readers

The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

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%