Literature DB >> 11351539

A predictive model of mercury fish tissue concentrations for the southeastern United States.

S S Qian1, W Warren-Hicks, J Keating, D R Moore, R S Teed.   

Abstract

We developed a statistical model for predicting mercury concentrations in fish tissue in four southeastern states in the United States with an emphasis on identifying important predictor variables. A number of variables that could influence mercury fish tissue concentration, including proximity to sources of mercury, environmental factors affecting mercury movement and transformation, and factors affecting mercury accumulation, were considered. The model consists of three components using classification and regression three modeling, generalized additive modeling, and universal kriging, respectively. Each modeling component accounts for a different level of variation in fish tissue mercury concentration. Important factors for predicting mercury fish tissue concentrations are: (1) location, (2) species, (3) water body pH, and (4) fish weight. South central Arkansas and southeast Mississippi are the two "hot spots" with high fish tissue mercury concentrations. In addition, relatively high mercury levels were found near the Arkansas-Louisiana border and the mid-section of Mississippi.

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Year:  2001        PMID: 11351539     DOI: 10.1021/es0013069

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  4 in total

1.  Mercury concentration in the muscle of seven fish species from Chagan Lake, Northeast China.

Authors:  Lilu Zhu; Baixing Yan; Lixia Wang; Xiaofeng Pan
Journal:  Environ Monit Assess       Date:  2011-04-06       Impact factor: 2.513

2.  Mercury concentrations in lentic fish populations related to ecosystem and watershed characteristics.

Authors:  Andrew L Rypel
Journal:  Ambio       Date:  2010-02       Impact factor: 5.129

3.  Shallow groundwater mercury supply in a Coastal Plain stream.

Authors:  Paul M Bradley; Celeste A Journey; Mark A Lowery; Mark E Brigham; Douglas A Burns; Daniel T Button; Francis H Chapelle; Michelle A Lutz; Mark C Marvin-Dipasquale; Karen Riva-Murray
Journal:  Environ Sci Technol       Date:  2012-07-06       Impact factor: 9.028

4.  Climate and pH predict the potential range of the invasive apple snail (Pomacea insularum) in the southeastern United States.

Authors:  James E Byers; William G McDowell; Shelley R Dodd; Rebecca S Haynie; Lauren M Pintor; Susan B Wilde
Journal:  PLoS One       Date:  2013-02-22       Impact factor: 3.240

  4 in total

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