Effects of metal contamination from mine tailings on allozyme distributions of populations of great plains fishes

Authors

  • Shaun Roark,

    1. Department of Biological Sciences, Wichita State University, Wichita, Kansas 67260–0026, USA
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  • Karen Brown

    Corresponding author
    1. Department of Biological Sciences, Wichita State University, Wichita, Kansas 67260–0026, USA
    • Department of Biological Sciences, Wichita State University, Wichita, Kansas 67260–0026, USA
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Abstract

This study was conducted to assess the effects of zinc and lead on genetic variability of minnow populations (Gambusia affinis, Pimephales notatus, and Fundulus notatus) sampled from two creeks, one receiving mine drainage (Willow Creek) and one reference (Brush Creek), in the Tri-State Mining District in Kansas. Zinc and lead concentrations were greater in water samples taken from sites in Willow Creek compared to sites sampled in Brush Creek. Although total numbers of fish captured from Willow Creek were smaller than numbers taken from Brush Creek, there were no differences in these fish communities for estimates of species diversity, richness, and evenness. Genetic differentiation within creeks was rare. However, there was significant differentiation between creeks for allozymes of the enzymes glucose phosphate isomerase (Gpi) in F. notatus and P. notatus, malate dehydrogenase (Mdh) in G. affinis, and phosphogluconate dehydrogenase (Pgdh) in F. notatus. Proportions of heterozygous genotypes of P. notatus and G. affinis were higher in Willow Creek compared to Brush Creek. In vitro experiments were conducted to assess the effects of zinc and lead on sensitivity of enzyme staining during electrophoresis. Results indicated allozyme sensitivity to zinc for Gpi and Pgdh loci, but not for products of the Mdh locus. No sensitivity to lead was noted for allozymes. The significant differentiation between creek populations and the results of the in vitro tests indicate a selective effect of zinc on allozymic distributions of these fishes. These results provide additional support for the use of genetic structure and variability as a bioindicator of heavy metal contamination.

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