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AUTHORS: Darcy Cashatt, Iowa Department of Natural Resources; Nathan Mills, Iowa State University, Michael Weber, Iowa State University; Clay Pierce, Iowa Cooperative Fish and Wildlife Research Unit
ABSTRACT: Mercury contamination in aquatic ecosystems is a global concern due to the health risks of consuming contaminated organisms, particularly fishes. Mercury concentrations in fishes are highly variable within and among systems, and factors influencing fish mercury concentrations across Iowa lake systems are unknown. Bluegill (Lepomis macrochirus, n=275), white and black crappie (Pomoxis annularis, n=112; P. nigromaculatus, n=203), largemouth bass (Micropterus salmoides, n=503), walleye (Sander vitreus, n=248), muskellunge (Esox masquinongy, n=30), and northern pike (E. lucius, n=45) were collected between April and October, 2013-2015, from natural lakes (n=8), constructed lakes (n=18), and reservoirs (n=4) and tested for mercury contamination. Various land use, water chemistry, and fish characteristics were used to explain differences in mercury concentrations across and within lakes. Mercury concentrations of Iowa fishes are generally low, and contained a high percentage of undetectable concentrations (< 0.05 mg Hg/kg; 43% of observations). Thus, we first used multiple linear regression to evaluate factors related to detected mercury concentrations. Second, we used logistic regression with detected and undetected observations to predict the probability of detecting mercury. Mercury concentrations were highest in muskellunge, northern pike, walleye and largemouth bass but lowest in black and white crappie and bluegill. Fish mercury concentration was strongly positively related to length and age. Lake mean depth, watershed area, lake area, latitudinal and longitudinal coordinates were positively related to fish mercury concentrations. Alkalinity was the only water quality metric related to mercury concentrations. Together, these factors explained 71% of the variation in fish mercury concentrations. The logistic model correctly predicted the probability of detecting mercury concentrations for 85% of the 1,416 fish sampled. Our study has implications for consumption advisories in Iowa.
