Relations between and among contaminant concentrations and biomarkers in black bass (Micropterus spp.) and common carp (Cyprinus carpio) from large U.S. rivers, 1995–2004

Environmental contaminant and biomarker monitoring data from major U.S. river basins were summarized for black bass (Micropterus spp.) and common carp (Cyprinus carpio) sampled over a nine year period. Cumulative frequency distributions revealed taxon differences for many organochlorine residue concentrations, elemental contaminant concentrations, and biomarkers, but few gender differences were evident for chemical concentrations. Concentrations of dacthal, pentachloroanisole, p,p′-DDE, endosulfan sulfate, barium, cadmium, copper, manganese, lead, selenium, vanadium, and zinc were greater in carp than bass, but concentrations of mercury and magnesium were greater in bass. Gender differences were evident in bass for mercury and in carp for zinc, but the differences were small compared to taxon differences. Greater vitellogenin concentrations, 17β-estradiol concentrations, 17β-estradiol/11-ketotestosterone ratios, and percent oocyte atresia in female carp compared to female bass may be related to the sequential spawning of carp. Regression analyses indicated that as much as 78% of biomarker variation was explained by chemical contaminant concentrations. Sites grouped consistently by river basin in the chemical contaminant principal components analysis (PCA) models and were driven by mercury, magnesium, barium, mirex, and oxychlordane. PCA models for the biomarkers did not group the sites by basin for either bass or carp. Statistical analyses and data interpretation were limited by the study design. The implications of these limitations are discussed. Recommendations to be considered during the planning of future monitoring studies include the exclusion of gender- and species-specific sampling for certain chemical contaminants considering analytical methods with appropriate sensitivities; and allowing for the addition of new chemical and biological variables as methods and information needs evolve.