Geologic processes influence the effects of mining on aquatic ecosystems.

Geologic processes strongly influence water and sediment quality in aquatic ecosystems but rarely are geologic principles incorporated into routine biomonitoring studies. We test if elevated concentrations of metals in water and sediment are restricted to streams downstream of mines or areas that may discharge mine wastes. We surveyed 198 catchments classified as "historically mined" or "unmined," and based on mineral-deposit criteria, to determine whether water and sediment quality were influenced by naturally occurring mineralized rock, by historical mining, or by a combination of both. By accounting for different geologic sources of metals to the environment, we were able to distinguish aquatic ecosystems limited by metals derived from natural processes from those due to mining. Elevated concentrations of metals in water and sediment were not restricted to mined catchments; depauperate aquatic communities were found in unmined catchments. The type and intensity of hydrothermal alteration and the mineral deposit type were important determinants of water and sediment quality as well as the aquatic community in both mined and unmined catchments. This study distinguished the effects of different rock types and geologic sources of metals on ecosystems by incorporating basic geologic processes into reference and baseline site selection, resulting in a refined assessment. Our results indicate that biomonitoring studies should account for natural sources of metals in some geologic environments as contributors to the effect of mines on aquatic ecosystems, recognizing that in mining-impacted drainages there may have been high pre-mining background metal concentrations.

Critical tissue residue approach linking accumulated metals in aquatic insects to population and community-level effects.

Whole body Zn concentrations in individuals (n = 825) from three aquatic insect taxa (mayflies Rhithrogena spp. and Drunella spp. and the caddisfly Arctopsyche grandis) were used to predict effects on populations and communities (n = 149 samples). Both mayflies accumulated significantly more Zn than the caddisfly. The presence/absence of Drunella spp. most reliably distinguished sites with low and high Zn concentrations; however, population densities of mayflies were more sensitive to increases in accumulated Zn. Critical tissue residues (634 µg/g Zn for Drunella spp. and 267 µg/g Zn for Rhithrogena spp.) caused a 20% reduction in maximum (90th quantile) mayfly densities. These critical tissue residues were associated with exposure to 7.0 and 3.9 µg/L dissolved Zn for Drunella spp. and Rhithrogena spp., respectively. A threshold in a measure of taxonomic completeness (observed/expected) was observed at 5.4 µg/L dissolved Zn. Dissolved Zn concentrations associated with critical tissue residues in mayflies were also associated with adverse effects in the aquatic community as a whole. These effects on populations and communities occurred at Zn concentrations below the U.S. EPA hardness-adjusted continuous chronic criterion.

Development of a new toxic-unit model for the bioassessment of metals in streams.

Two toxic-unit models that estimate the toxicity of trace-metal mixtures to benthic communities were compared. The chronic criterion accumulation ratio (CCAR), a modification of biotic ligand model (BLM) outputs for use as a toxic-unit model, accounts for the modifying and competitive influences of major cations (Ca²(+), Mg²(+), Na(+), K(+), H(+)), anions (HCO3⁻, CO²â»3 ,SO²â»4, Cl⁻, S²â») and dissolved organic carbon (DOC) in determining the free metal ion available for accumulation on the biotic ligand. The cumulative criterion unit (CCU) model, an empirical statistical model of trace-metal toxicity, considers only the ameliorative properties of Ca²(+) and Mg²(+) (hardness) in determining the toxicity of total dissolved trace metals. Differences in the contribution of a metal (e.g., Cu, Cd, Zn) to toxic units as determined by CCAR or CCU were observed and attributed to how each model incorporates the influences of DOC, pH, and alkalinity. Akaike information criteria demonstrate that CCAR is an improved predictor of benthic macroinvertebrate community metrics as compared with CCU. Piecewise models depict great declines (thresholds) in benthic macroinvertebrate communities at CCAR of 1 or more, while negative changes in benthic communities were detected at a CCAR of less than 1. We observed a 7% reduction in total taxa richness and a 43% decrease in Heptageniid abundance between background (CCAR = 0.1) and the threshold of chronic toxicity on the basis of continuous chronic criteria (CCAR = 1). In this first application of the BLM as a toxic-unit model, we found it superior to CCU.