Copper toxicity in Bristol Bay headwaters: Part 2—Olfactory inhibition in low‐hardness water

Morris, Jeffrey M.; Brinkman, Stephen F.; Takeshita, Ryan; McFadden, Andrew K.; Carney, Michael W.; Lipton, Joshua

doi:10.1002/etc.4295

Cited by 11 publications

(11 citation statements)

References 28 publications

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“…While behavioral avoidance of Cu is likely a natural defense mechanism, avoidance behavior can be seen as an adverse effect of Cu (or any substance) because it can interfere with other important life history behaviors such as natural movements or migrations (Saunders and Sprague 1967). In laboratory swim chambers settings where the chemical is released into one side of the chamber and in the absence of other behavioral cues, avoidance responses may occur at up to 15X lower than concentrations that are acutely lethal (Giattina et al 1982;Hansen et al 1999a;Morris et al 2018).…”

Section: Coppermentioning

confidence: 99%

Bioavailability and toxicity models of copper and zinc to freshwater life: the state of the science and alternatives for water quality criteria

Mebane¹

2022

Preprint

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The importance of water conditions on the bioavailability and toxicity of metals has long been recognized. In the United States and elsewhere, regulatory criteria to protect aquatic life have likewise acknowledged factors that modify bioavailability, and incorporated water hardness-toxicity regressions into criteria for several metals. Biotic ligand models (BLMs) became a dominant paradigm in predicting the aquatic toxicology of metals as mechanistic functions of modeled metals speciation and cation competition for binding to ionoregulatory sites on the gill or biotic ligand surface, disrupting the internal mineral balance of organisms and leading to stress or death. Following development of software that efficiently executed BLM calculations, in 2007 the U.S. Environmental Protection Agency (USEPA) published national recommended aquatic life criteria for copper (Cu) that was based upon the BLM construct and software. However, there has not been widespread adoption by states of the USEPA’s recommended BLM-based aquatic life criteria into their water quality standards. Reasons for the languishing of the BLM-based Cu criteria presumably include that the BLM-based Cu criteria are far more complex than any previous aquatic life criteria and that the BLM requires much more data than water hardness to calculate the criteria. pH, dissolved organic carbon (DOC), a suite of major ions, alkalinity, and specialized software are required to calculate BLM-based criteria. The purpose of the present study is to compare the leading available aquatic life criteria models for predicting Cu and zinc (Zn) toxicity (or lack of toxicity) to diverse freshwater species and ecosystems: 1) the single linear regression hardness models; 2) Multiple Linear Regression (MLR) models that predict toxicity as a function of DOC, hardness, and pH, and 3) BLM-based criteria. The scope of the review for Zn was truncated relative to that of Cu because no generally applicable MLR model for Zn was available at the time of writing.The comparisons included evaluating the performance of the models for predicting Cu toxicity and the models’ behavior in natural waters. The evaluations of toxicity predictions were limited to freshwater animals and included testing model predictions against literature reports of observed acute and chronic responses with trout, other fish, mussels and other invertebrates, and olfactory impairment or avoidance responses in salmonids. The presumed “safe” criteria concentrations were also compared against effects attributed to Cu in field studies or ecosystem experiments. The comparisons emphasize natural waters in California, however conditions in California waters are diverse and the comparisons are broadly relevant to other freshwaters.The results were consistent with previous work that found that the MLR toxicity predictions were generally more reliable than the BLM for predicting Cu toxicity across the vast majority of natural water types, but that the BLM predictions were more reliable in situations with low or high pH (less than about 5.7 or greater than about 9) or in waters with unusual ionic composition. However, both the MLR and BLM performed well with many datasets and aquatic life criteria calculation procedures both produced criteria concentrations that mostly appeared safe in comparisons with field and ecosystem studies and with particularly sensitive species and endpoints such as chemoreception and avoidance behaviors in salmonids. In marked contrast, the hardness-regression model toxicity predictions performed poorly with all datasets tested, with little correspondences between predicted and observed effects. The comparisons of the hardness-criteria concentrations with Cu effects thresholds estimated from field and ecosystem studies showed that the hardness-based criteria failed to reliably produce protective concentrations. In soft waters with less than about 40 mg/L hardness, the hardness-based criteria would be protective but not at higher hardnesses. In natural waters, the hardness criteria had little correlation to the MLR, which was the most accurate proxy for truly toxic or nontoxic conditions, and in some steams, the hardness-based criteria actually had negative correlations with the MLR criteria.Th performance and protectiveness of the Cu MLR and BLM models and criteria were largely similar. However, the Cu MLR has advantages for adoption into water quality standards over the BLM because of its reduced data requirements, simpler form, ease of calculation, transparency, and non-dependence on specialized computer software. The Cu MLR could be structured in tiers to accommodate missing data by setting conservative default values for pH or DOC, for example, pH 7 and 1 mg/L DOC. Then, only if environmental Cu concentrations exceeded criteria as calculated with default values would actual DOC and pH data be needed.

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Section: Coppermentioning

confidence: 99%

Bioavailability and toxicity models of copper and zinc to freshwater life: the state of the science and alternatives for water quality criteria

Mebane¹

2022

Preprint

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“…Aquatic life is highly sensitive to divalent metals such as Cu [6]. Salmonids are particularly sensitive, with Cu impacts to the gills, olfaction, and lateral line [7][8][9][10]. At very low concentrations, Cu can cause salmonids to lose their ability locate home streams [10,11] or detect alarm pheromones that warn of nearby predators [7,12].…”

Section: Environmental Risksmentioning

confidence: 99%

“…Salmonids are particularly sensitive, with Cu impacts to the gills, olfaction, and lateral line [7][8][9][10]. At very low concentrations, Cu can cause salmonids to lose their ability locate home streams [10,11] or detect alarm pheromones that warn of nearby predators [7,12]. Previous work has shown that the natural waters in the Pebble deposit area are very low in Cu, frequently below a detection limit of 0.2 µg/L, and low in alkalinity and dissolved organic carbon which could ameliorate Cu toxicity impacts to some extent [13,14].…”

Section: Environmental Risksmentioning

confidence: 99%

“…Previous work has shown that the natural waters in the Pebble deposit area are very low in Cu, frequently below a detection limit of 0.2 µg/L, and low in alkalinity and dissolved organic carbon which could ameliorate Cu toxicity impacts to some extent [13,14]. Research with site water suggests that small increases of Cu that enter salmonid habitat could quickly become bioavailable [15] with sublethal and acute impacts [7,16].…”

Section: Environmental Risksmentioning

confidence: 99%

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Potential Impacts to Wetlands and Water Bodies Due to Mineral Exploration, Pebble Copper-Gold Prospect, Southwest Alaska

Zamzow¹,

Chambers²

2019

Environments

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There is little information in the literature about the impacts of mineral exploration drilling on natural waters. A copper-gold-molybdenum mining deposit in Alaska was heavily explored until 2012 and partially reclaimed; however, full reclamation of drill sites remained incomplete in 2016. Copper is sub-lethally toxic to salmon, a highly-valued resource in this area. Of 109 sites inspected, 9 sites had confirmed impacts due to un-reclaimed drill-holes or drill waste disposal practices. At seven sites artesian waters at the drill stem resulted in surface water or sediment elevated in aluminum, iron, copper, or zinc with neutral pH. Copper concentrations at artesian sites were <0.4, 0.7, 2, 7, 15, 76, and 215 µg/L; the latter four exceed water quality criteria. Drilling waste is known to have been disposed of in ponds and unlined sumps. At one of five ponds sampled, copper declined from 51 to 8 µg/L over nine years. At the one sump area with historical data, copper increased from 0.3 to 1.8 µg/L at a downgradient wetland spring over five years. This research identifies contaminant types and sources and can be used to guide future ecotoxicity studies and improve regulatory oversight.

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“…The present study focuses on our laboratory evaluation of the acute effects of Cu exposure on the survival of salmonids and other fish. The companion study to the present study details our follow‐up evaluation of the effects of Cu on the salmonid olfactory system under similar water quality conditions (Morris et al [this issue]).…”

Section: Introductionmentioning

confidence: 99%

Copper toxicity in Bristol Bay headwaters: Part 1—Acute mortality and ambient water quality criteria in low‐hardness water

Morris

Brinkman

Carney

et al. 2018

Enviro Toxic and Chemistry

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The world-class Alaskan Bristol Bay salmon fishery and vast deposits of copper (Cu) and other metals in the watershed warrant further investigation into the potential toxicity of Cu to salmonids under the low water-hardness conditions that occur in the watershed. Therefore we investigated the acute toxicity of Cu to rainbow trout (Oncorhynchus mykiss) and fathead minnows (Pimephales promelas) in low-hardness water (∼ 30 mg/L as CaCO ) formulated in the laboratory and collected from the Bristol Bay watershed. The median lethal concentration (LC50) for rainbow trout exposed to Cu in low-hardness laboratory water was 16 μg Cu/L (95% confidence intervals [CIs]: 12, 21; dissolved Cu, filtered to 0.45 μm). The LC50 values for fathead minnows exposed to Cu in low-hardness laboratory water or site water were 29 and 79 μg Cu/L (95% CIs: 23, 35 and 58, 125; dissolved Cu), respectively. The biotic ligand model (BLM) LC50 estimates for these bioassays were 1.3 to 2.3 times higher than the actual LC50 values. We also calculated and analyzed acute Cu water quality criteria, also known as criterion maximum concentration (CMC), using hardness-based methods and the BLM for water samples collected throughout the Bristol Bay watershed in 2007. Biotic ligand model CMCs ranged from 0.05 to 17.5 μg Cu/L and hardness-based CMCs ranged from 2.3 to 6.1 μg Cu/L for the 65 samples analyzed. Our results show the need for site-specific research and subsequent water quality guidelines in low-hardness aquatic habitats. Environ Toxicol Chem 2018;9999:1-8. © 2018 SETAC.

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Copper toxicity in Bristol Bay headwaters: Part 2—Olfactory inhibition in low‐hardness water

Cited by 11 publications

References 28 publications

Bioavailability and toxicity models of copper and zinc to freshwater life: the state of the science and alternatives for water quality criteria

Bioavailability and toxicity models of copper and zinc to freshwater life: the state of the science and alternatives for water quality criteria

Potential Impacts to Wetlands and Water Bodies Due to Mineral Exploration, Pebble Copper-Gold Prospect, Southwest Alaska

Copper toxicity in Bristol Bay headwaters: Part 1—Acute mortality and ambient water quality criteria in low‐hardness water

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