Determination of aquatic hazard concentrations for the oil spill response product class of surface washing agents using species sensitivity distributions.

Surface washing agents (SWAs) are a diverse class of oil spill response products intended to facilitate removal of stranded oil from shorelines. This class of agents has high application rates relative to other categories of spill response products, but global toxicity data is generally limited to two standard test species: inland silverside and mysid shrimp. Here, we provide a framework to maximize the utility of limited toxicity data across a product class. To characterize species sensitivity to SWAs, the toxicity of three agents spanning a range of chemical and physical properties were tested in eight species. The relative sensitivity of mysids shrimp and inland silversides as surrogate test organisms was determined. Toxicity normalized species sensitivity distributions (SSDn) were used to estimate fifth centile hazard concentration (HC5) values for SWAs with limited toxicity data. Chemical toxicity distributions (CTD) of SWA HC5 values were used to compute a fifth centile chemical hazard distribution (HD5) to provide a more comprehensive assessment of hazard across a spill response product class with limited toxicity data than traditional single species or single agent approaches can give.

Recommendations for advancing media preparation methods used to assess aquatic hazards of oils and spill response agents.

Laboratory preparation of aqueous test media is a critical step in developing toxicity information needed for oil spill response decision-making. Multiple methods have been used to prepare physically and chemically dispersed oils which influence test outcome, interpretation, and utility for hazard assessment and modeling. This paper aims to review media preparation strategies, highlight advantages and limitations, provide recommendations for improvement, and promote the standardization of methods to better inform assessment and modeling. A benefit of media preparation methods for oil that rely on low to moderate mixing energy coupled with a variable dilution design is that the dissolved oil composition of the water accommodation fraction (WAF) stock is consistent across diluted treatments.  Further, analyses that support exposure confirmation maybe reduced and reflect dissolved oil exposures that are bioavailable and amenable to toxicity modeling.  Variable loading tests provide a range of dissolved oil compositions that require analytical verification at each oil loading. Regardless of test design, a preliminary study is recommended to optimize WAF mixing and settling times to achieve equilibrium between oil and test media. Variable dilution tests involving chemical dispersants (CEWAF) or high energy mixing (HEWAF) can increase dissolved oil exposures in treatment dilutions due to droplet dissolution when compared to WAFs. In contrast, HEWAF/CEWAFs generated using variable oil loadings are expected to provide dissolved oil exposures more comparable to WAFs. Preparation methods that provide droplet oil exposures should be environmentally relevant and informed by oil droplet concentrations, compositions, sizes, and exposure durations characteristic of field spill scenarios. Oil droplet generators and passive dosing techniques offer advantages for delivering controlled constant or dynamic dissolved exposures and larger volumes of test media for toxicity testing. Adoption of proposed guidance for improving media preparation methods will provide greater comparability and utility of toxicity testing in oil spill response and assessment.

Recommendations for advancing test protocols examining the photo-induced toxicity of petroleum and polycyclic aromatic compounds.

Photo-induced toxicity of petroleum products and polycyclic aromatic compounds (PACs) is the enhanced toxicity caused by their interaction with ultraviolet radiation and occurs by two distinct mechanisms: photosensitization and photomodification. Laboratory approaches for designing, conducting, and reporting of photo-induced toxicity studies are reviewed and recommended to enhance the original Chemical Response to Oil Spills: Ecological Research Forum (CROSERF) protocols which did not address photo-induced toxicity. Guidance is provided on conducting photo-induced toxicity tests, including test species, endpoints, experimental design and dosing, light sources, irradiance measurement, chemical characterization, and data reporting. Because of distinct mechanisms, aspects of photosensitization (change in compound energy state) and photomodification (change in compound structure) are addressed separately, and practical applications in laboratory and field studies and advances in predictive modeling are discussed. One goal for developing standardized testing protocols is to support lab-to-field extrapolations, which in the case of petroleum substances often requires a modeling framework to account for differential physicochemical properties of the constituents. Recommendations are provided to promote greater standardization of laboratory studies on photo-induced toxicity, thus facilitating comparisons across studies and generating data needed to improve models used in oil spill science.

Advancing Fifth Percentile Hazard Concentration Estimation Using Toxicity-Normalized Species Sensitivity Distributions.

The species sensitivity distribution (SSD) is an internationally accepted approach to hazard estimation using the probability distribution of toxicity values that is representative of the sensitivity of a group of species to a chemical. Application of SSDs in ecological risk assessment has been limited by insufficient taxonomic diversity of species to estimate a statistically robust fifth percentile hazard concentration (HC5). We used the toxicity-normalized SSD (SSDn) approach, (Lambert, F. N.; Raimondo, S.; Barron, M. G. Environ. Sci. Technol.2022,56, 8278-8289), modified to include all possible normalizing species, to estimate HC5 values for acute toxicity data for groups of carbamate and organophosphorous insecticides. We computed mean and variance of single chemical HC5 values for each chemical using leave-one-out (LOO) variance estimation and compared them to SSDn and conventionally estimated HC5 values. SSDn-estimated HC5 values showed low uncertainty and high accuracy compared to single-chemical SSDs when including all possible combinations of normalizing species within the chemical-taxa grouping (carbamate-all species, carbamate-fish, organophosphate-fish, and organophosphate-invertebrate). The SSDn approach is recommended for estimating HC5 values for compounds with insufficient species diversity for HC5 computation or high uncertainty in estimated single-chemical HC5 values. Furthermore, the LOO variance approach provides SSD practitioners with a simple computational method to estimate confidence intervals around an HC5 estimate that is nearly identical to the conventionally estimated HC5.

Relationships Between Aquatic Toxicity, Chemical Hydrophobicity, and Mode of Action: Log Kow Revisited.

Relationships between toxicity and chemical hydrophobicity have been known for nearly 100 years in mammals and fish, typically using the log of the octanol:water partition coefficient (Kow). The current study reassessed the influence of mode of action (MOA) on acute aquatic toxicity-log Kow relationships using a comprehensive database of 617 organic chemicals with curated and standardized acute toxicity data that did not exceed solubility limits, their consensus log Kow values, and weight of evidence-based MOA classifications (including 6 broad and 26 specific MOAs). A total of 166 significant (p < 0.05) log Kow-toxicity models were developed across six taxa groups that included QSARs for 5 of the broad and 13 of the specific MOAs. In this study, we demonstrate that QSARs based on MOAs can significantly increase LC50 prediction accuracy for specific acting chemicals. Prediction accuracy increases when QSARs are built based on highly specific MOAs, rather than broad MOA classifications. Additionally, we demonstrate that building QSAR models with chemicals in specific MOA groupings, rather than broader MOA groups leads to significantly better estimates. We also evaluated the differences between models developed from mass-based (µg/L) and mole-based (µmol/L) toxicity data and demonstrate that both are suitable for QSAR development with no clear trend in greater model accuracy. Overall, the results reveal that, despite high variance in all taxa and MOA groups, specific MOA-based models can improve the accuracy of aquatic toxicity predictions over more general groupings.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.The affiliations are correct.

Assessment of a New Approach Method for Grouped Chemical Hazard Estimation: The Toxicity-Normalized Species Sensitivity Distribution (SSDn).

New approach methods are being developed to address the challenges of reducing animal testing and assessing risks to the diversity of species in aquatic environments for the multitude of chemicals with minimal toxicity data. The toxicity-normalized species sensitivity distribution (SSDn) approach is a novel method for developing compound-specific hazard concentrations using data for toxicologically similar chemicals. This approach first develops an SSDn composed of acute toxicity values for multiple related chemicals that have been normalized by the sensitivity of a common species tested with each compound. A toxicity-normalized hazard concentration (HC5n) is then computed from the fifth percentile of the SSDn. Chemical-specific HC5 values are determined by back-calculating the HC5n using the chemical-specific sensitivity of the normalization species. A comparison of the SSDn approach with the single-chemical SSD method was conducted by using data for nine transition metals to generate and compare HC5 values between the two methods. We identified several guiding principles for this method that, when applied, resulted in accurate HC5 values based on comparisons with results from single-metal SSDs. The SSDn approach shows promise for developing statistically robust hazard concentrations when adequate taxonomic representation is not available for a single chemical.

Comparative Toxicity of Oil Spill Herding Agents to Aquatic Species.

Chemical herding agents are surfactant mixtures used to coalesce spilled oil and increase slick thickness to facilitate mechanical recovery or in situ burning. Only two herders are currently listed on the United States' National Oil and Hazardous Substances Pollution Contingency Plan or National Contingency Plan product schedule for potential use in spill response: the surface collecting agents Siltech OP-40™ and ThickSlick 6535™. Toxicity data for spill response agents are frequently available only for two estuarine species, mysid shrimp (Americamysis bahia) and inland silversides (Menidia beryllina), and are particularly limited for herding agents. Toxicity can vary over several orders of magnitude across product type and species, even within specific categories of spill response agents. Seven aquatic species were tested with both Siltech OP-40™ and ThickSlick 6535™ to evaluate acute herder toxicity and relative species sensitivity. The toxicity assessment included: acute tests with A. bahia and M. beryllina, the freshwater crustacean Ceriodaphina dubia, and the freshwater fish Pimephales promelas; development of the echinoderm Arbacia unctulate; and growth of a freshwater alga Raphidocelis subcapitata and marine alga Dunaliella tertiolecta. Siltech acute toxicity values ranged from 1.1 to 32.8 ppm. ThickSlick acute toxicity values ranged from 2.2 to 126.4 ppm. The results of present study show greater toxicity of Siltech compared to ThickSlick with estimated acute hazard concentrations intended to provide 95% species protection of 1.1 and 3.6 ppm, respectively, on empirical data and 0.64 and 3.3 ppm, respectively, with the addition of interspecies correlation data. The present study provides a greater understanding of species sensitivity of these two oil spill response agents. Environ Toxicol Chem 2022;41:1311-1318. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Daphnia magna and Ceriodaphnia dubia Have Similar Sensitivity in Standard Acute and Chronic Toxicity Tests.

The cladocerans Daphnia magna and Ceriodaphnia dubia have been used for decades to assess the hazards of chemicals and effluents, but toxicity data for these species have traditionally been treated separately. Numerous standard acute and chronic test guidelines have been developed for both species. In the present study, data were compiled and curated for acute survival (48 h) and growth and reproduction tests with D. magna (21 days chronic) and C. dubia (7 days chronic) toxicity assays. Orthogonal regressions were developed to statistically compare the acute and chronic sensitivity of D. magna and C. dubia across a diversity of chemicals and modes of action. Acute orthogonal regressions between D. magna and D. pulex, a widely accepted surrogate species, were used to set a data-driven benchmark for what would constitute a suitable D. magna surrogate. The results indicate that there is insufficient evidence to suggest a difference in acute or chronic sensitivity of D. magna and C. dubia in standard toxicity tests. Further, the variability in the acute D. magna and C. dubia regressions were of the same magnitude as that in D. magna and D. pulex regressions. Slope and y-intercept values were also comparable. The absence of significant differences in toxicity values suggests similar species sensitivity in standard tests across a range of chemical classes and modes of action. Environ Toxicol Chem 2022;41:134-147. © 2021 SETAC.

Potential for Interspecies Toxicity Estimation in Soil Invertebrates.

Interspecies correlation estimation (ICE) models are linear regressions that predict toxicity to a species with few data using a known toxicity value in a surrogate species. ICE models are well established for estimating toxicity to fish and aquatic invertebrates but have not been generally developed or applied to soil organisms. To facilitate the development of ICE models for soil invertebrates, a database of single chemical toxicity values was compiled from knowledgebases and reports that included 853 records encompassing 192 chemicals and 12 species. Most toxicity data for single chemicals tested in soil media were for species of earthworms, with only limited data for other species and taxa. ICE models were developed for eleven separate species pairs as least squares log-linear regressions of acute toxicity values of the same chemicals tested in both the surrogate and predicted species of soil organisms. Model uncertainty was assessed using leave one out cross-validation as the fold difference between a predicted and measured toxicity value. ICE models showed high accuracy within order (e.g., earthworm to earthworm), but less prediction accuracy in the two across-taxa models (Arthropoda to Annelida and the inverse). This study provides a proof-of-concept demonstration that ICE models can be developed for soil invertebrates.

Causal Bayesian networks in assessments of wildfire risks: Opportunities for ecological risk assessment and management.

Wildfire risks and losses have increased over the last 100 years, associated with population expansion, land use and management practices, and global climate change. While there have been extensive efforts at modeling the probability and severity of wildfires, there have been fewer efforts to examine causal linkages from wildfires to impacts on ecological receptors and critical habitats. Bayesian networks are probabilistic tools for graphing and evaluating causal knowledge and uncertainties in complex systems that have seen only limited application to the quantitative assessment of ecological risks and impacts of wildfires. Here, we explore opportunities for using Bayesian networks for assessing wildfire impacts to ecological systems through levels of causal representation and scenario examination. Ultimately, Bayesian networks may facilitate understanding the factors contributing to ecological impacts, and the prediction and assessment of wildfire risks to ecosystems. Integr Environ Assess Manag 2021;17:1168-1178. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Ecological Thresholds of Toxicological Concern: A Review.

The ecological threshold of toxicological concern (ecoTTC) is analogous to traditional human health-based TTCs but with derivation and application to ecological species. An ecoTTC is computed from the probability distribution of predicted no effect concentrations (PNECs) derived from either chronic or extrapolated acute toxicity data for toxicologically or chemically similar groups of chemicals. There has been increasing interest in using ecoTTCs in screening level environmental risk assessments and a computational platform has been developed for derivation with aquatic species toxicity data (https://envirotoxdatabase.org/). Current research and development areas include assessing mode of action-based chemical groupings, conservatism in estimated PNECs and ecoTTCs compared to existing regulatory values, and the influence of taxa (e.g., algae, invertebrates, and fish) composition in the distribution of PNEC values. The ecoTTC continues to develop as a valuable alternative strategy within the toolbox of traditional and new approach methods for ecological chemical assessment. This brief review article describes the ecoTTC concept and potential applications in ecological risk assessment, provides an overview of the ecoTTC workflow and how the values can be derived, and highlights recent developments and ongoing research. Future applications of ecoTTC concept in different disciplines are discussed along with opportunities for its use.

Derivation of algal acute to chronic ratios for use in chemical toxicity extrapolations.

Algal toxicity studies are required by regulatory agencies for a variety of purposes including classification and labeling and environmental risk assessment of chemicals. Algae are also frequently the most sensitive taxonomic group tested. Acute to chronic ratios (ACRs) have been challenging to derive for algal species because of the complexities of the underlying experimental data including: a lack of universally agreed upon algal inhibition endpoints; evolution of experimental designs over time and by different standardization authorities; and differing statistical approaches (e.g., regression versus hypothesis-based effect concentrations). Experimental data for developing globally accepted algal ACRs have been limited because of data availability, and in most regulatory frameworks an ACR of 10 is used regardless of species, chemical type or mode of action. Acute and chronic toxicity (inhibition) data on 17 algal species and 442 chemicals were compiled from the EnviroTox database (https://envirotoxdatabase.org/) and a proprietary database of algal toxicity records. Information was probed for growth rate, yield, and final cell density endpoints focusing primarily on studies of 72 and 96 h duration. Comparisons of acute and chronic data based on either single (e.g., growth rate) and multiple (e.g., growth rate, final cell density) endpoints were used to assess acute and chronic relationships. Linear regressions of various model permutations were used to compute ACRs for multiple combinations of taxa, chemicals, and endpoints, and showed that ACRs for algae were consistently around 4 (ranging from 2.43 to 5.62). An ACR of 4 for algal toxicity is proposed as an alternative to a default value of 10, and recommendations for consideration and additional research and development are provided.

A Bayesian network approach to refining ecological risk assessments: Mercury and the Florida panther (Puma concolor coryi).

Traditionally hazard quotients (HQs) have been computed for ecological risk assessment, often without quantifying the underlying uncertainties in the risk estimate. We demonstrate a Bayesian network approach to quantitatively assess uncertainties in HQs using a retrospective case study of dietary mercury (Hg) risks to Florida panthers (Puma concolor coryi). The Bayesian network was parameterized, using exposure data from a previous Monte Carlo-based assessment of Hg risks (Barron et al., 2004. ECOTOX 13:223), as a representative example of the uncertainty and complexity in HQ calculations. Mercury HQs and risks to Florida panthers determined from a Bayesian network analysis were nearly identical to those determined using the prior Monte Carlo probabilistic assessment and demonstrated the ability of the Bayesian network to replicate conventional HQ-based approaches. Sensitivity analysis of the Bayesian network showed greatest influence on risk estimates from daily ingested dose by panthers and mercury levels in prey, and less influence from toxicity reference values. Diagnostic inference was used in a high-risk scenario to demonstrate the capabilities of Bayesian networks for examining probable causes for observed effects. Application of Bayesian networks in the computation of HQs provides a transparent and quantitative analysis of uncertainty in risks.

Long-Term Ecological Impacts from Oil Spills: Comparison of Exxon Valdez, Hebei Spirit, and Deepwater Horizon.

The long-term ecological impacts of the Exxon Valdez oil spill (EVOS) are compared to two extensively studied and more recent large spills: Deepwater Horizon (DWH) and the Hebei Spirit oil spill (HSOS). Each of the three spills differed in magnitude and duration of oil released, environmental conditions, ecological communities, response and clean up measures, and ecological recovery. The EVOS began on March 24, 1989, and released 40.8 million liters of Alaska North Slope crude oil into the cold, nearly pristine environment of Prince William Sound, Alaska. EVOS oiled wildlife and rocky intertidal shorelines and exposed early life stages of fish to embryotoxic levels of polycyclic aromatic hydrocarbons (PAH). Long-term impacts following EVOS were observed on seabirds, sea otters, killer whales, and subtidal communities. The DWH spill began on April 20, 2010, and released 507 million liters of light Louisiana crude oil from 1600 m on the ocean floor into the Gulf of Mexico over an 87-day period. The DWH spill exposed a diversity of complex aquatic communities in the deep ocean, offshore pelagic areas, and coastal environments to petroleum hydrocarbons. Large-scale persistent ecological effects included impacts to deep ocean corals, failed recruitment of oysters over multiple years, damage to coastal wetlands, and reduced dolphin, sea turtle, and seabird populations. The HSOS began on December 7, 2007, and released approximately 13 million liters of Middle East crude oils into ecologically sensitive areas of the Taean area of western Korea. Environmental conditions and the extensive initial cleanup of HSOS oil stranded on shorelines limited the long-term impacts to changes in composition and abundance of intertidal benthic communities. Comparisons of EVOS, DWH, and HSOS show the importance and complexity of the interactions among the environment, oil spill dynamics, affected ecological systems, and response actions.

Toxicity of oil spill response agents and crude oils to five aquatic test species.

The majority of aquatic toxicity data for petroleum products has been limited to a few intensively studied crude oils and Corexit chemical dispersants, and acute toxicity testing in two standard estuarine test species: mysids (Americamysis bahia) and inland silversides (Menidia beryllina). This study compared the toxicity of two chemical dispersants commonly stock piled for spill response (Corexit EC9500A®, Finasol®OSR 52), three less studied agents (Accell Clean®DWD dispersant; CytoSol® surface washing agent; Gelco200® solidifier), and three crude oils differing in hydrocarbon composition (Dorado, Endicott, Alaska North Slope). Consistent with listings on the U.S. National Contingency Plan Product Schedule, general rank order toxicity was greatest for dispersants and lowest for the solidifier. The results indicate that freshwater species can have similar sensitivity as the conventionally tested mysids and silversides, and that the sea urchin (Arbacia punctulata) appears to be a reasonable addition to increase taxa diversity in standardized oil agent testing.

Mode of Action Classifications in the EnviroTox Database: Development and Implementation of a Consensus MOA Classification.

Multiple mode of action (MOA) frameworks have been developed in aquatic ecotoxicology, mainly based on fish toxicity. These frameworks provide information on a key determinant of chemical toxicity, but the MOA categories and level of specificity remain unique to each of the classification schemes. The present study aimed to develop a consensus MOA assignment within EnviroTox, a curated in vivo aquatic toxicity database, based on the following MOA classification schemes: Verhaar (modified) framework, Assessment Tool for Evaluating Risk, Toxicity Estimation Software Tool, and OASIS. The MOA classifications from each scheme were first collapsed into one of 3 categories: non-specifically acting (i.e., narcosis), specifically acting, or nonclassifiable. Consensus rules were developed based on the degree of concordance among the 4 individual MOA classifications to attribute a consensus MOA to each chemical. A confidence rank was also assigned to the consensus MOA classification based on the degree of consensus. Overall, 40% of the chemicals were classified as narcotics, 17% as specifically acting, and 43% as unclassified. Sixty percent of chemicals had a medium to high consensus MOA assignment. When compared to empirical acute toxicity data, the general trend of specifically acting chemicals being more toxic is clearly observed for both fish and invertebrates but not for algae. EnviroTox is the first approach to establishing a high-level consensus across 4 computationally and structurally distinct MOA classification schemes. This consensus MOA classification provides both a transparent understanding of the variation between MOA classification schemes and an added certainty of the MOA assignment. In terms of regulatory relevance, a reliable understanding of MOA can provide information that can be useful for the prioritization (ranking) and risk assessment of chemicals. Environ Toxicol Chem 2019;38:2294-2304. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Creation of a Curated Aquatic Toxicology Database: EnviroTox.

Flexible, rapid, and predictive approaches that do not require the use of large numbers of vertebrate test animals are needed because the chemical universe remains largely untested for potential hazards. Development of robust new approach methodologies and nontesting approaches requires the use of existing information via curated, integrated data sets. The ecological threshold of toxicological concern (ecoTTC) represents one such new approach methodology that can predict a conservative de minimis toxicity value for chemicals with little or no information available. For the creation of an ecoTTC tool, a large, diverse environmental data set was developed from multiple sources, with harmonization, characterization, and information quality assessment steps to ensure that the information could be effectively organized and mined. The resulting EnviroTox database contains 91 217 aquatic toxicity records representing 1563 species and 4016 unique Chemical Abstracts Service numbers and is a robust, curated database containing high-quality aquatic toxicity studies that are traceable to the original information source. Chemical-specific information is also linked to each record and includes physico-chemical information, chemical descriptors, and mode of action classifications. Toxicity data are associated with the physico-chemical data, mode of action classifications, and curated taxonomic information for the organisms tested. The EnviroTox platform also includes 3 analysis tools: a predicted-no-effect concentration calculator, an ecoTTC distribution tool, and a chemical toxicity distribution tool. Although the EnviroTox database and tools were originally developed to support ecoTTC analysis and development, they have broader applicability to the field of ecological risk assessment. Environ Toxicol Chem 2019;9999:1-12. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

In Silico Site-Directed Mutagenesis Informs Species-Specific Predictions of Chemical Susceptibility Derived From the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) Tool.

Chemical hazard assessment requires extrapolation of information from model organisms to all species of concern. The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed as a rapid, cost-effective method to aid cross-species extrapolation of susceptibility to chemicals acting on specific protein targets through evaluation of protein structural similarities and differences. The greatest resolution for extrapolation of chemical susceptibility across species involves comparisons of individual amino acid residues at key positions involved in protein-chemical interactions. However, a lack of understanding of whether specific amino acid substitutions among species at key positions in proteins affect interaction with chemicals made manual interpretation of alignments time consuming and potentially inconsistent. Therefore, this study used in silico site-directed mutagenesis coupled with docking simulations of computational models for acetylcholinesterase (AChE) and ecdysone receptor (EcR) to investigate how specific amino acid substitutions impact protein-chemical interaction. This study found that computationally derived substitutions in identities of key amino acids caused no change in protein-chemical interaction if residues share the same side chain functional properties and have comparable molecular dimensions, while differences in these characteristics can change protein-chemical interaction. These findings were considered in the development of capabilities for automatically generated species-specific predictions of chemical susceptibility in SeqAPASS. These predictions for AChE and EcR were shown to agree with SeqAPASS predictions comparing the primary sequence and functional domain sequence of proteins for more than 90% of the investigated species, but also identified dramatic species-specific differences in chemical susceptibility that align with results from standard toxicity tests. These results provide a compelling line of evidence for use of SeqAPASS in deriving screening level, species-specific, susceptibility predictions across broad taxonomic groups for application to human and ecological hazard assessment.

Calcification in Caribbean reef-building corals at high pCO2 levels in a recirculating ocean acidification exposure system.

Projected increases in ocean pCO2 levels are anticipated to affect calcifying organisms more rapidly and to a greater extent than other marine organisms. The effects of ocean acidification (OA) have been documented in numerous species of corals in laboratory studies, largely tested using flow-through exposure systems. We developed a recirculating ocean acidification exposure system that allows precise pCO2 control using a combination of off-gassing measures including aeration, water retention devices, venturi injectors, and CO2 scrubbing. We evaluated the recirculating system performance in off-gassing effectiveness and maintenance of target pCO2 levels over an 84-day experiment. The system was used to identify changes in calcification and tissue growth in response to elevated pCO2 (1000 µatm) in three reef-building corals of the Caribbean: Pseudodiploria clivosa, Montastraea cavernosa, and Orbicella faveolata. All three species displayed an overall increase in net calcification over the 84-day exposure period regardless of pCO2 level (control +0.28- 1.12 g, elevated pCO2 +0.18- 1.16 g), and the system was effective at both off-gassing acidified water to ambient pCO2 levels, and maintaining target elevated pCO2 levels over the 3-month experiment.

Mixed phylogenetic signal in fish toxicity data across chemical classes.

Chemical use in society is growing rapidly and is one of the five major pressures on biodiversity worldwide. Since empirical toxicity studies of pollutants generally focus on a handful of model organisms, reliable approaches are needed to assess sensitivity to chemicals across the wide variety of species in the environment. Phylogenetic comparative methods (PCM) offer a promising approach for toxicity extrapolation incorporating known evolutionary relationships among species. If phylogenetic signal in toxicity data is high, i.e., closely related species are more similarly sensitive as compared to distantly related species, PCM could ultimately help predict species sensitivity when toxicity data are lacking. Here, we present the largest ever test of phylogenetic signal in toxicity data by combining phylogenetic data from fish with acute mortality data for 42 chemicals spanning 10 different chemical classes. Phylogenetic signal is high for some chemicals, particularly organophosphate pesticides, but not necessarily for many chemicals in other classes (e.g., metals, organochlorines). These results demonstrate that PCM may be useful for toxicity extrapolation in untested species for those chemicals with clear phylogenetic signal. This study provides a framework for using PCM to understand the patterns and causes of variation in species sensitivity to pollutants.