A field-based model of the relationship between extirpation of salt-intolerant benthic invertebrates and background conductivity

Using Single-Species and Whole Community Stream Mesocosm Exposures for Identifying Major Ion Effects in Doses Mimicking Resource Extraction Wastewaters

Wastewaters and leachates from various inland resource extraction activities contain high ionic concentrations and differ in ionic composition, which complicates the understanding and effective management of their relative risks to stream ecosystems. To this end, we conducted a stream mesocosm dose-response experiment using two dosing recipes prepared from industrial salts. One recipe was designed to generally reflect the major ion composition of deep well brines (DWB) produced from gas wells (primarily Na+, Ca2+, and Cl-) and the other, the major ion composition of mountaintop mining (MTM) leachates from coal extraction operations (using salts dissociating to Ca2+, Mg2+, Na+, SO42- and HCO3-)-both sources being extensive in the Central Appalachians of the USA. The recipes were dosed at environmentally relevant nominal concentrations of total dissolved solids (TDS) spanning 100 to 2000 mg/L for 43 d under continuous flow-through conditions. The colonizing native algal periphyton and benthic invertebrates comprising the mesocosm ecology were assessed with response sensitivity distributions (RSDs) and hazard concentrations (HCs) at the taxa, community (as assemblages), and system (as primary and secondary production) levels. Single-species toxicity tests were run with the same recipes. Dosing the MTM recipe resulted in a significant loss of secondary production and invertebrate taxa assemblages that diverged from the control at all concentrations tested. Comparatively, intermediate doses of the DWB recipe had little consequence or increased secondary production (for emergence only) and had assemblages less different from the control. Only the highest dose of the DWB recipe had a negative impact on certain ecologies. The MTM recipe appeared more toxic, but overall, for both types of resource extraction wastewaters, the mesocosm responses suggested significant changes in stream ecology would not be expected for specific conductivity below 300 µS/cm, a published aquatic life benchmark suggested for the region.

A review of regulatory modeling frameworks supporting numeric water quality criteria development in the United States

The US Environmental Protection Agency (USEPA) has a long history of leveraging environmental models and integrated modeling frameworks to support the regulatory development of numeric ambient water quality criteria for the protection of aquatic life and human health. Primary modeling types include conceptual, mechanistic, and data-driven empirical models; Bayesian and probabilistic models; and risk-based modeling frameworks. These models and modeling frameworks differ in their applicability to and suitability for various water quality criteria objectives. They require varying knowledge of system processes and stressor-response relationships, data availability, and expertise of stakeholders. In addition, models can be distinguished by their ability to characterize variability and uncertainty. In this work, we review USEPA recommendations for model use in existing regulatory frameworks, technical support documents, and peer-reviewed literature. We characterize key attributes, identify knowledge gaps and opportunities for future research, and highlight where renewed USEPA guidance is needed to promote the development and use of models in numeric criteria derivation. These outcomes then inform a decision-based framework for determining model suitability under particular scenarios of available knowledge, data, and access to technical resources. Integr Environ Assess Manag 2023;19:191-201. © 2022 SETAC.

Laboratory evaluation of open source and commercial electrical conductivity sensor precision and accuracy: How do they compare?

Variation in the electrical conductivity (EC) of water can reveal environmental disturbance and natural dynamics, including factors such as anthropogenic salinization. Broader application of open source (OS) EC sensors could provide an inexpensive method to measure water quality. While studies show that other water quality parameters can be robustly measured with sensors, a similar effort is needed to evaluate the performance of OS EC sensors. To address this need, we evaluated the accuracy (mean error, %) and precision (sample standard deviation) of OS EC sensors in the laboratory via comparison to EC calibration standards using three different OS and OS/commercial-hybrid (OS/C) EC sensors and data logger configurations and two commercial (C) EC sensors and data logger configurations. We also evaluated the effect of cable length (7.5 m and 30 m) and sensor calibration on OS sensor accuracy and precision. We found a significant difference between OS sensor mean accuracy (3.08%) and all other sensors combined (9.23%). Our study also found that EC sensor precision decreased across all sensor configurations with increasing calibration standard EC. There was also a significant difference between OS sensor mean precision (2.85 μS/cm) and the mean precision of all other sensors combined (9.12 μS/cm). Cable length did not affect OS sensor precision. Furthermore, our results suggest that future research should include evaluating how performance is impacted by combining OS sensors with commercial data loggers as this study found significantly decreased performance in OS/commercial-hybrid sensor configurations. To increase confidence in the reliability of OS sensor data, more studies such as ours are needed to further quantify OS sensor performance in terms of accuracy and precision across different settings and OS sensor and data collection platform configurations.

Acute Toxicity of Major Geochemical Ions to Fathead Minnows (Pimephales promelas): Part B-Modeling Ion Toxicity

Mathematical models are presented for the acute median lethal concentrations of major geochemical ions (Na+ , K+ , Ca2+ , Mg2+ , Cl- , SO4 2- , HCO3 - /CO3 2- ) to fathead minnows (Pimephales promelas), based on an extensive series of experiments presented in a companion article. Toxicity relationships across different dilution waters, individual salts, and salt mixtures suggest six independent mechanisms of toxicity to consider in modeling efforts, including Mg/Ca-specific toxicity, osmolarity-related toxicity, SO4 -specific toxicity, K-specific toxicity, effects of high pH/alkalinity, and a multiple ion-related toxicity at low Ca distinct from the other mechanisms. Models are evaluated using chemical activity-based exposure metrics pertinent to each mechanism, but concentration-based alternative models that are simpler to apply are also addressed. These models are compared to those previously provided for Ceriodaphnia dubia, and various issues regarding their application to risk assessments are discussed. Environ Toxicol Chem 2022;41:2095-2106. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Lakes at Risk of Chloride Contamination

Lakes in the Midwest and Northeast United States are at risk of anthropogenic chloride contamination, but there is little knowledge of the prevalence and spatial distribution of freshwater salinization. Here, we use a quantile regression forest (QRF) to leverage information from 2773 lakes to predict the chloride concentration of all 49 432 lakes greater than 4 ha in a 17-state area. The QRF incorporated 22 predictor variables, which included lake morphometry characteristics, watershed land use, and distance to the nearest road and interstate. Model predictions had an r² of 0.94 for all chloride observations, and an r² of 0.86 for predictions of the median chloride concentration observed at each lake. The four predictors with the largest influence on lake chloride concentrations were low and medium intensity development in the watershed, crop density in the watershed, and distance to the nearest interstate. Almost 2000 lakes are predicted to have chloride concentrations above 50 mg L^-1 and should be monitored. We encourage management and governing agencies to use lake-specific model predictions to assess salt contamination risk as well as to augment their monitoring strategies to more comprehensively protect freshwater ecosystems from salinization.

High-Frequency Data Reveal Deicing Salts Drive Elevated Specific Conductance and Chloride along with Pervasive and Frequent Exceedances of the U.S. Environmental Protection Agency Aquatic Life Criteria for Chloride in Urban Streams

Increasing specific conductance (SC) and chloride concentrations [Cl] negatively affect many stream ecosystems. We characterized spatial variability in SC, [Cl], and exceedances of Environmental Protection Agency [Cl] criteria using nearly 30 million high-frequency observations (2-15 min intervals) for SC and modeled [Cl] from 93 sites across three regions in the eastern United States: Southeast, Mid-Atlantic, and New England. SC and [Cl] increase substantially from south to north and within regions with impervious surface cover (ISC). In the Southeast, [Cl] weakly correlates with ISC, no [Cl] exceedances occur, and [Cl] concentrations are constant with time. In the Mid-Atlantic and New England, [Cl] and [Cl] exceedances strongly correlate with ISC. [Cl] criteria are frequently exceeded at sites with greater than 9-10% ISC and median [Cl] higher than 30-80 mg/L. Tens to hundreds of [Cl] exceedances observed annually at most of these sites help explain previous research where stream ecosystems showed changes at (primarily nonwinter) [Cl] as low as 30-40 mg/L. Mid-Atlantic chronic [Cl] exceedances occur primarily in December-March. In New England, exceedances are common in nonwinter months. [Cl] is increasing at nearly all Mid-Atlantic and New England sites with the largest increases at sites with higher [Cl].

Geographical origin determines responses to salinity of Mediterranean caddisflies

Many freshwater ecosystems worldwide, and particularly Mediterranean ones, show increasing levels of salinity. These changes in water conditions could affect abundance and distribution of inhabiting species as well as the provision of ecosystem services. In this study we conduct laboratory experiments using the macroinvertebrate Smicridea annulicornis as a model organism. Our factorial experiments were designed to evaluate the effects of geographical origin of organisms and salinity levels on survival and behavioral responses of caddisflies. The experimental organisms were captured from rivers belonging to three hydrological basins along a 450 Km latitudinal gradient in the Mediterranean region of Chile. Animals were exposed to three conductivity levels, from 180 to 1400 μS/cm, close to the historical averages of the source rivers. We measured the behavioral responses to experimental stimuli and the survival time. Our results showed that geographical origin shaped the behavioral and survival responses to salinity. In particular, survival and activity decreased more strongly with increasing salinity in organisms coming from more dilute waters. This suggests local adaptation to be determinant for salinity responses in this benthic invertebrate species. In the current scenario of fast temporal and spatial changes in water levels and salt concentration, the conservation of geographic intra-specific variation of aquatic species is crucial for lowering the risk of salinity-driven biodiversity loss.

Modeling Spatial and Temporal Variation in Natural Background Specific Conductivity

Understanding how background levels of dissolved minerals vary in streams temporally and spatially is needed to assess salinization of fresh water, establish reasonable thresholds and restoration goals, and determine vulnerability to extreme climate events like drought. We developed a random forest model that predicts natural background specific conductivity (SC), a measure of total dissolved ions, for all stream segments in the contiguous United States at monthly time steps between the years 2001 to 2015. Models were trained using 11 796 observations made at 1785 minimally impaired stream segments and validated with observations from an additional 92 segments. Static predictors of SC included geology, soils, and vegetation parameters. Temporal predictors were related to climate and enabled the model to make predictions for different dates. The model explained 95% of the variation in SC among validation observations (mean absolute error = 29 μS/cm, Nash-Sutcliffe efficiency = 0.85). The model performed well across the period of interest but exhibited bias in Coastal Plain and Xeric regions (26 and 30%, respectively). National model predictions showed large spatial variation with the greatest SC predicted to occur in the desert southwest and plains. Model predictions also reflected changes at individual streams during drought.

Predicting combined effects of land use and climate change on river and stream salinity

Agricultural, industrial and urban development have all contributed to increased salinity in streams and rivers, but the likely effects of future development and climate change are unknown. I developed two empirical models to estimate how these combined effects might affect salinity by the end of this century (measured as electrical conductivity, EC). The first model predicts natural background from static (e.g. geology and soils) and dynamic (i.e. climate and vegetation) environmental factors and explained 78% of the variation in EC. I then compared the estimated background EC with current measurements at 2001 sites chosen probabilistically from all conterminous USA streams. EC was more than 50% greater at 34% of these sites. The second model predicts deviation of EC from background as a function of human land use and environmental factors and explained 60% of the variation in alteration from background. I then predicted the effects of climate and land use change on EC at the end of the century by replacing dynamic variables with published projections of future conditions based on the A2 emissions scenario. By the end of the century, the median EC is predicted to increase from 0.319 mS cm^-1 to 0.524 mS cm^-1 with over 50% of streams having greater than 50% increases in EC and 35% more than doubling their EC. Most of the change is related to increases in human land use, with climate change accounting for only 12% of the increase. In extreme cases, increased salinity may make water unsuitable for human use, but widespread moderate increases are likely a greater threat to stream ecosystems owing to the elimination of low EC habitats.This article is part of the theme issue 'Salt in freshwaters: causes, ecological consequences and future prospects'.

Regulations are needed to protect freshwater ecosystems from salinization

Anthropogenic activities such as mining, agriculture and industrial wastes have increased the rate of salinization of freshwater ecosystems around the world. Despite the known and probable consequences of freshwater salinization, few consequential regulatory standards and management procedures exist. Current regulations are generally inadequate because they are regionally inconsistent, lack legal consequences and have few ion-specific standards. The lack of ion-specific standards is problematic, because each anthropogenic source of freshwater salinization is associated with a distinct set of ions that can present unique social and economic costs. Additionally, the environmental and toxicological consequences of freshwater salinization are often dependent on the occurrence, concentration and ratios of specific ions. Therefore, to protect fresh waters from continued salinization, discrete, ion-specific management and regulatory strategies should be considered for each source of freshwater salinization, using data from standardized, ion-specific monitoring practices. To develop comprehensive monitoring, regulatory, and management guidelines, we recommend the use of co-adaptive, multi-stakeholder approaches that balance environmental, social, and economic costs and benefits associated with freshwater salinization.This article is part of the theme issue 'Salt in freshwaters: causes, ecological consequences and future prospects'.

A field-based characterization of conductivity in areas of minimal alteration: A case example in the Cascades of northwestern United States

The concentration of salts in streams is increasing world-wide making freshwater a declining resource. Developing thresholds for freshwater with low specific conductivity (SC), a measure of dissolved ions in water, may protect high quality resources that are refugia for aquatic life and that dilute downstream waters. In this case example, methods are illustrated for estimating protective levels for streams with low SC. The Cascades in the Pacific Northwest of the United States of America was selected for the case study because a geophysical model indicated that the SC of freshwater streams was likely to be very low. Also, there was an insufficient range in the SC data to accurately derive a criterion using the 2011, US Environmental Protection Agency field-based extirpation concentration distribution method. Instead, background and a regression model was used to estimate chronic and acute SC levels that could extirpate 5% of benthic invertebrate genera. Background SC was estimated at the 25th centile (33μS/cm) of the measured data and used as the independent variable in a least squares empirical background-to-criteria (B-C) model. Because no comparison could be made with effect levels estimated from a paired SC and biological data set from the Cascades, the lower 50% prediction limit (PL) was identified as an example chronic water quality criterion (97μS/cm). The maximum exposure threshold was estimated at the 90th centile SC of streams meeting the chronic SC level. The example acute SC level was 190μS/cm. Because paired aquatic life and SC data are often sparse, the B-C method is useful for developing SC criteria for other systems with limited data.

Field-based method for evaluating the annual maximum specific conductivity tolerated by freshwater invertebrates

Most water quality criteria are based on laboratory toxicity tests and usually include chronic and acute magnitudes. Field-based criteria are typically based on long-term or continuous exposures, so they are chronic. Biological responses of quantified, short-term aqueous exposures are seldom documented in the field. However, acute values may be derived by estimating an upper limit using temporal variance and chronic values. This method estimates an upper limit from the variance of pollutant measurements from stream locations that attain the chronic criterion. The formula for deriving a 90th centile of a standard normal distribution is used to identify the upper limit, a criterion maximum exposure concentration (CMEC). The calculated CMEC is interpreted as a maximum exposure that 95% of organisms may tolerate if the chronic exposure is not exceeded. The methods of deriving chronic and acute criteria are illustrated with specific conductivity in a mountainous area in the eastern United States. The biological relevance of the CMEC was assessed using the maximum annual exposure during the life cycle of the most salt-intolerant genera. The method using the chronic criterion and the variance of water chemistry data is practical, whereas frequently collecting and analyzing paired biological and chemical samples at numerous sites is impractical and may give misleading results due to lags in biological response. This method can be used anywhere with sufficient data to estimate the temporal variability and may be applicable for field-based criteria other than the specific conductivity criteria illustrated here.

A field-based characterization of conductivity in areas of minimal alteration: A case example in the Cascades of northwestern United States

The concentration of salts in streams is increasing world-wide making freshwater a declining resource. Developing thresholds for freshwater with low specific conductivity (SC), a measure of dissolved ions in water, may protect high quality resources that are refugia for aquatic life and that dilute downstream waters. In this case example, methods are illustrated for estimating protective levels for streams with low SC. The Cascades in the Pacific Northwest of the United States of America was selected for the case study because a geophysical model indicated that the SC of freshwater streams was likely to be very low. Also, there was an insufficient range in the SC data to accurately derive a criterion using the 2011, US Environmental Protection Agency field-based extirpation concentration distribution method. Instead, background and a regression model was used to estimate chronic and acute SC levels that could extirpate 5% of benthic invertebrate genera. Background SC was estimated at the 25th centile (33μS/cm) of the measured data and used as the independent variable in a least squares empirical background-to-criteria (B-C) model. Because no comparison could be made with effect levels estimated from a paired SC and biological data set from the Cascades, the lower 50% prediction limit (PL) was identified as an example chronic water quality criterion (97μS/cm). The maximum exposure threshold was estimated at the 90th centile SC of streams meeting the chronic SC level. The example acute SC level was 190μS/cm. Because paired aquatic life and SC data are often sparse, the B-C method is useful for developing SC criteria for other systems with limited data.

Field-based method for evaluating the annual maximum specific conductivity tolerated by freshwater invertebrates

Most water quality criteria are based on laboratory toxicity tests and usually include chronic and acute magnitudes. Field-based criteria are typically based on long-term or continuous exposures, so they are chronic. Biological responses of quantified, short-term aqueous exposures are seldom documented in the field. However, acute values may be derived by estimating an upper limit using temporal variance and chronic values. This method estimates an upper limit from the variance of pollutant measurements from stream locations that attain the chronic criterion. The formula for deriving a 90th centile of a standard normal distribution is used to identify the upper limit, a criterion maximum exposure concentration (CMEC). The calculated CMEC is interpreted as a maximum exposure that 95% of organisms may tolerate if the chronic exposure is not exceeded. The methods of deriving chronic and acute criteria are illustrated with specific conductivity in a mountainous area in the eastern United States. The biological relevance of the CMEC was assessed using the maximum annual exposure during the life cycle of the most salt-intolerant genera. The method using the chronic criterion and the variance of water chemistry data is practical, whereas frequently collecting and analyzing paired biological and chemical samples at numerous sites is impractical and may give misleading results due to lags in biological response. This method can be used anywhere with sufficient data to estimate the temporal variability and may be applicable for field-based criteria other than the specific conductivity criteria illustrated here.

A flow-chart for developing water quality criteria from two field-based methods

Field-based methods increase relevance and realism when setting water quality criteria. They also pose challenges. To enable a consistent process, a flow chart was developed for choosing between two field-based methods and then selecting among candidate results. The two field-based methods estimated specific conductivity (SC) levels likely to extirpate 5% of benthic invertebrate genera: an extirpation concentration distribution (XCD) method and a background-to-criterion (B-C) model developed by the U.S. Environmental Protection Agency. The B-C model is a least squares regression of the 5th centile of XCD (XCD₀₅) values against estimates of background SC. Selection of an XCD₀₅ from the flowchart is determined by characteristics of the paired chemical and biological data sets and method for estimating the XCD₀₅ values. Confidence in these example SC XCD₀₅ values is based on the size of the data sets and ecoregional SC disturbance. The level of ecoregional SC disturbance was judged by comparing the background SC (the 25th centile of the data set used to calculate a XCD₀₅) and an estimate of natural base-flow SC modeled from geophysical attributes in the region. The B-C approach appears to be a viable option for estimating a SC benchmark with inexpensive estimates of SC background while the XCD method is used when the data are abundant. To illustrate the use of the flow chart, example SC XCD₀₅ values were calculated for 63 of 86 Level III ecoregions in the conterminous United States of America.

Assessing background levels of specific conductivity using weight of evidence

There are many ways to estimate background levels, and many types of evidence may contribute to determining whether a water, air, or soil is at background. As a result, it is important to define background in each case and to weigh the available evidence to determine the best estimate of background. A weight-of-evidence approach is demonstrated that assesses whether the background SC is sufficiently similar in streams of Ecoregion 70 in West Virginia and Ohio. During planning, five relevant considerations were identified to assess background SC: physical properties, measured SC, spatial distribution of low SC sites, biological properties, and data relevance and reliability. For each consideration, diverse types of evidence were generated, evaluated, and synthesized using weight of evidence. In the example, evidence was weighed for the hypothesis that background SC is similar in two areas in Ecoregion 70, the Western Allegheny Plateau in the eastern United States. Where, as in this case, background is not well characterized by measurements, because data sets are small or sampling designs or anthropogenic inputs may influence estimates of background, it is suggested that information about regional properties, related to and affected by SC, may be used to determine whether SC in the less characterized area is sufficiently similar to a well characterized area.