Efforts to standardize wildlife toxicity values remain unrealized

Mayfield, David; Fairbrother, Anne

doi:10.1002/ieam.1357

Cited by 17 publications

(16 citation statements)

References 35 publications

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“…As noted by previous authors, NOAELs/ LOAELs have shortcomings because of limitations in study design or sample size and lack of attention to the full doseresponse curve or treatment group variability. Furthermore, in certain circumstances, the use of NOAELs/LOAELs may lead to inconsistent, problematic, or inappropriate TRVs to characterize risks (Allard et al 2010;Mayfield and Fairbrother 2013;Mayfield et al 2014;Sample et al 2014aSample et al , 2014b. Thus, performing dose-response analyses, when data are sufficient, is frequently recommended to reduce uncertainty in detailed (postscreening) risk assessments (US Environmental Protection Agency 1997, 1998Allard et al 2010;Landis and Chapman 2011;Mayfield et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Benchmark dose analysis framework for developing wildlife toxicity reference values

Mayfield

Skall

2018

Enviro Toxic and Chemistry

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The effects characterization phase of ecological risk assessments (ERAs) often includes the selection or development of toxicity reference values (TRVs) for chemicals under investigation. In wildlife risk assessments, TRVs are thresholds represented by a dose or concentration associated with a specified adverse response. Traditionally, a TRV may be derived from an estimate of the no-observed-adverse effect level or lowest-observed-adverse-effect level, identified from a controlled toxicity study. Because of the limitations of this approach, risk assessors are increasingly developing TRVs using alternative methods. Benchmark dose (BMD) analysis is widely recognized as one approach for developing TRVs. A BMD is derived using the full dose-response relationship from all experimental doses and may represent a user-specified response level (e.g., 5, 10, 20, or 50%). Although many regulatory programs consider the use of BMD-derived wildlife TRVs, there is limited guidance available for implementing the BMD approach, particularly for ERA. The present study provides a framework for ecological risk assessors to identify appropriate data, examine dose-response relationships, estimate BMDs, and document the results for use in risk analysis. This framework demonstrates the process of developing a TRV using BMD analysis and identifies applications for which this approach may enhance ERAs (e.g., site assessment, chemical or pesticide registration programs). Environ Toxicol Chem 2018;37:1496-1508. © 2018 SETAC.

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Section: Introductionmentioning

confidence: 99%

Benchmark dose analysis framework for developing wildlife toxicity reference values

Mayfield

Skall

2018

Enviro Toxic and Chemistry

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“…Although no clear guidance for selecting TRVs suitable for developing soil cleanup values is available from regulatory agencies , multiple viable options for data based, site‐specific selections have been made in the present study and elsewhere []. Although several of the approaches necessitate time‐consuming literature searches and data retrieval, the number of species and feeding guilds for which TRVs are required for site cleanup is less than that for initial screening.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity of ecological soil‐screening levels for metals to exposure model parameterization and toxicity reference values

Sample¹,

Fairbrother

Kaiser

et al. 2014

Enviro Toxic and Chemistry

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Ecological soil-screening levels (Eco-SSLs) were developed by the United States Environmental Protection Agency (USEPA) for the purposes of setting conservative soil screening values that can be used to eliminate the need for further ecological assessment for specific analytes at a given site. Ecological soil-screening levels for wildlife represent a simplified dietary exposure model solved in terms of soil concentrations to produce exposure equal to a no-observed-adverse-effect toxicity reference value (TRV). Sensitivity analyses were performed for 6 avian and mammalian model species, and 16 metals/metalloids for which Eco-SSLs have been developed. The relative influence of model parameters was expressed as the absolute value of the range of variation observed in the resulting soil concentration when exposure is equal to the TRV. Rank analysis of variance was used to identify parameters with greatest influence on model output. For both birds and mammals, soil ingestion displayed the broadest overall range (variability), although TRVs consistently had the greatest influence on calculated soil concentrations; bioavailability in food was consistently the least influential parameter, although an important site-specific variable. Relative importance of parameters differed by trophic group. Soil ingestion ranked 2nd for carnivores and herbivores, but was 4th for invertivores. Different patterns were exhibited, depending on which parameter, trophic group, and analyte combination was considered. The approach for TRV selection was also examined in detail, with Cu as the representative analyte. The underlying assumption that generic body-weight–normalized TRVs can be used to derive protective levels for any species is not supported by the data. Whereas the use of site-, species-, and analyte-specific exposure parameters is recommended to reduce variation in exposure estimates (soil protection level), improvement of TRVs is more problematic. Environ Toxicol Chem 2014;33:2386–2398.

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“…The Eco‐SSL process relies on numerous assumptions (e.g., body weights and food ingestion rates) to convert the administered exposures (usually dietary concentrations) to a uniform daily oral dose (USEPA ). The conversion process can result in variable estimates of dose, depending on the judgments of the risk assessor, resulting in imprecise estimates of NOAEL or LOAELs (McDonald and Wilcockson ; Mayfield and Fairbrother ). Although the protocols developed for the Eco‐SSLs standardized the exposure conversion assumptions, these may not be applicable to all sites and should be reviewed after the screening phase of the risk assessment.…”

Section: Limitations Of Existing Trv Derivation Methodsmentioning

confidence: 99%

Furthering the derivation of predictive wildlife toxicity reference values for use in soil cleanup decisions

Mayfield

Johnson

Burris³

et al. 2013

Integr Envir Assess & Manag

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The development of media-specific ecological values for risk assessment includes the derivation of acceptable levels of exposure for terrestrial wildlife (e.g., birds, mammals, reptiles, and amphibians). Although the derivation and subsequent application of these values can be used for screening purposes, there is a need to identify toxicological effects thresholds specifically for making remedial decisions at individual contaminated sites. A workshop was held in the fall of 2012 to evaluate existing methods and recent scientific developments for refining ecological soil screening levels (Eco-SSLs) and improving the derivation of site-specific ecological soil clean-up values for metals (Eco-SCVs). This included a focused session on the development and derivation of toxicity reference values (TRVs) for terrestrial wildlife. Topics that were examined included: methods for toxicological endpoint selection, techniques for dose-response assessment, approaches for cross-species extrapolation, and tools to incorporate environmental factors (e.g., metal bioavailability and chemistry) into a reference value. The workgroup also made recommendations to risk assessors and regulators on how to incorporate site-specific wildlife life history and toxicity information into the derivation of TRVs to be used in the further development of soil cleanup levels.

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Efforts to standardize wildlife toxicity values remain unrealized

Cited by 17 publications

References 35 publications

Benchmark dose analysis framework for developing wildlife toxicity reference values

Benchmark dose analysis framework for developing wildlife toxicity reference values

Sensitivity of ecological soil‐screening levels for metals to exposure model parameterization and toxicity reference values

Furthering the derivation of predictive wildlife toxicity reference values for use in soil cleanup decisions

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