Species Sensitivity Distributions Approach Research Articles

Recommended rates of azoxystrobin and tebuconazole seem to be environmentally safe but ineffective against target fungi

The use of fungicides in agriculture has been playing a role in the enhancement of agricultural yields through the control of pathogens causing serious diseases in crops. Still, adverse environmental and human health effects resulting from its application have been reported. In this study, the possibility of readjusting the formulation of a commercial product combining azoxystrobin and tebuconazole (active ingredients – AIs; Custodia®) towards environmentally safer alternative(s) was investigated. Specifically, the sensitivity of non-target aquatic communities to each AI was first evaluated by applying the Species Sensitivity Distributions (SSDs) approach. Then, mixtures of these AIs were tested in a non-target organism (Raphidocelis subcapitata) denoting sensitivity to both AIs as assessed from SSDs. The resulting data supported the design of the last stage of this study, where mixtures of those AIs at equivalent vs. alternative ratios and rates as in the commercial formulation were tested against two target fungal species: Pyrenophora teres CBS 123929 and Rhynchosporium secalis CBS 110524. The comparison between the sensitivity of non-target aquatic species and the corresponding efficacy towards target fungi revealed that currently applied mixture and rates of these AIs are generally environmentally safe (antagonistic interaction; concentrations below the EC1 for R. subcapitata and generally below the HC5 for aquatic non-target communities), but ineffective against target organisms (maximum levels of inhibition of 70 and 50% in P. teres CBS 123929 and R. secalis CBS 110524, respectively). Results additionally suggest a potentiation of the effects of the AIs by the other formulants added to the commercial product at tested rates. Overall, this study corroborates that commercial products can be optimized during design stages based on a systematic ecotoxicological testing for ingredient interactions and actual efficacy against targets. This could be a valuable pathway to reduce environmental contamination during transition to a more sustainable agricultural production.

The strategy for estrogen receptor mediated-risk assessment in environmental water: A combination of species sensitivity distributions and in silico approaches

Risk assessment for molecular toxicity endpoints of environmental matrices may be a pressing issue. Here, we combined chemical analysis with species sensitivity distributions (SSD) and in silico docking for multi-species estrogen receptor mediated-risk assessment in water from Dongjiang River, China. The water contains high levels of phenolic endocrine-disrupting chemicals (PEDCs) and phthalic acid esters (PAEs). The concentration of ∑4PEDCs and ∑6PAEs ranged from 2202 to 3404 ng/L and 834–4368 ng/L, with an average of 3241 and 2215 ng/L, respectively. The SSD approach showed that 4-NP, BPA, E2 of PEDCs, and DBP, DOP, and DEHP could severely threaten the aquatic ecosystems, while most other target compounds posed low-to-medium risks. Moreover, binding affinities from molecular docking among PEDCs, PAEs, and estrogen receptors (ERα, Erβ, and GPER) were applied as toxic equivalency factors. Estrogen receptor-mediated risk suggested that PEDCs were the main contributors, containing 53.37–69.79% of total risk. They potentially pose more severe estrogen-receptor toxicity to zebrafish, turtles, and frogs. ERβ was the major contributor, followed by ERα and GPER. This study is the first attempt to assess the estrogen receptor-mediated risk of river water in multiple aquatic organisms. The in silico simulation approach could complement toxic effect evaluations in molecular endpoints.

Ecological risk assessment of an antifouling biocide triphenyl (octadecylamine) boron in the Seto Inland Sea, Japan

In this study, we derived the predicted no-effect concentrations (PNEC) for triphenyl (octadecylamine) boron (TPB-18) and investigated the occurrence of triphenylboranes (TPBs), including TPB-18, for ecological risk assessment in the Seto Inland Sea, Japan. We tested algal growth inhibition, crustacean immobilization, and reproductive toxicity and performed toxicity tests in fish to assess acute and chronic toxicity and generate the PNEC for TPB-18. The minimum toxicity value was 0.30 μg/L, as determined by the 72-h no-observed-effect concentration (NOEC) for the alga Chaetoceros gracilis. The 5th-percentile of hazardous concentration (HC5), derived from NOECs using the species sensitivity distributions approach, was 0.059 μg/L, which indicated the PNEC of 0.0059 μg/L. In comparison, the highest concentration in seawater sampled from the Seto Inland Sea was 0.00034 μg/L, suggesting that the ecological risks posed by TPB-18 are currently low.

Acute and Chronic Toxicity of Cobalt to Freshwater Organisms: Using a Species Sensitivity Distribution Approach to Establish International Water Quality Standards

Water quality standards for cobalt (Co) have not been developed for the European Union or United States. The objective of the present study was to produce freshwater Co toxicity data that could be used by both the European Union and the United States to develop appropriate regulatory standards (i.e., environmental quality standards or predicted-no-effect concentrations in Europe and ambient water quality criteria or state water quality standards in the United States). Eleven species, including algae, an aquatic plant, and several invertebrate and fish species, were used in the performance of acute and chronic Co toxicity tests. Acute median lethal or median effective concentration (LC50 or EC50) values ranged from 90.1 µg Co/L for duckweed (Lemna minor) to 157 000 µg Co/L for midges (Chironomus tentans). Chronic 10% effect concentration (EC10) values ranged from 4.9 µg Co/L for duckweed to 2170 µg Co/L for rainbow trout (Oncorhynchus mykiss). Chronic 20% effect concentration (EC20) values ranged from 11.1 µg Co/L for water flea (Ceriodaphnia dubia) to 2495 µg Co/L for O. mykiss. Results indicated that invertebrate and algae/plant species are more sensitive to chronic Co exposures than fish. Acute-to-chronic ratios (derived as acute LC50s divided by chronic EC20s) were lowest for juvenile O. mykiss (0.6) and highest for the snail Lymnaea stagnalis (2670). Following the European-based approach and using EC10 values, species sensitivity distributions (SSDs) were developed and a median hazardous concentration for 5% of the organisms of 1.80 µg Co/L was derived. Chronic EC20 values were used, also in an SSD approach, to derive a US Environmental Protection Agency-style final chronic value of 7.13 µg Co/L. Environ Toxicol Chem 2020;39:799-811. © 2020 SETAC.

Environmental benchmarks based on ecotoxicological assessment with planktonic species might not adequately protect benthic assemblages in lotic systems

Freshwater ecosystems face widespread diffuse and point-source contamination. Species Sensitivity Distributions (SSDs) have been used as a tool to determine chemical concentration benchmarks that represent protective levels for most species in the environment. Here we used a SSD approach to assess on the adequacy of standard planktonic organisms to reflect the response of benthic communities, critically supporting the structure and function of lotic ecosystems. For the purpose, SSDs reflecting non-lethal responses of standard planktonic and selected benthic organisms were built based on EC50 values (collected in the literature or estimated following testing herein) regarding three model contaminants: potassium dichromate (PD), 3,5-dichlorophenol (DCP) and lead chloride (LC). The derived HC5 estimates were discriminatory between chemicals and the uncertainty associated with the estimate was remarkably low. The HC5 estimates with corresponding uncertainty were generally within the same order of magnitude for the three chemicals tested, with better discrimination between chemicals regarding their hazardous potential being achieved for benthic organisms: DCP was clearly less hazardous than PD, but LC tends to be as hazardous as PD and DCP (assuming the confidence interval ranges). Moreover, benthic communities were more sensitive to both DCP and PD, in this later case the HC5 being lower by more than one order of magnitude than that found for planktonic communities; for LC, confidence intervals overlapped, preventing a feasible assumption regarding differential sensitivity of the compared communities. Microphytobenthos was highlighted as the most sensitive group to the three tested chemicals in SSDs covering the benthic compartment, while SSDs with planktonic organisms did not consistently show trends in sensitivity ordering. Overall, our results suggest that protective benchmarks retrieved from SSDs built with the responses of standard planktonic organisms (which are the most commonly used for regulation purposes) do not adequately protect benthic communities.

An analysis of potential bias in the sensitivity of toxicity data used to construct sensitivity distributions for copper.

Since the mid-1970s, thousands of studies have evaluated the toxicity of various chemicals to aquatic organisms. Results from many of these studies have been used to develop species sensitivity distributions (SSDs) or genus sensitivity distributions (GSDs) for deriving water quality guidelines. Recently, there has been more emphasis on evaluating the toxicity of chemicals to sensitive organisms rather than the entire range of sensitivities. The SSD approach is intended to inform the derivation of guidelines for the protection of all species, not just those that were included in the SSD. The overemphasis of the more sensitive end of the SSD can contribute to a skew in the observed distribution such that the shape of the distribution is distorted from what it would be if all species could be tested, which ultimately affects the derived guideline value. The freshwater acute Cu GSD derived by the US Environmental Protection Agency (USEPA) is one that exemplifies this trend, with one-third of the genera in the GSD belonging to only 3 taxonomic families, all of which are nearer to the sensitive end of the distribution. The stronger representation of the more sensitive families does not seem to mirror the overall abundance of species within those families in nature. This tendency toward testing sensitive organisms is not seen in the chronic Cu SSD. In the present study, Cu toxicity literature is reviewed and long-term trends in the availability of toxicity information for species of varying sensitivity are examined. As part of the present review, the apparent bias that favors the publication of toxicity data for sensitive taxa is demonstrated, and implications for the representativeness of SSDs and their use in developing water quality guidelines are discussed. Integr Environ Assess Manag 2019;00:000-000. © 2019 SETAC.

Environmental Risk Assessment Strategy for Nanomaterials.

An Environmental Risk Assessment (ERA) for nanomaterials (NMs) is outlined in this paper. Contrary to other recent papers on the subject, the main data requirements, models and advancement within each of the four risk assessment domains are described, i.e., in the: (i) materials, (ii) release, fate and exposure, (iii) hazard and (iv) risk characterisation domains. The material, which is obviously the foundation for any risk assessment, should be described according to the legislatively required characterisation data. Characterisation data will also be used at various levels within the ERA, e.g., exposure modelling. The release, fate and exposure data and models cover the input for environmental distribution models in order to identify the potential (PES) and relevant exposure scenarios (RES) and, subsequently, the possible release routes, both with regard to which compartment(s) NMs are distributed in line with the factors determining the fate within environmental compartment. The initial outcome in the risk characterisation will be a generic Predicted Environmental Concentration (PEC), but a refined PEC can be obtained by applying specific exposure models for relevant media. The hazard information covers a variety of representative, relevant and reliable organisms and/or functions, relevant for the RES and enabling a hazard characterisation. The initial outcome will be hazard characterisation in test systems allowing estimating a Predicted No-Effect concentration (PNEC), either based on uncertainty factors or on a NM adapted version of the Species Sensitivity Distributions approach. The risk characterisation will either be based on a deterministic risk ratio approach (i.e., PEC/PNEC) or an overlay of probability distributions, i.e., exposure and hazard distributions, using the nano relevant models.

Using a Risk-based Approach for Derivation of Water Quality Guidelines for Sulphate

Sulphate is a major salt component in acid mine drainage and a crucial ecological concern in most coal and gold mining regions, globally. However, there remains a paucity of data on sulphate salinity toxicity on freshwater taxa. In this study, we hypothesised sensitivity differences for five freshwater species (Adenophlebia auriculata, Burnupia stenochorias, Caridina nilotica, Pseudokirchneriella subcapitata, and Oreochromis mossambicus) to increasing sulphate salinity concentrations after 240 h of exposure. Species sensitivity distributions (SSDs) were used to rank the sensitivity of tested species to the inorganic sulphate salts, which included magnesium sulphate (MgSO4), sodium sulphate (Na2SO4), and calcium sulphate (CaSO4) as models of mining salinisation in South Africa. The SSDs were also used to estimate appropriate protective concentrations of the salts for the tested species. Sensitivity differences were measured and Na2SO4 was the most toxic of the tested salts. A concentration of 0.020 g/L Na2SO4, 0.055 g/L CaSO4, and 0.108 g/L MgSO4 or a combined salts limit of 0.067 g/L would be protective of 95% of the populations of the five species tested; these all suggest that the 0.25 g/L compliance limit for South Africa is insufficient. Future studies should incorporate more species in the SSD approach to be coupled by field validations to further improve the ecological relevance of these findings. © 2017, Springer-Verlag GmbH Germany.

Environmental risk assessment of pesticides in the River Madre de Dios, Costa Rica using PERPEST, SSD, and msPAF models

This study assesses the ecological risks (ERA) of pesticides to aquatic organisms in the River Madre de Dios (RMD), which receives surface runoff water from banana, pineapple, and rice plantations on the Caribbean coast of Costa Rica. Water samples collected over 2 years at five sites in the RMD revealed a total of 26 pesticides. Their toxicity risk to aquatic organisms was assessed using three recent ERA models. (1) The PERPEST model showed a high probability (>50 %) of clear toxic effects of pesticide mixtures on algae, macrophytes, zooplankton, macroinvertebrates, and community metabolism and a low probability (<50 %) of clear effects on fish. (2) Species sensitivity distributions (SSD) showed a moderate to high risk of three herbicides: ametryn, bromacil, diuron and four insecticides: carbaryl, diazinon, ethoprophos, terbufos. (3) The multi-substance potentially affected fraction (msPAF) model showed results consistent with PERPEST: high risk to algae (maximum msPAF: 73 %), aquatic plants (61 %), and arthropods (25 %) and low risk to fish (0.2 %) from pesticide mixtures. The pesticides posing the highest risks according to msPAF and that should be substituted with less toxic substances were the herbicides ametryn, diuron, the insecticides carbaryl, chlorpyrifos, diazinon, ethoprophos, and the fungicide difenoconazole. Ecological risks were highest near the plantations and decreased progressively further downstream. The risk to fish was found to be relatively low in these models, but water samples were not collected during fish kill events and some highly toxic pesticides known to be used were not analyzed for in this study. Further sampling and analysis of water samples is needed to determine toxicity risks to fish during peaks of pesticide mixture concentrations. The msPAF model, which estimates the ecological risks of mixtures based on their toxic modes of action, was found to be the most suitable model to assess toxicity risks to aquatic organisms in the RMD. The PERPEST model was found to be a strong tool for screening risk assessments. The SSD approach is useful in deriving water quality criteria for specific pesticides. This study, through the application of three ERA models, clearly shows that pesticides used in plantations within the RMD watershed are expected to have severe adverse effects on most groups of aquatic organisms and that actions are urgently needed to reduce pesticide pollution in this high biodiversity ecosystem.

Development and application of the SSD approach in scientific case studies for ecological risk assessment.

Species sensitivity distributions (SSDs) are used in ecological risk assessment for extrapolation of the results of toxicity tests with single species to a toxicity threshold considered protective of ecosystem structure and functioning. The attention to and importance of the SSD approach has increased in scientific and regulatory communities since the 1990s. Discussion and criticism have been triggered on the concept of the approach as well as its technical aspects (e.g., distribution type, number of toxicity endpoints). Various questions remain unanswered, especially with regard to different endpoints, statistical methods, and protectiveness of threshold levels, for example. In the present literature review (covering the period 2002-2013), case studies are explored in which the SSD approach was applied, as well as how endpoint types, species choice, and data availability affect SSDs. How statistical methods may be used to construct reliable SSDs and whether the lower 5th percentile hazard concentrations (HC5s) from a generic SSD can be protective for a specific local community are also investigated. It is shown that estimated protective concentrations were determined by taxonomic groups rather than the statistical method used to construct the distribution. Based on comparisons between semifield and laboratory-based SSDs, the output from a laboratory SSD was protective of semifield communities in the majority of studies. Environ Toxicol Chem 2016;35:2149-2161. © 2016 SETAC.

Multispecies toxicity test for silver nanoparticles to derive hazardous concentration based on species sensitivity distribution for the protection of aquatic ecosystems

With increasing concerns about the release of silver nanoparticles (AgNPs) into the environment and the risks they pose to ecological and human health, a number of studies of AgNP toxicity to aquatic organisms have been conducted. USEPA and EU JRC have published risk assessment reports for AgNPs. However, most previous studies have focused on the adverse effects of AgNPs on individual species. Hazardous concentration (HC) of AgNPs for protection of aquatic ecosystems that are based on species sensitivity distributions (SSDs) have not yet been derived because sufficient data have not been available. In this study, we conducted multispecies toxicity tests, including acute assays using eight species from five different taxonomic groups (bacteria, algae, flagellates, crustaceans and fish) and chronic assays using six species from four different taxonomic groups (algae, flagellates, crustaceans and fish). Using the results of these assays, we used a SSD approach to derive an AgNP aquatic HC5 (Hazard concentrations at the 5% species) of 0.614 μg/L. To our knowledge, this is the first report of a proposed HC of AgNPs for the protection of aquatic ecosystems that is based on SSDs and uses chronic toxicity data.

Metal toxicity to freshwater organisms as a function of pH: A meta-analysis.

Acidification caused by climate change and seasonal fluctuation can have profound implications for chemical toxicity to freshwater organisms. The present study aims to address this challenging issue through a comprehensive meta-analysis by comparing acute median lethal or effect concentration data (LC50 or EC50) for 10 metals and metalloids for various freshwater species obtained at different pH values. Our results revealed that element toxicity generally follows three different models, including Model-I: decreasing toxicity with increasing pH, Model-II: increasing toxicity with increasing pH, and Model-III: minimal toxicity at intermediate (optimal) pH (pH(opt)) with increasing toxicity as pH increases or decreases from pH(opt). We further examined these observations by constructing pH-dependent species sensitivity distributions (SSDs). The results indicated that the 10(th) percentile hazardous concentrations (HC10s) for copper, lead, selenium and silver generally exhibited a positive linear relationship with pH, following the Model-I. The ability to accurately predict toxicity of elements to biota in natural waters as a function of pH may be limited, however, the pH-dependent SSD approach presented in this study facilitates and helps characterize the role of pH in water quality guidelines and ecological risk assessment.

Predicting the aquatic risk of realistic pesticide mixtures to species assemblages in Portuguese river basins

Although pesticide regulatory tools are mainly based on individual substances, aquatic ecosystems are usually exposed to multiple pesticides from their use on the variety of crops within the catchment of a river. This study estimated the impact of measured pesticide mixtures in surface waters from 2002 and 2008 within three important Portuguese river basins (‘Mondego’, ‘Sado’ and ‘Tejo’) on primary producers, arthropods and fish by toxic pressure calculation. Species sensitivity distributions (SSDs), in combination with mixture toxicity models, were applied. Considering the differences in the responses of the taxonomic groups as well as in the pesticide exposures that these organisms experience, variable acute multi-substance potentially affected fractions (msPAFs) were obtained. The median msPAF for primary producers and arthropods in surface waters of all river basins exceeded 5%, the cut-off value used in the prospective SSD approach for deriving individual environmental quality standards. A ranking procedure identified various photosystem II inhibiting herbicides, with oxadiazon having the relatively largest toxic effects on primary producers, while the organophosphorus insecticides, chlorfenvinphos and chlorpyrifos, and the organochloride endosulfan had the largest effects on arthropods and fish, respectively. These results ensure compliance with European legislation with regard to ecological risk assessment and management of pesticides in surface waters.

Derivation of marine water quality criteria for metals based on a novel QICAR-SSD model.

Establishment of water quality criteria (WQC) is one procedure for protection of marine organisms and their ecosystems. This study, which integrated two separate approaches, quantitative ion character-activity relationships (QICARs) and species sensitivity distributions (SSDs), developed a novel QICAR-SSD model. The QICARs predict relative potencies of individual elements while SSDs integrate relative sensitivities among organisms. The QICAR-SSD approach was applied to derive saltwater WQC for 34 metals or metalloids. Relationships between physicochemical properties of metal ions and their corresponding potencies for acute toxicity to eight selected marine species were determined. The softness index (σp) exhibited the strongest correlation with the acute toxicity of metals (r (2) > 0.66, F > 5.88, P < 0.94 × 10(-2)). Predictive criteria maximum concentrations for the eight metals, derived by applying the SSD approach to values predicted by use of QICARs, were within the same order of magnitude as values recommended by the US EPA (2009). In general, the results support that the QICAR-SSD approach is a rapid method to estimate WQC for metals for which little or no information is available for marine organisms.

Augmenting aquatic species sensitivity distributions with interspecies toxicity estimation models

Species sensitivity distributions (SSDs) are cumulative distribution functions of species toxicity values. The SSD approach is being used increasingly in ecological risk assessment but is often limited by available toxicity data needed for diverse species representation. In the present study, the authors evaluate augmenting aquatic species databases limited to standard test species using toxicity values extrapolated from interspecies correlation estimation (ICE) models for SSD development. The authors compared hazard concentrations at the 5th centile (HC5) of SSDs developed using limited measured data augmented with ICE toxicity values (augmented SSDs) with those estimated using larger measured toxicity datasets of diverse species (reference SSDs). When SSDs had similar species composition to the reference SSDs, 0.76 of the HC5 estimates were closer to the reference HC5; however, the proportion of augmented HC5s that were within 5-fold of the reference HC5s was 0.94, compared with 0.96 when predicted SSDs had random species assemblages. The range of toxicity values among represented species in all SSDs also depended on a chemical's mode of action. Predicted HC5 estimations for acetylcholinesterase inhibitors showed the greatest discrepancies from the reference HC5 when SSDs were limited to commonly tested species. The results of the present study indicate that ICE models used to augment datasets for SSDs do not greatly affect HC5 uncertainty. Uncertainty analysis of risk assessments using SSD hazard concentrations should address species composition, especially for chemicals with known taxa-specific differences in toxicological effects. This article is a US Government work and is in the public domain in the USA.

System-oriented ecotoxicological research: Which way to go?

This paper presents an overview of the possibilities for further development of tools and. approaches for the ecological assessment and management of diffusively contaminated ecosystems. It is based on the results of the “Netherlands Stimulation Programme on Ecosystem-oriented Ecotoxicological Research”, the SSEO programme, which ran from 1998 to 2006, and on opinions of international experts on ecological and ecotoxicological risk-assessment methods and their legal applications. The paper also discusses the pros and cons of the set-up of the SSEO programme.Proper management of diffusively polluted areas has to be based on an integral risk-based and system approach. The approach has to be founded on the relationships between pollution, natural stresses, management measures and the presence and activities of specific species. Furthermore, the relationships between biodiversity in ecosystems and its stability and functioning have to be known. The assessment of aquatic ecosystem quality is now based on the comparisons of the composition of actual species with that of reference species. This type of system does not yet exist for the assessment of soil quality, but it is being developed. It is shown that ecological quality criteria based on a Species Sensitivity Distributions approach are sufficiently conservative to avoid or prevent major ecological impacts of diffuse pollution at concentrations below legal standards.However, a proper quality relationship of biodiversity and ecosystem functioning is lacking in the ecological assessment methods. Future research should focus on the relationship of ecosystem structure (species composition) and ecosystem functioning and on the impact of disturbing the environment and appropriate management measures.

Do we have to incorporate ecological interactions in the sensitivity assessment of ecosystems? An examination of a theoretical assumption underlying species sensitivity distribution models

Species sensitivity distributions (SSDs) are statistical distributions which extrapolate single-species toxicity test results to ecosystem effects. This SSD approach assumes that ecological interactions between populations, such as grazing and competition, do not influence the sensitivity of ecosystems. The validity of this assumption in a simple freshwater pelagic ecosystem was tested using ecosystem modelling. For each of a 1000 hypothetical toxicants, a lognormal SSD was fitted to chronic single-species EC10s of the species present. As such, these distributions did not account for ecological interactions and were therefore termed ‘conventional SSDs’ (cSSDs). Next, sensitivity distributions that did take into account ecological interactions were constructed (eco-SSD) for the same 1000 toxicants, using an ecosystem model. For 254 of the 1000 hypothetical toxicants, mean and/or variance of the cSSD were significantly higher than mean and/or variance of the eco-SSD, as such rejecting the general validity of the tested assumption. A classification tree approach indicated that especially toxicants which directly affect phytoplankton (i.e. herbicides) may have a higher mean for cSSD than for eco-SSD. Conversely, means of eco-SSD and cSSD tend to be equal for toxicants directly affecting zooplankton and fish, e.g. insecticides. For the 254 hypothetical toxicants for which the tested assumption was false, a predicted no effect concentration (PNEC) calculated as the lowest single-species EC10 divided by an application factor of 10 was on average a factor 10 lower than the corresponding ecosystem-NOEC calculated by the ecosystem model.

Using biological traits to predict species sensitivity to toxic substances

Species sensitivity distributions (SSD) assume that sensitivity to toxicants within target species is random. While the SSD approach has shown promise, it is limited by the fact that data are sparse for most compounds, and that these data are largely based on the lethal responses of a small group of testing lab species. Here we present an alternative approach, based on the hypothesis that organisms’ sensitivity to stress is a function of their biology, and can be predicted from species traits such as morphology, life history, physiology and feeding ecology. Using data from the US EPA's AQUIRE database, we found that four species traits explained 71% of the variability in sensitivity to toxicants within a group of 12 species exposed to 15 chemicals. Our results indicate that this approach has promise, but effort is needed to compile species trait information to increase the power, precision and taxonomic representativeness of this approach.

Bayesian and Time-Independent Species Sensitivity Distributions for Risk Assessment of Chemicals

Species sensitivity distributions (SSDs) are increasingly used to analyze toxicity data but have been criticized for a lack of consistency in data inputs, lack of relevance to the real environment, and a lack of transparency in implementation. This paper shows how the Bayesian approach addresses concerns arising from frequentist SSD estimation. Bayesian methodologies are used to estimate SSDs and compare results obtained with time-dependent (LC50) and time-independent (predicted no observed effect concentration) endpoints for the insecticide chlorpyrifos. Uncertainty in the estimation of each SSD is obtained either in the form of a pointwise percentile confidence interval computed by bootstrap regression or an associated credible interval. We demonstrate that uncertainty in SSD estimation can be reduced by applying a Bayesian approach that incorporates expert knowledge and that use of Bayesian methodology permits estimation of an SSD that is more robust to variations in data. The results suggest that even with sparse data sets theoretical criticisms of the SSD approach can be overcome.

Species Sensitivity Distributions Revisited: A Critical Appraisal

We revisit the assumptions associated with the derivation and application of species sensitivity distributions (SSDs). Our questions are (1) Do SSDs clarify or obscure the setting of ecological effects thresholds for risk assessment? and (2) Do SSDs reduce or introduce uncertainty into risk assessment? Our conclusions are that if we could determine a community sensitivity distribution, this would provide a better estimate of an ecologically relevant effects threshold and therefore be an improvement for risk assessment. However, the distributions generated are typically based on haphazard collections of species and endpoints and by adjusting these to reflect more realistic trophic structures we show that effects thresholds can be shifted but in a direction and to an extent that is not predictable. Despite claims that the SSD approach uses all available data to assess effects, we demonstrate that in certain frequently used applications only a small fraction of the species going into the SSD determine the effects threshold. If the SSD approach is to lead to better risk assessments, improvements are needed in how the theory is put into practice. This requires careful definition of the risk assessment targets and of the species and endpoints selected for use in generating SSDs.