Alamichel, L., Arbel, J., Kon Kam King, G., Prünster, I., 2026. Species sensitivity distribution revisited: a Bayesian nonparametric approach. J. R. Stat. Soc. Ser. C. Appl. Stat. qlag007.
https://doi.org/10.1093/jrsssc/qlag007Aldenberg, T., Slob, W., 1993. Confidence-Limits for Hazardous Concentrations Based on Logistically Distributed Noec Toxicity Data. Ecotox. Environ. Safe. 25, 48–63.
https://doi.org/10.1006/eesa.1993.1006aus der Beek, T., Weber, F.-A., Bergmann, A., Hickmann, S., Ebert, I., Hein, A., Küster, A., 2016. Pharmaceuticals in the environment-Global occurrences and perspectives. Environ Toxicol Chem 35, 823–835.
https://doi.org/10.1002/etc.3339Barron, M.G., 2012. Ecological Impacts of the Deepwater Horizon Oil Spill: Implications for Immunotoxicity. Toxicol Pathol 40, 315–320.
https://doi.org/10.1177/0192623311428474Barron, M.G., Otter, R.R., Connors, K.A., Kienzler, A., Embry, M.R., 2021. Ecological Thresholds of Toxicological Concern: A Review. Front. Toxicol. 3.
https://doi.org/10.3389/ftox.2021.640183Brain, R.A., Sanderson, H., Sibley, P.K., Solomon, K.R., 2006. Probabilistic ecological hazard assessment: Evaluating pharmaceutical effects on aquatic higher plants as an example. Ecotoxicology and Environmental Safety 64, 128–135.
https://doi.org/10.1016/j.ecoenv.2005.08.007Brink, P.J.V. den, Blake, N., Brock, T.C.M., Maltby, L., 2006. Predictive Value of Species Sensitivity Distributions for Effects of Herbicides in Freshwater Ecosystems. Human and Ecological Risk Assessment: An International Journal 12, 645–674.
https://doi.org/10.1080/10807030500430559Brix, K.V., DeForest, D.K., Adams, W.J., 2001. Assessing acute and chronic copper risks to freshwater aquatic life using species sensitivity distributions for different taxonomic groups. Environmental toxicology and chemistry 20, 1846–1856.
https://doi.org/10.1002/etc.5620200831Carr, G.J., Belanger, S.E., 2019. SSDs Revisited: Part I-A Framework for Sample Size Guidance on Species Sensitivity Distribution Analysis. Environ Toxicol Chem 38, 1514–1525.
https://doi.org/10.1002/etc.4445Connors, K.A., Beasley, A., Barron, M.G., Belanger, S.E., Bonnell, M., Brill, J.L., De Zwart, D., Kienzler, A., Krailler, J., Otter, R., Phillips, J.L., Embry, M.R., 2019. Creation of a Curated Aquatic Toxicology Database: EnviroTox. Environmental Toxicology and Chemistry 38, 1062–1073.
https://doi.org/10.1002/etc.4382Daam, M.A., Pereira, A.C.S., Silva, E., Caetano, L., Cerejeira, M.J., 2013. Preliminary aquatic risk assessment of imidacloprid after application in an experimental rice plot. Ecotoxicology and Environmental Safety 97, 78–85.
https://doi.org/10.1016/j.ecoenv.2013.07.011De Schamphelaere, K.A.C., Janssen, C.R., 2004. Bioavailability and Chronic Toxicity of Zinc to Juvenile Rainbow Trout (Oncorhynchus mykiss): Comparison with Other Fish Species and Development of a Biotic Ligand Model. Environ. Sci. Technol. 38, 6201–6209.
https://doi.org/10.1021/es049720mDobbins, L.L., Brain, R.A., Brooks, B.W., 2008. Comparison of the Sensitivities of Common in Vitro and in Vivo Assays of Estrogenic Activity: Application of Chemical Toxicity Distributions. Environmental Toxicology and Chemistry 27, 2608–2616.
https://doi.org/10.1897/08-126.1Dreier, D.A., Rodney, S.I., Moore, D.R., Grant, S.L., Chen, W., Valenti, T.W., Brain, R.A., 2020. Integrating Exposure and Effect Distributions with the Ecotoxicity Risk Calculator: Case Studies with Crop Protection Products. Integrated Environmental Assessment and Management 17, 321–330.
https://doi.org/10.1002/ieam.4344Duboudin, C., Ciffroy, P., Magaud, H., 2004. Effects of data manipulation and statistical methods on species sensitivity distributions. Environmental Toxicology and Chemistry 23, 489–499.
https://doi.org/10.1897/03-159EFSA Scientific Committee, 2016. Coverage of endangered species in environmental risk assessments at EFSA. EFS2 14.
https://doi.org/10.2903/j.efsa.2016.4312Escher, B.I., Allinson, M., Altenburger, R., Bain, P.A., Balaguer, P., Busch, W., Crago, J., Denslow, N.D., Dopp, E., Hilscherova, K., Humpage, A.R., Kumar, A., Grimaldi, M., Jayasinghe, B.S., Jarosova, B., Jia, A., Makarov, S., Maruya, K.A., Medvedev, A., Mehinto, A.C., Mendez, J.E., Poulsen, A., Prochazka, E., Richard, J., Schifferli, A., Schlenk, D., Scholz, S., Shiraishi, F., Snyder, S., Su, G., Tang, J.Y.M., van der Burg, B., van der Linden, S.C., Werner, I., Westerheide, S.D., Wong, C.K.C., Yang, M., Yeung, B.H.Y., Zhang, X., Leusch, F.D.L., 2014. Benchmarking organic micropollutants in wastewater, recycled water and drinking water with in vitro bioassays. Environ Sci Technol 48, 1940–1956.
https://doi.org/10.1021/es403899tFick, J., Söderström, H., Lindberg, R.H., Phan, C., Tysklind, M., Larsson, D.G.J., 2009. Contamination of surface, ground, and drinking water from pharmaceutical production. Environ Toxicol Chem 28, 2522–2527.
https://doi.org/10.1897/09-073.1Forbes, V.E., Calow, P., 2002. Species Sensitivity Distributions Revisited: A Critical Appraisal. Human and Ecological Risk Assessment 8, 473–492.
https://doi.org/10.1080/20028091057033French-McCay, D.P., 2004. Oil spill impact modeling: development and validation. Environ Toxicol Chem 23, 2441–2456.
https://doi.org/10.1897/03-382Gao, P., Li, Z., Gibson, M., Gao, H., 2014. Ecological risk assessment of nonylphenol in coastal waters of China based on species sensitivity distribution model. Chemosphere 104, 113–119.
https://doi.org/10.1016/j.chemosphere.2013.10.076González-Doncel, M., Ortiz, J., Izquierdo, J.J., Martín, B., Sánchez, P., Tarazona, J.V., 2006. Statistical evaluation of chronic toxicity data on aquatic organisms for the hazard identification: The chemicals toxicity distribution approach. Chemosphere 63, 835–844.
https://doi.org/10.1016/j.chemosphere.2005.07.060Gottschalk, F., Nowack, B., 2013. A probabilistic method for species sensitivity distributions taking into account the inherent uncertainty and variability of effects to estimate environmental risk. Integrated Environmental Assessment and Management 9, 79–86.
https://doi.org/10.1002/ieam.1334Green, J.W., Springer, T.A., Holbech, H., 2018. Statistical Analysis of Ecotoxicity Studies, 1st ed. Wiley.
https://doi.org/10.1002/9781119488798Grist, E.P.M., Leung, K.M.Y., Wheeler, J.R., Crane, M., 2002. Better bootstrap estimation of hazardous concentration thresholds for aquatic assemblages. Environmental Toxicology and Chemistry 21, 1515–1524.
https://doi.org/10.1002/etc.5620210725Hanson, M.L., Wolff, B.A., Green, J.W., Kivi, M., Panter, G.H., Warne, M.S.J., Agerstrand, M., Sumpter, J.P., 2017. How we can make ecotoxicology more valuable to environmental protection. Science of the Total Environment 578, 228–235.
https://doi.org/10.1016/j.scitotenv.2016.07.160Iwasaki, Y., Hayashi, T.I., Kamo, M., 2013. Estimating population-level HC5 for copper using a species sensitivity distribution approach. Environ Toxicol Chem 32, 1396–1402.
https://doi.org/10.1002/etc.2181Kefford, B.J., Palmer, C.G., Jooste, S., Warne, M.St.J., Nugegoda, D., 2005. What is Meant by “95% of Species”? An Argument for the Inclusion of Rapid Tolerance Testing. Human and Ecological Risk Assessment: An International Journal 11, 1025–1046.
https://doi.org/10.1080/10807030500257770Kerby, J.L., Richards-Hrdlicka, K.L., Storfer, A., Skelly, D.K., 2010. An examination of amphibian sensitivity to environmental contaminants: are amphibians poor canaries? Ecology Letters 13, 60–67.
https://doi.org/10.1111/j.1461-0248.2009.01399.xKhan, M.I., Mubashir, M., Zaini, D., Mahnashi, M.H., Alyami, B.A., Alqarni, A.O., Show, P.L., 2021. Cumulative impact assessment of hazardous ionic liquids towards aquatic species using risk assessment methods. Journal of Hazardous Materials 415, 125364.
https://doi.org/10.1016/j.jhazmat.2021.125364King, G.K.K., Veber, P., Charles, S., Delignette-Muller, M.L., 2014. MOSAIC_SSD: a new web tool for species sensitivity distribution to include censored data by maximum likelihood. Environmental toxicology and chemistry / SETAC 33, 2133–9.
https://doi.org/10.1002/etc.2644King, G.K.K., Veber, P., Charles, S., Delignette-Muller, M.L., 2013. MOSAIC_SSD: a new web-tool for the Species Sensitivity Distribution, allowing to include censored data by maximum likelihood.
Kon Kam King, G., Delignette-Muller, M.L., Kefford, B.J., Piscart, C., Charles, S., 2015a. Constructing Time-Resolved Species Sensitivity Distributions Using a Hierarchical Toxico-Dynamic Model. Environ. Sci. Technol. 49, 12465–12473.
https://doi.org/10.1021/acs.est.5b02142Kon Kam King, G., Larras, F., Charles, S., Delignette-Muller, M.L., 2015b. Hierarchical modelling of species sensitivity distribution: Development and application to the case of diatoms exposed to several herbicides. Ecotoxicology and Environmental Safety 114, 212–221.
https://doi.org/10.1016/j.ecoenv.2015.01.022Lambert, F.N., Raimondo, S., Barron, M.G., 2022. Assessment of a New Approach Method for Grouped Chemical Hazard Estimation: The Toxicity-Normalized Species Sensitivity Distribution (SSDn). Environ. Sci. Technol. 56, 8278–8289.
https://doi.org/10.1021/acs.est.1c05632Le Goc, G., Lafaye, J., Karpenko, S., Bormuth, V., Candelier, R., Debrégeas, G., 2021. Thermal modulation of Zebrafish exploratory statistics reveals constraints on individual behavioral variability. BMC Biol 19, 208.
https://doi.org/10.1186/s12915-021-01126-wLeung, K.M.Y., Morritt, D., Wheeler, J.R., Whitehouse, P., Sorokin, N., Toy, R., Holt, M., Crane, M., 2001. Can Saltwater Toxicity be Predicted from Freshwater Data? Marine Pollution Bulletin 42, 1007–1013.
https://doi.org/10.1016/S0025-326X(01)00135-7Li, Y., Mu, D., Wu, H.-Q., Liu, H.-J., Wang, Y.-H., Ma, G.-C., Duan, X.-M., Zhou, J.-J., Zhang, C.-M., Lu, X.-H., Liu, X.-H., Sun, J., Ji, Z.-Y., 2023. Derivation of copper water quality criteria in Bohai Bay for the protection of local aquatic life and the ecological risk assessment. Marine Pollution Bulletin 190, 114863.
https://doi.org/10.1016/j.marpolbul.2023.114863Liu, Y., Wu, F., Mu, Y., Feng, C., Fang, Y., Chen, L., Giesy, J.P., 2014. Setting Water Quality Criteria in China: Approaches for Developing Species Sensitivity Distributions for Metals and Metalloids. Reviews of Environmental Contamination and Toxicology, Vol 230 230, 35–57.
https://doi.org/10.1007/978-3-319-04411-8_2Maltby, L., Blake, N., Brock, T.C.M., Van den Brink, P.J., 2005. Insecticide species sensitivity distributions: Importance of test species selection and relevance to aquatic ecosystems. Environmental Toxicology and Chemistry 24, 379–388.
https://doi.org/10.1897/04-025R.1Moore, D.R., Priest, C.D., Galic, N., Brain, R.A., Rodney, S.I., 2020. Correcting for Phylogenetic Autocorrelation in Species Sensitivity Distributions. Integrated Environmental Assessment and Management 16, 53–65.
https://doi.org/10.1002/ieam.4207Morrissey, C.A., Mineau, P., Devries, J.H., Sanchez-Bayo, F., Liess, M., Cavallaro, M.C., Liber, K., 2015. Neonicotinoid contamination of global surface waters and associated risk to aquatic invertebrates: A review. Environment International 74, 291–303.
https://doi.org/10.1016/j.envint.2014.10.024Natsch, A., Emter, R., Haupt, T., Ellis, G., 2018. Deriving a No Expected Sensitization Induction Level for Fragrance Ingredients Without Animal Testing: An Integrated Approach Applied to Specific Case Studies. Toxicol Sci 165, 170–185.
https://doi.org/10.1093/toxsci/kfy135Newman, M.C., Ownby, D.R., Mézin, L.C.A., Powell, D.C., Christensen, T.R.L., Lerberg, S.B., Anderson, B.-A., 2000. Applying species‐sensitivity distributions in ecological risk assessment: Assumptions of distribution type and sufficient numbers of species. Environmental Toxicology and Chemistry 19, 508–515.
https://doi.org/10.1002/etc.5620190233Omeira, N., Barbour, E.K., Nehme, P.A., Hamadeh, S.K., Zurayk, R., Bashour, I., 2006. Microbiological and chemical properties of litter from different chicken types and production systems. Science of The Total Environment 367, 156–162.
https://doi.org/10.1016/j.scitotenv.2006.02.019Posthuma, L., II, G.W.S., Traas, T.P. (Eds.), 2001. Species Sensitivity Distributions in Ecotoxicology. CRC Press, Boca Raton.
https://doi.org/10.1201/9781420032314Posthuma, L., Van Gils, J., Zijp, M.C., Van De Meent, D., De Zwart, D., 2019. Species sensitivity distributions for use in environmental protection, assessment, and management of aquatic ecosystems for 12 386 chemicals. Environmental Toxicology and Chemistry 38, 905–917.
https://doi.org/10.1002/etc.4373Rizzi, C., Villa, S., Cuzzeri, A.S., Finizio, A., 2021. Use of the Species Sensitivity Distribution Approach to Derive Ecological Threshold of Toxicological Concern (eco-TTC) for Pesticides. Int J Environ Res Public Health 18, 12078.
https://doi.org/10.3390/ijerph182212078Rodrigues, E.T., Pardal, M.A., Gante, C., Loureiro, J., Lopes, I., 2017. Determination and validation of an aquatic Maximum Acceptable Concentration-Environmental Quality Standard (MAC-EQS) value for the agricultural fungicide azoxystrobin. Environmental Pollution 221, 150–158.
https://doi.org/10.1016/j.envpol.2016.11.058Russo, R.C., 2002. Development of marine water quality criteria for the USA. Marine Pollution Bulletin 45, 84–91.
https://doi.org/10.1016/S0025-326X(02)00136-4Shi, R., Yang, C., Su, R., Jin, J., Chen, Y., Liu, H., Giesy, J., Yu, H., 2014. Weighted species sensitivity distribution method to derive site-specific quality criteria for copper in Tai Lake, China. Environmental Science and Pollution Research 21, 12968–12978.
https://doi.org/10.1007/s11356-014-3156-5Straalen, N.M. van, 2002. Threshold models for species sensitivity distributions applied to aquatic risk assessment for zinc. Environmental Toxicology and Pharmacology 11, 167–172.
https://doi.org/10.1016/S1382-6689(01)00114-4Thorley, J., Schwarz, C., 2018. ssdtools: An R package to fit Species Sensitivity Distributions. Journal of Open Source Software 3, 1082.
https://doi.org/10.21105/joss.01082US EPA, O., 2015. Guidelines for Deriving Numerical National Water Quality Criteria for the Protection of Aquatic Organisms and Their Uses [WWW Document]. URL
https://www.epa.gov/wqc/guidelines-deriving-numerical-national-water-quality-criteria-protection-aquatic-organisms-and (accessed 3.25.26).
Vieira, L.R., Gravato, C., Soares, A.M.V.M., Morgado, F., Guilhermino, L., 2009. Acute effects of copper and mercury on the estuarine fish Pomatoschistus microps: linking biomarkers to behaviour. Chemosphere 76, 1416–1427.
https://doi.org/10.1016/j.chemosphere.2009.06.005Wagner, C., Lokke, H., 1991. Estimation of Ecotoxicological Protection Levels from Noec Toxicity Data. Water research 25, 1237–1242.
https://doi.org/10.1016/0043-1354(91)90062-UWang, X., Yan, Z., Liu, Z., Zhang, C., Wang, W., Li, H., 2014. Comparison of species sensitivity distributions for species from China and the USA. Environmental Science and Pollution Research 21, 168–176.
https://doi.org/10.1007/s11356-013-2110-2Wheeler, J.R., Grist, E.P.M., Leung, K.M.Y., Morritt, D., Crane, M., 2002. Species sensitivity distributions: data and model choice. Mar. Pollut. Bull. 45, 192–202.
https://doi.org/10.1016/S0025-326X(01)00327-7Williams, E.S., Berninger, J.P., Brooks, B.W., 2011. Application of Chemical Toxicity Distributions to Ecotoxicology Data Requirements Under Reach. Environmental Toxicology and Chemistry 30, 1943–1954.
https://doi.org/10.1002/etc.583Xu, F.-L., Li, Y.-L., Wang, Y., He, W., Kong, X.-Z., Qin, N., Liu, W.-X., Wu, W.-J., Jorgensen, S.E., 2015. Key issues for the development and application of the species sensitivity distribution (SSD) model for ecological risk assessment. Ecological Indicators 54, 227–237.
https://doi.org/10.1016/j.ecolind.2015.02.001Yanagihara, M., Hiki, K., Iwasaki, Y., 2024. Which distribution to choose for deriving a species sensitivity distribution? Implications from analysis of acute and chronic ecotoxicity data. Ecotoxicology and Environmental Safety 278, 116379.
https://doi.org/10.1016/j.ecoenv.2024.116379Zhao, J., Chen, B., 2016. Species sensitivity distribution for chlorpyrifos to aquatic organisms: Model choice and sample size. Ecotoxicology and Environmental Safety 125, 161–169.
https://doi.org/10.1016/j.ecoenv.2015.11.039