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Field studies to determine the effects of chemicals on earthworm communities are generally conducted according to International Organization for Standardization standard 11268‐3 (and later comments). However, statistical test procedures suggested in the guideline are frequently criticized, mainly for 2 reasons: 1) Earthworm abundances are count data and often do not fulfill requirements for multiple t tests (normal distribution and homogeneity of variance), and 2) the resulting toxicity metrics of multiple testing procedures (no/lowest‐observed‐effect concentrations [NOEC/LOEC]) fail to adequately detect the actual level of effects. Recently, a new method to overcome these shortcomings was presented by the introduction of the closure principle computational approach test (CPCAT). We applied this statistical method to assess chemical effects on abundance in a large dataset of 26 earthworm field studies (with up to 3 test chemical application rates) and an additional extended study with 6 application rates. A comparative analysis was provided considering results of well‐established multiple testing approaches (Dunnett's test) with particular consideration of the degree of overdispersion found in these data. It was shown that the CPCAT detects substantially more effects in earthworm field tests as statistically significant than standard t test approaches. This lowered the LOEC/NOEC for many chemical treatments to control comparisons. As a consequence, the statistically detected NOECs/LOECs were often set at lower percentage deviations between control and chemical treatment. This is the first time the performance of the CPCAT has been assessed within a comprehensive analysis of earthworm field study data. Environ Toxicol Chem 2021;40:1750–1760. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. [ABSTRACT FROM AUTHOR]

A sediment contact test (SCT) battery consisting of five ecotoxicological test systems was applied to 21 native freshwater sediments characterized by a broad variety of geochemical properties and anthropogenic contamination. Higher plants ( Myriophyllum aquaticum), nematodes ( Caenorhabditis elegans), oligochaetes ( Lumbriculus variegatus), zebrafish embryos ( Danio rerio), and bacteria ( Arthrobacter globiformis), representing various trophic levels and exposure pathways, were used as test organisms. The test battery detected sediment toxicity caused by anthropogenic pollution, whereas the various tests provided site-specific, nonredundant information to the overall toxicity assessment. Based on the toxicity pattern derived from the test battery, the sediments were classified according to a newly proposed classification system for sediment toxicity assessment. The SCT-derived classification generally agreed well with the application of consensus-based sediment quality guidelines (SQGs), especially with regard to sediments with high toxic potential. For sediments with low to medium toxic potential, the SQGs often underestimated the toxicity that was detected by the SCTs, underpinning the need for toxicity tests in sediment quality assessment. Environ. Toxicol. Chem. 2013;32:144-155. © 2012 SETAC [ABSTRACT FROM AUTHOR]