Moving Beyond p < 0.05 in Ecotoxicology: A Guide for Practitioners

Meta-analysis of vegetation responses to experimental nitrogen enrichments done in salt marshes under different sea level rise regimes reveal interaction of N supply and sea level rise

Agricultural-style fertilization studies to assess responses of salt marsh vegetation to increased nitrogen supply have been done in many coastal regions of the world. Initial enrichment experiments first revealed the role of nitrogen (N) supply as a key control of vegetation responses. A review of results from 43 N-fertilization studies carried out in a variety of coasts worldwide found increased responses by above-ground salt marsh vegetation in 94.5 % of the enrichments. The responses, although variable, increased significantly as N supply increased, confirming the limiting function of N supply. Enrichments with urea, a mix of N forms, or ammonium were more effective than enrichment with nitrate. Synthesis of compiled data suggested an interaction of N supply with sea level rise may be important. Sea level rise >3.4 mm yr-1 damped the ability of above-ground salt marsh vegetation to respond to increased N supply, and it is possible that critical thresholds (about 15 mm yr-1) for above-ground marsh vegetation may be reached by 2100. Below-ground vegetation responses were not greatly affected by N enrichment in the data compiled, but as sea level increases in the future, data trendlines suggest a possible future threshold (perhaps about 9 mm yr-1) in submergence that would impair below-ground vegetation responses. These findings suggest that sea level rise effects may overwhelm the positive effects of increased N supply, an interaction that may impair salt marsh vegetation function, leading to increasing future submergence of these valuable habitats. These results emphasize the urgency for new mitigation strategies.

Revealing the mediating mechanisms between BMI and osteoarthritis: a Mendelian randomization and mediation analysis

BACKGROUND

Despite well-documented associations between Body mass index (BMI) and Osteoarthritis (OA), the specific biological pathways and mediators involved remain poorly understood. This study aims to explore mediators through which BMI influences OA risk, particularly knee osteoarthritis (KOA), using Mendelian Randomization (MR) and mediation analysis.

METHODS

We used a two-step MR approach with data from the IEU OpenGWAS and FinnGen version 7 databases. BMI (N = 322,154) was the primary exposure, with knee disorders (KD), total bone mineral density (TBMD), metabolic disorders (MD), and anxiety disorders (AD) as potential mediators. Outcomes included KOA (N = 22,347), hip OA (HOA) (N = 11,989), and all OA (AllOA) (N = 50,508). Univariate MR evaluated causal relationships, followed by multivariate MR to quantify mediation effects. Multiple sensitivity analyses were conducted to validate robustness, while horizontal pleiotropy and heterogeneity were assessed using MR-Egger intercept and Cochran's Q statistic.

RESULTS

BMI significantly increased the risk of KOA (odds ratio [OR]: 2.00, 95% confidence interval [CI]: 1.56-2.56), HOA (OR: 2.05, 95% CI: 1.40-2.98), and AllOA (OR: 1.66, 95% CI: 1.41-1.95). KD and TBMD significantly mediated the effect on KOA, with mediation proportions of 20.89% and 3.59%, respectively. MD and AD showed no significant effects. Sensitivity analyses supported the robustness of these findings. Horizontal pleiotropy and heterogeneity tests indicated minimal evidence of bias, supporting the reliability of our results.

CONCLUSIONS

BMI increases OA risk, with KD and TBMD partially mediating the effect, particularly for KOA. The direct impact of BMI remains predominant, emphasizing the importance of weight reduction, joint protection, and physical activity as preventive measures.

EthoCRED: a framework to guide reporting and evaluation of the relevance and reliability of behavioural ecotoxicity studies

Behavioural analysis has been attracting significant attention as a broad indicator of sub-lethal toxicity and has secured a place as an important subdiscipline in ecotoxicology. Among the most notable characteristics of behavioural research, compared to other established approaches in sub-lethal ecotoxicology (e.g. reproductive and developmental bioassays), are the wide range of study designs being used and the diversity of endpoints considered. At the same time, environmental hazard and risk assessment, which underpins regulatory decisions to protect the environment from potentially harmful chemicals, often recommends that ecotoxicological data be produced following accepted and validated test guidelines. These guidelines typically do not address behavioural changes, meaning that these, often sensitive, effects are not represented in hazard and risk assessments. Here, we propose a new tool, the EthoCRED evaluation method, for assessing the relevance and reliability of behavioural ecotoxicity data, which considers the unique requirements and challenges encountered in this field. This method and accompanying reporting recommendations are designed to serve as an extension of the "Criteria for Reporting and Evaluating Ecotoxicity Data (CRED)" project. As such, EthoCRED can both accommodate the wide array of experimental design approaches seen in behavioural ecotoxicology, and could be readily implemented into regulatory frameworks as deemed appropriate by policy makers of different jurisdictions to allow better integration of knowledge gained from behavioural testing into environmental protection. Furthermore, through our reporting recommendations, we aim to improve the reporting of behavioural studies in the peer-reviewed literature, and thereby increase their usefulness to inform chemical regulation.

Environmental Risk Assessment of Trace Metal Pollution: A Statistical Perspective

Trace metal pollution is primarily driven by industrial, agricultural, and mining activities and presents complex environmental challenges with significant implications for ecological and human health. Traditional methods of environmental risk assessment (ERA) often fall short in addressing the intricate dynamics of trace metals, necessitating the adoption of advanced statistical techniques. This review focuses on integrating contemporary statistical methods, such as Bayesian modeling, machine learning, and geostatistics, into ERA frameworks to improve risk assessment precision, reliability, and interpretability. Using these innovative approaches, either alone or preferably in combination, provides a better understanding of the mechanisms of trace metal transport, bioavailability, and their ecological impacts can be achieved while also predicting future contamination patterns. The use of spatial and temporal analysis, coupled with uncertainty quantification, enhances the assessment of contamination hotspots and their associated risks. Integrating statistical models with ecotoxicology further strengthens the ability to evaluate ecological and human health risks, providing a broad framework for managing trace metal pollution. As new contaminants emerge and existing pollutants evolve in their behavior, the need for adaptable, data-driven ERA methodologies becomes ever more pressing. The advancement of statistical tools and interdisciplinary collaboration will be essential for developing more effective environmental management strategies and informing policy decisions. Ultimately, the future of ERA lies in integrating diverse data sources, advanced analytical techniques, and stakeholder engagement, ensuring a more resilient approach to mitigating trace metal pollution and protecting environmental and public health.

A clustering-based survival comparison procedure designed to study the Caenorhabditis elegans model

Caenorhabditis elegans is highly important in current research, serving as a pivotal model organism that has greatly advanced the understanding of fundamental biological processes such as development, cellular biology, and neurobiology, helping to promote major advances in various fields of science. In this context, the survival of a nematode under various conditions is commonly investigated via statistical survival analysis, which is typically based on hypothesis testing, providing valuable insights into the factors influencing its longevity and response to various environmental factors. The extensive reliance on hypothesis testing is acknowledged as a concern in the scientific analysis process, emphasizing the need for a comprehensive evaluation of alternative statistical approaches to ensure a rigorous and unbiased interpretation of research findings. In this work, we propose an alternative method to hypothesis testing for evaluating differences in nematode survival. Our approach relies on a clustering technique that takes into account the complete structure of survival curves, enabling a more comprehensive assessment of survival dynamics. The proposed methodology helps to identify complex effects on nematode survival and enables us to derive the probability that treatment induces a specific effect. To highlight the application and benefits of the proposed methodology, it is applied to two different datasets, one simple and one more complex.

Versatile enhancement for anaerobic moving bed biofilm (AnMBBR) treating pretreated landfill leachate by hydrochar: Energy recovery, greenhouse gas emission reduction and underlying microbial mechanisms

Hydrochars were prepared from fruit peels (HC-1) and vegetable waste (HC-2), and combined with fiber spheres, respectively, to form homogeneous biocompatible carriers, which were used for anaerobic moving bed biofilm reactor (AnMBBR) to enhance anaerobic digestion (AD) performance and energy recovery of landfill leachate treatment. Compared with the control AnMBBR with conventional fiber spheres as carriers, the chemical oxygen demand (COD) removal efficiency of the AnMBBR with HC-2 increased from 75 % to 88 %, methane yield increased from 77.7 mL/g-COD to 155.3 mL/g-COD, and achieved greenhouse gases (GHG) emission reductions of 1.74 t CO2 eq/a during long-term operation. HC-2-fiber sphere biocarriers provided more sites for attached-growth biomass (AGBS) and significantly enhanced the abundance of functional microbial community, with the relative abundance of methanogenic bacteria Methanothrix increased from 0.03 % to over 24.4 %. Moreover, the gene abundance of most the key enzymes encoding the hydrolysis, acidogenesis and methanogenesis pathways were up-regulated with the assistance of HC-2. Consequently, hydrochar-assisted AnMBBR were effective to enhance methanogenesis performance, energy recovery and carbon reduction for high-strength landfill leachate treatment.

Wildlife ecological risk assessment in the 21st century: Promising technologies to assess toxicological effects

Despite advances in toxicity testing and the development of new approach methodologies (NAMs) for hazard assessment, the ecological risk assessment (ERA) framework for terrestrial wildlife (i.e., air-breathing amphibians, reptiles, birds, and mammals) has remained unchanged for decades. While survival, growth, and reproductive endpoints derived from whole-animal toxicity tests are central to hazard assessment, nonstandard measures of biological effects at multiple levels of biological organization (e.g., molecular, cellular, tissue, organ, organism, population, community, ecosystem) have the potential to enhance the relevance of prospective and retrospective wildlife ERAs. Other factors (e.g., indirect effects of contaminants on food supplies and infectious disease processes) are influenced by toxicants at individual, population, and community levels, and need to be factored into chemically based risk assessments to enhance the "eco" component of ERAs. Regulatory and logistical challenges often relegate such nonstandard endpoints and indirect effects to postregistration evaluations of pesticides and industrial chemicals and contaminated site evaluations. While NAMs are being developed, to date, their applications in ERAs focused on wildlife have been limited. No single magic tool or model will address all uncertainties in hazard assessment. Modernizing wildlife ERAs will likely entail combinations of laboratory- and field-derived data at multiple levels of biological organization, knowledge collection solutions (e.g., systematic review, adverse outcome pathway frameworks), and inferential methods that facilitate integrations and risk estimations focused on species, populations, interspecific extrapolations, and ecosystem services modeling, with less dependence on whole-animal data and simple hazard ratios. Integr Environ Assess Manag 2024;20:725-748. © 2023 His Majesty the King in Right of Canada and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

A novel approach to assessing natural resource injury with Bayesian networks

Quantifying the effects of environmental stressors on natural resources is problematic because of complex interactions among environmental factors that influence endpoints of interest. This complexity, coupled with data limitations, propagates uncertainty that can make it difficult to causally associate specific environmental stressors with injury endpoints. The Natural Resource Damage Assessment and Restoration (NRDAR) regulations under the Comprehensive Environmental Response, Compensation, and Liability Act and Oil Pollution Act aim to restore natural resources injured by oil spills and hazardous substances released into the environment; exploration of alternative statistical methods to evaluate effects could help address NRDAR legal claims. Bayesian networks (BNs) are statistical tools that can be used to estimate the influence and interrelatedness of abiotic and biotic environmental variables on environmental endpoints of interest. We investigated the application of a BN for injury assessment using a hypothetical case study by simulating data of acid mine drainage (AMD) affecting a fictional stream-dwelling bird species. We compared the BN-generated probability estimates for injury with a more traditional approach using toxicity thresholds for water and sediment chemistry. Bayesian networks offered several distinct advantages over traditional approaches, including formalizing the use of expert knowledge, probabilistic estimates of injury using intermediate direct and indirect effects, and the incorporation of a more nuanced and ecologically relevant representation of effects. Given the potential that BNs have for natural resource injury assessment, more research and field-based application are needed to determine their efficacy in NRDAR. We expect the resulting methods will be of interest to many US federal, state, and tribal programs devoted to the evaluation, mitigation, remediation, and/or restoration of natural resources injured by releases or spills of contaminants. Integr Environ Assess Manag 2024;20:562-573. Published 2023. This article is a U.S. Government work and is in the public domain in the USA. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Introducing the No-Significant-Effect Concentration

The no-effect concentration (NEC) is the preferred threshold metric for single-species toxicity tests applied to derive safe concentration thresholds for contaminants in the environment for use in species sensitivity distributions. However, the NEC is only suitable when concentration-response (C-R) data exhibit a threshold response. We describe an alternative toxicity estimate, the no-significant-effect concentration (NSEC), which is better suited to C-R data for which the response is a monotonically decreasing function of concentration and no threshold effects are evident. We use a flexible, three-parameter sigmoidal function to describe the C-R relationship and detail both Bayesian and frequentist approaches to estimation and inference for the NSEC. While the NSEC is conceptually linked to the traditional no-observed-effect concentration (NOEC), it is a substantial improvement over the NOEC because it decouples the estimate from being directly dependent on the placement of treatment concentrations as well as admitting statements of precision of the resulting toxicity estimate. Environ Toxicol Chem 2023;42:2019-2028. © 2023 Commonwealth of Australia and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Environmental pollution impacts: Are p values over-valued?

An examination revealed the dominance of the published literature of environmental science by p values. Meanwhile, the use of effect size has been neglected in publications reporting primary data, yet the size of effect is often more informative than p values inference in assessing the effects of pollution on living organisms, comparing susceptibility/resistance among organisms, and ranking pollutants according to their potency, among others. Statistical significance does not necessarily mean biological, practical, or scientific significance, and its use based on (often misinterpreted) p values reflects the average response or effect at average conditions based on an assumed linear model fit to the entire sample. However, pollution impacts and organismal responses are rarely characterized by linear and symmetric features, and dichotomous 'statistical significance' based on p values is inadequate to fully describe data and findings. Considering 'the fallacy of the average', variance, and differential response of different population percentiles in new studies would provide otherwise wasted biologically, practically, or scientifically significant information. Since p values often inform as to whether some findings warrant further examination, journals should consider mandating the reporting of effect sizes and confidence intervals, together with p values (should they be used), to provide more integrated information regarding pollution impacts. Moreover, replacing 'statistical significance' with language of evidence, especially in key components of publications, such as abstracts and conclusions, could help preventing potential misleading of the public and decision and policy makers.

Pesticide impacts on avian species with special reference to farmland birds: a review

For decades, we have observed a major biodiversity crisis impacting all taxa. Avian species have been particularly well monitored over the long term, documenting their declines. In particular, farmland birds are decreasing worldwide, but the contribution of pesticides to their decline remains controversial. Most studies addressing the effects of agrochemicals are limited to their assessment under controlled laboratory conditions, the determination of lethal dose 50 (LD₅₀) values and testing in a few species, most belonging to Galliformes. They often ignore the high interspecies variability in sensitivity, delayed sublethal effects on the physiology, behaviour and life-history traits of individuals and their consequences at the population and community levels. Most importantly, they have entirely neglected to test for the multiple exposure pathways to which individuals are subjected in the field (cocktail effects). The present review aims to provide a comprehensive overview for ecologists, evolutionary ecologists and conservationists. We aimed to compile the literature on the effects of pesticides on bird physiology, behaviour and life-history traits, collecting evidence from model and wild species and from field and lab experiments to highlight the gaps that remain to be filled. We show how subtle nonlethal exposure might be pernicious, with major consequences for bird populations and communities. We finally propose several prospective guidelines for future studies that may be considered to meet urgent needs.

Potential disruption of thyroid hormones by perfluoroalkyl acids in an Arctic seabird during reproduction

Arctic marine ecosystems are experiencing rapid change, such as ocean warming and enhanced pollutants. Perfluoroalkyl acids (PFAAs) arriving via long-range transport have been detected in Arctic wildlife, including seabirds which are considered sentinels of marine ecosystem health. There is evidence that PFAA exposure leads to the disruption of thyroid hormones (THs), such as thyroxine (T4) and triiodothyronine (T3), which play important roles in metabolism, incubation, and thermoregulation in seabirds. Here, we investigated relationships between PFAAs and THs [total T4 (TT4), free T4 (FT4), total T3 (TT3) and free T3 (FT3)] in blood plasma collected from 63 thick-billed murres (Uria lomvia) at a colony located in northern Hudson Bay (2016-2018). We then tested if PFAAs and TH levels were related to fitness-associated reproductive traits, such as body mass and hatch dates. PFUdA, PFOS, and PFTrDA were the dominant PFAAs in murre blood, accounting for approximately 77% of ∑PFAA. Females had higher PFAAs than males, possibly due to higher trophic feeding. While FT3 increased with PFOS, PFNA, PFDA, PFDoA, PFTeDA, ∑PFCA7, and ∑PFAA in murres, TT3 decreased with PFOS, PFDoA, and PFTeDA in males, but not females, suggesting thyroid disruption. TT3 increased with body mass, whereas several long-chain PFAAs were negatively correlated with body mass. Negative relationships between PFNA, PFDoA, PFTrDA, PFTeDA, and ∑PFAA with hatch dates may be the result of a disruption in incubation behaviour, resulting in earlier hatch dates. Consequently, TT3 concentrations were highest in males and females in 2018, a year in which PFAAs were lowest and hatch dates were delayed relative to 2017. As an Arctic seabird experiencing several indirect effects of climate change, the interaction of PFAAs on thyroid activity may cause additional stress to murres.

Toward a Universal Acute Fish Threshold of Toxicological Concern

Threshold of toxicological concern (TTC) is a concept that has been around for decades in human health sciences. Ecotoxicology recently adopted a variant of this concept as eco-TTC. Adoption of the concept of TTC considerably reduces the amount of animal testing required for regulatory purposes. We provide an application of a universal TTC for the entirety of acute fish toxicity data (i.e., establishment of an exposure level below which there would be minimal probability of acute fish toxicity for any chemical, without consideration of mechanism of action). We calculated TTC values for a number of subgroups using various approaches. These approaches were evaluated using data from a cohort of 69 999 acute fish toxicological assays. This database was normalized/curated for units, exposure duration, quality assurance/control, and duplicates, which reduced it to 47 694 assays. Data were not normally but log-normally distributed, making geometric means the most appropriate statistical parameter. Thus, we developed descriptive statistics using geometric means with 95, 99, and 99.9% confidence intervals. Various assessment factors (akin to predicted-no-effect concentration derivation) were applied to the geometric means to derive TTCs. Other approaches employed were the calculation of y = 0 intercepts as well as development of 95 and 99.75% cutoffs of cumulative data as well as modular uncertainty scoring tool (MUST) analysis. All of the methodologies derived highly congruent TTCs ranging from to 2 to 8 μg/L except for the 99.75th percentile cutoff of 0.3 μg/L. The data would be most useful in making a binary testing/no testing required decision. For acute fish toxicity, a TTC value of 2 μg/L was most appropriate, based on the 95th percentile of data distribution without any assessment factor. Environ Toxicol Chem 2021;40:1740-1749. © 2021 SETAC.

Correlations between Per- and Polyfluoroalkyl Substances and Body Morphometrics in Fledgling Shearwaters Impacted by Plastic Consumption from a Remote Pacific Island

We investigated the concentrations of 45 per- and polyfluoroalkyl substances (PFASs) in fledgling flesh-footed shearwater (Ardenna carneipes; n = 33) and wedge-tailed shearwater (A. pacifica; n = 9) livers via liquid chromatography-tandem mass spectrometry and their relationship to body morphometrics and ingested plastic mass recorded in 2019 on Lord Howe Island (NSW, Australia). Sixteen PFASs were detected, of which perfluorooctanesulfonate (PFOS) was the dominant compound, detected in 100% of birds (1.34-13.4 ng/g wet wt). Long-chain perfluorocarboxylic acids, including perfluorodecanoic acid (PFDA; <0.04-0.79 ng/g wet wt) and perfluorotridecanoic acid (PFTrDA; <0.05-1.6 ng/g wet wt) were detected in >50% of birds. There was a positive correlation between PFDA and PFTrDA concentrations and wing chord length (R_s  = 0.36, p = 0.0204; R_s  = 0.44, p = 0.0037, respectively), and between PFDA concentrations and total body mass (R_s  = 0.33, p = 0.032), suggesting that these compounds may impact shearwater fledgling morphometrics. Plastic was present in the intestinal tract of 79% of individuals (<7.6 g), although there was no correlation between PFAS concentrations and plastic mass, indicating that ingested plastic is not the likely primary exposure source. The widespread occurrence of PFASs in fledgling marine birds from a relatively pristine location in the Southern Hemisphere suggests that further studies in adult shearwaters and other marine birds are warranted to investigate whether there are any long-term physiological effects on bird species. Environ Toxicol Chem 2021;40:799-810. © 2020 SETAC.

Per- and Polyfluoroalkyl Substances Are Positively Associated with Thyroid Hormones in an Arctic Seabird

Per- and polyfluoroalkyl substances (PFAS) are associated with several disrupted physiological and endocrine parameters. Regarding endocrine mechanisms, laboratory studies suggest that PFAS could disrupt the thyroid hormone system and alter circulating thyroid hormone concentrations. Thyroid hormones play a ubiquitous role-controlling thermoregulation, metabolism, and reproduction. However, evidence for disruption of thyroid hormones by PFAS remains scarce in wildlife. The present study investigated the associations between concentrations of PFAS, thyroid hormones, and body condition in an arctic seabird, the black-legged kittiwake (Rissa tridactyla). We collected blood from kittiwakes sampled in Svalbard, Norway (2013 and 2014). Plasma samples were analyzed for total thyroxine (TT4) and total triiodothyronine (TT3) concentrations; detected PFAS included branched and linear (lin) C₈ perfluoroalkyl sulfonates (i.e., perfluoroctane sulfonate [PFOS]) and C₉ -C₁₄ perfluoroalkyl carboxylates (PFCAs). The dominant PFAS in the kittiwakes were linPFOS and C₁₁ - and C₁₃ -PFCAs. Generally, male kittiwakes had higher concentrations of PFAS than females. We observed positive correlations between linPFOS, C₁₀ -PFCA, and TT4 in males, whereas in females C_12-14 -PFCAs were positively correlated to TT3. Interestingly, we observed contrasted correlations between PFAS and body condition; the direction of the relationship was sex-dependent. Although these results show relationships between PFAS and circulating thyroid hormone concentrations in kittiwakes, the study design does not allow for concluding on causal relationships related to effects of PFAS on the thyroid hormone system. Future experimental research is required to quantify this impact of PFAS on the biology of kittiwakes. The apparently different associations among PFAS and body condition for males and females are puzzling, and more research is required. Environ Toxicol Chem 2021;40:820-831. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Long-Term Studies of Fish Health before and after the Closure of a Bleached Kraft Pulp Mill in Northern Ontario, Canada

Changes in ecosystems after the removal of stress provide a rich source of information for conservation science. We used a long-term regional data set on the performance of white sucker (Catostomus commersonii) collected before and after the closure of a pulp mill to explore recovery in fish. Physiological indicators, including liver enzymes and plasma steroids, showed some compelling changes after the closure of the mill consistent with reduced exposure to pulp mill effluent but did not unequivocally demonstrate recovery. However, persistent signals in these fish may indicate effects of impoundment or discharge of sewage. We also used quantile regression with environmental covariates and bootstrap iteration to determine if systematic variation remained in relative body weight, liver weight, and gonad weight. In fish formerly exposed to pulp mill effluent, we found evidence of improvements (male gonad weight and liver weight of males and females), degradation (gonad weight of females), and no change (body weight). Although the observed patterns may be associated with closure of the mill, some differences were also found at regional locations, suggesting roles of additional stressors and challenging the clear association of change at the Mattagami River exposure site with the closure of the mill. However, fish captured at this location show responses consistent with regional locations, suggesting no residual impacts and highlights the challenges of identifying changes in fish even after large and known interventions. Environ Toxicol Chem 2021;40:162-176. © 2020 SETAC.

The Minimum Detectable Difference (MDD) Concept for Establishing Trust in Nonsignificant Results: A Critical Review

Current regulatory guidelines for pesticide risk assessment recommend that nonsignificant results should be complemented by the minimum detectable difference (MDD), a statistical indicator that is used to decide whether the experiment could have detected biologically relevant effects. We review the statistical theory of the MDD and perform simulations to understand its properties and error rates. Most importantly, we compare the skill of the MDD in distinguishing between true and false negatives (i.e., type II errors) with 2 alternatives: the minimum detectable effect (MDE), an indicator based on a post hoc power analysis common in medical studies; and confidence intervals (CIs). Our results demonstrate that MDD and MDE only differ in that the power of the MDD depends on the sample size. Moreover, although both MDD and MDE have some skill in distinguishing between false negatives and true absence of an effect, they do not perform as well as using CI upper bounds to establish trust in a nonsignificant result. The reason is that, unlike the CI, neither MDD nor MDE consider the estimated effect size in their calculation. We also show that MDD and MDE are no better than CIs in identifying larger effects among the false negatives. We conclude that, although MDDs are useful, CIs are preferable for deciding whether to treat a nonsignificant test result as a true negative, or for determining an upper bound for an unknown true effect. Environ Toxicol Chem 2020;39:2109-2123. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.