A new regression model for overdispersed binomial data accounting for outliers and an excess of zeros.

Binary outcomes are extremely common in biomedical research. Despite its popularity, binomial regression often fails to model this kind of data accurately due to the overdispersion problem. Many alternatives can be found in the literature, the beta-binomial (BB) regression model being one of the most popular. The additional parameter of this model enables a better fit to overdispersed data. It also exhibits an attractive interpretation in terms of the intraclass correlation coefficient. Nonetheless, in many real data applications, a single additional parameter cannot handle the entire excess of variability. In this study, we propose a new finite mixture distribution with BB components, namely, the flexible beta-binomial (FBB), which is characterized by a richer parameterization. This allows us to enhance the variance structure to account for multiple causes of overdispersion while also preserving the intraclass correlation interpretation. The novel regression model, based on the FBB distribution, exploits the flexibility and large variety of the distribution's possible shapes (which includes bimodality and various tail behaviors). Thus, it succeeds in accounting for several (possibly concomitant) sources of overdispersion stemming from the presence of latent groups in the population, outliers, and excessive zero observations. Adopting a Bayesian approach to inference, we perform an intensive simulation study that shows the superiority of the new regression model over that of the existing ones. Its better performance is also confirmed by three applications to real datasets extensively studied in the biomedical literature, namely, bacteria data, atomic bomb radiation data, and control mice data.

Eutrophic status influences the impact of pesticide mixtures and predation on Daphnia pulex populations.

Pesticides, nutrients, and ecological stressors such as competition or predation co-occur in freshwater ecosystems impacted by agriculture. The extent to which combinations of these stressors affect aquatic populations and the role of nutrients availability in modulating these responses requires further understanding. In this study, we assessed how pesticides affecting different taxonomic groups and predation influence the response of Daphnia pulex populations under different trophic conditions. An outdoor experiment was designed following a factorial design, with the insecticide chlorpyrifos, the herbicide diuron, and the predation by Notonecta sp. individuals as key stressors. The single impact of each of these stressors, and their binary and tertiary combinations, was evaluated on D. pulex abundance and population structure under mesotrophic and eutrophic conditions for 21 days. Data were analyzed using generalized linear mixed models estimated by means of a novel Bayesian shrinkage technique. Our study shows a significant influence of each of the evaluated stressors on D. pulex abundance; however, the impacts of the herbicide and predation were lower under eutrophic conditions as compared to the mesotrophic ones. We found that binary stressor interactions were generally additive in the mesotrophic scenario, except for the herbicide-predation combination, which resulted in synergistic effects. The impacts of the binary stressor combinations in the eutrophic scenario were classified as antagonistic, except for the insecticide-herbicide combination, which was additive. The tertiary interaction resulted in significant effects on some sampling dates; however, these were rather antagonistic and resembled the most important binary stressor combination in each trophic scenario. Our study shows that the impact of pesticides on freshwater populations depends on the predation pressure, and demonstrates that the combined effect of pesticides and ecological stressors is influenced by the food availability and organism fitness related to the trophic status of freshwater ecosystems.

Ecological hazard assessment via species sensitivity distributions: The non-exchangeability issue.

Probabilistic approaches to hazard assessment use species sensitivity distributions (SSDs) to characterize hazard for toxicants exposure for different species within a community. Many of the assumptions at the core of SSDs are unrealistic, among them the assumption that the tolerance levels of all species in a specific ecological community are a priori exchangeable for each new toxic substance. Here we propose the use of a particular test to detect situations where such an assumption is violated. Then, a new method based on non-nested random effects model is required to identify novel SSDs capable of taking into account species non-exchangeability. Credible intervals, representing SSD uncertainty, could be determined based on our procedure. This leads to new and reliable estimates of the environmental hazard. We present a Bayesian modeling approach to address model inference issues, using Markov chain Monte Carlo sampling.

A new mixed-effects mixture model for constrained longitudinal data.

Biomedical research often features continuous responses bounded by the interval [0, 1]. The well-known beta regression model addresses the constrained nature of these data, while its augmented and mixed-effects variants can address the presence of zeros and/or ones and longitudinal or clustered response values, respectively. However, these models are not robust to the presence of outliers and/or excessive number of observations near the tails. We propose a new augmented mixed-effects regression model based on a special beta mixture distribution that is capable of handling these issues. Extensive simulation studies show the superiority of the proposed model to the models most often used in the literature. The proposed model is applied to two real datasets: one taken from a long-term study of Parkinson's disease and the other taken from a study on reading accuracy.

Natural variability of biochemical biomarkers in the macro-zoobenthos: Dependence on life stage and environmental factors.

Biomarkers are widely used in ecotoxicology as indicators of exposure to toxicants. However, their ability to provide ecologically relevant information remains controversial. One of the major problems is understanding whether the measured responses are determined by stress factors or lie within the natural variability range. In a previous work, the natural variability of enzymatic levels in invertebrates sampled in pristine rivers was proven to be relevant across both space and time. In the present study, the experimental design was improved by considering different life stages of the selected taxa and by measuring more environmental parameters. The experimental design considered sampling sites in 2 different rivers, 8 sampling dates covering the whole seasonal cycle, 4 species from 3 different taxonomic groups (Plecoptera, Perla grandis; Ephemeroptera, Baetis alpinus and Epeorus alpicula; Tricoptera, Hydropsyche pellucidula), different life stages for each species, and 4 enzymes (acetylcholinesterase, glutathione S-transferase, alkaline phosphatase, and catalase). Biomarker levels were related to environmental (physicochemical) parameters to verify any kind of dependence. Data were statistically elaborated using hierarchical multilevel Bayesian models. Natural variability was found to be relevant across both space and time. The results of the present study proved that care should be paid when interpreting biomarker results. Further research is needed to better understand the dependence of the natural variability on environmental parameters. Environ Toxicol Chem 2017;36:3158-3167. © 2017 SETAC.

Risk of POP mixtures on the Arctic food chain.

The exposure of the Arctic ecosystem to persistent organic pollutants (POPs) was assessed through a review of literature data. Concentrations of 19 chemicals or congeneric groups were estimated for the highest levels of the Arctic food chain (Arctic cod, ringed seals, and polar bears). The ecotoxicological risk for seals, bears, and bear cubs was estimated by applying the concentration addition (CA) concept. The risk of POP mixtures was very low in seals. By contrast, the risk was 2 orders of magnitude higher than the risk threshold for adult polar bears and even more (3 orders of magnitude above the threshold) for bear cubs fed with contaminated milk. Based on the temporal trends available for many of the chemicals, the temporal trend of the mixture risk for bear cubs was calculated. Relative to the 1980s, a decrease in risk from the POP mixture is evident, mainly because of international control measures. However, the composition of the mixture substantially changes, and the contribution of new POPs (particularly perfluorooctane sulfonate) increases. These results support the effectiveness of control measures, such as those promulgated in the Stockholm Convention, as well as the urgent need for their implementation for new and emerging POPs. Environ Toxicol Chem 2017;36:1181-1192. © 2017 SETAC.

Toxicity on the luminescent bacterium Vibrio fischeri (Beijerinck). II: Response to complex mixtures of heterogeneous chemicals at low levels of individual components.

The toxicity of eight complex mixtures of chemicals with different chemical structures and toxicological modes of action (narcotics, polar narcotics, herbicides, insecticides, fungicides) was tested on the luminescent bacterium Vibrio fischeri. There were maximum 84 individual chemicals in the mixtures. Suitable statistical approaches were applied for the comparison between experimental results and theoretical predictions. The results demonstrated that the two models of Concentration Addition (CA) and Independent Action (IA) are suitable to explain the effect of the mixtures.Even extremely lower concentrations of individual chemicals contributed to the effect of the mixtures. Synergistic effects were not observed in any of the tested mixtures. In particular, the CA approach well predicted the effects of six out of eight mixtures and slightly overestimated the effects of the remaining two mixtures. Therefore, the CA model can be proposed as a pragmatic and adequately protective approach for regulatory purposes.

SSD-based rating system for the classification of pesticide risk on biodiversity.

A novel approach, based on Species sensitivity distribution (SSD), is proposed for the development of an index for classifying ecotoxicological pesticide risk in surface waters. In this approach, the concept of TER (Toxicity Exposure Ratio), commonly used in traditional risk indices, is substituted by the concept of PAF (Potentially Affected Fraction), which takes into account several species within the biological community of interest, rather than just a small number of indicator species assumed as being representative of the ecosystem. The procedure represents a probabilistic tool to quantitatively assess the ecotoxicological risk on biodiversity considering the distribution of toxicological sensitivity. It can be applied to assess chemical risk on generic aquatic and terrestrial communities as well as on site-specific natural communities. Examples of its application are shown for some pesticides in freshwater ecosystems. In order to overcome the problem of insufficient reliable ecotoxicological data, a methodology and related algorithms are proposed for predicting SSD curves for chemicals that do not have sufficient available data. The methodology is applicable within congeneric classes of chemicals and has been tested and statistically validated on a group of organophosphorus insecticides. Values and limitations of the approach are discussed.

Toxicity on the luminescent bacterium Vibrio fischeri (Beijerinck). I: QSAR equation for narcotics and polar narcotics.

Toxicity data on chemicals, supposed to have a narcotic or polar narcotic toxicological mode of action, have been produced on the luminescent bacterium Vibrio fischeri using the Microtox test procedure. Advanced statistical methods have been used to calculate statistically sound values for ecotoxicological endpoints. Simple quantitative structure activity relationship (QSAR) equations were developed for narcotics and polar narcotics. These equations were compared with those proposed by the European Technical Guidance Document on Risk Assessment for other aquatic organisms (algae, Daphnia, and fish). Similarities and differences are discussed. The need for including the bacterial component in the ecotoxicological risk assessment for aquatic ecosystems is highlighted.