Evaluation of interregional consistency in associations between neonicotinoid insecticides and functions of benthic invertebrate communities in rivers in urban rice-paddy areas

Dinotefuran exposure alters biochemical, metabolomic, gut microbiome, and growth responses in decapoda pacific white shrimp Penaeus vannamei

Dinotefuran, a neonicotinoid insecticide, may impact nontarget organisms such as Decapoda P. vannamei shrimp with nervous systems similar to insects. Exposing shrimp to low dinotefuran concentrations (6, 60, and 600 μg/L) for 21 days affected growth, hepatosomatic index, and survival. Biomarkers erythromycin-N-demethylase, alanine aminotransferase, and catalase increased in all exposed groups, while glutathione S-transferase is the opposite; aminopyrin-N-demethylase, malondialdehyde, and aspartate aminotransferase increased at 60 and 600 μg/L. Concentration-dependent effects on gut microbiota altered the abundance of bacterial groups, increased potentially pathogenic and oxidative stress-resistant phenotypes, and decreased biofilm formation. Gram-positive/negative microbiota changed significantly. Metabolite differences between the exposed and control groups were identified using mass spectrometry and KEGG pathway enrichment. N-acetylcystathionine showed potential as a reliable dinotefuran metabolic marker. Weighted correlation network analysis (WGCNA) results indicated high connectivity of cruecdysone in the metabolite network and significant enrichment at 600 μg/L dinotefuran. The WGCNA results revealed a highly significant negative correlation between two key metabolites, caldine and indican, and the gut microbiota within co-expression modules. Overall, the risk of dinotefuran exposure to non-target organisms in aquatic environments still requires further attention.

Experiments and simulation of adsorption characteristics of typical neonicotinoids in urban stream sediments

Sediment adsorption is one of the main environmental fates of neonicotinoids (NEOs) in aquatic environments. Little information is available on for the adsorption characteristics of NEOs on urban stream sediments. In this study, urban tidal stream sediments were collected to determine the adsorption properties of four selected NEOs. The influence of environmental factors on NEO adsorption was determined by the RSM-CCD method. The NEO adsorption rates on sediments were established by multiple regression equations. As a result, the adsorption of four NEOs onto sediments fitted a linear isotherm model. The adsorption amounts of thiacloprid (THA), clothianidin (CLO), acetamiprid (ACE), and imidacloprid (IMI) were 1.68 to 2.24, 1.71 to 2.89, 1.88 to 3.07, and 2.23 to 3.16 mg/kg, respectively. The adsorption processes of four NEOs on urban sediments were favorable. Moreover, adsorption behaviors of NEOs were typical physical adsorption and readily adsorbed onto urban sediments. The adsorption processes of NEOs were exothermic reactions, and their adsorption rates decreased with increasing pH. Flow rates and organic matter contents could promote the adsorption ratios of typical NEOs. Multiple linear regression was used to assess the relationships between the adsorption rates of NEOs and environmental factors. The p-values of the fitting equations of adsorption rates were all less than 0.05. Within the ranges of concentration of the investigated factors, the multiple regression equations were able to reasonably model and predict the sorption of typical NEOs onto urban stream sediments. Therefore, the adsorption rate equations effectively predicted the NEO adsorption performance of urban streams and were helpful for controlling risk assessment of NEOs.

What do we want to estimate from observational datasets? Choosing appropriate statistical analysis methods based on the chemical management phase

The goals of observational dataset analysis vary with the management phase of environments threatened by anthropogenic chemicals. For example, identifying severely compromised sites is necessary to determine candidate sites in which to implement measures during early management phases. Among the most effective approaches is developing regression models with high predictive power for dependent variable values using the Akaike information criterion. However, this analytical approach may be theoretically inappropriate to obtain the necessary information in various chemical management phases, such as the intervention effect size of a chemical required in the late chemical management phase to evaluate the necessity of an effluent standard and its specific value. However, choosing appropriate statistical methods based on the data analysis objective in each chemical management phase has rarely been performed. This study provides an overview of the primary data analysis objectives in the early and late chemical management phases. For each objective, several suitable statistical analysis methods for observational datasets are detailed. In addition, the study presents examples of linear regression analysis procedures using an available dataset derived from field surveys conducted in Japanese rivers. Integr Environ Assess Manag 2022;18:1414-1422. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Pond chironomid communities revealed by molecular species delimitation reflect eutrophication

Farm ponds, a valued habitat for freshwater organisms, are being negatively affected by the recent changes in the environment as well as anthropological activities. In these ponds, biodiversity researchers have tended to focus on species that prefer natural habitats and/or can be identified based on morphological characters. In contrast, this study focused on the insect family Chironomidae, which is widely distributed from clear to polluted waters of ponds, but is hard to identify morphologically as an aquatic larva. We adopted DNA barcoding and molecular species delimitation to identify every single specimen of quantitative collections. From bottom sediments of 17 ponds in summer in the Banshu Plain of Japan, a total of 62 species were delimited based on the DNA sequences of the mitochondrial COI region. Chironomid communities from these ponds were classified into four groups in a two-dimensional ordination of multivariate analysis (NMDS). One of the dimensions was well correlated with the gradient of eutrophication, while another dimension was not clearly assigned to any general feature of the environmental gradient, but rice cultivation could possibly be involved.