New Publications

Here, we studied the community composition of zooplankton in the Belgian part of the North Sea over the course of 1 year. We identified zooplankton using both a traditional approach based on morphological characteristics and by metabarcoding of a 650 bp fragment of the V4-V5 region of the 18S rRNA gene using nanopore sequencing. Using long rDNA sequences, we were able to identify several taxa at the species level, across a broad taxonomic scale. 
Neonicotinoid insecticides have become of global concern for the aquatic environment. Harpacticoid copepods are amongst the most sensitive organisms to neonicotinoids. We used these results in combination with publicly available ecotoxicity data to derive Environmental Quality Standards (EQS). These EQS were ultimately used in a single‐substance and mixture risk assessment for the Belgian part of the North Sea. 

The present study aimed at investigating interactive effects between dietary lipids and both short- and long-term exposures to a low, environmentally realistic, cadmium (Cd) concentration. We found that both dietary lipids and Cd exposure influenced fatty acid homeostasis and metabolism. 

Mechanistic population models are gaining considerable interest in ecological risk assessment. The dynamic energy budget approach for toxicity (debtox) and the general unified threshold model for survival (guts) is a well‐established theoretical framework that describes sub‐lethal and lethal effects of a chemical stressor, respectively. However, there have been limited applications of these models for mixtures of chemicals, especially to predict long‐term effects on populations.

The increasing number of chemicals detected in the marine environment underlines the need for appropriate prioritization strategies prior to further testing and potential inclusion into monitoring programs. Here, a prioritization strategy is proposed for chemicals detected in the North Sea over the last decade, through the development of a Concern Index (CI) using exposure and toxicity data obtained from peer-review publications and the ToxCast database, respectively. 

Organisms in the marine environment are being exposed to an increasing variety of chemicals. This research presents an effect-based monitoring method for the derivation of a margin of safety for environmentally realistic chemical mixtures. The method is based on a combination of passive sampling and ecotoxicity testing. Across eight marine samples, diatom growth inhibition was observed at REF ≥ 3.2 and margins of safety were found between REF 1.1–11.0. In addition, we found that reconstitution of extracts in HPLC-water was suitable to overcome the solvent-related challenges in biotesting that are usually associated with passive sampler extract spiking, whilst it still allowed REFs up to 44 in the biotest medium to be achieved.
Microplastics are ubiquitous pollutants within the marine environment, predominantly (>90%) accumulating in sediments worldwide. Here, we examine those characteristics of microplastics that are essential to adequately evaluate potential remediation techniques such as sedimentation and (air) flotation techniques. We analyzed the sinking behavior of typical microplastics originating from real plastic waste samples and identified the best-available drag model to quantitatively describe their sinking behavior.

The generalized bioavailability model (gBAM) has been proposed as an alternative to the biotic ligand model (BLM) for modeling bioavailability and chronic toxicity of copper. The gBAM combines a log‐linear effect of pH on free Cu2+ ion toxicity with BLM‐type parameters for describing the protective effects of major cations. In the present study, a WHAM VII‐based gBAM for fish has been parametrized based on an existing chronic (30d‐mortality) dataset of juvenile rainbow trout. Overall, the chronic Cu gBAM developed here is a valuable alternative for the existing chronic Cu BLM for rainbow trout and performs sufficiently well to be used in risk assessment according to currently accepted standards of bioavailability model performance. 

In order to predict whether populations are able to persist or adapt to such new conditions, it is essential to understand the molecular basis of such adaptations, which ultimately get translated into these physiological responses. To explore variation in population gene expression across time and space, we investigated transcriptome-level profiles of the calanoid copepod Temora longicornis, that were collected at four different locations in the Belgian Part of the North Sea (BPNS) on three different time points (April, June, October) in 2018. RNA-seq analysis of field collected adults identified large seasonal differences in gene expression, mainly between spring-summer and autumn samples.
The degree of biological variability within a population is an important factor for its ecological success. Yet, individual-based population models (IBMs) that utilize the Dynamic Energy Budget (DEB) theory as a mechanistic basis to simulate an individual's life history, largely rely on rule-of-thumb estimates of inter-individual variability of their parameter values. In this study, we explored how data from previous life-history experiments with the copepod Nitocra spinipes could be used to make realistic estimates of variability in DEB parameter values for this species.

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