New Publications

The effect of multiple stressors on marine ecosystems remains poorly understood and most of the knowledge available is related to phytoplankton. To partly address this knowledge gap, we tested if combining multimodel inference with generalized additive modelling could quantify the relative contribution of environmental variables on the population dynamics of a zooplankton species in the Belgian part of the North Sea.

In collaboration with researchers from the Norwegian Institute for Water Research, we developed a framework to study the effects of combined environmental stress at the molecular level. This framework can provide a new way to tackle the challenges of combined stressors in risk assessment. Addressing these challenges is crucial as ecosystems are often exposed to a multitude of stressors, both chemical and natural.

In collaboration with researchers from the French nuclear institute, we studied the effects of gamma radiation on the waterflea. We have observed that effect of gamma radiation o the methylation of DNA in the first generation of animals are transmitted to the subsequent unexposed generations of offspring (children and grandchildren). Studying the effects of radiation across multiple generations will give us a better insight into the effects of nuclear power plants and other sources of radiation on our ecosystems.

Ecological risk assessment (ERA) is commonly based on single generation ecotoxicological tests that are usually performed at one standard temperature. We investigate the effects of nickel (Ni) on Daphnia magna reproduction at 15, 20 and 25°C along four generations.
The population structure of the non-indigenous calanoid copepod Pseudodiaptomus marinus (Sato, 1913) in the Belgian part of the North Sea (BPNS) is reported for the first time. Detailed P. marinus abundance data including sex and age class of the individuals was gathered on a monthly basis from February 2015 to February 2016 at six sites within the BPNS and Belgian harbors.
Under natural conditions, organisms can experience a variety of abiotic (e.g. temperature, pH) and biotic (e.g. species interactions) conditions, which can interact with toxicant effects. By ignoring species interactions conventional ecotoxicological studies (i.e. single species tests) oversimplify the actual field situation. Here, we investigated whether temperature and interspecific competition affected the effects of zinc on a Daphnia longispina population.
Urban regions of the world are expanding rapidly, placing additional stress on water resources. These water bodies receive chemical emissions arising from either single or multiple point sources, diffuse sources which can be continuous, intermittent, or seasonal. Thus, aquatic organisms in these water bodies are exposed to temporally and compositionally variable mixtures. We have delineated source-specific signatures of these mixtures for diffuse urban runoff and urban point source exposure scenarios to support risk assessment and management of these mixtures.

Copepods are an important component of aquatic ecosystems and constitute a large portion of the total animal biomass on earth. Over the last few decades, the copepod Nitocra spinipes has become a popular test species in environmental toxicity studies. While the amount of short- and long-term toxicity data for this species keeps increasing, little is known about the mechanisms that lead to observable effects on e.g. its growth, development, and reproduction. The Dynamic Energy Budget (DEB) theory can help increase our understanding of those processes. 

Although metal mixture toxicity has been studied relatively intensely, there is no general consensus yet on how to incorporate metal mixture toxicity into aquatic risk assessment. Here, we combined existing data on chronic metal mixture toxicity at the species level with species-sensitivity-distribution (SSD)-based in-silico metal mixture risk predictions at the community-level for mixtures of Ni, Zn, Cu, Cd and Pb, in order to develop a tiered risk assessment scheme for metal mixtures in freshwater.

In ponds, lakes and other water bodies, organisms face a multitude of environmental challenges which include chemical pollution and harmful algal blooms. To better understand and protect our water bodies, we need to be able to model and predict how organisms grow and reproduce under these environmental challenges. Here, we use gene expression patterns in combination with network methodology and statistical modelling to predict the reproduction of waterfleas after exposure to insecticides and cyanobacteria at environmentally relevant concentrations. Our developed models were able to predict reproduction of waterfleas under these different conditions. In particular, the models were able to predict the combined effect of combinations of insecticides and cyanobacteria on the reproduction of the waterfleas. These results provide a valuable mechanistic framework that consists of using gene expression data to quantify higher level effects.

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