New Publications

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.

Freshwater biota are usually exposed to mixtures of different metals in the environment, which raises concern because risk-assessment procedures for metals are still mainly based on single-metal toxicity. Because microalgae are primary producers and therefore at the base of the food web, it is of utmost importance to understand the effects of metal mixtures on these organisms. The objective of the present study was to test if combined effects of mixtures to Pseudokirchneriella subcapitata were the same or different across natural waters showing diverse water-chemistry characteristics. This was done by performing experiments with ternary Cu–Ni–Zn mixtures in 3 natural waters and with binary Cu–Ni mixtures in 5 natural waters.

Little is known about the effect of metal mixtures on marine organisms, especially after exposure to environmentally realistic concentrations. This information is, however, required to evaluate the need to include mixtures in future l risk assessment procedures. We assessed the effect of copper (Cu)–Nickel (Ni) binary mixtures on Mytilus edulis larval development using a full factorial design that included environmentally relevant metal concentrations and ratios.

Understanding and predicting ecosystem functioning under environmental change has become a focus in ecological research due to the impact of human activities on natural ecosystems and the services they deliver. Ecosystem functioning under stress can depend on whether the response traits driving changes in species densities also predict direct stress effects on the species’ contribution to functioning. Based on our results, we expect a disproportionate loss of functioning when traits driving species densities do not allow to maintain ecosystem functioning under stress.

Tetracycline is a commonly used antibiotic in aquaculture, veterinary and agriculture. Due to its widespread use, tetracycline is commonly found in our environment where it can harm other organisms. Here we studied the effects of tetracycline on the waterflea daphnia. We particularly focused on studying the long-term effects of tetracycline, which consists of three generations of daphnia exposed to tetracycline (from grandparents to grandchildren) at the molecular level. We observed effects of tetracycline in all generations particularly targeted the molting related genes, which are in daphnia also responsible for growth. We also observed that when exposing daphnia to different concentrations of tetracycline specific genes called vitellogenin were affected and these genes could be linked to effects on reproduction. Our results show that the effects of chemicals to different generations and to different concentrations are very different and that these effects cannot be neglected in the environmental risk assessment of tetracycline.

Metal contamination of rivers and streams generally occurs as a combination of multiple metals (also called mixtures). However, it is yet unresolved how risks of mixed metal contamination to ecosystems should be evaluated. To increase the knowledge about chronic mixture effects, the authors investigated whether metal mixture effects are dependent on the biological species, mixture composition, and metal concentration ratio. The authors evaluated the effects of quaternary Ni-Zn-Cu-Cd and ternary Ni-Zn-Cu mixtures on 48-h algal growth rate (Pseudokirchneriella subcapitata) and 7-d daphnid reproduction (Ceriodaphnia dubia) using a ray design.

To obtain a better understanding of the biological responses to unpredictable environmental change, the early transcriptional response of the keystone species Daphnia magna to twelve environmental perturbations was characterised. We discovered that approximately one-third of the Daphnia genes, enriched for metabolism, cell signalling and general stress response, drives transcriptional early response to environmental stress and it is shared among genetic backgrounds. 

To assess the consequences of ongoing biodiversity changes, hundreds of biodiversity experiments have been carried out since the 1990s. However, changes in ecosystem functioning between systems can not only result from differences in the number of species, but also from differences in what species are present (i.e. species identities). Additive partitioning methods are therefore generally used in biodiversity research. These factor out species identify effects by comparing the observed level of ecosystem functioning against that predicted by the null model for the given species composition of the system. These species’ deviations from the null can be partitioned between several terms reflecting the various mechanisms through which biodiversity can affect ecosystem functioning. Current partitioning methods, however, quantify biodiversity effects based on linear relationships between species functional traits and their deviations from the null model. In this paper, we demonstrate that non-linear relationships frequently occur, and derived a non-linear extension of additive partitioning methods to quantify these more complex biodiversity effects on ecosystem functioning.

Toxicity of metals like zinc (Zn) to freshwater organisms is not only dependent on the concentration of the metals itself, but also on other properties of the water, like its hardness and its acidity (pH). This is called bioavailability. In the European Union, safe levels of Zn can be calculated as a function of these properties, using so-called bioavailability models. Previously, the existing models could not be applied to more than 25% of European waters, because hardness or pH were higher than those for which the models were originally developed. In this research, we have shown with new experimental work that the existing model for algae can also be used at a much wider range of hardness and pH than previously thought. Our work with water fleas, however, showed that the existing model needed to be considerably improved.
Metal contamination of rivers and streams generally occurs as a combination of multiple metals (so called mixtures). However, it is yet unresolved how risks of mixed metal contamination to ecosystems should be evaluated. We collated data from 30 different toxicity tests with metal mixtures and analysed them in a systematic way to derive general conclusions that can be used in risk assessment. We found  cases in which different metals, each individually causing <10% toxicity (relative to uncontaminated water), caused much larger toxicity (up to 66%) when combined. This suggests that the current metal-by-metal approach in risk assessment may not be conservative enough for the environment. We also considered the use of two common mixture toxicity models to predict metal mixture toxicity.