Publications by authors named "K A C De Schamphelaere"
Exposure to chemical mixtures is the norm in natural environments. Yet, water quality regulations are still mostly constructed for individual chemicals. However, an important ambition of the European Green Deal is the future implementation of mixture toxicity to address the risks posed by the joint presence of multiple chemicals in aquatic ecosystems (e.
View Article and Find Full Text PDFWidespread use of ciprofloxacin (CIP) in surface waters has raised ecological and human health concerns. However, the measured environmental concentration (MEC) of CIP may not directly indicate its ecological impact because CIP bioavailability and thus toxicity are influenced by environmental factors, such as pH and dissolved organic carbon (DOC). The present study integrates CIP toxicity as a function of pH and DOC into an environmental risk assessment (ERA) of CIP in European surface waters.
View Article and Find Full Text PDFPopulation models can be a useful tool for ecological risk assessment to increase ecological realism. In the present study, population models were used to extrapolate toxicity test results of four metals (Ag, Cu, Ni, Zn) to the population level. In total, three primary producers, five invertebrate species, and five fish species were covered.
View Article and Find Full Text PDFArticle Synopsis
- The study investigates the effects of metal mixtures on daphnid and algal communities in a two-trophic level microcosm, revealing that the presence of metals can impact species interactions and community dynamics.
- Daphnid densities decreased with exposure to metals, while algal densities showed a positive response in the two-trophic context due to reduced grazing pressure, illustrating the complexity of food web interactions.
- Results indicate that metal effects do not act independently but instead propagate across trophic levels, highlighting the limitations of traditional effect assessment models which fail to account for these dynamic community-level interactions.
Population models are increasingly used to predict population-level effects of chemicals. For trout, most toxicity data are available on early-life stages, but this may cause population models to miss true population-level effects. We predicted population-level effects of copper (Cu) on a brook trout (Salvelinus fontinalis) population based on individual-level effects observed in either a life-cycle study or an early-life stage study.
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