title: Brief communication: the ecosystem perspective in ecotoxicology as a way forward for the ecological risk assessment of chemicals.
abstract: One of the objectives of the European Union (EU) ecological risk assessment of chemicals (ERA) is to derive maximum environmental concentrations that are not expected to cause adverse ecological effects. To this end, related EU directives list protection goals as well as guidelines that should be used to reach these goals. It is generally accepted that the individual-level endpoints on which these guidelines are based do not correspond to the listed population- and ecosystem-level protection goals. In this article, we identify 5 research topics that are key to bridging this gap: 1) the refinement of population-level effects and recovery rates by explicitly taking into account competition and 2) predation, 3) the assessment of chemical effects on biodiversity, 4) the assessment of chemical stress on ecosystem functions and services, and 5) the quantification of the effects of chemical mixtures. In addition, we illustrate why an ecosystem perspective is needed to address these topics and to inform the risk assessment process. We propose the use of existing ecotoxicological community, food web, and ecosystem models to tackle these issues and discuss why new models are needed to predict chemical effects on biodiversity.
authors.affiliation: Laboratory of Environmental Toxicology and Aquatic Ecology, Gent, Belgium. Frederik.delaender@ugent.be
authors.forename: Frederik
authors.initials: F
authors.lastname: De Laender
authors.forename: Colin R
authors.initials: CR
authors.lastname: Janssen
mesh_terms: D044822:Biodiversity; D017753:Ecosystem; D054750:Ecotoxicology / Q000379:methods*; D004781:Environmental Exposure; D004784:Environmental Monitoring / Q000379:methods*; D020387:Food Chain; D008954:Models, Biological; D018570:Risk Assessment / Q000379:methods; D014874:Water Pollutants, Chemical / Q000633:toxicity*
chemical_list: D014874:Water Pollutants, Chemical
keywords: Biodiversity; Community models; Ecosystem models; Food-web models; Risk assessment