Mesocosm experiments that study the ecological impact of chemicals are often analysed using the multivariate method 'Principal Response Curves' (PRCs). Recently, the extension of generalised linear models (GLMs) to multivariate data was introduced as a tool to analyse community data in ecology. Moreover, data aggregation techniques that can be analysed with univariate statistics have been proposed. The aim of this study was to compare their performance. We compiled macroinvertebrate abundance datasets of mesocosm experiments designed for studying the effect of various organic chemicals, mainly pesticides, and re-analysed them. GLMs for multivariate data and selected aggregated endpoints were compared to PRCs regarding their performance and potential to identify affected taxa. In addition, we analysed the inter-replicate variability encountered in the studies. Mesocosm experiments characterised by a higher taxa richness of the community and/or lower taxonomic resolution showed a greater inter-replicate variability, whereas variability decreased the more zero counts were encountered in the samples. GLMs for multivariate data performed equally well as PRCs regarding the community response. However, compared to first axis PRCs, GLMs provided a better indication of individual taxa responding to treatments, as separate models are fitted to each taxon. Data aggregation methods performed considerably poorer compared to PRCs. Multivariate community data, which are generated during mesocosm experiments, should be analysed using multivariate methods to reveal treatment-related community-level responses. GLMs for multivariate data are an alternative to the widely used PRCs.

Introduction and backgroundPrimary producers play critical structural and functional roles in aquatic ecosystems; therefore, it is imperative that the potential risks of toxicants to aquatic plants are adequately assessed in the risk assessment of chemicals. The standard required macrophyte test species is the floating (non-sediment-rooted) duckweed Lemna spp. This macrophyte species might not be representative of all floating, rooted, emergent, and submerged macrophyte species because of differences in the duration and mode of exposure; sensitivity to the specific toxic mode of action of the chemical; and species-specific traits (e.g., duckweed's very short generation time).Discussion and perspectivesThese topics were addressed during the workshop entitled “Aquatic Macrophyte Risk Assessment for Pesticides” (AMRAP) where a risk assessment scheme for aquatic macrophytes was proposed. Four working groups evolved from this workshop and were charged with the task of developing Tier 1 and higher-tier aquatic macrophyte risk assessment procedures. Subsequently, a SETAC Advisory Group, the Macrophyte Ecotoxicology Group (AMEG) was formed as an umbrella organization for various macrophyte working groups. The purpose of AMEG is to provide scientifically based guidance in all aspects of aquatic macrophyte testing in the laboratory and field, including prospective as well as retrospective risk assessments for chemicals. As AMEG expands, it will begin to address new topics including bioremediation and sustainable management of aquatic macrophytes in the context of ecosystem services.

Because of their high ecological relevance, algae are often used in environmental monitoring of freshwater ecosystems. They are used to assess the state of the environment, and can be used to estimate the diversity and productivity of the ecosystem. Chlorophyll a is the most commonly used indicator where no taxonomic information is obtained. In this two-year study, algae were monitored in small lotic waterbodies using a high precision method of evaluating algal pigments: delayed fluorescence (DF). The method allows quantifying algae and differentiating algal groups using pigments unique to each algal group. DF correlated strongly with biovolume (derived from cell count) data (r 2 D 0.94) and could therefore be recommended as a biomonitoring tool. In addition, seasonal dynamics in both the attached and suspended algal communities were studied. Both algal fractions displayed seasonal variations with either a single peak in biomass in summer (type 1), or with two peaks in biomass in spring and fall (type 2). Green algae dominated type 1 patterned communities whereas diatoms dominated type 2 patterned communities. Spatial synchronicity between sampling sites and waterbodies was observed within the studied watershed. Sampling time rather than spatial site selection was found to be a key factor in the study of algal communities in lotic bodies of water.

Aquatic mesocosms are complex test systems used within regulatory risk assessment of plant protection products. These model ecosystems allow researchers to capture interactions of multiple species under realistic environmental conditions. They enable assessment of direct and indirect effects of stressors at all trophic levels (i.e., from primary producers to secondary consumers) and impacts on ecosystem functions. Due to the limited ability to test the multitude of potential exposure scenarios, cross-linking aquatic mesocosm studies with virtual mesocosms, i.e., aquatic system models (ASMs), can serve to meet the demand for more environmental realism and ecological relevance in risk assessment. In this study, full control data sets from seven aquatic mesocosm studies conducted at a single test facility under GLP were analysed graphically and using descriptive statistics. Thereby, not only a comprehensive data base but also an insight into the species present, their dynamics over time, and variability in unchallenged mesocosms was observed. While consistency in dynamics could be discerned for physical and chemical parameters, variability was evident for several biological endpoints. This variability points to amplification of small differences over time as well as to stochastic processes. The outline of existing gaps and uncertainties in data leads to the estimation of what can be expected to be captured and predicted by ASMs.