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Modelling vs. experimental testing of chemical toxicity of environmental mixtures of pesticides on freshwater algae

Poster (konferens)
Författare Anton Sandblom
Thomas Backhaus
Natàlia Corcoll
Publicerad i SETAC Helsinki - SETAC Europe 29th Annual Meeting, 26 - 30 May 2019, Helsinki, Finland
Publiceringsår 2019
Publicerad vid Institutionen för biologi och miljövetenskap
Språk en
Länkar https://helsinki.setac.org
Ämneskategorier Biologiska vetenskaper, Geovetenskap och miljövetenskap, Kemi, Statistik, data- och systemvetenskap


Mixture toxicity modelling has emerged as a promising tool for mixture toxicity risk assessment, however, such models have not been fully validated against experimental testing. In our project we want to take a step further and compare risk assessment from mixtures of pesticides on algae between modeling and experimental testing using real environmental mixtures, and compare risk assessment models based on a single species-oriented approach vs. a species sensitivity distribution (SSD) approach. In this study, a field sampling was carried out in three agricultural streams, presenting different levels of pesticide pollution (SE Sweden), in September and October 2016. For each sampling site, pesticide levels in surface water and from passive samplers (e.g Chemcatchers) were analyzed. The risk of identified pesticide mixtures on freshwater algae was assessed by mixture toxicity modelling and with ongoing laboratory ecotoxicity tests using the field passive sampler extracts. Our ecotoxicity tests are performed in an optimized semi high-throughput assay (24/96-well microplates) for the freshwater algae Raphidocellis subcapitata based on algal growth, following the OECD protocol (201), to increase the capacity of ecotoxicological testing. Based on mixture toxicity modeling, five pesticides (three herbicides and two fungicides) with different modes of actin (MoA) were identified as the toxicity drivers in studied rivers. The toxicity of these compounds on algae is tested in two settings: single compounds exposure vs. artificial mixture. This will allow us to validate the precision and utility of the current prediction models - concentration addition (CA) and independent action (IA) - that are based on a single-species approach. The same workflow will be used to generate ecotoxicity data for five different species of freshwater algae from distant phylogenetic groups (i.e. Chlorophyta, Rhodophyta, Bacillariophyta, Cyanophyta and Chrysophyta), in order to produce species sensitivity distribution curves (SSD) and infer a community approach. The SSD approach is of particular interest since different species are expected to present different sensitivities to toxicity drivers (with different MoA) when exposed alone and in combination. Mixture toxicity modelling combined with the SSD approach might give us new insights on how to expand the mixture toxicity risk assessment for algae on a community level and use this tool for a better protection of the aquatic environment.

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