Utilizing environmental genomics to study multiple agricultural stressor impacts on stream invertebrates and ecosystem functions

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Biodiversity loss is proceeding at unprecedented rates with detrimental consequences for ecosystem functions and services. Stream ecosystems are especially impacted by this loss. Agricultural stressors, including pesticides, rank amongst the most relevant causes of biodiversity loss. However, pesticides usually co-occur and may interact with other stressors such as increased fine sediment influx from open agricultural soils. Such multiple stressor interactions can lead to complex non-linear responses, i.e. they can result in weaker or stronger effects on organisms and ecosystem functions than predicted from single stressor responses. Therefore, reliable ecosystem management requires understanding and the ability to predict the effects of multiple stressors. Discerning effects from pesticides and fine sediment as well as identifying potential joint effects is therefore a highly relevant and timely challenge. However, testing for multiple stressor effects requires independence of the stressors, which is almost impossible to achieve in correlative field studies. Furthermore, high taxonomic resolution facilitates the identification of stressor impacts, yet is rarely available given the difficulty of taxonomic identification. Therefore, new experimental and analytical approaches are needed in multiple stressor research to improve stressor discrimination. In our project, we will conduct innovative lab and field experiments to study individual and joint effects of chlorantraniliprole as a model pesticide and deposited fine sediment on stream invertebrates and associated ecosystem functions (organic matter decomposition). The first Work Package (WP1) will feature a quantitative approach to DNA-based community assessment using DNA metabarcoding and hybrid enrichment. While both approaches can be used for species assessment of pooled samples, inferring biomass or abundances from the resulting sequencing data is hampered due to PCR bias. We therefore propose the integration of a unique tagging sequence (degenerate base region, DBR) to estimate the true number of template molecules and thereby biomass. With the improved quantitative tools we will assess stressor responses of stream invertebrates to pesticide and fine sediment. In WP2 we will assess individual and joint impacts of the pesticide and fine sediment on changes in gene expression (transcriptomics) in four invertebrate shredders, key taxa in organic matter degradation. We will test if physiological stress responses can be translated to observed community and functional changes. Furthermore, by performing biotic interaction experiments we will quantify the relative importance of biotic interactions for the stressor responses, which is a very timely topic in functional ecology. Through integrating the disciplines of environmental genomics, ecotoxicology, ecology and bioinformatics this project seeks to move forward from describing to truly understanding and predicting multiple stressor effects.