Response of freshwater invertebrates to natural environmental and agricultural stressor gradients across larger scales

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Agrochemicals, especially pesticides, have been shown to be important contributors to the local loss of many sensitive species, for instance, up to 42% of invertebrates in freshwater ecosystems of different agricultural regions of the world. Most research has focused on pesticide effects on the individual and population level, which constrains the ability of scientists to appropriately assess the ecological risks and predict community-level effects. Trait-based approaches have been advocated to establish mechanistic trait-stressor relationships that allow for community prediction and for discrimination between stressors, which is of particular relevance for freshwater managers. Various studies scrutinised whether similar environmental conditions in a habitat lead to a predictable trait composition of freshwater invertebrate communities. The results show that the predictability is often context-dependent. One fact that has insufficiently been considered in many studies on trait-environment relationships and that may explain part of the context-dependency, is that traits do not occur independently of one another, but they are often intercorrelated. We will examine to which extent accounting for these intercorrelations in terms of trait profiles improves the consistency of trait-environment relationship across larger scales, defined here as continental and intercontinental scale, and consequently improves prediction of community structure. In Work Package (WP) 1 we will extract trait profiles and groups for the taxa pools from different global regions, namely Europe, North America, Australia, New Zealand and Bolivia using trait databases. Subsequently, we will compare these trait profile groups and associated trait states across and within the regions. In WP 2 we will first identify the most important response traits and trait profile groups (established in WP 1) for predicting pesticide stress, also accounting for other agricultural stressors and different stream types. Afterwards, we will evaluate to which extent criteria for stressor-specificity are met by the response traits with the highest predictability for pesticide stress. Finally, we will scrutinise their specificity for pesticide stress in an agricultural multiple stressor context including additional stressors such as excessive nutrient loading. Overall, our project will inform on the utility and limitations of trait-based approaches, for instance, regarding the transferability of trait-environment relationships across regions and for use in agricultural multiple stress contexts.