Climate and land-use change drive a suite of stressors that shape ecosystems and interact to yield complex ecological responses, i.e. additive, antagonistic and synergistic effects.Currently we know little about the spatial scale relevant for the outcome of such interactions and about effect sizes. This knowledge gap needs to be filled to underpin future land management decisions or climate mitigation interventions, for protecting and restoring freshwater ecosystems. The study combines data across scales from 33 mesocosm experiments with those from 14 river basins and 22 cross-basin studies in Europe producing 174 combinations of paired-stressor effects on a biological response variable. Generalised linear models showed that only one of the two stressors had a significant effect in 39% of the analysed cases, 28% of the paired-stressor combinations resulted in additive and 33% in interactive (antagonistic, synergistic, opposing or reversal) effects. For lakes the frequency of additive and interactive effects was similar for all spatial scales addressed, while for rivers this frequency increased with scale. Nutrient enrichment was the overriding stressor for lakes, generally exceeding those of secondary stressors. For rivers, the effects of nutrient enrichment were dependent on the specific stressor combination and biological response variable. These results vindicate the traditional focus of lake restoration and management on nutrient stress, while highlighting that river management requires more bespoke management solutions.

Running water ecosystems of Europe are affected by various human pressures. However, little is known about the prevalence, spatial patterns, interactions with natural environment and co-occurrence of pressures. This study represents the first high-resolution data analysis of human pressures at the European scale, where important pressure criteria for 9330 sampling sites in 14 European countries were analysed. We identified 15 criteria describing major anthropogenic degradation and combined these into a global pressure index by taking additive effects of multiple pressures into account. Rivers are affected by alterations of water quality (59%), hydrology (41%) and morphology (38%). Connectivity is disrupted at the catchment level in 85% and 35% at the river segment level. Approximately 31% of all sites are affected by one, 29% by two, 28% by three and 12% by four pressure groups; only 21% are unaffected. In total, 47% of the sites are multi-impacted. Approximately 90% of lowland rivers are impacted by a combination of all four pressure groups.

This work addresses human stressors and their impacts on fish assemblages at pan-European scale by analysing single and multiple stressors and their interactions. Based on an extensive dataset with 3105 fish sampling sites, patterns of stressors, their combination and nature of interactions, i.e. synergistic, antagonistic and additive were investigated. Geographical distribution and patterns of seven human stressor variables, belonging to four stressor groups (hydrological-, morphological-, water quality- and connectivity stressors), were examined, considering both single and multiple stressor combinations. To quantify the stressors' ecological impact, a set of 22 fish metrics for various fish assemblage types (headwaters, medium gradient rivers, lowland rivers and Mediterranean streams) was analysed by comparing their observed and expected response to different stressors, both acting individually and in combination. Overall, investigated fish sampling sites are affected by 15 different stressor combinations, including 4 stressors acting individually and 11 combinations of two or more stressors; up to 4 stressor groups per fish sampling site occur. Stressor-response analysis shows divergent results among different stressor categories, even though a general trend of decreasing ecological integrity with increasing stressor quantity can be observed. Fish metrics based on density of species 'intolerant to water quality degradation' and 'intolerant to oxygen depletion" responded best to single and multiple stressors and their interactions. Interactions of stressors were additive (40%), synergistic (30%) or antagonistic (30%), emphasizing the importance to consider interactions in multi-stressor analyses. While antagonistic effects are only observed in headwaters and medium-gradient rivers, synergistic effects increase from headwaters over medium gradient rivers and Mediterranean streams to large lowland rivers. The knowledge gained in this work provides a basis for advanced investigations in European river basins and helps prioritizing further restoration and management actions.

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Species distribution modelling, as a central issue in freshwater ecology, is an important tool for conservation and management of aquatic ecosystems. The brown trout (Salmo trutta) is a sensitive species which reacts to habitat changes induced by human impacts. Therefore, the identification of suitable habitats is essential. This study explores the potential distribution of brown trout by a species distribution modelling approach for Iran. Furthermore, modelling results are compared to the distribution described in the literature. Areas outside the currently known distribution which may offer potential habitats for brown trout are identified. The species distribution modelling was based on five different modelling techniques: Generalised Linear Model, Generalised Additive Model, Generalised Boosting Model, Classification Tree Analysis and Random Forests, which are finally summarised in an ensemble forecasting approach. We considered four environmental descriptors at the local scale (slope, bankfull width, wetted width, and elevation) and three climatic parameters (mean air temperature, range of air temperature and annual precipitation) which were extracted on three different spatial extents (1/5/10 km). The performance of all models was excellent (≥0.8) according to the TSS (True Skill Statistic) criterion. Slope, mean and range of air temperature were the most important variables in predicting brown trout occurrence. Presented results deepen the knowledge about distribution patterns of brown trout in Iran. Moreover, this study gives a basic background for the future development of assessment methods for riverine ecosystems in Iran.