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.

Construction of small hydropower plants (<10 megawatts) is booming worldwide, exacerbating ongoing habitat fragmentation and degradation, and further fueling biodiversity loss. A systematic approach for selecting hydropower sites within river networks may help to minimize the detrimental effects of small hydropower on biodiversity. In addition, a better understanding of reach‐ and basin‐scale impacts is key for designing planning tools. We synthesize the available information about (1) reach‐scale and (2) basin‐scale impacts of small hydropower plants on biodiversity and ecosystem function, and (3) interactions with other anthropogenic stressors. We then discuss state‐of‐the‐art, spatially explicit planning tools and suggest how improved knowledge of the ecological and evolutionary impacts of hydropower can be incorporated into project development. Such tools can be used to balance the benefits of hydropower production with the maintenance of ecosystem services and biodiversity conservation. Adequate planning tools that consider basin‐scale effects and interactions with other stressors, such as climate change, can maximize long‐term conservation.

Identifying and quantifying relationships among landscape patterns, anthropogenic disturbances, and aquatic ecosystems is a new and rapidly developing approach to riverine ecology. In this review, we begin by describing the policy and management drivers for landscape-scale riverine research and we synthesize the technological advances that have enabled dramatic progress in the field. We then describe the development of landscape-scale riverine research through a series of landmark theoretical and review papers. Focusing on landscape-fish relationships, we consider the degree to which past efforts have been successful at meeting three challenges: (1) Has new research effectively incorporated the strengths of new technologies or are we doing the same old thing with more expensive data? (2) Have we incorporated key concepts from landscape ecology to improve our understanding of how landscapes affect rivers? (3) Have we been able to use landscape analyses to address management and policy needs? We conclude with a review of opportunities for advancement in the field of landscape-scale riverine research. These include moving toward the development of mechanistic theories of how landscapes affect rivers across disparate regions; considering the spatio-temporal structure of human impacts to landscapes; harnessing new statistical tools; and carefully defining landscape and response metrics to capture specific features.

We classified homogenous river types across Europe and searched for fish metrics qualified to show responses to specific pressures (hydromorphological pressures or water quality pressures) vs. multiple pressures in these river types. We analysed fish taxa lists from 3105 sites in 16 ecoregions and 14 countries. Sites were pre-classified for 15 selected pressures to separate unimpacted from impacted sites. Hierarchical cluster analysis was used to split unimpacted sites into four homogenous river types based on species composition and geographical location. Classification trees were employed to predict associated river types for impacted sites with four environmental variables. We defined a set of 129 candidate fish metrics to select the best reacting metrics for each river type. The candidate metrics represented tolerances/intolerances of species associated with six metric types: habitat, migration, water quality sensitivity, reproduction, trophic level and biodiversity. The results showed that 17 uncorrelated metrics reacted to pressures in the four river types. Metrics responded specifically to water quality pressures and hydromorphological pressures in three river types and to multiple pressures in all river types. Four metrics associated with water quality sensitivity showed a significant reaction in up to three river types, whereas 13 metrics were specific to individual river types. Our results contribute to the better understanding of fish assemblage response to human pressures at a pan-European scale. The results are especially important for European river management and restoration, as it is necessary to uncover underlying processes and effects of human pressures on aquatic communities.

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.

The catchment land-use composition of 249 fish sampling sites in Austrian running waters revealed effects on the biological integrity. Beyond correlative analysis, we investigated (1) which land-use category had the strongest effect on fish, (2) whether metrics of functional fish guilds reacted differently, (3) whether there were cumulative effects of land-use categories, and (4) whether effects varied in strength across river types. We fed 5 land-use categories into regression trees to predict the European Fish Index or fish metric of intolerant species (mainly Salmo trutta fario). Agriculture and urbanisation were the best predictors and indicated significant effects at levels of >23.3 and >2%, respectively. Model performance was R2 = 0.15 with the Fish Index and R2 = 0.46 with intolerant species. The tree structure showed a cumulative effect from agriculture and urbanisation. For the intolerant species metric, a combination of high percentages for agriculture and urbanisation was related to moderate status, whereas <7.3% agriculture were related to good status, although urbanisation was higher than 1.8%. Headwater river types showed stronger responses to land use than river types of lower gradient and turned out to be more sensitive to urbanisation than agriculture.

Using a large pan-European dataset, we compared least disturbed sites to sites impacted by human pressures across broad river types to assess which aspects of bio-ecological traits of the fish assemblage are most sensitive to alterations of the river ecosystem. To control for variation across river types and large-scale environmental gradients, we began by clustering the least disturbed sites (n = 716) into four homogenous fish assemblage types (FATs) differing by four fish metrics, i.e., lithophilic, rheophilic, omnivorous, and potamodromous fish. We predicted these FATs (headwater streams, medium gradient rivers, lowland rivers, and Mediterranean streams) using environmental variables, i.e., altitude, river slope, temperature, precipitation, latitude, and longitude for impacted sites in our dataset (n = 2,389). Using tests of sensitivity and intensity, 17 fish metrics showed a clear reaction to human pressures. However, 12 metrics responded exclusively within only one of the four FATs. Hence we observed a divergent reaction of fish metrics to human pressures in, e.g., headwater versus lowland rivers. Type-specific reactions are useful in customizing impact assessment for particular river types. It is of primary importance to understand the comparative sensitivity and efficiency of fish-based indicators of water quality for detecting humaninduced degradation of river ecosystems.

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