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Fluvial fishes are threatened globally from intensive human landscape stressors degrading aquatic ecosystems. However, impacts vary regionally, as stressors and natural environmental factors differ between ecoregions and continents. To date, a comparison of fish responses to landscape stressors over continents is lacking, limiting understanding of consistency of impacts and hampering efficiencies in conserving fishes over large regions. This study addresses these shortcomings through a novel, integrative assessment of fluvial fishes throughout Europe and the conterminous United States. Using large-scale datasets, including information on fish assemblages from more than 30,000 locations on both continents, we identified threshold responses of fishes summarized by functional traits to landscape stressors including agriculture, pasture, urban area, road crossings, and human population density. After summarizing stressors by catchment unit (local and network) and constraining analyses by stream size (creeks vs. rivers), we analyzed stressor frequency (number of significant thresholds) and stressor severity (value of identified thresholds) within ecoregions across Europe and the United States. We document hundreds of responses of fish metrics to multi-scale stressors in ecoregions across two continents, providing rich findings to aid in understanding and comparing threats to fishes across the study regions. Collectively, we found that lithophilic species and, as expected, intolerant species are most sensitive to stressors in both continents, while migratory and rheophilic species are similarly strongly affected in the United States. Also, urban land use and human population density were most frequently associated with declines in fish assemblages, underscoring the pervasiveness of these stressors in both continents. This study offers an unprecedented comparison of landscape stressor effects on fluvial fishes in a consistent and comparable manner, supporting conservation of freshwater habitats in both continents and worldwide.

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Aquatic foods are critical for food and nutrition security in Malawi, but it is unclear which populations benefit from different aquatic foods and what factors shape food access. Spatial analysis of food flows across value chains from Lake Malawi to domestic consumers shows that usipa (Engraulicypris sardella) reaches more consumers than chambo (Oreochromis karongae) across all Malawi districts, particularly rural populations. Higher number of markets, nutrient content, and overall supply coupled with lower retail prices and volumes make usipa more accessible to consumers than chambo. Spatial analysis of food flows can guide policymakers towards supporting fisheries that reach vulnerable populations and designing interventions that enhance physical and economic access to fish.

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Despite increasing efforts globally to remove dams and construct fish passage structures, broad-scale analyses balancing tradeoffs between cost and habitat gains from these mitigations infrequently consider invasive species. We present an optimization-based approach for prioritizing dam mitigations to restore habitat connectivity for native fish species, while limiting invasive species spread. Our methodology is tested with a case study involving 240 dams in the Upper Mississippi River, USA. We integrate six native migratory fish species distribution models, distributions of two invasive fishes, and estimated costs for dam removal and construction of fish passes. Varying budgets and post-mitigation fish passage rates are analyzed for two scenarios: 'no invasives' where non-selective mitigations (e.g., dam removal) are used irrespective of potential invasive species habitat gains and 'invasives' where a mixture of selective (e.g., lift-and-sort fish passage) and non-selective mitigations are deployed to limit invasive species range expansion. To achieve the same overall habitat connectivity gains, we find that prioritizations accounting for invasive species are 3 to 6 times more costly than those that do not. Habitat gains among native fish species were highly variable based on potential habitat overlap with invasive species and post-mitigation passabilities, ranging from 0.4-58.9% ('invasives') and 7.9-95.6% ('no invasives') for a $50M USD budget. Despite challenges associated with ongoing nonnative fish invasions, opportunities still exist to restore connectivity for native species as indicated by individual dams being frequently selected in both scenarios across varying passabilities and budgets, however increased restoration costs associated with invasive species control indicates the importance of limiting their further spread within the basin. Given tradeoffs in managing for native vs. invasive species in river systems worldwide, our approach demonstrates strategies for identifying a portfolio of candidate barriers that can be investigated further for their potential to enhance native fish habitat connectivity while concurrently limiting invasive species dispersal.

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Changes in climate are known to alter air temperature and precipitation and their associated thermal and hydrological regimes of freshwater systems, and such alterations in habitat are anticipated to modify fish composition in fluvial systems. Despite these expected changes, assessing climate change effects on habitat and fish over large regions has proven challenging. The goal of this study is to describe an approach to assess and identify stream reaches within a large region that are susceptible to climate changes based on responses of multiple fish species to changes in thermal and hydrological habitats occurring with changes in climate. We present a six-step approach to connect climate, habitat, and fish responses, demonstrated through an example to assess effects of climate change on fishes for all stream reaches in a large U.S. ecoregion (955,029 km2). Step 1 identified measures of air temperature and precipitation expected to change substantially in the future. Step 2 identified the climatic measures strongly associated with stream thermal and hydrologic metrics calculated from measured data from a subset of streams. Step 3 linked thermal and hydrologic metrics identified in Step 2 with abundances of fish species from the same stream reaches, and these fishes were combined into groups based on similar associations with specific thermal or hydrologic metrics. Step 4 used the linkages between fish groups and climatic measures and their associated thermal and hydrologic metrics to classify stream reaches. Step 5 assigned all stream reaches into classes based on the established classification under current climate measures and then re-assigned all stream reaches using projected climatic measures for three future time windows. Step 6 assessed changes in classes of stream reaches between current and future climate conditions. Stream reaches projected to change in stream classes were considered "vulnerable" to future climate change, as they would no longer support the same fish composition. The projected vulnerable streams for the years 2040, 2060, and 2090 were mapped and summarized to identify temporal patterns and identify their spatial distribution, along with underlying mechanisms leading to changes. Our results showed that 45.7% of the 320,000 reaches and 49.3% of the overall 650,000 km stream length in the study region were expected to change stream class by the year 2090, with spatially-explicit changes including streams' responding to changing air temperature or precipitation. This study provides critical guidance for integrating climate projections, landscape factors, stream habitat data, and fish data into a meaningful approach for understanding linkage. Outcomes greatly improve our ability to describe habitat changes at a stream reach scale throughout large regions, and they can aid in prioritizing management strategies to adapt to climate change at local and regional scales.

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Hydropower generation has advantages for societies that seek low-carbon, renewable energy alternatives, but sustainable hydropower production will require an explicit consideration of potential tradeoffs between socioeconomic and environmental priorities. These tradeoffs are often explored during a formal environmental impact assessment process that can be complex and controversial. The steps taken to address stakeholder concerns through impact hypotheses and field studies are not always transparent. We have created a Checklist of River Function Indicators to facilitate stakeholder discussions during hydropower licensing and to support more transparent, holistic, and scientifically informed hydropower environmental analyses. Based on a database of environmental metrics collected from hydropower project studies documented by the Federal Energy Regulatory Commission (FERC), the International Hydropower Association, the Low Impact Hydropower Institute, and peer-reviewed scientific literature, our proposed Checklist of River Function Indicators contains 51 indicators in six categories. We have tested the usefulness of the Indicators by applying them to seven hydropower projects documented by FERC. Among the case study projects, 44 of the 51 Indicators were assessed according to the FERC documentation. Even though each hydropower project presents unique natural resource issues and stakeholder priorities, the proposed Indicators can provide a transparent starting point for stakeholder discussions about which ecological impacts should be considered in hydropower planning and relicensing assessments.

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A series of three papers was written about the development of multimetric indices (MMIs) using diatoms in rivers, streams and lakes for transcontinental surveys conducted by the United States Environmental Protection Agency. Stevenson et al. (2013) used the surface sediment diatom data from the 2007 National Lake Assessment to develop national scale site specific models for MMIs to account for natural variation in condition among sites. Liu and Stevenson (2017) also used the 2007 lakes data to evaluate performance of MMIs by grouping sites by ecoregions or typologies (naturally similar types of lakes defined by similarity in diatom species composition) with site specific metric models (SSMMs) that adjust metrics for natural variability among sites. Tang et al. (2016) used benthic diatom data from the 2008-2009 National River and Stream Assessment to develop SSMMs and MMIs by ecoregion and typology. All three studies showed that SSMMs improved performance of diatom MMIs by accounting for natural variation among sites. None of the studies provided consistent evidence that grouping sites by typologies produced better MMI performance than grouping sites by ecoregions. Liu and Cao (2018) criticized the Tang et al. (2016) paper for using means and standard errors to evaluate relative performance of MMI calculation methods at the site group scale, however, their criticism is incorrect. Actually, Tang et al. (2016) only used means to summarize and report relative performance of MMI calculation methods in the body of the paper. Tang et al. (2016) appropriately used non-parametric rank sum approaches to evaluate the probability that the multiple MMI calculations for separate site groups were the same for ecoregion (n = 9) and typology (n = 7) site groups. Liu and Stevenson (2017) used this same non-parametric approach for tests of lake diatom MMIs. Liu and Cao's (2018) concerns can be addressed by distinguishing between the goals and methods used for testing and evaluation of MMI calculation methods at the national and site-group scales. Tang et al. (2016) did not aggregate data across site groups to test MMI performance at the national scale because they were following standard EPA methods that develop separate MMIs for each site group. In conclusion, Liu and Cao (2018) misunderstood the MMI evaluation in Tang et al. (2016) and added no new information to this body of work, because all the concerns they raised were discussed in Liu and Stevenson (2017).

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Dams have been a fundamental part of the U.S. national agenda over the past two hundred years. Recently, however, dam removal has emerged as a strategy for addressing aging, obsolete infrastructure and more than 1,100 dams have been removed since the 1970s. However, only 130 of these removals had any ecological or geomorphic assessments, and fewer than half of those included before- and after-removal (BAR) studies. In addition, this growing, but limited collection of dam-removal studies is limited to distinct landscape settings. We conducted a meta-analysis to compare the landscape context of existing and removed dams and assessed the biophysical responses to dam removal for 63 BAR studies. The highest concentration of removed dams was in the Northeast and Upper Midwest, and most have been removed from 3rd and 4th order streams, in low-elevation (< 500 m) and low-slope (< 5%) watersheds that have small to moderate upstream watershed areas (10-1000 km2) with a low risk of habitat degradation. Many of the BAR-studied removals also have these characteristics, suggesting that our understanding of responses to dam removals is based on a limited range of landscape settings, which limits predictive capacity in other environmental settings. Biophysical responses to dam removal varied by landscape cluster, indicating that landscape features are likely to affect biophysical responses to dam removal. However, biophysical data were not equally distributed across variables or clusters, making it difficult to determine which landscape features have the strongest effect on dam-removal response. To address the inconsistencies across dam-removal studies, we provide suggestions for prioritizing and standardizing data collection associated with dam removal activities.

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Despite the prevalence of damming as a global disturbance to river habitats, detailed reach-based assessments of the ecological effects of dams are lacking, particularly across large spatial extents. Using data from nearly 50,000 large dams, we assessed stream network fragmentation and flow alteration by large dams for streams of the conterminous USA. We developed 21 dam metrics characterizing a diversity of dam influences operating at both localized (e.g., distances-to-dams) and landscape scales (e.g., cumulative reservoir storage throughout stream networks) for every stream reach in the study region. We further evaluated how dams have affected stream fish assemblages within large ecoregions using more than 37,000 stream fish samples. Streams have been severely fragmented by large dams, with the number of stream segments increasing by 801% compared to free-flowing streams in the absence of dams and a staggering 79% of stream length is disconnected from their outlet (i.e., oceans and Great Lakes). Flow alteration metrics demonstrate a landscape-scale disturbance of dams, resulting in total upstream reservoir storage volumes exceeding estimated annual discharge volumes of many of the nation's largest rivers. Further, we show large-scale changes in fish assemblages with dams. Species adapted to lentic habitats increase with dams across the conterminous USA, while rheophils, lithophils, and intolerant fishes decrease with dams. Overall, fragmentation and flow alteration by dams have affected fish assemblages as much or more than other anthropogenic stressors, with dam effects generally increasing with stream size. Dam-induced stream fragmentation and flow alteration are critical natural resource issues. This study emphasizes the importance of considering dams as a landscape-scale disturbance to river habitats along with the need to assess differential effects that dams may have on river habitats and the fishes they support. Together, these insights are essential for more effective conservation of stream resources and biotic communities globally.

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Regional variation in both natural environment and human disturbance can influence performance of ecological assessments. In this study we calculated 5 types of benthic diatom multimetric indices (MMIs) with 3 different approaches to account for variation in ecological assessments. We used: site groups defined by ecoregions or diatom typologies; the same or different sets of metrics among site groups; and unmodeled or modeled MMIs, where models accounted for natural variation in metrics within site groups by calculating an expected reference condition for each metric and each site. We used data from the USEPA's National Rivers and Streams Assessment to calculate the MMIs and evaluate changes in MMI performance. MMI performance was evaluated with indices of precision, bias, responsiveness, sensitivity and relevancy which were respectively measured as MMI variation among reference sites, effects of natural variables on MMIs, difference between MMIs at reference and highly disturbed sites, percent of highly disturbed sites properly classified, and relation of MMIs to human disturbance and stressors. All 5 types of MMIs showed considerable discrimination ability. Using different metrics among ecoregions sometimes reduced precision, but it consistently increased responsiveness, sensitivity, and relevancy. Site specific metric modeling reduced bias and increased responsiveness. Combined use of different metrics among site groups and site specific modeling significantly improved MMI performance irrespective of site grouping approach. Compared to ecoregion site classification, grouping sites based on diatom typologies improved precision, but did not improve overall performance of MMIs if we accounted for natural variation in metrics with site specific models. We conclude that using different metrics among ecoregions and site specific metric modeling improve MMI performance, particularly when used together. Applications of these MMI approaches in ecological assessments introduced a tradeoff with assessment consistency when metrics differed across site groups, but they justified the convenient and consistent use of ecoregions.

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Ecosystems often experience multiple environmental stressors simultaneously that can differ widely in their pathways and strengths of impact. Differences in the relative impact of environmental stressors can guide restoration and management prioritization, but few studies have empirically assessed a comprehensive suite of stressors acting on a given ecosystem. To fill this gap in the Laurentian Great Lakes, where considerable restoration investments are currently underway, we used expert elicitation via a detailed online survey to develop ratings of the relative impacts of 50 potential stressors. Highlighting the multiplicity of stressors in this system, experts assessed all 50 stressors as having some impact on ecosystem condition, but ratings differed greatly among stressors. Individual stressors related to invasive and nuisance species (e.g., dreissenid mussels and ballast invasion risk) and climate change were assessed as having the greatest potential impacts. These results mark a shift away from the longstanding emphasis on nonpoint phosphorus and persistent bioaccumulative toxic substances in the Great Lakes. Differences in impact ratings among lakes and ecosystem zones were weak, and experts exhibited surprisingly high levels of agreement on the relative impacts of most stressors. Our results provide a basin-wide, quantitative summary of expert opinion on the present-day influence of all major Great Lakes stressors. The resulting ratings can facilitate prioritizing stressors to achieve management objectives in a given location, as well as providing a baseline for future stressor impact assessments in the Great Lakes and elsewhere.

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The growing quality and availability of spatial map layers (e.g., climate, geology, and land use) allow stream studies, which historically have occurred over small areas like a single watershed or stream reach, to increasingly explore questions from a landscape perspective. This large-scale perspective for fluvial studies depends on the ability to characterize influences on streams resulting from throughout entire upstream networks or catchments. While acquiring upstream information for a single reach is relatively straight-forward, this process becomes demanding when attempting to obtain summaries for all streams throughout a stream network and across large basins. Additionally, the complex nature of stream networks, including braided streams, adds to the challenge of accurately generating upstream summaries. This paper outlines an approach to solve these challenges by building a database and applying an algorithm to gather upstream landscape information for digitized stream networks. This approach avoids the need to directly use spatial data files in computation, and efficiently and accurately acquires various types of upstream summaries of landscape information across large regions using tabular processing. In particular, this approach is not limited to the use of any specific database software or programming language, and its flexibility allows it to be adapted to any digitized stream network as long as it meets a few minimum requirements. This efficient approach facilitates the growing demand of acquiring upstream summaries at large geographic scales and helps to support the use of landscape information in assisting management and decision-making across large regions.

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With increasing pressure placed on natural systems by growing human populations, both scientists and resource managers need a better understanding of the relationships between cumulative stress from human activities and valued ecosystem services. Societies often seek to mitigate threats to these services through large-scale, costly restoration projects, such as the over one billion dollar Great Lakes Restoration Initiative currently underway. To help inform these efforts, we merged high-resolution spatial analyses of environmental stressors with mapping of ecosystem services for all five Great Lakes. Cumulative ecosystem stress is highest in near-shore habitats, but also extends offshore in Lakes Erie, Ontario, and Michigan. Variation in cumulative stress is driven largely by spatial concordance among multiple stressors, indicating the importance of considering all stressors when planning restoration activities. In addition, highly stressed areas reflect numerous different combinations of stressors rather than a single suite of problems, suggesting that a detailed understanding of the stressors needing alleviation could improve restoration planning. We also find that many important areas for fisheries and recreation are subject to high stress, indicating that ecosystem degradation could be threatening key services. Current restoration efforts have targeted high-stress sites almost exclusively, but generally without knowledge of the full range of stressors affecting these locations or differences among sites in service provisioning. Our results demonstrate that joint spatial analysis of stressors and ecosystem services can provide a critical foundation for maximizing social and ecological benefits from restoration investments.

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