Natural variability in flow is a primary factor controlling geomorphic and ecological processes in riverine ecosystems. Within the hydropower industry, there is growing pressure from environmental groups and natural resource managers to change reservoir releases from daily peaking to run‐of‐river operations on the basis of the assumption that downstream biological communities will improve under a more natural flow regime. In this paper, we discuss the importance of assessing sub‐daily flows for understanding the physical and ecological dynamics within river systems. We present a variety of metrics for characterizing sub‐daily flow variation and use these metrics to evaluate general trends among streams affected by peaking hydroelectric projects, run‐of‐river projects and streams that are largely unaffected by flow altering activities. Univariate and multivariate techniques were used to assess similarity among different stream types on the basis of these sub‐daily metrics. For comparison, similar analyses were performed using analogous metrics calculated with mean daily flow values. Our results confirm that sub‐daily flow metrics reveal variation among and within streams that are not captured by daily flow statistics. Using sub‐daily flow statistics, we were able to quantify the degree of difference between unaltered and peaking streams and the amount of similarity between unaltered and run‐of‐river streams. The sub‐daily statistics were largely uncorrelated with daily statistics of similar scope. On short temporal scales, sub‐daily statistics reveal the relatively constant nature of unaltered stream reaches and the highly variable nature of  hydropower‐affected streams, whereas daily statistics show just the opposite over longer temporal scales. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

In order for habitat restoration in regulated rivers to be effective at large scales, broadly applicable frameworks are needed that provide measurable objectives and contexts for management. The Ecological Limits of Hydrologic Alteration (ELOHA) framework was created as a template to assess hydrologic alterations, develop relationships between altered streamflow and ecology, and establish environmental flow standards. We tested the utility of ELOHA in informing flow restoration applications for fish and riparian communities in regulated rivers in the Upper Tennessee River Basin (UTRB). We followed the steps of ELOHA to generate univariate relationships between altered flows and ecology within the UTRB. By comparison, we constructed multivariate models to determine improvements in predictive capacity with the addition of non-flow variables. We then determined whether those relationships could predict fish and riparian responses to flow restoration in the Cheoah River, a regulated system within the UTRB. Although ELOHA provided a robust template to construct hydrologic information and predict hydrology for ungaged locations, our results do not suggest that univariate relationships between flow and ecology (step 4, ELOHA process) can produce results sufficient to guide flow restoration in regulated rivers. After constructing multivariate models, we successfully developed predictive relationships between flow alterations and fish/ riparian responses. In accordance with model predictions, riparian encroachment displayed consistent decreases with increases in flow magnitude in the Cheoah River; however, fish richness did not increase as predicted 4 years after restoration. Our results suggest that altered temperature and substrate and the current disturbance regime may have reduced opportunities for fish species colonization. Our case study highlights the need for interdisciplinary science in defining environmental flows for regulated rivers and the need for adaptive management approaches once flows are restored.

Hydrologic classifications unveil the structure of relationships among groups of streams with differing streamflows and provide a foundation for drawing inferences about the principles that govern those relationships. Hydrologic classes provide a template to generalize hydrologic responses to disturbance and stratify research and management needs applicable to ecohydrology. We used a mixed-modelling approach to create hydrologic classifications for the continental USA using three streamflow datasets, a reference dataset compiled under more strict traditional standards and two additional datasets compiled under more relaxed assumptions. A variety of models were applied to each dataset, and Bayes criteria were used to identify optimal models and numbers of clusters. Using only reference-quality gauges, we classified 1715 stream gauges into 12 classes across the USA. By including more streamflow gauges (n = 2402 and 2618) of lesser reference quality in subsequent classifications, we observed minimal increases in dimensionality (i.e. multivariate space) at the expense of increasing uncertainty and outliers. Part of the utility of classification systems rests in their ability to classify new objects and stratify data by common properties. We constructed separate random forest models to predict hydrologic class membership on the basis of hydrologic indices or landscape variables. In addition, we provide an approach to assessing potential outliers due to hydrologic alteration based on class assignment. Departures from class membership due to disturbance take into account multiple hydrologic indices simultaneously; thus, classes can be used to determine if disturbed streams are functioning within the natural range of hydrologic variability. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.Supporting information may be found in the online version of this article.

Primary biodiversity data constitute observations of particular species at given points in time and space. Open‐access electronic databases provide unprecedented access to these data, but their usefulness in characterizing species distributions and patterns in biodiversity depend on how complete species inventories are at a given survey location and how uniformly distributed survey locations are along dimensions of time, space, and environment. Our aim was to compare completeness and coverage among three open‐access databases representing ten taxonomic groups (amphibians, birds, freshwater bivalves, crayfish, freshwater fish, fungi, insects, mammals, plants, and reptiles) in the contiguous United States. We compiled occurrence records from the Global Biodiversity Information Facility (GBIF), the North American Breeding Bird Survey (BBS), and federally administered fish surveys (FFS). We aggregated occurrence records by 0.1° × 0.1° grid cells and computed three completeness metrics to classify each grid cell as well‐surveyed or not. Next, we compared frequency distributions of surveyed grid cells to background environmental conditions in a GIS and performed Kolmogorov–Smirnov tests to quantify coverage through time, along two spatial gradients, and along eight environmental gradients. The three databases contributed >13.6 million reliable occurrence records distributed among >190,000 grid cells. The percent of well‐surveyed grid cells was substantially lower for GBIF (5.2%) than for systematic surveys (BBS and FFS; 82.5%). Still, the large number of GBIF occurrence records produced at least 250 well‐surveyed grid cells for six of nine taxonomic groups. Coverages of systematic surveys were less biased across spatial and environmental dimensions but were more biased in temporal coverage compared to GBIF data. GBIF coverages also varied among taxonomic groups, consistent with commonly recognized geographic, environmental, and institutional sampling biases. This comprehensive assessment of biodiversity data across the contiguous United States provides a prioritization scheme to fill in the gaps by contributing existing occurrence records to the public domain and planning future surveys.

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Lotic fish have developed life history strategies adapted to the natural variation in stream flow regimes. The natural timing, duration, and magnitude of flow events has contributed to the diversity, production, and composition of fish assemblages over time. Studies evaluating the role of hydrology in structuring fish assemblages have been more common at the local or regional scale with very few studies conducted at the continental scale. Furthermore, quantitative linkages between natural hydrologic patterns and fish assemblages are rarely used to make predictions of ecological consequences of hydrologic alterations. We ask two questions: (1) what is the relative role of hydrology in structuring fish assemblages at large scales? and (2) can relationships between fish assemblages and natural hydrology be utilized to predict fish assemblage responses to hydrologic disturbance? We developed models to relate fish life histories and reproductive strategies to landscape and hydrologic variables separately and then combined. Models were then used to predict the ecological consequences of altered hydrology due to dam regulation. Although hydrology plays a considerable role in structuring fish assemblages; the performance of models using only hydrologic variables was lower than that of models constructed using landscape variables. Isolating the relative importance of hydrology in structuring fish assemblages at the continental scale is difficult since hydrology is interrelated to many landscape factors. By applying models to dam-regulated hydrologic data, we observed some consistent predicted responses in fish life history strategies and modes of reproduction. In agreement with existing literature, equilibrium strategists are predicted to increase following dam regulation, whereas opportunistic and periodic species are predicted to decrease. In addition, dam regulation favors the selection of reproductive strategies with extended spawning seasons and preference for stable conditions.

Human consumption of freshwater is now approaching or surpassing the rate at which water sources are being naturally replenished in many regions, creating water shortage risks for people and ecosystems. Here we assess the impact of human water uses and their connection to water scarcity and ecological damage across the United States, identify primary causes of river dewatering and explore ways to ameliorate them. We find irrigation of cattle-feed crops to be the greatest consumer of river water in the western United States, implicating beef and dairy consumption as the leading driver of water shortages and fish imperilment in the region. We assess opportunities for alleviating water scarcity by reducing cattle-feed production, finding that temporary, rotational fallowing of irrigated feed crops can markedly reduce water shortage risks and improve ecological sustainability. Long-term water security and river ecosystem health will ultimately require Americans to consume less beef that depends on irrigated feed crops.

River regulation has resulted in substantial losses in habitat connectivity, biodiversity and ecosystem services. River managers are faced with a growing need to protect the key aspects of the natural flow regime. A practical approach to providing environmental flow standards is to create a regional framework by classifying unregulated streams into groups of similar hydrologic properties, which represent natural flow regime targets. Because spatial resolution can influence the structure of regional datasets, it may be advantageous to relate datasets created at different scales in order to establish hierarchical structure and to understand how the relative importance of variables change with regard to scale. The purpose of this study was to classify unregulated streams within an eight-state region into groups in order to provide environmental flow standards for managers and to relate that dataset to frameworks created at larger scales. Using USGS daily stream gauge information, we used 66 hydrologic statistics to classify 292 streams in groups of similar hydrologic properties. We isolated six flow classes in a sub-region of the Southeastern US that ranged from extremely stable to highly variable to intermittent. We developed classification trees to reduce the number of hydrologic variables for future classifications. By comparing flow classes in our study to those of the entire US, we found that hierarchical structure did exist and that the divergence of flow classes will largely depend on the spatial resolution.