Differentiating between point and non-point source nutrient loadings of wastewater in an agriculturally impacted area using a hybrid statistical model.

Nutrient contamination from point and non-point sources can lead to harmful consequences, such as algal blooms. Point and non-point nutrient loading estimation is determined using modeling approaches and often require an abundance of variables and observations for calibration. Small rural streams that lack water use designations often lack available data to utilize current modeling strategies. This study proposes the use of a 3-phase hybrid stepwise statistical modeling approach using generalized linear mixed models (GLMM) and a reference stream. Two streams in Central Texas were sampled for 13 months between February 2020 and February 2021, one being impacted by a wastewater treatment plant (WWTP). Dissolved phosphorus (PO4-P), ammonia (NH3-N), nitrite/nitrate (NO2 + NO3-N), total nitrogen (TN), and total phosphorus (TP) were sampled in both streams for each month. Non-point sources of contamination, such as land use/land cover and geomorphology composition, were quantified for both sub-basin drainage areas. Phase I models predicted nutrient concentrations in the reference stream using non-point source variables along with discharge and temporal variables. Best fit models were carried forward to phase II and leveraged a point-source variable, which is a naïve estimate of effluent nutrient concentration in the absence of assimilation. Phase II model coefficients highlight the significance of point-source contamination in predicting nutrient concentration, but overall lacked the ability to make future predictions under new hydrologic regimes from WWTP intensification. Phase III models included deterministically calculating an uptake variable using the relationship between discharge and wetted widths, predicting background non-point concentrations by leveraging phase I models, and calculating future nutrient loadings from WWTP intensification. This approach predicted significant increases in nutrient concentrations under planned WWTP intensification scenarios and decreased uptake efficiencies under the new hydrologic regimes.

Mutually beneficial outcomes for hydropower expansion and environmental protection at a basin scale.

Reshaping the scale of planning for hydropower development, from reaches to basin-scales, has been recommended as a more effective way to ameliorate the environmental impacts of hydropower. One approach is identifying mutually exclusive areas where development is precluded for conservation purposes and areas of low conservation value that present fewer barriers to development. This strategy, however, is less adoptable in developed countries where hydropower is already widespread and large-scale construction of new dams is unlikely. To broaden the adoption of basin-scale planning, alternative approaches and planning tools are needed for identifying mutually beneficial opportunities for simultaneous increases in hydropower capacity while improving environmental conditions. In this study, we present the Basin Scale Opportunity Assessment as a methodology to improve environmental conditions through either direct (on-site) or indirect (off-site) mitigation. We assess whether direct or indirect mitigation activities lead to optimal results in terms of added hydropower, environmental improvement, and monetary cost at a basin scale. We present two case studies for the Connecticut River and Roanoke River Basins, USA. Significant opportunities for expanding hydropower generating capacity are numerous in both basins. Results suggest that total hydropower capacity could be increased 4 to 7 % in the Roanoke and Connecticut Basins, respectively, without new dam construction and with net improvements in environmental conditions. We found that environmentally and economically optimal win-win strategies for increasing hydropower capacity and improving environmental conditions included improving environmental conditions in rivers downstream of existing dams. Off-site mitigation opportunities, such as dam removal and wetland mitigation, were identified as optimum solutions for achieving net environmental improvements only when they were associated with new hydropower construction. Our results demonstrate that opportunities to increase hydropower capacity and improve environmental conditions are expanded by viewing cumulative benefits at basin scales; however, increasing regulatory flexibility may be required to realize these opportunities.

Mapping hydrologic alteration and ecological consequences in stream reaches of the conterminous United States.

Environmental flows are critical for balancing societal water needs with that of riverine ecosystems; however, data limitations often hinder the development of predictive relationships between anthropogenic modifications to streamflow regimes and ecological responses - these relationships are the basis for setting regional water policy standards for rivers. Herein, we present and describe a comprehensive dataset of modeled hydrologic alteration and consequences for native fish biodiversity, both mapped at the stream-reach resolution for the conterminous U.S. Using empirical observations of reference conditions and anthropogenically altered streamflow at over 7000 stream gauges, we developed a predictive model of hydrologic alteration, which was extended to >2.6 million stream reaches. We then used a previous nationwide assessment of ecological responses to hydrologic alteration to predict fish biodiversity loss in stream reaches resulting from streamflow modification. Validation efforts suggested hydrologic alteration models had satisfactory performance, whereas modeled ecological responses were susceptible to compounded errors. The dataset could ameliorate regional data deficits for setting environmental flow standards while providing tools for prioritizing streamflow protection or restoration.

Anthropogenically driven climate and landscape change effects on inland water carbon dynamics: What have we learned and where are we going?

Inland waters serve as important hydrological connections between the terrestrial landscape and oceans but are often overlooked in global carbon (C) budgets and Earth System Models. Terrestrially derived C entering inland waters from the watershed can be transported to oceans but over 83% is either buried in sediments or emitted to the atmosphere before reaching oceans. Anthropogenic pressures such as climate and landscape changes are altering the magnitude of these C fluxes in inland waters. Here, we synthesize the most recent estimates of C fluxes and the differential contributions across inland waterbody types (rivers, streams, lakes, reservoirs, and ponds), including recent measurements that incorporate improved sampling methods, small waterbodies, and dried areas. Across all inland waters, we report a global C emission estimate of 4.40 Pg C/year (95% confidence interval: 3.95-4.85 Pg C/year), representing a 13% increase from the most recent estimate. We also review the mechanisms by which the most globally widespread anthropogenically driven climate and landscape changes influence inland water C fluxes. The majority of these drivers are expected to influence terrestrial C inputs to inland waters due to alterations in terrestrial C quality and quantity, hydrological pathways, and biogeochemical processing. We recommend four research priorities for the future study of anthropogenic alterations to inland water C fluxes: (1) before-and-after measurements of C fluxes associated with climate change events and landscape changes, (2) better quantification of C input from land, (3) improved assessment of spatial coverage and contributions of small inland waterbodies to C fluxes, and (4) integration of dried and drawdown areas to global C flux estimates. Improved measurements of inland water C fluxes and quantification of uncertainty in these estimates will be vital to understanding both terrestrial C losses and the "moving target" of inland water C emissions in response to rapid and complex anthropogenic pressures.

U.S. national water and energy land dataset for integrated multisector dynamics research.

Understanding resource demands and tradeoffs among energy, water, and land socioeconomic sectors requires an explicit consideration of spatial scale. However, incorporation of land dynamics within the energy-water nexus has been limited due inconsistent spatial units of observation from disparate data sources. Herein we describe the development of a National Water and Energy Land Dataset (NWELD) for the conterminous United States. NWELD is a 30-m, 86-layer rasterized dataset depicting the land use of mappable components of the United States energy sector life cycles (and related water used for energy), specifically the extraction, development, production, storage, distribution, and operation of eight renewable and non-renewable technologies. Through geospatial processing and programming, the final products were assembled using four different methodologies, each depending upon the nature and availability of raw data sources. For validation, NWELD provided a relatively accurate portrayal of the spatial extent of energy life cycles yet displayed low measures of association  with mainstream land cover and land use datasets, indicating the provision of new land use information for the energy-water nexus.

A comprehensive petrochemical vulnerability index for marine fishes in the Gulf of Mexico.

Oil and gas extraction activities occur across the globe, yet species-specific toxicological information on the biological and ecological impacts of exposure to petrochemicals is lacking for the vast majority of marine species. To help prioritize species for recovery, mitigation, and conservation in light of significant toxicological data gaps, a trait-based petrochemical vulnerability index was developed and applied to the more than 1700 marine fishes present across the entire Gulf of Mexico, including all known bony fishes, sharks, rays and chimaeras. Using life history and other traits related to likelihood of exposure, physiological sensitivity to exposure, and population resiliency, final calculated petrochemical vulnerability scores can be used to provide information on the relative sensitivity, or resilience, of marine fish populations across the Gulf of Mexico to oil and gas activities. Based on current knowledge of traits, marine fishes with the highest vulnerability scores primarily occur in areas of high petrochemical activity, are found at or near the surface, and have low reproductive turnover rates and/or highly specialized diet and habitat requirements. Relative population vulnerability scores for marine fishes can be improved with additional toxicokinetic studies, including those that account for the synergistic or additive effect of multiple stressors, as well as increased research on ecological and life history traits, especially for deep living species.

Integrated watershed process model for evaluating mercury sources, transport, and future remediation scenarios in an industrially contaminated site.

We used the Soil Water Assessment Tool (SWAT) as a framework to develop an empirical Hg flux model for Upper East Fork Poplar Creek (UEFPC), a Hg-contaminated watershed in Oak Ridge, Tennessee. By integrating long-term Hg monitoring data with simulated flow and suspended solid loads in a site-specific empirical Hg transport model, we (1) quantified the spatial, temporal, and flow regime controls on daily Hg flux (adjusted R2 = 0.82) and (2) made predictions about Hg flux under future climate, land use, and management scenarios. We found that 62.79% of the average daily Hg flux in the watershed is currently driven by base flow, whereas variability in Hg flux is driven by storm and extreme flow. We estimate an average annual Hg flux of 28.82 g day-1 leaving the watershed under baseline precipitation, with an estimated 43.73% reduction in daily Hg flux under drought conditions and a 296% increase in daily Hg flux in extreme precipitation scenarios. We estimated that a new mercury treatment facility would result in a 24.7% reduction in Hg flux under baseline conditions and a 33.4% reduction under extreme precipitation scenarios. The study demonstrated the merit of this approach, which can be replicated for sites where information on flow, suspended solids, and Hg concentrations is available.

Comparison of potential drinking water source contamination across one hundred U.S. cities.

Drinking water supplies of cities are exposed to potential contamination arising from land use and other anthropogenic activities in local and distal source watersheds. Because water quality sampling surveys are often piecemeal, regionally inconsistent, and incomplete with respect to unregulated contaminants, the United States lacks a detailed comparison of potential source water contamination across all of its large cities. Here we combine national-scale geospatial datasets with hydrologic simulations to compute two metrics representing potential contamination of water supplies from point and nonpoint sources for over a hundred U.S. cities. We reveal enormous diversity in anthropogenic activities across watersheds with corresponding disparities in the potential contamination of drinking water supplies to cities. Approximately 5% of large cities rely on water that is composed primarily of runoff from non-pristine lands (e.g., agriculture, residential, industrial), while four-fifths of all large cities that withdraw surface water are exposed to treated wastewater in their supplies.

A dataset of eco-evidence tools to inform early-stage environmental impact assessments of hydropower development.

The datasets described herein provide the foundation for a decision support prototype (DSP) toolkit aimed at assisting stakeholders in determining evidence of which aspects of river ecosystems have been impacted by hydropower. The DSP toolkit and its application are presented and described in the article "Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development" [1]. Development of the DSP and the output for decision support centralize around 42 river function indicators describing the dimensionality of river ecosystems through six main categories: biota and biodiversity, water quality, hydrology, geomorphology, land cover, and river connectivity. Three main tools are represented in the DSP: A science-based questionnaire (SBQ), an environmental envelope model (EEM), and a river function linkage assessment tool (RFLAT). The SBQ is a structured survey-style questionnaire whose objective is to provide evidence of which indicators have been impacted by hydropower. Based on a global literature review, 140 questions were developed from general hypotheses regarding the impacts of dams on rivers. The EEM is a model to predict the likelihood of hydropower impacting indicators based on a several variables. The intended use of the EEM is for situations of new hydropower development where results of the SBQ are incomplete or highly uncertain. The EEM was developed through the compilation of a dataset containing attributes of dams, reservoirs, and geospatial information on environmental concerns, which was combined with data on ecological indicators documented at those sites through literature review. The model operates through 247 "envelopes" and weighting factors, representing the individual effect of each variable on each indicator, all available through spreadsheets. Finally, the RFLAT is a tool to examine causal relationships amongst indicators. Inter-indicator relationships were hypothesized based on literature review and summarized into node and edge datasets to represent the structure of a graphical network. Bayes theorem was used estimate conditional probabilities of inter-indicator relationships based on the output of the SBQ. Nodes and edges were imported into R programming environment to visualize ecological indicator networks. The datasets can be expanded upon and enriched with more detailed questions for the SBQ, building upon the EEM with to develop more sophisticated models, and identifying new relationships for the RFALT. Additionally, once the tools are applied to numerous hydropower developments, the output of the tools (e.g. evidence of impacted indicators) becomes a very useful dataset for meta-analyses of hydropower impacts.

Methods for integrating high-resolution land, climate, and infrastructure scenarios in a hydrologic simulation model.

Global alterations of the hydrologic cycle by humans have led to alarming rates of water shortages and irreversible ecosystem change. Our ability to manage water resources lies in accurately modeling water availability at scales meaningful to management. Although hydrologic models have been used to understand the implications of future climate and land cover change on regional water availability, many modeling approaches fail to integrate human infrastructures (HI) with bio-geophysical drivers to facilitate sustainable regional water resource management. This paper presents an integrated framework, inclusive of modeling and data needs, to quantify the effects of both bio-geophysical and HI influence on regional surface water hydrology. The framework enables the integration of high spatial and temporal anthropogenic alterations of water availability for identifying hot-spots and hot-moments of hydrological stresses within individual river-segments using a hydrologic simulation model, Soil and Water Analysis Tool (SWAT). •A high-resolution river network for the study region with a greater spatial granularity compared to contemporary SWAT applications attempted to account for HI.•The anthropogenic influence on water balance for each river segment was estimated using data on human infrastructures, such as water intakes, power production facilities, discharges, dams, and land transformation.

Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development.

Global expansion of hydropower resources has increased in recent years to meet growing energy demands and fill worldwide gaps in electricity supply. However, hydropower induces significant environmental impacts on river ecosystems - impacts that are addressed through environmental impact assessment (EIA) processes. The need for effective EIA processes is increasing as environmental regulations are either stressed in developing countries undertaking rapid expansion of hydropower capacity or time- and resource-intensive in developed countries. Part of the challenge in implementing EIAs lies in reaching a consensus among stakeholders regarding the most important environmental factors as the focus of impact studies. To help address this gap, we developed a weight-of-evidence approach (and toolkit) as a preliminary and coarse assessment of the most relevant impacts of hydropower on primary components of the river ecosystem, as identified using river function indicators. Through a science-based questionnaire and predictive model, users identify which environmental indicators may be impacted during hydropower development as well as those indicators that have the highest levels of uncertainty and require further investigation. Furthermore, an assessment tool visualizes inter-dependent indicator relationships, which help formulate hypotheses about causal relationships explored through environmental studies. We apply these tools to four existing hydropower projects and one hypothetical new hydropower project of varying sizes and environmental contexts. We observed consistencies between the output of our tools and the Federal Energy Regulatory Commission licensing process (inclusive of EIAs) but also important differences arising from holistic scientific evaluations (our toolkit) versus regulatory policies. The tools presented herein are aimed at increasing the efficiency of the EIA processes that engender environmental studies without loss of rigor or transparency of rationale necessary for understanding, considering, and mitigating the environmental consequences of hydropower.

Multi-model Hydroclimate Projections for the Alabama-Coosa-Tallapoosa River Basin in the Southeastern United States.

This study uses a high-resolution, process-based modeling framework to assess the impacts of changing climate on water resources for the Alabama-Coosa-Tallapoosa River Basin in the southeastern United States. A 33-member ensemble of hydrologic projections was generated using 3 distributed hydrologic models (Precipitation-Runoff Modeling System, Variable Infiltration Capacity, and Distributed Hydrology Soil Vegetation Model) of different complexity. These hydrologic models were driven by dynamically downscaled and bias-corrected future climate simulations from 11 Coupled Model Intercomparison Project Phase 5 global climate models under Representative Concentration Pathway 8.5 emission scenario, with 40 years each in baseline (1966-2005) and future (2011-2050) periods. The hydroclimate response, in general, projects an increase in mean seasonal precipitation, runoff, and streamflow. The high and low flows are projected to increase and decrease, respectively, in general, suggesting increased likelihood of extreme rainfall events and intensification of the hydrologic cycle. The uncertainty associated with the ensemble hydroclimate response, analyzed through an analysis of variance technique, suggests that the choice of climate model is more critical than the choice of hydrologic model for the studied region. This study provides in-depth insights of hydroclimate response and associated uncertainties to support informed decisions by water resource managers.

A Checklist of River Function Indicators for hydropower ecological assessment.

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.

A stream classification system for the conterminous United States.

Stream classifications are important for understanding stream ecosystem diversity while also serving as tools for aquatic conservation and management. With current rates of land and riverscape modification within the United States (US), a comprehensive inventory and evaluation of naturally occurring stream habitats is needed, as this provides a physical template upon which stream biodiversity is organized and maintained. To adequately represent the heterogeneity of stream ecosystems, such a classification needs to be spatially extensive where multiple stream habitat components are represented at the highest resolution possible. Herein, we present a multi-layered empirically-driven stream classification system for the conterminous US, constructed from over 2.6 million stream reaches within the NHDPlus V2 stream network. The classification is based on emergent natural variation in six habitat layers meaningful at the stream-reach resolution: size, gradient, hydrology, temperature, network bifurcation, and valley confinement. To support flexibility of use, we provide multiple alternative approaches to developing classes and report uncertainty in classes assigned to stream reaches. The stream classification and underlying data provide valuable resources for stream conservation and research.

A stream classification system to explore the physical habitat diversity and anthropogenic impacts in riverscapes of the eastern United States.

Describing the physical habitat diversity of stream types is important for understanding stream ecosystem complexity, but also prioritizing management of stream ecosystems, especially those that are rare. We developed a stream classification system of six physical habitat layers (size, gradient, hydrology, temperature, valley confinement, and substrate) for approximately 1 million stream reaches within the Eastern United States in order to conduct an inventory of different types of streams and examine stream diversity. Additionally, we compare stream diversity to patterns of anthropogenic disturbances to evaluate associations between stream types and human disturbances, but also to prioritize rare stream types that may lack natural representation in the landscape. Based on combinations of different layers, we estimate there are anywhere from 1,521 to 5,577 different physical types of stream reaches within the Eastern US. By accounting for uncertainty in class membership, these estimates could range from 1,434 to 6,856 stream types. However, 95% of total stream distance is represented by only 30% of the total stream habitat types, which suggests that most stream types are rare. Unfortunately, as much as one third of stream physical diversity within the region has been compromised by anthropogenic disturbances. To provide an example of the stream classification's utility in management of these ecosystems, we isolated 5% of stream length in the entire region that represented 87% of the total physical diversity of streams to prioritize streams for conservation protection, restoration, and biological monitoring. We suggest that our stream classification framework could be important for exploring the diversity of stream ecosystems and is flexible in that it can be combined with other stream classification frameworks developed at higher resolutions (meso- and micro-habitat scales). Additionally, the exploration of physical diversity helps to estimate the rarity and patchiness of riverscapes over large region and assist in conservation and management.

Identifying non-reference sites to guide stream restoration and long-term monitoring.

The reference condition paradigm has served as the standard for assessing the outcomes of restoration projects, particularly their success in meeting project objectives. One limitation of relying solely on the reference condition in designing and monitoring restoration projects is that reference conditions do not necessarily elucidate impairments to effective restoration, especially diagnosing the causal mechanisms behind unsuccessful outcomes. We provide a spatial framework to select both reference and non-reference streams to guide restoration planning and long-term monitoring through reliance on anthropogenically altered ecosystems to understand processes that govern ecosystem biophysical properties and ecosystem responses to restoration practices. We then applied the spatial framework to East Fork Poplar Creek (EFPC), Tennessee (USA), a system receiving 30years of remediation and pollution abatement actions from industrialization, pollution, and urbanization. Out of >13,000 stream reaches, we identified anywhere from 4 to 48 reaches, depending on the scenario, that could be used in restoration planning and monitoring for specific sites. Preliminary comparison of fish species composition at these sites compared to EFPC sites were used to identify potential mechanisms limiting the ecological recovery following remediation. We suggest that understanding the relative role of anthropogenic pressures in governing ecosystem responses is required to successful, process-driven restoration.

US cities can manage national hydrology and biodiversity using local infrastructure policy.

Cities are concentrations of sociopolitical power and prime architects of land transformation, while also serving as consumption hubs of "hard" water and energy infrastructures. These infrastructures extend well outside metropolitan boundaries and impact distal river ecosystems. We used a comprehensive model to quantify the roles of anthropogenic stressors on hydrologic alteration and biodiversity in US streams and isolate the impacts stemming from hard infrastructure developments in cities. Across the contiguous United States, cities' hard infrastructures have significantly altered at least 7% of streams, which influence habitats for over 60% of North America's fish, mussel, and crayfish species. Additionally, city infrastructures have contributed to local extinctions in 260 species and currently influence 970 indigenous species, 27% of which are in jeopardy. We find that ecosystem impacts do not scale with city size but are instead proportionate to infrastructure decisions. For example, Atlanta's impacts by hard infrastructures extend across four major river basins, 12,500 stream km, and contribute to 100 local extinctions of aquatic species. In contrast, Las Vegas, a similar size city, impacts <1,000 stream km, leading to only seven local extinctions. So, cities have local policy choices that can reduce future impacts to regional aquatic ecosystems as they grow. By coordinating policy and communication between hard infrastructure sectors, local city governments and utilities can directly improve environmental quality in a significant fraction of the nation's streams reaching far beyond their city boundaries.

A global database of nitrogen and phosphorus excretion rates of aquatic animals.

Animals can be important in modulating ecosystem-level nutrient cycling, although their importance varies greatly among species and ecosystems. Nutrient cycling rates of individual animals represent valuable data for testing the predictions of important frameworks such as the Metabolic Theory of Ecology (MTE) and ecological stoichiometry (ES). They also represent an important set of functional traits that may reflect both environmental and phylogenetic influences. Over the past two decades, studies of animal-mediated nutrient cycling have increased dramatically, especially in aquatic ecosystems. Here we present a global compilation of aquatic animal nutrient excretion rates. The dataset includes 10,534 observations from freshwater and marine animals of N and/or P excretion rates. These observations represent 491 species, including most aquatic phyla. Coverage varies greatly among phyla and other taxonomic levels. The dataset includes information on animal body size, ambient temperature, taxonomic affiliations, and animal body N:P. This data set was used to test predictions of MTE and ES, as described in Vanni and McIntyre (2016; Ecology DOI: 10.1002/ecy.1582).

Environmental flows in the context of unconventional natural gas development in the Marcellus Shale.

Quantitative flow-ecology relationships are needed to evaluate how water withdrawals for unconventional natural gas development may impact aquatic ecosystems. Addressing this need, we studied current patterns of hydrologic alteration in the Marcellus Shale region and related the estimated flow alteration to fish community measures. We then used these empirical flow-ecology relationships to evaluate alternative surface water withdrawals and environmental flow rules. Reduced high-flow magnitude, dampened rates of change, and increased low-flow magnitudes were apparent regionally, but changes in many of the flow metrics likely to be sensitive to withdrawals also showed substantial regional variation. Fish community measures were significantly related to flow alteration, including declines in species richness with diminished annual runoff, winter low-flow, and summer median-flow. In addition, the relative abundance of intolerant taxa decreased with reduced winter high-flow and increased flow constancy, while fluvial specialist species decreased with reduced winter and annual flows. Stream size strongly mediated both the impact of withdrawal scenarios and the protection afforded by environmental flow standards. Under the most intense withdrawal scenario, 75% of reference headwaters and creeks (drainage areas <99 km2 ) experienced at least 78% reduction in summer flow, whereas little change was predicted for larger rivers. Moreover, the least intense withdrawal scenario still reduced summer flows by at least 21% for 50% of headwaters and creeks. The observed 90th quantile flow-ecology relationships indicate that such alteration could reduce species richness by 23% or more. Seasonally varying environmental flow standards and high fixed minimum flows protected the most streams from hydrologic alteration, but common minimum flow standards left numerous locations vulnerable to substantial flow alteration. This study clarifies how additional water demands in the region may adversely affect freshwater biological integrity. The results make clear that policies to limit or prevent water withdrawals from smaller streams can reduce the risk of ecosystem impairment.

Filling in the GAPS: evaluating completeness and coverage of open-access biodiversity databases in the United States.

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.