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USGS2022

Environmental DNA methods for ecological monitoring and biodiversity assessment in estuaries

Environmental DNA (eDNA) detection methods can complement traditional biomonitoring to yield new ecological insights in aquatic systems. However, the conceptual and methodological frameworks for aquatic eDNA detection and interpretation were developed primarily in freshwater environments and have not been well established for estuaries and marine environments that are by nature dynamic, turbid, and hydrologically complex. Environmental context and species life history are critical for successful application of eDNA methods, and the challenges associated with eDNA detection in estuaries were the subject of a symposium held at the University of California Davis on January 29, 2020 ( https://marinescience.ucdavis.edu/engagement/past-events/edna ). Here, we elaborate upon topics addressed in the symposium to evaluate eDNA methods in the context of monitoring and biodiversity studies in estuaries. We first provide a concise overview of eDNA science and methods, and then examine the San Francisco Estuary (SFE) as a case study to illustrate how eDNA detection can complement traditional monitoring programs and provide regional guidance on future potential eDNA applications. Additionally, we offer recommendations for enhancing communication between eDNA scientists and natural resource managers, which is essential for integrating eDNA methods into existing monitoring programs. Our intent is to create a resource that is accessible to those outside the field of eDNA, especially managers, without oversimplifying the challenges or advantages of these methods.

Estuaries and Coasts↗

USGS2013

U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration

Executive Summary Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes. This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being. The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct. The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking: Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales. Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics. Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time. Develop tools, technologies, and capacities to inform decisionmaking about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis. Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway. Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy: Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research. Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science. Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process. Support decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management. Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs. The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio. Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.

Circular↗

USGS2020

Urban stream syndrome and contaminant uptake in salamanders of Central Texas

We studied the ecological health of springs experiencing varying levels of urban development to assess impacts to rare endemic salamanders ( Eurycea spp.) of Central Texas. We evaluated measures of invertebrate species richness, water quality, and contaminant uptake by salamanders to determine how springs and their inhabitants were being affected by urban growth and changing land-use patterns. The number of environmental contaminants present and concentrations of contaminants increased in both water and salamander tissues with increasing age of the developments (i.e., years postconstruction) and increasing levels of impervious cover (e.g., roads) in urban watersheds compared with nondeveloped sites. We conclude that urbanization and associated increases in pollutant loading in watersheds can result in a loss of spring biodiversity and the accumulation of persistent and potentially toxic pollutants in salamanders. Although we detected generally low levels of pollutants, the altered water quality and invertebrate composition observed at springs, coupled with the changing hydrology and chronic contaminant exposure inherent in urban landscapes, is cause for concern, with potential implications for the long-term health, survival, and recovery of salamanders.

Texas↗

USGS1981

Assessment of impacts of proposed coal-resource and related economic development on water resources, Yampa River basin, Colorado and Wyoming: A summary

Expanded mining and use of coal resources in the Rocky Mountain region of the western United States will have substantial impacts on water resources, environmental amenities, and social and economic conditions. The U.S. Geological Survey has completed a 3-year assessment of the Yampa River basin, Colorado and Wyoming, where increased coal-resource development has begun to affect the environment and quality of life. Economic projections of the overall effects of coal-resource development were used to estimate water use and the types and amounts of waste residuals that need to be assimilated into the environment. Based in part upon these projections, several physical-based models and other semiquantitative assessment methods were used to determine possible effects upon the basin's water resources. Depending on the magnitude of mining and use of coal resources in the basin, an estimated 0.7 to 2.7 million tons (0.6 to 2.4 million metric tons) of waste residuals may be discharged annually into the environment by coal-resource development and associated economic activities. If the assumed development of coal resources in the basin occurs, annual consumptive use of water, which was approximately 142,000 acre-feet (175 million cubic meters) during 1975, may almost double by 1990. In a related analysis of alternative cooling systems for coal-conversion facilities, four to five times as much water may be used consumptively in a wet-tower, cooling-pond recycling system as in once-through cooling. An equivalent amount of coal transported by slurry pipeline would require about one-third the water used consumptively by once-through cooling for in-basin conversion. Current conditions and a variety of possible changes in the water resources of the basin resulting from coal-resource development were assessed. Basin population may increase by as much as threefold between 1975 and 1990. Volumes of wastes requiring treatment will increase accordingly. Potential problems associated with ammonia-nitrogen concentrations in the Yampa River downstream from Steamboat Springs were evaluated using a waste-load assimilative-capacity model. Changes in sediment loads carried by streams due to increased coal mining and construction of roads and buildings may be apparent only locally; projected increases in sediment loads relative to historic loads from the basin are estimated to be 2 to 7 percent. Solid-waste residuals generated by coal-conversion processes and disposed of into old mine pits may cause widely dispersed ground-water contamination, based on simulation-modeling results. Projected increases in year-round water use will probably result in the construction of several proposed reservoirs. Current seasonal patterns of streamflow and of dissolvedsolids concentrations in streamflow will be altered appreciably by these reservoirs. Decreases in time-weighted mean-annual dissolved-solids concentrations of as much as 34 percent are anticipated, based upon model simulations of several configurations of proposed reservoirs. Detailed statistical analyses of water-quality conditions in the Yampa River basin were made. Regionalized maximum waterquality concentrations were estimated for possible comparison with future conditions. Using Landsat imagery and aerial photographs, potential remote-sensing applications were evaluated to monitor land-use changes and to assess both snow cover and turbidity levels in streams. The technical information provided by the several studies of the Yampa River basin assessment should be useful to regional planners and resource managers in evaluating the possible impacts of development on the basin's water resources.

Colorado, Wyoming↗

USGS2004

Predicting patterns of non-native plant invasions in Yosemite National Park, California, USA

One of the major issues confronting management of parks and reserves is the invasion of non-native plant species. Yosemite National Park is one of the largest and best-known parks in the United States, harbouring significant cultural and ecological resources. Effective management of non-natives would be greatly assisted by information on their potential distribution that can be generated by predictive modelling techniques. Our goal was to identify key environmental factors that were correlated with the percent cover of non-native species and then develop a predictive model using the Genetic Algorithm for Rule-set Production technique. We performed a series of analyses using community-level data on species composition in 236 plots located throughout the park. A total of 41 non-native species were recorded which occurred in 23.7% of the plots. Plots with non-natives occurred most frequently at low- to mid-elevations, in flat areas with other herbaceous species. Based on the community-level results, we selected elevation, slope, and vegetation structure as inputs into the GARP model to predict the environmental niche of non-native species. Verification of results was performed using plot data reserved from the model, which calculated the correct prediction of non-native species occurrence as 76%. The majority of the western, lower-elevation portion of the park was predicted to have relatively low levels of non-native species occurrence, with highest concentrations predicted at the west and south entrances and in the Yosemite Valley. Distribution maps of predicted occurrences will be used by management to: efficiently target monitoring of non-native species, prioritize control efforts according to the likelihood of non-native occurrences, and inform decisions relating to the management of non-native species in postfire environments. Our approach provides a valuable tool for assisting decision makers to better manage non-native species, which can be readily adapted to target non-native species in other locations.

Diversity and Distributions↗

USGS2014

Landscape alterations influence differential habitat use of nesting buteos and ravens within sagebrush ecosystem: implications for transmission line development

A goal in avian ecology is to understand factors that influence differences in nesting habitat and distribution among species, especially within changing landscapes. Over the past 2 decades, humans have altered sagebrush ecosystems as a result of expansion in energy production and transmission. Our primary study objective was to identify differences in the use of landscape characteristics and natural and anthropogenic features by nesting Common Ravens ( Corvus corax ) and 3 species of buteo (Swainson's Hawk [ Buteo swainsoni ], Red-tailed Hawk [ B. jamaicensis ], and Ferruginous Hawk [ B. regalis ]) within a sagebrush ecosystem in southeastern Idaho. During 2007–2009, we measured multiple environmental factors associated with 212 nest sites using data collected remotely and in the field. We then developed multinomial models to predict nesting probabilities by each species and predictive response curves based on model-averaged estimates. We found differences among species related to nesting substrate (natural vs. anthropogenic), agriculture, native grassland, and edge (interface of 2 cover types). Most important, ravens had a higher probability of nesting on anthropogenic features (0.80) than the other 3 species (<0.10), and the probability of nesting near agriculture was greatest for ravens (0.55) followed by Swainson's Hawk (0.28). We also describe changes in nesting densities over 4 decades at this site as related to natural and anthropogenic disturbances. Since the 1970s, the composition of the raptor and raven nesting community has drastically changed with anthropogenic alterations and loss of continuous stands of sagebrush ( Artemisia spp.), favoring increased numbers of nesting ravens and fewer nesting Ferruginous Hawks. Our results indicate that habitat alterations, fragmentation, and forthcoming disturbances anticipated with continued energy development in sagebrush steppe ecosystems can lead to predictable changes in raptor and raven communities.

Idaho↗

USGS2007

Global rates of habitat loss and implications for amphibian conservation

A large number of factors are known to affect amphibian population viability, but most authors agree that the principal causes of amphibian declines are habitat loss, alteration, and fragmentation. We provide a global assessment of land use dynamics in the context of amphibian distributions. We accomplished this by compiling global maps of amphibian species richness and recent rates of change in land cover, land use, and human population growth. The amphibian map was developed using a combination of published literature and digital databases. We used an ecoregion framework to help interpret species distributions across environmental, rather than political, boundaries. We mapped rates of land cover and use change with statistics from the World Resources Institute, refined with a global digital dataset on land cover derived from satellite data. Temporal maps of human population were developed from the World Resources Institute database and other published sources. Our resultant map of amphibian species richness illustrates that amphibians are distributed in an uneven pattern around the globe, preferring terrestrial and freshwater habitats in ecoregions that are warm and moist. Spatiotemporal patterns of human population show that, prior to the 20 th century, population growth and spread was slower, most extensive in the temperate ecoregions, and largely exclusive of major regions of high amphibian richness. Since the beginning of the 20 th century, human population growth has been exponential and has occurred largely in the subtropical and tropical ecoregions favored by amphibians. Population growth has been accompanied by broad-scale changes in land cover and land use, typically in support of agriculture. We merged information on land cover, land use, and human population growth to generate a composite map showing the rates at which humans have been changing the world. When compared with the map of amphibian species richness, we found that many of the regions of the earth supporting the richest assemblages of amphibians are currently undergoing the highest rates of landscape modification.

Copeia↗

USGS2024

Development and calibration of HEC–RAS hydraulic, temperature, and nutrient models for the Mohawk River, New York

In support of a preliminary analysis performed by New York State Department of Environmental Conservation that found elevated nutrient levels along selected reaches of the Mohawk River, a one-dimensional, unsteady hydraulic and water-quality model (Hydrologic Engineering Center River Analysis System Nutrient Simulation Module 1 [HEC–RAS NSM I]) was developed by the U.S. Geological Survey for the 127-mile reach of the Mohawk River between Rome and Cohoes, New York. The model was designed to accurately simulate within-channel flow conditions for this highly regulated, control-structure dense river reach. The model was calibrated for the period of May through September 2016 using available streamflow, temperature, and water-quality data. Nitrogen, phosphorus, dissolved oxygen, and water column algae were balanced within the model; however, the nutrient model calibration was focused on phosphorus. The HEC–RAS hydraulic model simulated streamflow adequately at the calibration locations with observed and simulated daily flows demonstrating coefficient of determination ( r 2 ) values ranging from 0.91 to 0.97, mean absolute error ranging from 15–20 percent, and bias ranging from −7 to 16 percent. The water temperature model within HEC–RAS NSM I demonstrated remarkable ability to simulate water temperature: typical water temperature errors were less than 1.0 degree Celsius (°C). Simulated water temperature results closely tracked observed continuous water temperature data at three locations on the Mohawk River, with mean absolute error for the 2016 study period ranging from 0.87 to 0.90 °C, and a root mean square error of 1.00 to 1.07 °C. Performance criteria for the water-quality (nutrient) model were applied differently than the water temperature model because of the temporally coarse discrete samples collected for the project. The average difference between final simulated concentrations and observed concentrations of organic phosphorus for all sample locations was within 0.01 milligrams per liter (mg/L) and within 0.09 mg/L for orthophosphate using all locations except Rome, which was within 0.25 mg/L. The calibrated model was used to implement nine phosphorus reduction scenarios by applying reductions to wastewater treatment plant effluent concentrations within the model. Monthly mean differences were computed for five comparison locations. Scenario results were generally linear and predictable; scenarios implementing the highest reductions showed correspondingly larger differences in Mohawk River concentrations downstream from the wastewater treatment plants associated with those reductions. The largest monthly mean differences were realized from reduction scenario nine and ranged from −0.018 to −0.076 mg/L for organic phosphorus and from 0.001 to −0.138 mg/L for orthophosphate.

New York↗

USGS1984

Flow-through bioassay for measuring bioaccumulation of toxic substances from sediment

Over 10 million cubic meters of sediment are dredged annually from Great Lakes waterways. Because much of this material is taken from harbors, connecting channels, and other nearshore areas that often are contaminated with toxic substances, the sediments proposed for dredging need to be evaluated for the presence of bioavailable contaminants and the potential for toxicity to the biota. Sound decisions on the appropriate disposal of the dredged material can be made only after such an evaluation. Presently, no standardized procedure exists for evaluating dredged material in freshwater systems although current criteria for discharge of dredged material into marine water have been developed (USEPA/CE 1977). In the ocean discharge guideline, it is recommended that bioassays be conducted on liquid, solid, and suspended particulate phases of dredged material. because it appears that the solid phase has the greatest potential for environmental damage and because measurement of bioaccumulation must be made to evaluate sediments for disposal (USEPA/CE 1977, Seeyle and Mac 1983), we developed a bioassay for testing the solid phase of dredged material that measures the survival of organisms and, perhaps more important, the bioaccumulation of toxic substances by aquatic organisms from naturally contaminated sediments (Peddicord et al. 1980; Rubinstein et al. 1980, 1983; Seeyle st al. 1982), several have used testing methods that result in unacceptable mortality to control organisms (Bahnick et al. 1981, Prater et al. 1983). Our bioassay is intended to estimate the potential for bioaccumlation of contaminants from sediments that are not acutely toxic to test organisms, but are suspected of containing persistent contaminants. By using test organisms that are not highly susceptible to toxic compounds, the bioaccumulation test allows estimation of the potential food-chain accumulation of contaminants that may occur in local biota from surficial sediments. In practice, bioaccumulation observed in this bioassay by organisms exposed to test sediments (sediments to be dredged) would be compared to bioaccumulation observed from sediments collected from a reference site (e.g. a disposal site or open lake), and also from control sediments (relatively clean sediment). Decisions could then be based on a comparison of results between tests and reference sediments to determine if disposal would cause dehydration to the habitat, and between reference and control sediment to determine if even the reference material is seriously contaminated. Although the test is not intended to be a toxicity test per se, use of test, reference, and control sediments enables interpretation of any mortality of organisms that may occur during the bioassays. High mortality in bioassays with test or reference sediment would indicate acute toxicity of sediments in the project area. However if high mortality occurs in all three sediments, it can be assumed that the organisms were not in a healthy state at the time of testing. We describe the results of 10-day sediment bioassays in which both mortality and bioaccumulation were measured in four aquatic organisms. We exposed two infaunal organisms and two species of fish to test and control sediments in the laboratory.

Report↗

USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗

USGS2015

StreamStats in Georgia: A water-resources web application

Summary Part of the mission of the U.S. Geological Survey (USGS) is to provide information on streamflow in the Nation's streams to help understand the Nation's water resources. Streamflow statistics are used by water managers, engineers, scientists, and others to protect people and property during floods and droughts, and to manage, protect, and enhance water resources. StreamStats is a Web-based Geographic Information System (GIS) application that was created by the USGS, in cooperation with the Environmental Systems Research Institute, Inc., that allows users to easily obtain streamflow statistics, basin characteristics, and descriptive information for USGS streamgages and user-selected ungaged locations on streams (Ries and others, 2008). StreamStats is being implemented on a State-by-State basis to allow for customization of the data development and underlying datasets to address their specific needs, issues, and objectives. The USGS, in cooperation with the Georgia Environmental Protection Division and Georgia Department of Transportation, has implemented StreamStats for Georgia. The Georgia StreamStats Web site is available through the national StreamStats Web-page portal at http://streamstats.usgs.gov. Links are provided on this Web page for individual State applications, instructions for using StreamStats, definitions of basin characteristics and streamflow statistics, and other supporting information.

Georgia↗

USGS1996

Susceptibility of ground water to surface and shallow sources of contamination in Mississippi

Ground water, because of its extensive use in agriculture, industry, and public-water supply, is one of Mississippi's most important natural resources. Ground water is the source for about 80 percent of the total freshwater used by the State's population (Solley and others, 1993). About 2,600 Mgal/d of freshwater is withdrawn from aquifers in Mississippi (D.E. Burt, Jr., U.S. Geological Survey, oral commun., 1995). Wells capable of yielding 200 gal/min of water with quality suitable for most uses can be developed nearly anywhere in the State (Bednar, 1988). The U.S. Geological Survey (USGS), in cooperation with the Mississippi Department of Environmental Quality, Office of Pollution Control, and the Mississippi Department of Agriculture and Commerce, Bureau of Plant Industry, conducted an investigation to evaluate the susceptibility of ground water to contamination from surgace and shallow sources in Mississippi. A geographic information system (GIS) was used to develop and analyze statewide spatial data layers that contain geologic, hydrologic, physiographic, and cultural information.

Mississippi↗

USGS2013

Forecasting the effects of coastal protection and restoration projects on wetland morphology in coastal Louisiana under multiple environmental uncertainty scenarios

Few landscape scale models have assessed the effects of coastal protection and restoration projects on wetland morphology while taking into account important uncertainties in environmental factors such as sea-level rise (SLR) and subsidence. In support of Louisiana's 2012 Coastal Master Plan, we developed a spatially explicit wetland morphology model and coupled it with other predictive models. The model is capable of predicting effects of protection and restoration projects on wetland area, landscape configuration, surface elevation, and soil organic carbon (SOC) storage under multiple environmental uncertainty scenarios. These uncertainty scenarios included variability in parameters such as eustatic SLR (ESLR), subsidence rate, and Mississippi River discharge. Models were run for a 2010–2060 simulation period. Model results suggest that under a “future-without-action” condition (FWOA), coastal Louisiana is at risk of losing between 2118 and 4677 km 2 of land over the next 50 years, but with protection and restoration projects proposed in the Master Plan, between 40% and 75% of that loss could be mitigated. Moreover, model results indicate that under a FWOA condition, SOC storage (to a depth of 1 m) could decrease by between 108 and 250 million metric tons, a loss of 12% to 30% of the total coastwide SOC, but with the Master Plan implemented, between 35% and 74% of the SOC loss could be offset. Long-term maintenance of project effects was best attained in areas of low SLR and subsidence, with a sediment source to support marsh accretion. Our findings suggest that despite the efficacy of restoration projects in mitigating losses in certain areas, net loss of wetlands in coastal Louisiana is likely to continue. Model results suggest certain areas may eventually be lost regardless of proposed restoration investment, and, as such, other techniques and strategies of adaptation may have to be utilized in these areas.

Louisiana↗

USGS2015

Landscapes for energy and wildlife: conservation prioritization for golden eagles across large spatial scales

Proactive conservation planning for species requires the identification of important spatial attributes across ecologically relevant scales in a model-based framework. However, it is often difficult to develop predictive models, as the explanatory data required for model development across regional management scales is rarely available. Golden eagles are a large-ranging predator of conservation concern in the United States that may be negatively affected by wind energy development. Thus, identifying landscapes least likely to pose conflict between eagles and wind development via shared space prior to development will be critical for conserving populations in the face of imposing development. We used publicly available data on golden eagle nests to generate predictive models of golden eagle nesting sites in Wyoming, USA, using a suite of environmental and anthropogenic variables. By overlaying predictive models of golden eagle nesting habitat with wind energy resource maps, we highlight areas of potential conflict among eagle nesting habitat and wind development. However, our results suggest that wind potential and the relative probability of golden eagle nesting are not necessarily spatially correlated. Indeed, the majority of our sample frame includes areas with disparate predictions between suitable nesting habitat and potential for developing wind energy resources. Map predictions cannot replace on-the-ground monitoring for potential risk of wind turbines on wildlife populations, though they provide industry and managers a useful framework to first assess potential development.

Wyoming↗

USGS2020

Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System

Smallmouth buffalo (Ictiobus bubalus) is a common and widely distributed large-bodied species of the family Catostomidae. It inhabits large rivers and reservoirs of the eastern continental United States (east of the continental Divide) and is most abundant and common in the large rivers of the Midwest and Central Plains, though it does occur as far north and east as the Hudson Bay drainage and as far south and west as Arizona (Edwards and Twoney 1982). Historically, smallmouth buffalo were an important component of commercial fisheries on both the Mississippi and Illinois Rivers. However, following the introduction of common carp (Cyprinus carpio) in the mid-1800s (Carlander 1954), the construction of a system of navigation dams on Upper Mississippi and Illinois River in the 1930s (USGS 1999), and water quality/pollution issues through the 1980s (Weiner 2010), the role of smallmouth buffalo in the overall UMRS fish community and commercial fishery has generally diminished relative to historical standards. Still, smallmouth buffalo remains an important and valued component of the UMRS commercial fishery. The study area is represented by three study reaches on the Illinois River and three study reaches on the Upper Mississippi River (Figure 1). Collectively, these study reaches represent nearly 1200 river km and exist across strong and pronounced ecological and disturbance gradients. For example, habitat composition, water quality, commercial navigation intensity, aquatic plant prominence, and the number and abundance of nonnative fish species vary strongly across the study domain, with northern Mississippi River reaches exhibiting less navigation traffic, better water quality, markedly greater aquatic plant prominence, more diverse habitat composition, and comparably much smaller numbers of nonnative species than the lower Mississippi River study reach and those on the Illinois River (USGS 1999; Johnson and Hagerty [eds] 2008; Irons et al. 2009). Long term monitoring efforts conducted under the auspices of the Upper Mississippi River Restoration program over the past 27 years have provided tremendous insights into shifts and changes of the overall UMRS fish community (Ickes et al. 2005; Garvey et al. 2010; Schramm and Ickes 2016). However, these monitoring efforts observe only the most basic aspects of the UMRS fish community (i.e., catch, length, weight, distribution, and occurrence). To gain a greater understanding of forces driving community level shifts and changes, more directed study is needed on the functional attributes of fish populations (i.e., growth, mortality, recruitment). Collectively, these functional attributes of populations are termed population dynamics and/or vital rates. It is important to note, the population dynamics of fishes in large rivers is generally poorly understood, especially for non-game species (Ickes 2018). The prevailing view is that abiotic factors largely govern inter-annual population dynamics, typically based upon rather short-term observations and correlations with assorted abiotic river attributes that vary on a seasonal or annual basis (for example, Risotto and Turner 1985). However, the role that longer-term abiotic factors play in regulating population abundance, or that biotic factors internal to the population (e.g., spawner-recruit dynamics, growth dynamics) or external to the population (e.g., predator-prey dynamics, sympatric competitors, disease) remain poorly understood. Achieving a greater understanding of these dynamics is important for stock, game, and invasive species management. In 2017, as part of a larger study designed to gain vital population rate information for smallmouth buffalo in the Upper Mississippi and Illinois Rivers (“Smallmouth Buffalo population demographics of the Upper Mississippi River System”; UMRR LTRM 2018SOW project items 2018MMBF1-2018MMBF6) annual growth patterns in smallmouth buffalo were determined and evaluated. This was accomplished by measuring growth histories recorded in annual growth increments on hard bony parts (here otoliths), a method known generically as biochronology, and somewhat analogous to dendrochronology practiced by foresters. These methods allow one to generate time-series of annual growth histories that depend upon age, year class (i.e., cohort), and annual environmental conditions experienced by the population over time (Weisberg, 1993). Biochronology methods were used to develop a 36-year time series of smallmouth buffalo growth in the Upper Mississippi and Illinois Rivers across a 1200 km ecological and human use disturbance gradient. Annual growth intervals were identified and measured from otoliths to determine fish age and growth history. A mixed model that parses the growth increment into age and year effects was fit to these data. Given the pronounced ecological and disturbance gradients inherent to the UMRS and the study domain, an a priori expectation of differing patterns in growth is accepted as a null hypothesis to test. The goal of this study was to model smallmouth buffalo growth as a function of the age of the fish and the growth year in which the growth was gained. The primary modeling objective was to parse growth observed on each annulus into a portion attributable to the age of the fish and the portion attributable to the year in which the growth was gained. In effect, this modeling approach removes the somewhat trivial age effects on growth so that a non-confounded growth year effect can be gained. Results attributable to growth year provide a time series of growth information that is of the same duration as the oldest fish observed and solely reflects environmental influences on growth. These model responses can then be investigated relative to environmental covariate time-series suspected of influencing growth of smallmouth buffalo in the Upper Mississippi and Illinois Rivers (e.g., temperature, discharge, population density, population mortality, forage availability, sympatric competition, habitat composition, navigation intensity, nonnative fish prominence, etc.). Thus, the primary scientific objective was to investigate if and how smallmouth buffalo growth varies in accordance with innate ecological and disturbance gradients across the study domain.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗

USGS2015

Habitat influences distribution of chronic wasting disease in white-tailed deer

Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in 1967 in a captive research facility in Colorado. In the northeastern United States, CWD was first confirmed in white-tailed deer ( Odocoileus virginianus ) in 2005. Because CWD is a new and emerging disease with a spatial distribution that had yet to be assessed in the Northeast, we examined demographic, environmental, and spatial effects to determine how each related to this spatial distribution. The objectives of our study were to identify environmental and spatial effects that best described the spatial distribution of CWD in free-ranging white-tailed deer and identify areas that support deer that are at risk for CWD infection in the Northeast. We used Bayesian hierarchical modeling that incorporated demographic covariates, such as sex and age, along with environmental covariates, which included elevation, slope, riparian corridor, percent clay, and 3 landscapes (i.e., developed, forested, open). The model with the most support contained landscape covariates and spatial effects that represented clustering of CWD in adjacent grid cells. Forested landscapes had the strongest relationship with the distribution of CWD, with increased risk of CWD occurring in areas that had lesser amounts of forest. Our results will assist resource managers in understanding the spatial distribution of CWD within the study area, and in surrounding areas where CWD has yet to be found. Efficiency of disease surveillance and containment efforts can be improved by allocating resources used for surveillance in areas with deer populations that are at greatest risk for infection.

Journal of Wildlife Management↗

USGS2018

Evaluating the waterfowl breeding population and habitat survey for scaup

Potential bias in breeding population estimates of certain duck species from the Waterfowl Breeding Population and Habitat Survey (WBPHS) has been a concern for decades. The WBPHS does not differentiate between lesser ( Aythya affinis ) and greater ( A . marila ) scaup, but lesser scaup comprise 89% of the combined scaup population and their population estimates are suspected to be biased. We marked female lesser scaup (i.e., marked scaup) in the Mississippi and Atlantic Flyways, Canada and United States, with implantable satellite transmitters to track their spring migration through the traditional and eastern survey areas of the WBPHS, 2005–2010. Our goal was to use data independent of the WBPHS to evaluate whether breeding population estimates for scaup were biased and identify variables that might be used in the future to refine population estimates. We found that the WBPHS estimates of breeding scaup are biased because, across years, only 30% of our marked scaup had settled for the breeding period when the strata in which they settled were surveyed, 43% were available to be counted in multiple survey strata as their migration continued during the WBPHS, 32% settled outside the WBPHS area, the number of times a marked scaup was available to be counted by survey crews varied positively with the latitude that a marked scaup settled on breeding areas, the probability of a marked scaup being in a stratum while it was surveyed varied among years, and these probabilities were positively correlated with the traditional and eastern breeding population estimates for scaup. Annual population estimates derived from banding data provide a less biased and preferable method of monitoring scaup population status and trend. Development of models that include metrics such as survey stratum latitude and annual spring environmental conditions might potentially be used to improve scaup breeding population estimates derived from the WBPHS, but independent estimates from banding data would be important to evaluate such models.

Journal of Wildlife Management↗

USGS2016

Physical and chemical constraints limit the habitat window for an endangered mussel

Development of effective conservation and restoration strategies for freshwater pearly mussels requires identification of environmental constraints on the distributions of individual mussel species. We examined whether the spatial distribution of the endangered Alasmidonta heterodon in Flat Brook, a tributary of the upper Delaware River, was constrained by water chemistry (i.e., calcium availability), bed mobility, or both. Alasmidonta heterodon populations were bracketed between upstream reaches that were under-saturated with respect to aragonite and downstream reaches that were saturated for aragonite during summer baseflow but had steep channels with high bed mobility. Variability in bed mobility and water chemistry along the length of Flat Brook create a “habitat window” for A. heterodon defined by bed stability (mobility index ≤1) and aragonite saturation (saturation index ≥1). We suggest the species may exist in a narrow biogeochemical window that is seasonally near saturation. Alasmidonta heterodon populations may be susceptible to climate change or anthropogenic disturbances that increase discharge, decrease groundwater inflow or chemistry, and thus affect either bed mobility or aragonite saturation. Identifying the biogeochemical microhabitats and requirements of individual mussel species and incorporating this knowledge into management decisions should enhance the conservation and restoration of endangered mussel species.

New Jersey↗