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USGS2012

USGS Environmental health science strategy: providing environmental health science for a changing world: Public review release

America has an abundance of natural resources. We have bountiful clean water, fertile soil, and unrivaled national parks, wildlife refuges, and public lands. These resources enrich our lives and preserve our health and wellbeing. These resources have been maintained because of our history of respect for their value and an enduring commitment to their vigilant protection. Awareness of the social, economic, and personal value of the health of our environment is increasing. The emergence of environmentally driven diseases caused by environmental exposure to contaminants and pathogens is a growing concern worldwide. New health threats and patterns of established threats are affected by both natural and anthropogenic changes to the environment. Human activities are key drivers of emerging (new and re-emerging) health threats. Societal demands for land and natural resources, a better quality of life, improved economic prosperity, and the environmental impacts associated with these demands will continue to increase. Natural earth processes, climate trends, and related climatic events will add to the environmental impact of human activities. These environmental drivers will influence exposure to disease agents, including viral, bacterial, prion, and fungal pathogens, parasites, natural earth materials, toxins and other biogenic compounds, and synthetic chemicals and substances. The U.S. Geological Survey (USGS) defines environmental health science broadly as the interdisciplinary study of relations among the quality of the physical environment, the health of the living environment, and human health. The interactions among these three spheres are driven by human activities, ecological processes, and natural earth processes; the interactions affect exposure to contaminants and pathogens and the severity of environmentally driven diseases in animals and people. This definition provides USGS with a framework for synthesizing natural science information from across the Bureau and providing it to environmental, natural resource, agricultural, and public-health managers. The USGS is a Federal science agency with a broad range of natural science expertise relevant to environmental health. USGS provides scientific information and tools as a scientific basis for management and policy decision making. USGS specializes in science at the environment-health interface, by characterizing the processes that affect the interaction among the physical environment, the living environment, and people, and the resulting factors that affect ecological and human exposure to disease agents. This report describes a 10-year strategy that encompasses the portfolio of USGS environmental health science. It summarizes national environmental health priorities that USGS is best suited to address, and will serve as a strategic framework for USGS environmental health science goals, actions, and outcomes for the next decade. Implementation of this strategy is intended to aid coordination of USGS environmental health activities and to provide a focal point for disseminating information to stakeholders. The "One Health" paradigm advocated by the World Health Organization (WHO, 2011), and the American Veterinary Medicine Association (AVMA, 2008), among others, is based on a general recognition that the health of humans, animals, and the environment are inextricably linked. Thus, successful efforts to protect that health will require increased interdisciplinary research and increased communication and collaboration among the broader scientific and health community. This strategy is built upon that paradigm. The vision, mission, and five cornerstone goals of the USGS Environmental Health Science Strategy were developed with significant input from a wide range of stakeholders. Vision - The USGS is a premier source of the environmental health science needed to safeguard the health of the environment, fish, wildlife, and people. Mission - The mission of USGS in environmental health science is to contribute scientific information to environmental, natural resource, agricultural, and public-health managers, who use that science to support sound decision making. USGS provides the science to: - Goal 1: Identify, prioritize, and detect contaminants and pathogens of emerging environmental concern. - Goal 2: Reduce the impact of contaminants on the environment, fish, wildlife, and people. - Goal 3: Reduce the impact of pathogens on the environment, fish, wildlife, and people. - Goal 4: Discover the complex interactions and combined effects of exposure to contaminants and pathogens. - Goal 5: Prepare for and respond to environmental impacts and related health threats of natural and anthropogenic disasters. Goals 1 through 4 are intended to provide science to address environmental health threats in a logical order, from informing prevention and preparedness, to supporting systematic management response to environmental health issues. Goal 4 addresses the interaction among contaminants and pathogens, an issue of emerging concern in environmental health science. Goal 5 acknowledges the fact that natural and anthropogenic disasters can cause immediate and prolonged adverse environmental health threats. This strategy proposes that USGS take the following strategic science actions to achieve each of the five goals of this strategy: Goal 1: Identify, prioritize, and detect contaminants and pathogens of emerging environmental concern. - Strategic Science Action 1. - Prioritize contaminants and pathogens of emerging concern to guide research, detection, and management activities. - Strategic Science Action 2. - Conduct surveillance and monitoring to provide early warning of emerging health threats. - Strategic Science Action 3. - Develop approaches and tools that identify vulnerable environmental settings, ecosystems, and species. Goal 2: Reduce the impact of contaminants on the environment, fish, wildlife, and people. - Strategic Science Action 1. - Systematically characterize the sources, occurrence, transport and fate of environmental contaminants to guide efforts to manage and mitigate contamination. - Strategic Science Action 2. - Evaluate the threats of contamination on the health of the environment, fish, wildlife, and people, and inform the associated management and protection efforts. - Strategic Science Action 3. - Characterize potential human exposure to support establishment of health-based standards or guidelines and contamination-reduction efforts. Goal 3: Reduce the impact of pathogens on the environment, fish, wildlife, and people. - Strategic Science Action 1. - Determine the biotic and abiotic factors that control the ecology of infectious diseases affecting natural populations of aquatic and terrestrial species and potential transmission to other animals and humans. - Strategic Science Action 2. - Establish how natural and anthropogenic environmental changes affect the distribution and severity of infectious diseases in natural populations of aquatic and terrestrial species and potential transmission to other animals and humans. - Strategic Science Action 3. - Develop surveillance systems to identify changing patterns of disease activity in priority geographic areas. Goal 4: Discover the complex interactions and combined effects of exposure to contaminants and pathogens. - Strategic Science Action 1. - Identify how exposure to one class of disease agents (contaminants or pathogens) can make an organism more susceptible to effects from exposure to the other class of disease agents. - Strategic Science Action 2. - Implement interdisciplinary studies that characterize the effects of combined exposure to pathogens and contaminants. Goal 5: Prepare for and respond to the environmental impacts and related health threats of natural and anthropogenic disasters. - Strategic Science Action 1. - Establish a formal interdisciplinary science capability to rapidly assess the environmental health risks associated with disasters. - Strategic Science Action 2. - Enhance methods to anticipate, prepare for, and identify environmental, ecological, and related health impacts of future disasters. This strategy is one of seven USGS science strategies developed concurrently: - Climate and Land Use Change - Core Science Systems - Ecosystems - Energy and Mineral Resources - Environmental Health - Natural Hazards - Water. This strategy describes how USGS will address the highest priority environmental health issues facing the Nation. The ultimate intended outcome of this science strategy is prevention and reduction of adverse impacts to the quality of the environment, the health of our living resources, and human health. Communication with, and receiving input from, partners and stakeholders regarding their science needs is essential for successful implementation of this strategy. It is incumbent on USGS to reach out to all stakeholders to ensure that USGS efforts are focused on the highest priority environmental health issues and that products are provided in the most timely and usable form to all those who can use them. USGS must reach out to the scientific community, internally and externally, to ensure that our efforts are integrated with and take full advantage of the activities of others.

Open-File Report↗

USGS2005

Bankfull characteristics of Ohio streams and their relation to peak streamflows

Regional curves, simple-regression equations, and multiple-regression equations were developed to estimate bankfull width, bankfull mean depth, bankfull cross-sectional area, and bankfull discharge of rural, unregulated streams in Ohio. The methods are based on geomorphic, basin, and flood-frequency data collected at 50 study sites on unregulated natural alluvial streams in Ohio, of which 40 sites are near streamflow-gaging stations. The regional curves and simple-regression equations relate the bankfull characteristics to drainage area. The multiple-regression equations relate the bankfull characteristics to drainage area, main-channel slope, main-channel elevation index, median bed-material particle size, bankfull cross-sectional area, and local-channel slope. Average standard errors of prediction for bankfull width equations range from 20.6 to 24.8 percent; for bankfull mean depth, 18.8 to 20.6 percent; for bankfull cross-sectional area, 25.4 to 30.6 percent; and for bankfull discharge, 27.0 to 78.7 percent. The simple-regression (drainage-area only) equations have the highest average standard errors of prediction. The multiple-regression equations in which the explanatory variables included drainage area, main-channel slope, main-channel elevation index, median bed-material particle size, bankfull cross-sectional area, and local-channel slope have the lowest average standard errors of prediction. Field surveys were done at each of the 50 study sites to collect the geomorphic data. Bankfull indicators were identified and evaluated, cross-section and longitudinal profiles were surveyed, and bed- and bank-material were sampled. Field data were analyzed to determine various geomorphic characteristics such as bankfull width, bankfull mean depth, bankfull cross-sectional area, bankfull discharge, streambed slope, and bed- and bank-material particle-size distribution. The various geomorphic characteristics were analyzed by means of a combination of graphical and statistical techniques. The logarithms of the annual peak discharges for the 40 gaged study sites were fit by a Pearson Type III frequency distribution to develop flood-peak discharges associated with recurrence intervals of 2, 5, 10, 25, 50, and 100 years. The peak-frequency data were related to geomorphic, basin, and climatic variables by multiple-regression analysis. Simple-regression equations were developed to estimate 2-, 5-, 10-, 25-, 50-, and 100-year flood-peak discharges of rural, unregulated streams in Ohio from bankfull channel cross-sectional area. The average standard errors of prediction are 31.6, 32.6, 35.9, 41.5, 46.2, and 51.2 percent, respectively. The study and methods developed are intended to improve understanding of the relations between geomorphic, basin, and flood characteristics of streams in Ohio and to aid in the design of hydraulic structures, such as culverts and bridges, where stability of the stream and structure is an important element of the design criteria. The study was done in cooperation with the Ohio Department of Transportation and the U.S. Department of Transportation, Federal Highway Administration.

Scientific Investigations Report↗

USGS2007

Isotopic analysis of N and O in nitrite and nitrate by sequential selective bacterial reduction to N2O

Nitrite is an important intermediate species in the biogeochemical cycling of nitrogen, but its role in natural aquatic systems is poorly understood. Isotopic data can be used to study the sources and transformations of NO 2 - in the environment, but methods for independent isotopic analyses of NO 2 - in the presence of other N species are still new and evolving. This study demonstrates that isotopic analyses of N and O in NO 2 - can be done by treating whole freshwater or saltwater samples with the denitrifying bacterium Stenotrophomonas nitritireducens , which selectively reduces NO 2 - to N 2 O for isotope ratio mass spectrometry. When calibrated with solutions containing NO 2 - with known isotopic compositions determined independently, reproducible δ 15 N and δ 18 O values were obtained at both natural-abundance levels (±0.2−0.5‰ for δ 15 N and ±0.4−1.0‰ for δ 18 O) and moderately enriched 15 N tracer levels (±20−50‰ for δ 15 N near 5000‰) for 5−20 nmol of NO 2 - (1−20 μmol/L in 1−5 mL aliquots). This method is highly selective for NO 2 - and was used for mixed samples containing both NO 2 - and NO 3 - with little or no measurable cross-contamination. In addition, mixed samples that were analyzed with S. nitritireducens were treated subsequently with Pseudomonas aureofaciens to reduce the NO 3 - in the absence of NO 2 - , providing isotopic analyses of NO 2 - and NO 3 - separately in the same aliquot. Sequential bacterial reduction methods like this one should be useful for a variety of isotopic studies aimed at understanding nitrogen cycling in aquatic environments. A test of these methods in an agricultural watershed in Indiana provides isotopic evidence for both nitrification and denitrification as sources of NO 2 - in a small stream.

Indiana↗

USGS2013

Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011

The lower Platte River corridor provides important habitats for two State- and federally listed bird species: the interior least tern (terns; Sternula antillarum athallassos) and the piping plover (plovers; Charadrius melodus). However, many of the natural morphological and hydrological characteristics of the Platte River have been altered substantially by water development, channelization, hydropower operations, and invasive vegetation encroachment, which have decreased the abundance of high-quality nesting and foraging habitat for terns and plovers. The lower Platte River (LPR), defined as 103 miles (mi) of the Platte River between its confluence with the Loup River and its confluence with the Missouri River, has narrowed since the late-19th and early-20th centuries, yet it partially retains many geomorphologic and hydrologic characteristics important to terns and plovers. These birds nest on the sandbars in the river and along shorelines at sand- and gravel-pit lakes in the adjacent valley. The need to balance continued economic, infrastructure, and resource development with the conservation of important physical and aquatic habitat resources requires increased understanding of the physical and biological dynamics of the lower Platte River. Spatially and temporally rich datasets for emergent sandbar habitats are necessary to quantify emergent sandbar dynamics relative to hypothesized controls and stressors. In cooperation with the Lower Platte South Natural Resources District, the U.S. Geological Survey initiated a pilot study of emergent sandbar dynamics along a 22-mi segment of the LPR downstream from its confluence with Salt Creek, near Ashland, Nebraska. The purposes of the study were to: (1) develop methods to rapidly assess sandbar geometries and locations in a wide, sand-bed river, and (2) apply and validate the method to assess emergent sandbar dynamics over three seasons in 2011. An examination of the height of sandbars relative to the local stage of the formative discharge event, and how subsequent river discharges, of both high and low magnitude, alter sandbar geometries and abundance within the LPR was of particular interest. A “rapid-assessment” method was developed with the goal of characterizing the spatial distribution and habitat-relevant geometries of the complete population of sandbars along the study segment. Three primary measures were used to assess emergent sandbar dynamics in the study segment: sandbar area, sandbar height, and sandbar location. Data to derive these measures were collected during three, week-long survey periods in 2011, herein named “spring survey period,” “summer survey period,” and “fall survey period.” Emergent sandbars were grouped into one of three generalized types: (1) bank-attached, (2) island-attached, and (3) mid-channel.

Nebraska↗

USGS2025

U.S. Geological Survey science strategy to address highly pathogenic avian influenza and its effects on wildlife health 2025–29

Executive Summary Highly pathogenic avian influenza (HPAI) is an ecologically and economically important animal disease that can also directly affect humans (a “zoonotic” disease). HPAI was once limited almost exclusively to domestic poultry but has rapidly adapted to diverse animal hosts. Viruses causing HPAI now appear to be maintained and dispersed by wild birds largely independent of poultry, though HPAI continues to cause considerable economic losses and supply chain disruptions in the domestic poultry trade. Coincident with the adaptation of HPAI viruses to wild birds, particularly waterfowl and gulls, increasingly diverse wild bird hosts are becoming exposed to HPAI, often resulting in disease and death. More sporadically, HPAI has caused mass mortality events, particularly among seabirds. Furthermore, viral spillover to wild and domestic mammals has become more common. Spillover to wild mammals has resulted in mortality among diverse terrestrial and marine taxa, including episodic losses of such scale as to represent potential conservation challenges. Since approximately March 2024, HPAI has also affected dairy cows, which represents a new threat to the agricultural economy. Lastly, HPAI has increasingly affected humans through domestic animal exposures, exemplifying the considerable implications of this disease beyond animal health. Rapid changes in the ecology of HPAI are currently outpacing research efforts. For example, it is not entirely clear which newly established hosts may become reservoirs for HPAI viruses (in other words, capable of maintaining HPAI viruses within a broad population indefinitely) and how this may influence viral evolution and dissemination. As a result, there are considerable information gaps regarding HPAI in wildlife that, if filled, would improve the ability of scientists, managers, agricultural industry representatives, and healthcare professionals to understand and to anticipate the effects of HPAI on wild animal, domestic animal, environmental, and human health (“One Health”). The U.S. Geological Survey (USGS) is the lead Federal agency providing scientific research on avian influenza viruses (AIVs), including HPAI viruses, that affect wildlife for which the Department of the Interior (DOI) has management authority. States have jurisdiction over wildlife on Federal lands within their borders (43 CFR § 24.3), so the USGS Ecosystems Mission Area (EMA) coordinates with State natural resource management agencies. The EMA focuses its research on HPAI through priorities identified by the USGS Avian Influenza Science Team ( app. 1 ). Priorities identified by the USGS Avian Influenza Science Team are based on Administration priorities, Congressional direction, and discussions with State, Federal, and Tribal natural resource management agencies that identify specific scientific gaps that need to be filled to inform sound wildlife management decisions. Notable non-DOI Federal partners include the U.S. Department of Agriculture, the lead for the HPAI regulatory response in poultry and livestock, and the Centers for Disease Control and Prevention (CDC), the lead agency for the HPAI response pertaining to human health. The USGS offers unique expertise and capacity pertaining to research on diseases affecting free-ranging wildlife populations. This expertise has been critical to interjurisdictional surveillance and capacity-building efforts, including programs administered by the U.S. Department of Agriculture and the CDC. The USGS also provides resources, guidance, and tools to inform surveillance and interventions conducted by natural resource management agencies. More specifically, the USGS EMA provides objective and rigorous scientific data for inferring (1) the utility of new methods to detect and characterize AIVs, including those maintained in wildlife and the environment; (2) effects of HPAI on wildlife; (3) spatiotemporal patterns of wildlife host and AIV dispersal; (4) the presence and persistence of AIVs in the environment; (5) how HPAI in wildlife influences consumptive and nonconsumptive utilization of wildlife; (6) how new tools and scientific methods may promote sound management decisions for HPAI-affected wildlife, particularly species of conservation concern; and (7) the combined effects of HPAI and other stressors on ecosystem health and resiliency. This science strategy builds upon research outlined in a previous USGS science strategy for HPAI (2016–20) by Harris and others (2016) . This strategy also details research priorities identified by the Administration (for example, U.S. Department of Agriculture, 2025 ) and others based on USGS Avian Influenza Science Team discussions with natural resource management agencies to address HPAI and wildlife health over the next 5 years (2025–29). This strategy presents 7 goals and 26 objectives that focus USGS and partner efforts on priorities that will fill data gaps regarding the effects of HPAI on wildlife managed by or co-managed with the U.S. Department of the Interior such that agencies and partners might anticipate or limit adverse effects on public resources. This strategy also identifies research priorities intended to address HPAI in wildlife and wildlife habitat that are anticipated to support interjurisdictional One Health efforts.

Circular↗

USGS2007

Arsenic in the environment: Biology and chemistry

Arsenic (As) distribution and toxicology in the environment is a serious issue, with millions of individuals worldwide being affected by As toxicosis. Sources of As contamination are both natural and anthropogenic and the scale of contamination ranges from local to regional. There are many areas of research that are being actively pursued to address the As contamination problem. These include new methods of screening for As in the field, determining the epidemiology of As in humans, and identifying the risk of As uptake in agriculture. Remediation of As-affected water supplies is important and research includes assessing natural remediation potential as well as phytoremediation. Another area of active research is on the microbially mediated biogeochemical interactions of As in the environment. In 2005, a conference was convened to bring together scientists involved in many of the different areas of As research. In this paper, we present a synthesis of the As issues in the light of long-standing research and with regards to the new findings presented at this conference. This contribution provides a backdrop to the issues raised at the conference together with an overview of contemporary and historical issues of As contamination and health impacts.

Science of the Total Environment↗

USGS2021

Discrete sample introduction module for quantitative and isotopic analysis of methane and other gases by cavity ring-down spectroscopy

Carbon dioxide (CO 2 ) and methane (CH 4 ) are natural and anthropogenic products that play a central role in the global carbon cycle and regulating Earth’s climate. Applications utilizing laser absorption spectroscopy, which continuously measure concentrations and stable isotope ratios of these greenhouse gases, are routinely employed to measure the source and magnitude of atmospheric inputs. We developed a discrete sample introduction module (DSIM) to enable measurements of methane and CO 2 concentrations and δ 13 C values from limited volume (5–100 mL) gas samples when interfaced with a commercially available cavity ring-down spectroscopy (CRDS) analyzer. The analysis has a dynamic range that spans six orders of magnitude from 100% analyte to the lower limit of instrument detection (2 ppm). We demonstrate system performance for methane by comparing concentrations and δ 13 C results from the DSIM-CRDS system and traditional methods for a variety of sample types, including low concentration (nanomolar CH 4 ) seawater and high concentration (>90% CH 4 ) natural gas. The expansive concentration range of the field-portable DSIM-CRDS system can measure enhances analytical performance for investigating methane and CO 2 dynamics and, potentially, other gases measured by laser absorption spectroscopy.

Environmental Science & Technology↗

USGS2015

National Park Service vegetation inventory program: Mississippi National River and Recreation Area, Minnesota

The Mississippi National River and Recreation Area (MISS) vegetation mapping project is an initiative of the National Park Service (NPS) Vegetation Inventory Program (VIP) to classify and map vegetation types of MISS. (Note: “MISS” is also referred to as “park” throughout this report.) The goals of the project are to adequately describe and map vegetation types of the park and to provide the NPS Natural Resource Inventory and Monitoring (I&M) Program, resource managers, and biological researchers with useful baseline vegetation information. The MISS vegetation mapping project was officially started in spring 2012, with a scoping meeting wherein partners discussed project objectives, goals, and methods. Major collaborators at this meeting included staff from the NPS MISS, the NPS Great Lakes Network (GLKN), NatureServe, and the USGS Upper Midwest Environmental Sciences Center. The Minnesota Department of Natural Resources (DNR) was also in attendance. Common to all NPS VIP projects, the three main components of the MISS vegetation mapping project are as follows: (1) vegetation classification, (2) vegetation mapping, and (3) map accuracy assessment (AA). In this report, each of these fundamental components is discussed in detail. With the completion of the MISS vegetation mapping project, all nine park units within the NPS GLKN have received vegetation classification and mapping products from the NPS and USGS vegetation programs. Voyageurs National Park and Isle Royale National Park were completed during 1996–2001 (as program pilot projects) and another six park units were completed during 2004–11, including the Apostle Islands National Lakeshore, Grand Portage National Monument, Indiana Dunes National Lakeshore, Pictured Rocks National Lakeshore, Saint Croix National Scenic Riverway, and Sleeping Bear Dunes National Lakeshore.

Natural Resource Report↗

USGS2022

Combining tangential flow filtration and size fractionation of mesocosm water as a method for the investigation of waterborne coral diseases

The causative agents of most coral diseases today remain unknown, complicating disease response and restoration efforts. Pathogen identifications can be hampered by complex microbial communities naturally associated with corals and seawater, which create complicating “background noise” that can potentially obscure a pathogen’s signal. Here, we outline an approach to investigate waterborne coral diseases that use a combination of coral mesocosms, tangential flow filtration, and size fractionation to reduce the impact of this background microbial diversity, compensate for unknown infectious dose, and further narrow the suspect pool of potential pathogens. As proof of concept, we use this method to compare the bacterial communities shed into six Montastraea cavernosa coral mesocosms and demonstrate this method effectively detects differences between diseased and healthy coral colonies. We found several amplicon sequence variants (ASVs) in the diseased mesocosms that represented 100% matches with ASVs identified in prior studies of diseased coral tissue, further illustrating the effectiveness of our approach. Our described method is an effective alternative to using coral tissue or mucus to investigate waterborne coral diseases of unknown etiology and can help more quickly narrow the pool of possible pathogens to better aid in disease response efforts. Additionally, this versatile method can be easily adapted to characterize either the entire microbial community associated with a coral or target-specific microbial groups, making it a beneficial approach regardless of whether a causative agent is suspected or is completely unknown.

Florida↗

USGS2018

Cinnamon gulch revisited: Another look at separating natural and mining-impacted contributions to instream metal load

Baseline, premining data for streams draining abandoned mine lands is virtually non existent, and indirect methods for estimating premining conditions are needed to establish realistic, cost effective cleanup goals. One such indirect method is the proximal analog approach, in which premining conditions are estimated using data from nearby mineralized areas that are unaffected by mining. In this paper, we combine the proximal analog approach with a quantitative mass balance framework using data from a spatially-detailed synoptic sampling campaign. The combined approach is applied to Cinnamon Gulch, a headwater stream with numerous draining adits. Synoptic sampling results indicate that three of the top five metal sources are affected by mining activities, and stream segments draining these sources account for a large percentage of overall metal loading within the study reach. These initial calculations overestimate the effects of mining, as the affected stream segments were likely acidic and metal rich prior to mining. Premining loads and concentrations were therefore determined through a replacement approach in which the chemistry of each mining-affected stream segment is revised based on proximal analog concentrations. The revised loading profiles indicate that 15–17% of the Al, Cd, Cu, Mn, Ni, and Zn loads are attributable to mining, whereas the mining contribution for Pb is 40%. Premining concentrations of Al, Cd, Cu, Mn, and Zn are estimated to be in excess of aquatic life standards over the length of the study reach.

Colorado↗

USGS2006

The use of synthetic jarosite as an analog for natural jarosite

The presence of jarosite in soil or mining waste is an indicator of acidic sulfate-rich conditions. Physical and chemical properties of synthetic jarosites are commonly used as analogs in laboratory studies to determine solubility and acid-generation of naturally occurring jarosites. In our work we have mineralogically and chemically characterized both natural and synthetic jarosites. Analysis of 32 natural hydrothermal and supergene K- and Na-jarosites indicates no (< 5 mole %) solid solution between K and Na end members. Instead, our detailed study of cell dimensions and composition reveals discrete mixtures of K and Na end members. Hydronium-bearing jarosite was detected in only one natural sample, and it appears that hydronium-bearing jarosites are metastable. Although the presence of hydronium in jarosite cannot be directly measured, we found that when synthetic hydronium-bearing jarosites are heated at 120°C for 78 days or 240°C for 24 hours, Fe(OH)SO4 is formed. The Fe(OH)SO4 is easily detected by X-ray diffraction and, hence, can be used as a post-mortem indicator of the presence of hydronium jarosite. Results from our synthetic jarosite studies indicate that natural metastable hydronium-bearing jarosite or iron-deficient forms of natural jarosite likely play an important role in acid generation in some mining wastes, but are not accurately represented by synthetic jarosite prepared by commonly used methods. The widespread practice of heating to at least 110°C after jarosite synthesis appears to drive off structural waters from protonated hydroxyl sites, which changes the properties of the jarosite. Therefore, synthetic jarosite should not be heated above 95 oC if it is to be used as an analog for low-temperature natural jarosite in mining wastes.

Conference Paper↗

USGS2014

Hydrologic Drought Decision Support System (HyDroDSS)

The hydrologic drought decision support system (HyDroDSS) was developed by the U.S. Geological Survey (USGS) in cooperation with the Rhode Island Water Resources Board (RIWRB) for use in the analysis of hydrologic variables that may indicate the risk for streamflows to be below user-defined flow targets at a designated site of interest, which is defined herein as data-collection site on a stream that may be adversely affected by pumping. Hydrologic drought is defined for this study as a period of lower than normal streamflows caused by precipitation deficits and (or) water withdrawals. The HyDroDSS is designed to provide water managers with risk-based information for balancing water-supply needs and aquatic-habitat protection goals to mitigate potential effects of hydrologic drought. This report describes the theory and methods for retrospective streamflow-depletion analysis, rank correlation analysis, and drought-projection analysis. All three methods are designed to inform decisions made by drought steering committees and decisionmakers on the basis of quantitative risk assessment. All three methods use estimates of unaltered streamflow, which is the measured or modeled flow without major withdrawals or discharges, to approximate a natural low-flow regime. Retrospective streamflow-depletion analysis can be used by water-resource managers to evaluate relations between withdrawal plans and the potential effects of withdrawal plans on streams at one or more sites of interest in an area. Retrospective streamflow-depletion analysis indicates the historical risk of being below user-defined flow targets if different pumping plans were implemented for the period of record. Retrospective streamflow-depletion analysis also indicates the risk for creating hydrologic drought conditions caused by use of a pumping plan. Retrospective streamflow-depletion analysis is done by calculating the net streamflow depletions from withdrawals and discharges and applying these depletions to a simulated record of unaltered streamflow. Rank correlation analysis in the HyDroDSS indicates the persistence of hydrologic measurements from month to month for the prediction of developing hydrologic drought conditions and quantitatively indicates which hydrologic variables may be used to indicate the onset of hydrologic drought conditions. Rank correlation analysis also indicates the potential use of each variable for estimating the monthly minimum unaltered flow at a site of interest for use in the drought-projection analysis. Rank correlation analysis in the HyDroDSS is done by calculating Spearman’s rho for paired samples and the 95-percent confidence limits of this rho value. Rank correlation analysis can be done by using precipitation, groundwater levels, measured streamflows, and estimated unaltered streamflows. Serial correlation analysis, which indicates relations between current and future values, can be done for a single site. Cross correlation analysis, which indicates relations among current values at one site and current and future values at a second site, also can be done. Drought-projection analysis in the HyDroDSS indicates the risk for being in a hydrologic drought condition during the current month and the five following months with and without pumping. Drought-projection analysis also indicates the potential effectiveness of water-conservation methods for mitigating the effect of withdrawals in the coming months on the basis of the amount of depletion caused by different pumping plans and on the risk of unaltered flows being below streamflow targets. Drought-projection analysis in the HyDroDSS is done with Monte Carlo methods by using the position analysis method. In this method the initial value of estimated unaltered streamflows is calculated by correlation to a measured hydrologic variable (monthly precipitation, groundwater levels, or streamflows from an index station identified with the rank correlation analysis). Then a pseudorandom number generator is used to create 251 six-month-long flow traces by using a bootstrap method. Serial correlation of the estimated unaltered monthly minimum streamflows determined from the rank correlation analysis is preserved within each flow trace. The sample of unaltered streamflows indicates the risk of being below flow targets in the coming months under simulated natural conditions (without historic withdrawals). The streamflow-depletion algorithms are then used to estimate risks of flow being below targets if selected pumping plans are used. This report also describes the implementation of the HyDroDSS. The HyDroDSS was developed as a Microsoft Access® database application to facilitate storage, handling, and use of hydrologic datasets with a simple graphical user interface. The program is implemented in the database by using the Visual Basic for Applications® (VBA) programming language. Program source code for the analytical techniques is provided in the HyDroDSS and in electronic text files accompanying this report. Program source code for the graphical user interface and for data-handling code, which is specific to Microsoft Access® and the HyDroDSS, is provided in the database. An installation package with a run-time version of the software is available with this report for potential users who do not have a compatible copy of Microsoft Access®. Administrative rights are needed to install this version of the HyDroDSS. A case study, to demonstrate the use of HyDroDSS and interpretation of results for a site of interest, is detailed for the USGS streamgage on the Hunt River (station 01117000) near East Greenwich in central Rhode Island. The Hunt River streamgage was used because it has a long record of streamflow and is in a well-studied basin with a substantial amount of hydrologic and water-use data including groundwater pumping for municipal water supply.

Rhode Island↗

USGS2019

Using the precipitation-runoff modeling system to predict seasonal water availability in the upper Klamath River basin, Oregon and California

Accurate forecasts of the streamflow expected during late spring and summer in the Upper Klamath River Basin in southern-central Oregon and northern California are used by water management agencies to balance water allocations for agriculture, aquatic habitat, and hydropower-production needs. Streamflow forecasts are also used by irrigation farmers for planning. The forecasts are typically made twice a month starting as early in the water year as December. Multiple regression equations relating real-time snowpack and precipitation conditions to seasonal streamflow volumes have been used for many years in forecasting. However, with warming temperature trends and lower snowpack, such forecasts based on historical data could become less reliable in the future. If the timing and relation of snowpack and precipitation are outside of the range of the historical data used to create the equations, the forecasts become extrapolations. Statistical forecast equations are also limited in their ability to forecast streamflow in groundwater-dominated basins having inter-annual lag. As an additional method for seasonal streamflow forecasting, a physical-process-based hydrologic model employing the Precipitation-Runoff Modeling System (PRMS) was developed in cooperation with the U.S. Bureau of Reclamation for the Upper Klamath Basin in this study. The model was calibrated for the portion of the basin draining into Upper Klamath Lake. PRMS is a deterministic, distributed-parameter, physical-process-based modeling system developed by the U.S. Geological Survey. It simulates daily streamflow, snow, solar radiation, evapotranspiration, surface-water, and groundwater processes within the basin. A model calibration and validation period for water years 2000–15 and water years 1984–99, respectively, was used. The model was calibrated and validated using measured streamflow, snowpack, evapotranspiration, and solar radiation data sets. Interpolated daily precipitation and air temperature data from 32 meteorological stations within and surrounding the Upper Klamath Basin were used as model input. Performance statistics, used to evaluate how well simulated daily streamflow matched with measured streamflow included percent bias, percent relative error, and root-mean-square error. The statistics were computed annually, monthly, for October–March, and for April–September. With the exception of the October–March period, percent bias statistics were all within plus or minus 5-percent for both the calibration and validation periods. Limitations to using the model are error in the precipitation and air temperature input time series data, which include measurement error and error in the spatial interpolation method. Other errors include measured daily streamflow data, which were adjusted for consumptive use losses to make them more closely resemble natural streamflow for calibration. The model developed for the Upper Klamath Basin can be used to forecast streamflow from the Sprague and Williamson River Basins and inflow to Upper Klamath Lake. Reliable forecasts at these locations are needed for managing water for irrigation, ecosystem health, and power production. Using the models in a forecast application requires assembling model input data sets of anticipated daily precipitation and minimum and maximum air temperature for the period after the date the forecast is made and the end of the forecasted period. These climate data sets can be based on historical or synthetic records, at the discretion of the forecaster. With the Ensemble Streamflow Prediction method, a suite of streamflow scenarios is simulated using multiple years of climate data as model input. The forecasted streamflow is determined from knowing the exceedance probabilities of the simulated streamflows. In this study, the model and the Ensemble Streamflow Prediction method were used to forecast the volume of inflow to Upper Klamath Lake for a 6-month period from April 1, 2015, to September 30, 2015, using a range of climate data sets based on El Niño Southern Oscillation (ENSO) criteria. Because 2015 was a warm phase ENSO period, climate data for 10 warm phase ENSO years from 1980 to 2010 were used as input to the model. The simulated April–September 2015 UKL inflow volume based on measured 2015 climate data was 482,000 acre-feet, which was very close to the 50th percent exceedance probability computed from 10 simulated scenarios that used warm phase ENSO climate input data from 1980–2010.

California, Oregon↗

USGS2010

Fort Collins Science Center- Policy Analysis and Science Assistance Branch : Integrating social, behavioral, economic and biological sciences

The Fort Collins Science Center's Policy Analysis and Science Assistance (PASA) Branch is a team of approximately 22 scientists, technicians, and graduate student researchers. PASA provides unique capabilities in the U.S. Geological Survey by leading projects that integrate social, behavioral, economic, and biological analyses in the context of human-natural resource interactions. Resource planners, managers, and policymakers in the U.S. Departments of the Interior (DOI) and Agriculture (USDA), State and local agencies, as well as international agencies use information from PASA studies to make informed natural resource management and policy decisions. PASA scientists' primary functions are to conduct both theoretical and applied social science research, provide technical assistance, and offer training to advance performance in policy relevant research areas. Management and research issues associated with human-resource interactions typically occur in a unique context, involve difficult to access populations, require knowledge of both natural/biological science in addition to social science, and require the skill to integrate multiple science disciplines. In response to these difficult contexts, PASA researchers apply traditional and state-of-the-art social science methods drawing from the fields of sociology, demography, economics, political science, communications, social-psychology, and applied industrial organization psychology. Social science methods work in concert with our rangeland/agricultural management, wildlife, ecology, and biology capabilities. The goal of PASA's research is to enhance natural resource management, agency functions, policies, and decision-making. Our research is organized into four broad areas of study.

Fact Sheet↗

USGS2016

Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to quantitatively monitor surface change over time relative to management activities.

Utah↗

USGS2009

Estimation of Leakage Potential of Selected Sites in Interstate and Tri-State Canals Using Geostatistical Analysis of Selected Capacitively Coupled Resistivity Profiles, Western Nebraska, 2004

With increasing demands for reliable water supplies and availability estimates, groundwater flow models often are developed to enhance understanding of surface-water and groundwater systems. Specific hydraulic variables must be known or calibrated for the groundwater-flow model to accurately simulate current or future conditions. Surface geophysical surveys, along with selected test-hole information, can provide an integrated framework for quantifying hydrogeologic conditions within a defined area. In 2004, the U.S. Geological Survey, in cooperation with the North Platte Natural Resources District, performed a surface geophysical survey using a capacitively coupled resistivity technique to map the lithology within the top 8 meters of the near-surface for 110 kilometers of the Interstate and Tri-State Canals in western Nebraska and eastern Wyoming. Assuming that leakage between the surface-water and groundwater systems is affected primarily by the sediment directly underlying the canal bed, leakage potential was estimated from the simple vertical mean of inverse-model resistivity values for depth levels with geometrically increasing layer thickness with depth which resulted in mean-resistivity values biased towards the surface. This method generally produced reliable results, but an improved analysis method was needed to account for situations where confining units, composed of less permeable material, underlie units with greater permeability. In this report, prepared by the U.S. Geological Survey in cooperation with the North Platte Natural Resources District, the authors use geostatistical analysis to develop the minimum-unadjusted method to compute a relative leakage potential based on the minimum resistivity value in a vertical column of the resistivity model. The minimum-unadjusted method considers the effects of homogeneous confining units. The minimum-adjusted method also is developed to incorporate the effect of local lithologic heterogeneity on water transmission. Seven sites with differing geologic contexts were selected following review of the capacitively coupled resistivity data collected in 2004. A reevaluation of these sites using the mean, minimum-unadjusted, and minimum-adjusted methods was performed to compare the different approaches for estimating leakage potential. Five of the seven sites contained underlying confining units, for which the minimum-unadjusted and minimum-adjusted methods accounted for the confining-unit effect. Estimates of overall leakage potential were lower for the minimum-unadjusted and minimum-adjusted methods than those estimated by the mean method. For most sites, the local heterogeneity adjustment procedure of the minimum-adjusted method resulted in slightly larger overall leakage-potential estimates. In contrast to the mean method, the two minimum-based methods allowed the least permeable areas to control the overall vertical permeability of the subsurface. The minimum-adjusted method refined leakage-potential estimation by additionally including local lithologic heterogeneity effects.

Scientific Investigations Report↗

USGS2003

Soil seed banks and the potential restoration of forested wetlands after farming

1 Changes in farming practice provide an opportunity to restore once extensive forested wetlands on agricultural land. In some parts of the world, however, it has proved difficult to restore the full complement of plant species through natural regeneration. Similarly, the restoration of forested wetlands by replanting has often resulted in ecosystems of low diversity. Better methods of restoring these important ecosystems are now required and baldcypress swamps provide an opportunity to investigate alternative approaches to the restoration of forested wetlands. This study examined the composition of seed banks of farmed fields to determine their value in restoring swamps in the south-eastern United States. 2 A seed bank assay of soils from baldcypress swamps was conducted to determine the extent to which seeds are maintained during farming for various lengths of time. Soils from swamps that were farmed for 0–50 years were collected near the northern boundary of the Mississippi Alluvial Valley along the Cache River, Illinois. Soils were placed in a glasshouse setting in flooded and freely drained conditions, and the numbers and species of seeds germinating were recorded. 3 Woody species including trees, shrubs, and vines were poorly represented in seed banks of both farmed and intact sites (51 and 9 sites, respectively). Missing dominants in the seed banks included tree species with short-lived seeds such as Taxodium distichum and Nyssa aquatica . Cephalanthus occidentalis constituted the most abundantly dispersed seed of all woody species. 4 Herbaceous species were well represented in the seed banks of both farmed and intact swamps (species richness of 207 vs. 173 species, respectively) suggesting that herbaceous species may live longer than woody species in seed banks. Few of the herbaceous species decreased in seed density in seed banks with time under cultivation, although seed density was lower at sites that had not been farmed. Species that relied on vegetative organs for dispersal were absent in the seed banks of farmed sites including Heteranthera dubia , Hottonia inflata , Lemna minor , Lemna trisulca and Wolffia columbiana . These species may require active reintroduction during restoration. 5 Synthesis and applications. Both restoration ecologists and managers of nature conservation areas need to be cognisant of seed bank and dispersal characteristics of species to effectively restore and manage forested wetlands. In the case of baldcypress swamps, critical components of the vegetation are not maintained in seed banks, which may make these floodplain wetlands difficult to restore via natural recolonization. Ultimately, the successful restoration of abandoned farm fields to forested wetlands may depend on the re-engineering of flood pulsing across landscapes to reconnect dispersal pathways.

Illinois↗

USGS2021

Review of ESA SYMP 7: A dynamic perspective on ecosystem restoration–establishing temporal connectivity at the intersection between paleoecology and restoration ecology

Landscape connectivity is vital not only spatially, but also temporally; as ecosystems change, it is important to be aware of past, present, and future variables that may impact ecosystem function and biodiversity. As climate and environments continue to change, choosing appropriate restoration targets is becoming more challenging. By considering the paleoecological and paleoenvironmental record for a given region, restoration practitioners are not only able to bear witness to that region’s dynamic history, but also potentially identify multiple, alternative natural ecosystem states. Indeed, one of the deliverables of conservation paleobiology, a field that applies paleontological data and methods to present-day conservation, is to inform restoration targets. Consideration of future change is equally important, and paleoecological and paleoclimatological data are essential for informing models that can help us understand how climate change is affecting species and ecosystems at different temporal scales. The symposium “A dynamic perspective on ecosystem restoration: Establishing temporal connectivity at the intersection between paleoecology and restoration ecology” gathered representatives from macroecology, paleoecology, and restoration ecology to share their perspectives on temporal connectivity and how consideration of an ecosystem’s past, present, and future can positively impact restoration and conservation. Some speakers approached the topic theoretically, while others considered it from a more practical and applied standpoint. The goals of the symposium were to build a stronger relationship among the subdisciplines, stimulate new ideas, and identify data and/or products that would be useful to share across subdisciplines.

Bulletin Ecological Society of America↗