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USGS2025

Exploration for blind geothermal systems in the eastern Great Basin of Utah: An update on the “Lund North” INGENIOUS detailed study site

Existing geothermal production in Utah is commonly collocated with surficial expressions of geothermal heat including active hot springs and hot spring deposits. However, geothermal potential across the Great Basin region is thought to be much higher for hidden or blind geothermal systems. Accordingly, exploration techniques that can locate geothermal resources that lack surface thermal features could support future development of these systems. The goal of the INGENIOUS project is to reduce exploration risk and discover new, economically viable hidden geothermal systems in the Great Basin region. This paper summarizes the efforts and preliminary results of blind geothermal resource prospecting in Utah as part of the larger INGENIOUS project. The Lund North site in the Basin and Range province of southwest Utah was designated as the fourth detailed study site for the project. The site was initially identified from the preliminary Play Fairway Analysis (PFA) geothermal favorability map, which is based on various data elements, and the identification of favorable structural settings across Utah. This site contains existing legacy data including a thermal gradient borehole with a heat-flow value exceeding 220 mW/m 2 . New data collected at this site include terrestrial gravity, magnetotellurics, transient electromagnetics, fluid geochemistry, geologic mapping, UAV-based lidar, paleomagnetism, aeromagnetic surveys, and a shallow temperature survey. Preliminary data and model interpretations corroborate the presence of a large, east-dipping, northeast-southwest-trending normal fault on the edge of a typical Basin and Range graben. Quaternary fault mapping refined by high-resolution lidar surveys suggests a complex step over fault geometry. Utilizing multi-disciplinary datasets for further site assessment at Lund North will facilitate the development of a local-scale PFA and geothermal conceptual model. This new data will be used to site successive thermal gradient drilling to verify heat flow with temperatures at depth at the Lund North site and further investigate the existence of a local geothermal system.

Utah↗

USGS2002

Selenium biotransformations into proteinaceous forms by foodweb organisms of selenium-laden drainage waters in California

Selenium contamination represents one of the few clear cases where environmental pollution has led to devastation of wildlife populations, most notably in agricultural drainage evaporation and power plant coal-fly ash receiving ponds. Complex biogeochemistry, in particular extensive biotransformations and foodchain transfer, governs Se ecotoxicology and toxicology, for which the mechanism(s) are still elusive. However, total waterborne Se concentration has been widely used as a criterion for regulating and mitigating Se risk in aquatic ecosystems, which does not account for Se biogeochemistry and its site-dependence. There is a need for more reliable indicator(s) that encompass Se ecotoxicity and/or toxicity. Selenomethionine warrants special attention since it simulates Se toxicosis of wildlife in laboratory feeding studies. While low in free selenomethionine, microphytes isolated from Se-laden agricultural evaporation ponds were abundant in proteinaceous selenomethionine. This prompted a more extensive survey of Se speciation in foodchain organisms including microphytes, macroinvertebrates, fish, and bird embryos residing mainly in the agricultural drainage systems of the San Joaquin Valley, California. Total Se in biomass, water-soluble fractions, and protein-rich fractions were measured along with GC-MS analysis of proteinaceous selenomethionine. In all foodchain organisms, water-soluble Se constituted the major fraction of total biomass Se, while proteinaceous Se was a substantial, if not dominant, fraction of the water-soluble Se. In turn, proteinaceous selenomethionine comprised an important fraction of proteinaceous Se. In terms of total biomass Se, an average 1400-fold of Se biomagnification from water to microphytes was observed while subsequent transfer from microphytes to macroinvertebrates exhibited an average of only 1.9-fold. The latter transfer was more consistent and greater in extent for proteinaceous Se and proteinaceous selenomethionine, which is consistent with their importance in foodchain transfer. Proteinaceous Se in the omnivorous carp (Cyprinus carpio) liver also demonstrated a relation to ovarian lesions, while deformed stilt (Himantopus mexicanus) embryo was more abundant in proteinaceous selenomethionine than were normal embryos. Although limited in the number of organisms surveyed, these findings provide an impetus for further field and laboratory feeding studies to substantiate the hypothesis that proteinaceous selenomethionine underlies Se ecotoxicity, which may in turn prove to be a reliable indicator of Se risk in aquatic ecosystems. Copyright ?? 2002 Elsevier Science B.V.

Aquatic Toxicology↗

USGS2018

Compounding effects of climate change reduce population viability of a montane amphibian

Anthropogenic climate change presents challenges and opportunities to the growth, reproduction, and survival of individuals throughout their life cycles. Demographic compensation among life‐history stages has the potential to buffer populations from decline, but alternatively, compounding negative effects can lead to accelerated population decline and extinction. In montane ecosystems of the U.S. Pacific Northwest, increasing temperatures are resulting in a transition from snow‐dominated to rain‐dominated precipitation events, reducing snowpack. For ectotherms such as amphibians, warmer winters can reduce the frequency of critical minimum temperatures and increase the length of summer growing seasons, benefiting post‐metamorphic stages, but may also increase metabolic costs during winter months, which could decrease survival. Lower snowpack levels also result in wetlands that dry sooner or more frequently in the summer, increasing larval desiccation risk. To evaluate how these challenges and opportunities compound within a species’ life history, we collected demographic data on Cascades frog ( Rana cascadae ) in Olympic National Park in Washington state to parameterize stage‐based stochastic matrix population models under current and future (A1B, 2040s, and 2080s) environmental conditions. We estimated the proportion of reproductive effort lost each year due to drying using watershed‐specific hydrologic models, and coupled this with an analysis that relates 15 yr of R. cascadae abundance data with a suite of climate variables. We estimated the current population growth (λ s ) to be 0.97 (95% CI 0.84–1.13), but predict that λ s will decline under continued climate warming, resulting in a 62% chance of extinction by the 2080s because of compounding negative effects on early and late life history stages. By the 2080s, our models predict that larval mortality will increase by 17% as a result of increased pond drying, and adult survival will decrease by 7% as winter length and summer precipitation continue to decrease. We find that reduced larval survival drives initial declines in the 2040s, but further declines in the 2080s are compounded by decreases in adult survival. Our results demonstrate the need to understand the potential for compounding or compensatory effects within different life history stages to exacerbate or buffer the effects of climate change on population growth rates through time.

Ecological Applications↗

USGS2017

Benefits of the fire mitigation ecosystem service in the Great Dismal Swamp National Wildlife Refuge, Virginia, USA

The Great Dismal Swamp (GDS) National Wildlife Refuge delivers multiple ecosystem services, including air quality and human health via fire mitigation. Our analysis estimates benefits of this service through its potential to reduce catastrophic wildfire related impacts on the health of nearby human populations. We used a combination of high-frequency satellite data, ground sensors, and air quality indices to determine periods of public exposure to dense emissions from a wildfire within the GDS. We examined emergency department (ED) visitation in seven Virginia counties during these periods, applied measures of cumulative Relative Risk to derive the effects of wildfire smoke exposure on ED visitation rates, and estimated economic losses using regional Cost of Illness values established within the US Environmental Protection Agency BenMAP framework. Our results estimated the value of one avoided catastrophic wildfire in the refuge to be \$3.69 million (2015 USD), or \$306 per hectare of burn. Reducing the frequency or severity of extensive, deep burning peatland wildfire events has additional benefits not included in this estimate, including avoided costs related to fire suppression during a burn, carbon dioxide emissions, impacts to wildlife, and negative outcomes associated with recreation and regional tourism. We suggest the societal value of the public health benefits alone provides a significant incentive for refuge mangers to implement strategies that will reduce the severity of catastrophic wildfires.

North Carolina, Virginia↗

USGS2024

EthoCRED: A framework to guide reporting and evaluation of the relevance and reliability of behavioural ecotoxicity studies

Behavioural analysis has been attracting significant attention as a broad indicator of sub-lethal toxicity and has secured a place as an important subdiscipline in ecotoxicology. Among the most notable characteristics of behavioural research, compared to other established approaches in sub-lethal ecotoxicology (e.g. reproductive and developmental bioassays), are the wide range of study designs being used and the diversity of endpoints considered. At the same time, environmental hazard and risk assessment, which underpins regulatory decisions to protect the environment from potentially harmful chemicals, often recommends that ecotoxicological data be produced following accepted and validated test guidelines. These guidelines typically do not address behavioural changes, meaning that these, often sensitive, effects are not represented in hazard and risk assessments. Here, we propose a new tool, the EthoCRED evaluation method, for assessing the relevance and reliability of behavioural ecotoxicity data, which considers the unique requirements and challenges encountered in this field. This method and accompanying reporting recommendations are designed to serve as an extension of the “Criteria for Reporting and Evaluating Ecotoxicity Data (CRED)” project. As such, EthoCRED can both accommodate the wide array of experimental design approaches seen in behavioural ecotoxicology, and could be readily implemented into regulatory frameworks as deemed appropriate by policy makers of different jurisdictions to allow better integration of knowledge gained from behavioural testing into environmental protection. Furthermore, through our reporting recommendations, we aim to improve the reporting of behavioural studies in the peer-reviewed literature, and thereby increase their usefulness to inform chemical regulation.

Biological Reviews↗

USGS2022

Mapping first to final uses for rare earth elements, globally and in the United States

Estimating the material flows of rare earth elements (REEs) is essential to understanding which industries are most vulnerable to potential REE supply disruptions which, in turn, may inform policy recommendations aimed at reducing the supply risk. However, the REEs are a group of mineral commodities characterized by highly uncertain estimates of supply and demand due to the REE market's complexity, opacity, and small size. In this study, a streamlined methodology was applied to map mineral commodity first-use to final-use applications and to estimate total requirements at the national level based on available industrial data for final-use finished goods. This analysis examines REEs both as a group and individually, showing that total US requirements are between 15% and 16.5% of world requirements for the year 2015, the latest year with the most complete information available. The findings shed light on US industrial capabilities by revealing the discrepancy between the types of REEs that go into US raw material consumption and those that are contained in embedded consumption. For instance, given the United States’ large oil refining industry, US raw material consumption of lanthanum is quite high. In contrast, US raw material consumption of neodymium is relatively low, whereas embedded demand is comparatively high. This reflects the lack of industrial capacity to process REE concentrates into magnet material combined with the US's high imports of products that contain rare earth permanent magnets.

Journal of Industrial Ecology↗

USGS2024

Societal benefits of cyanobacteria harmful algal bloom management in Lake Okeechobee in Florida—Potential damages avoided during the 2018 event under U.S. Army Corps of Engineers Harmful Algal Bloom Interception, Treatment, and Transformation System scenarios

Freshwater harmful algal blooms (HABs) formed by blue-green algae, or cyanobacteria, have emerged as a global environmental problem. Their negative impacts on aquatic ecosystems can affect the benefits nature provides to human society by reducing water quality; inhibiting aquatic recreation; killing fish, wildlife, and pets; and posing a risk to human health. To manage harmful algal blooms, the Engineer Research and Development Center of the U.S. Army Corps of Engineers is developing an advanced technology called the Harmful Algal Bloom Interception, Treatment, and Transformation System (HABITATS), which has been tested in pilot demonstrations upstream of spillways at HAB-affected waterbodies in Florida. The U.S. Geological Survey and cooperators from the U.S. Department of the Interior Office of Policy Analysis investigated the societal benefits of HABITATS technology by using data from an actual 2018 harmful algal bloom in Lake Okeechobee to characterize the observed societal impacts and then comparing observed effects to hypothetical scenarios of HABITATS deployment. This study estimated an economic value of $5.5 million in foregone recreation as a result of closed boating ramp facilities and other restrictions on aquatic recreation such as fishing and swimming during the 2018 cyanobacteria harmful algal bloom outbreak. The change in housing sales prices that could have resulted from murky water or bad odor during that outbreak was estimated as $2.3 million. The team also investigated drinking water contamination and human illness but did not find significant societal impacts in this case. If HABITATS had been deployed, the avoided losses less the cost of management could have provided net societal benefits that ranged between negative $2.1 million and positive $0.8 million, depending on the vertical distribution of algae in the water column and the HABITATS version used. The study’s estimated societal benefit is undoubtedly a lower bound estimate because current scientific knowledge is inadequate to characterize, or monetize, all the impacts.

Florida↗

USGS2021

Migrating whooping cranes avoid wind-energy infrastructure when selecting stopover habitat

Electricity generation from renewable-energy sources has increased dramatically worldwide in recent decades. Risks associated with wind-energy infrastructure are not well understood for endangered whooping cranes or other vulnerable crane populations. From 2010 to 2016, we monitored 57 whooping cranes with remote-telemetry devices in the United States Great Plains to determine potential changes in migration distribution (i.e., avoidance) caused by presence of wind-energy infrastructure. During our study, the number of wind towers tripled in the whooping crane migration corridor and quadrupled in the corridor’s center. Median distance of whooping crane locations from nearest wind tower was 52.1 km, and 99% of locations were >4.3 km from wind towers. A habitat selection analysis revealed that whooping cranes used areas ≤5.0 km (95% CI = 4.8–5.4) from towers less than expected (i.e., zone of influence) and that whooping cranes were 20 times (95% CI: 14–64) more likely to use areas outside compared to adjacent to towers. Eighty percent of whooping crane locations and 20% of wind towers were located in areas with the highest relative probability of whooping crane use based on our model, which comprised 20% of the study area. Whooping cranes selected for these places, whereas developers constructed wind infrastructure at random relative to desirable whooping crane habitat. As of early 2020, 4.6% of the study area and 5.0% of the highest-selected whooping crane habitat were within the collective zone of influence. The affected area equates to habitat loss ascribed to wind-energy infrastructure; losses from other disturbances have not been quantified. Continued growth of the whooping crane population during this period of wind infrastructure construction suggests no immediate population-level consequences. Chronic or lag effects of habitat loss are unknown but possible for long-lived species. Preferentially constructing future wind infrastructure outside of the migration corridor or inside of the corridor at sites with low probability of whooping crane use would allow for continued wind-energy development in the Great Plains with minimal additional risk to highly selected habitat that supports recovery of this endangered species.

Kansas, Montana, Nebraska, North Dakota, Oklahoma,↗

USGS2024

Large-scale assessment of genetic structure to assess risk of populations of a large herbivore to disease

Chronic wasting disease (CWD) can spread among cervids by direct and indirect transmission, the former being more likely in emerging areas. Identifying subpopulations allows the delineation of focal areas to target for intervention. We aimed to assess the population structure of white-tailed deer ( Odocoileus virginianus ) in the northeastern United States at a regional scale to inform managers regarding gene flow throughout the region. We genotyped 10 microsatellites in 5701 wild deer samples from Maryland, New York, Ohio, Pennsylvania, and Virginia. We evaluated the distribution of genetic variability through spatial principal component analysis and inferred genetic structure using non-spatial and spatial Bayesian clustering algorithms (BCAs). We simulated populations representing each inferred wild cluster, wild deer in each state and each physiographic province, total wild population, and a captive population. We conducted genetic assignment tests using these potential sources, calculating the probability of samples being correctly assigned to their origin. Non-spatial BCA identified two clusters across the region, while spatial BCA suggested a maximum of nine clusters. Assignment tests correctly placed deer into captive or wild origin in most cases (94%), as previously reported, but performance varied when assigning wild deer to more specific origins. Assignments to clusters inferred via non-spatial BCA performed well, but efficiency was greatly reduced when assigning samples to clusters inferred via spatial BCA. Differences between spatial BCA clusters are not strong enough to make assignment tests a reliable method for inferring the geographic origin of deer using 10 microsatellites. However, the genetic distinction between clusters may indicate natural and anthropogenic barriers of interest for management.

Maryland, New York, Ohio, Pennsylvania, West Virgi↗

USGS2013

Modeling rain-fed maize vulnerability to droughts using the standardized precipitation index from satellite estimated rainfall—Southern Malawi case study

During 1990s, disaster risk reduction emerged as a novel, proactive approach to managing risks from natural hazards. The World Bank, USAID, and other international donor agencies began making efforts to mainstream disaster risk reduction in countries whose population and economies were heavily dependent on rain-fed agriculture. This approach has more significance in light of the increasing climatic hazard patterns and the climate scenarios projected for different hazard prone countries in the world. The Famine Early Warning System Network (FEWS NET) has been monitoring the food security issues in the sub-Saharan Africa, Asia and in Haiti. FEWS NET monitors the rainfall and moisture availability conditions with the help of NOAA RFE2 data for deriving food security status in Africa. This paper highlights the efforts in using satellite estimated rainfall inputs to develop drought vulnerability models in the drought prone areas in Malawi. The satellite RFE2 based SPI corresponding to the critical tasseling and silking phases (in the months of January, February, and March) were statistically regressed with drought-induced yield losses at the district level. The analysis has shown that the drought conditions in February and early March lead to most damage to maize yields in this region. The district-wise vulnerabilities to drought were upscaled to obtain a regional maize vulnerability model for southern Malawi. The results would help in establishing an early monitoring mechanism for drought impact assessment, give the decision makers additional time to assess seasonal outcomes, and identify potential food-related hazards in Malawi.

International Journal of Disaster Risk Reduction↗

USGS2015

Resilience by Design: Bringing Science to Policy Makers

No one questions that Los Angeles has an earthquake problem. The “Big Bend” of the San Andreas fault in southern California complicates the plate boundary between the North American and Pacific plates, creating a convergent component to the primarily transform boundary. The Southern California Earthquake Center Community Fault Model has over 150 fault segments, each capable of generating a damaging earthquake, in an area with more than 23 million residents (Fig. 1). A Federal Emergency Management Agency (FEMA) analysis of the expected losses from all future earthquakes in the National Seismic Hazard Maps (Petersen et al., 2014) predicts an annual average of more than $3 billion per year in the eight counties of southern California, with half of those losses in Los Angeles County alone (Federal Emergency Management Agency [FEMA], 2008). According to Swiss Re, one of the world’s largest reinsurance companies, Los Angeles faces one of the greatest risks of catastrophic losses from earthquakes of any city in the world, eclipsed only by Tokyo, Jakarta, and Manila (Swiss Re, 2013).

California↗

USGS2001

Seismic Landslide Hazard for the City of Berkeley, California

This map describes the possible hazard from earthquake-induced landslides for the city of Berkeley, CA. The hazard depicted by this map was modeled for a scenario corresponding to an M=7.1 earthquake on the Hayward, CA fault. This scenario magnitude is associated with complete rupture of the northern and southern segments of the Hayward fault, an event that has an estimated return period of about 500 years. The modeled hazard also corresponds to completely saturated ground-water conditions resulting from an extreme storm event or series of storm events. This combination of earthquake and ground-water scenarios represents a particularly severe state of hazard for earthquake-induced landslides. For dry ground-water conditions, overall hazard will be less, while relative patterns of hazard are likely to change. Purpose: The map is intended as a tool for regional planning. Any site-specific planning or analysis should be undertaken with the assistance of a qualified geotechnical engineer. This hazard map should not be used as a substitute to the State of California Seismic Hazard Zones map for the same area. (See California Department of Conservation, Division of Mines and Geology, 1999). As previously noted for maps of this type by Wieczorek and others (1985), this map should not be used as a basis to determine the absolute risk from seismically triggered landslides at any locality, as the sole justification for zoning or rezoning any parcel, for detailed design of any lifeline, for site-specific hazard-reduction planning, or for setting or modifying insurance rates.

Miscellaneous Field Studies Map↗

USGS2023

Decision science as a framework for combining geomorphological and ecological modeling for the management of coastal systems

The loss of ecosystem services due to climate change and coastal development is projected to have significant impacts on local economies and conservation of natural resources. Consequently, there has been an increase in coastal management activities such as living shorelines, oyster reef restoration, marsh restoration, beach and dune nourishment, and revegetation projects. Coastal management decisions are complex and include challenging trade-offs. Decision science offers a useful framework to address such complex problems. Here, we provide a synthesis about how decision science can help to integrate research from multiple disciplines (physical and life sciences) with management of coastal and marine systems. Specifically, we discuss the importance of considering concepts and techniques from ecology, coastal geology, geomorphology, climate science, oceanography, and decision analysis when developing conservation plans for coastal restoration. We illustrate the process with several coastal restoration studies. Our capstone example is based on a recent barrier island restoration assessment project at Dauphin Island, Alabama, which included the development of geomorphological and ecological models. We show how decision science can be used as a framework to combine geomorphological and ecological modeling to help inform management decisions while considering uncertainty about system changes and risk tolerance. We also build on our examples through a review of recently developed techniques for spatial conservation planning for land acquisition decisions and the application of adaptive management for sequential decisions.

Alabama↗

USGS2024

Introduction and methods of analysis for peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States. This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States. Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.

Iowa, Illinois, Michigan, Missouri, Minnesota, Mon↗

USGS2014

Distribution and landscape controls of organic layer thickness and carbon within the Alaskan Yukon River Basin

Understanding of the organic layer thickness (OLT) and organic layer carbon (OLC) stocks in subarctic ecosystems is critical due to their importance in the global carbon cycle. Moreover, post-fire OLT provides an indicator of long-term successional trajectories and permafrost susceptibility to thaw. To these ends, we 1) mapped OLT and associated uncertainty at 30 m resolution in the Yukon River Basin (YRB), Alaska, employing decision tree models linking remotely sensed imagery with field and ancillary data, 2) converted OLT to OLC using a non-linear regression, 3) evaluate landscape controls on OLT and OLC, and 4) quantified the post-fire recovery of OLT and OLC. Areas of shallow (< 10 cm), moderate (≥ 10 cm and < 20 cm), moderately thick (≥ 20 cm and < 30 cm), and thick (≥ 30 cm) OLT, composed 34, 20, 14, and 18% of the YRB, respectively; the average OLT was 19.4 cm. Total OLC was estimated to be 3.38 Pg. A regional chronosequence analysis over 30 years revealed that OLT and OLC increased with stand age (OLT: R 2 = 0.68; OLC: R 2 = 0.66), where an average of 16 cm OLT and 5.3 kg/m 2 OLC were consumed by fires. Strong predictors of OLT included climate, topography, near-surface permafrost distributions, soil wetness, and spectral information. Our modeling approach enabled us to produce regional maps of OLT and OLC, which will be useful in understanding risks and feedbacks associated with fires and climate feedbacks.

Alaska↗

USGS2022

One hundred years of cobalt production in the Democratic Republic of the Congo

Cobalt is an indispensable element for the manufacture of strategic technologies including advanced batteries, jet engines, rare-earth permanent magnets, petroleum catalysts, and tool parts that enable construction, manufacturing, and mining. Cobalt routinely scores high in mineral supply risk assessments due to the concentration of cobalt mine production in the Democratic Republic of the Congo (DRC). This stands in contrast to the fact that DRC cobalt mine production had a 20% compound annual growth rate from 1995 through 2020—in large part due to investments by Chinese firms beginning in the mid-2000s. Given this continuous growth, one may ask why this supply is perceived to be so risky. This analysis illuminates the causes of historic disruptions to DRC cobalt mine and refinery production by analyzing country-level production, historical reports, and cobalt prices back to 1924. The results indicate that the main causes of supply disruptions were damage to transportation routes, underinvestment in maintaining nationalized mining assets, and the disintegration of the DRC economy during the early 1990s. On the other hand, cobalt mine production increased 50% from 1977 to 1979 despite two secessionist conflicts in DRC's cobalt producing region and increased seven-fold from 1996 to 2003 despite two African wars over the DRC and its resources. These results indicate that—barring another economic disintegration or mining industry nationalization—DRC mine production will likely continue to be the dominant supplier of the world's growing demand for cobalt in lithium-ion batteries. These results also indicate that sustained development of transportation (and other) infrastructure in Africa, as well as support for good governance in the DRC may prove key to the continued stability of DRC cobalt mine supplies.

Resources Policy↗

USGS2014

Estimation of potential scour at bridges on local government roads in South Dakota, 2009-12

In 2009, the U.S. Geological Survey and South Dakota Department of Transportation (SDDOT) began a study to estimate potential scour at selected bridges on local government (county, township, and municipal) roads in South Dakota. A rapid scour-estimation method (level-1.5) and a more detailed method (level-2) were used to develop estimates of contraction, abutment, and pier scour. Data from 41 level-2 analyses completed for this study were combined with data from level-2 analyses completed in previous studies to develop new South Dakota-specific regression equations: four regional equations for main-channel velocity at the bridge contraction to account for the widely varying stream conditions within South Dakota, and one equation for head change. Velocity data from streamgages also were used in the regression for average velocity through the bridge contraction. Using these new regression equations, scour analyses were completed using the level-1.5 method on 361 bridges on local government roads. Typically, level-1.5 analyses are completed at flows estimated to have annual exceedance probabilities of 1 percent (100-year flood) and 0.2 percent (500-year flood); however, at some sites the bridge would not pass these flows. A level-1.5 analysis was then completed at the flow expected to produce the maximum scour. Data presented for level-1.5 scour analyses at the 361 bridges include contraction, abutment, and pier scour. Estimates of potential contraction scour ranged from 0 to 32.5 feet for the various flows evaluated. Estimated potential abutment scour ranged from 0 to 40.9 feet for left abutments, and from 0 to 37.7 feet for right abutments. Pier scour values ranged from 2.7 to 31.6 feet. The scour depth estimates provided in this report can be used by the SDDOT to compare with foundation depths at each bridge to determine if abutments or piers are at risk of being undermined by scour at the flows evaluated. Replicate analyses were completed at 24 of the 361 bridges to provide quality-assurance/quality-control measures for the level-1.5 scour estimates. An attempt was made to use the same flows among replicate analyses. Scour estimates do not necessarily have to be in numerical agreement to give the same results. For example, if contraction scour replicate analyses are 18.8 and 30.8 feet, both scour depths can indicate susceptibility to scour for which countermeasures may be needed, even though one number is much greater than the other number. Contraction scour has perhaps the greatest potential for being estimated differently in replicate visits. For contraction scour estimates at the various flows analyzed, differences between results ranged from -7.8 to 5.5 feet, with a median difference of 0.4 foot and an average difference of 0.2 foot. Abutment scour appeared to be nearly as reproducible as contraction scour. For abutment scour estimates at the varying flows analyzed, differences between results ranged from -17.4 to 11 feet, with a median difference of 1.4 feet and an average difference of 1.7 feet. Estimates of pier scour tended to be the most consistently reproduced in replicate visits, with differences between results ranging from -0.3 to 0.5 foot, with a median difference of 0.0 foot and an average difference of 0.0 foot. The U.S. Army Corps of Engineers Hydraulics Engineering Center River Analysis Systems (HEC-RAS) software package was used to model stream hydraulics at the 41 sites with level-2 analyses. Level-1.5 analyses also were completed at these sites, and the performance of the level-1.5 method was assessed by comparing results to those from the more rigorous level-2 method. The envelope curve approach used in the level-1.5 method is designed to overestimate scour relative to the estimate from the level-2 scour analysis. In cases where the level-1.5 method estimated less scour than the level-2 method, the amount of underestimation generally was less than 3 feet. The level-1.5 method generally overestimated contraction, abutment, and pier scour relative to the level-2 method, as intended. Although the level-1.5 method is designed to overestimate scour relative to more involved analysis methods, many assumptions, uncertainties, and estimations are involved. If the envelope curves are adjusted such that the level-1.5 method never underestimates scour relative to the level-2 method, an accompanying result may be excessive overestimation.

South Dakota↗

USGS2014

Historic and contemporary mercury exposure and potential risk to yellow-billed loons ( Gavia adamsii ) breeding in Alaska and Canada

The Yellow-billed Loon (Gavia adamsii) is one of the rarest breeding birds in North America. Because of the small population size and patchy distribution, any stressor to its population is of concern. To determine risks posed by environmental mercury (Hg) loads, we captured 115 Yellow-billed Loons between 2002 and 2012 in the North American Arctic and sampled their blood and/or feather tissues and collected nine eggs. Museum samples from Yellow-billed Loons also were analyzed to examine potential changes in Hg exposure over time. An extensive database of published Hg concentrations and associated adverse effects in Common Loons (G. immer) is highly informative and representative for Yellow-billed Loons. Blood Hg concentrations reflect dietary uptake of methylmercury (MeHg) from breeding areas and are generally considered near background levels if less than 1.0 µg/g wet weight (ww). Feather (grown at wintering sites) and egg Hg concentrations can represent a mix of breeding and wintering dietary uptake of MeHg. Based on Common Loon studies, significant risk of reduced reproductive success generally occurs when adult Hg concentrations exceed 2.0 µg/g ww in blood, 20.0 µg/g fresh weight (fw) in flight feathers and 1.0 µg/g ww in eggs. Contemporary mercury concentrations for 176 total samples (across all study sites for 115 Yellow-billed Loons) ranged from 0.08 to 1.45 µg/g ww in blood, 3.0 to 24.9 µg/g fw in feathers and 0.21 to 1.23 µg/g ww in eggs. Mercury concentrations in blood, feather and egg tissues indicate that some individual Yellow-billed Loons in breeding populations across North America are at risk of lowered productivity resulting from Hg exposure. Most Yellow-billed Loons breeding in Alaska overwinter in marine waters of eastern Asia. Although blood Hg concentrations from most breeding loons in Alaska are within background levels, some individuals exhibit elevated feather and egg Hg concentrations, which likely indicate the uptake of MeHg originating from eastern Asia. Feather Hg concentrations tended to be highest in individuals overwintering farthest west (closer to Asia). A retrospective analysis of museum specimens (n = 25) found a two-fold increase in Yellow-billed Loon feather Hg concentrations from the pre-1920s (as early as 1845) to the present. The projected increase in Hg deposition (approximately four-fold by 2050) along with the uncertainty of Hg being released through the thawing of permafrost and Arctic sea ice suggest that Hg body burdens in Yellow-billed Loons may increase. These findings indicate that Hg is a current and potentially increasing environmental stressor for the Yellow-billed Loon and possibly other Nearctic-Palearctic migrant birds.

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