Depleted hydrocarbon reservoirs are subsurface geological structures capable of sequestering vast quantities of carbon dioxide (CO2) as well as storing other energy gases for later usage, such as natural gas, and potentially hydrogen (H2). Here we outline a methodology to quantify multi-gas storage resources in depleted conventional gas reservoirs for usage in assessments by the United States Geological Survey (USGS) at the scale of sedimentary basins. The methodology consists first of quantifying accessible pore volume in a depleted reservoir for natural gas storage using up to three equations. Input data are derived from commonly reported or estimated reservoir parameters and natural gas production volumes, and equations may be combined in linear models to improve pore volume estimates. Storage estimates from these equations are tested and validated for 31 reservoirs in the Michigan Basin Province, USA that were previously converted to underground gas storage facilities and have known (federally reported) natural gas storage capacities. Secondly, natural gas storage capacities can be transformed via fluid substitution calculations to estimate the storage resources for non-native fluids, applied here for, CO2, H2, and methane-H2 blends, accounting for molecule-specific deviations from ideal gas behavior at reservoir pressures and temperatures as well as differing storage efficiencies. Importantly, the storage of non-native fluids may not be appropriate in all depleted gas reservoir settings due to potential risks like leakage, in particular in the case of H2 storage, requiring additional knowledge of caprock sealing capacity. Given this caveat, we demonstrate the fluid substitution method for natural gas reservoirs of the Northern Niagaran Reef and Southern Niagaran Reef USGS plays in the Michigan Basin Province, as these trends of Silurian pinnacle reefs are capped with tight-sealing evaporite facies. The deterministic equations outlined from this methodology can be incorporated into future probabilistic USGS gas storage assessments for CO2, H2, and natural gas resources in the United States.
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D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918323,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263800,"text":"70263800 - 2024 - Detection probabilities of Flathead Catfish in small Kansas impoundments","interactions":[],"lastModifiedDate":"2025-03-26T15:57:43.955275","indexId":"70263800","displayToPublicDate":"2024-11-11T09:47:29","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Detection probabilities of Flathead Catfish in small Kansas impoundments","docAbstract":"A primary challenge of Flathead Catfish Pylodictis olivaris management is uncertainty associated with sampling strategies and resulting ambiguity in population-level information. Assessment of impoundment and environmental conditions that affect detection probability may aid in reducing sample variance and benefit inferences regarding changes to Flathead Catfish populations. We sampled eight small impoundments in Kansas (37–114 surface ha) using low-frequency electrofishing in summer, 2021. We revisited sites nine times over three months using an occupancy modeling framework to estimate the influence of impoundment and environmental conditions on detection probability of Flathead Catfish. We employed an information theoretic approach and ranked models built with impoundment as a random effect and three environmental variables predicted to influence detection of Flathead Catfish in small impoundments. Detection probability across all populations was 0.526 (SE = 0.020) and was influenced by water temperature, mean depth of the impoundment, and proportion of impoundment sampled. Generally, detection probability increased with all measured variables. The inclusion of detection probability in assessments of Flathead Catfish in small impoundments can inform interpretation of catch-related metrics. Further, variable detection suggests collection of multiple samples during a defined sampling period might be more suitable for characterizing populations than a single sample.
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Kowalewski","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":928337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kramer, Nicholas W.","contributorId":351292,"corporation":false,"usgs":false,"family":"Kramer","given":"Nicholas W.","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":928338,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lundgren, Seth A.","contributorId":351293,"corporation":false,"usgs":false,"family":"Lundgren","given":"Seth A.","affiliations":[{"id":81167,"text":"Kansas Department of Wildlife and Parks","active":true,"usgs":false}],"preferred":false,"id":928339,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":928340,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260851,"text":"70260851 - 2024 - Annual grass invasions and wildfire deplete ecosystem carbon storage by >50% to resistant base levels","interactions":[],"lastModifiedDate":"2024-11-12T15:20:21.159268","indexId":"70260851","displayToPublicDate":"2024-11-11T09:17:43","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19829,"text":"Nature Communications, Earth & Environment","active":true,"publicationSubtype":{"id":10}},"title":"Annual grass invasions and wildfire deplete ecosystem carbon storage by >50% to resistant base levels","docAbstract":"Ecological disturbance can affect carbon storage and stability and is a key consideration for managing lands to preserve or increase ecosystem carbon to ameliorate the global greenhouse gas problem. Dryland soils are massive carbon reservoirs that are increasingly impacted by species invasions and altered fire regimes, including the exotic-grass-fire cycle in the extensive sagebrush steppe of North America. Direct measurement of total carbon in 1174 samples from landscapes of this region that differed in invasion and wildfire history revealed that their impacts depleted soil carbon by 42–49%, primarily in deep horizons, which could amount to 17.1–20.0 Tg carbon lost across the ~400,000 ha affected annually. Disturbance effects on soil carbon stocks were not synergistic, suggesting that soil carbon was lowered to a floor—i.e. a resistant base-level—beneath which further loss was unlikely. Restoration and maintenance of resilient dryland shrublands/rangelands could stabilize soil carbon at magnitudes relevant to the global carbon cycle.
","language":"English","publisher":"Nature","doi":"10.1038/s43247-024-01795-9","usgsCitation":"Maxwell, T.M., Quicke, H.E., Price, S.J., and Germino, M., 2024, Annual grass invasions and wildfire deplete ecosystem carbon storage by >50% to resistant base levels: Nature Communications, Earth & Environment, v. 5, 669, 11 p., https://doi.org/10.1038/s43247-024-01795-9.","productDescription":"669, 11 p.","ipdsId":"IP-162810","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":466772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-024-01795-9","text":"Publisher Index Page"},{"id":463870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2024-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Maxwell, Toby Matthew 0000-0001-5171-0705","orcid":"https://orcid.org/0000-0001-5171-0705","contributorId":334690,"corporation":false,"usgs":true,"family":"Maxwell","given":"Toby","email":"","middleInitial":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918295,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quicke, Harold E.","contributorId":346166,"corporation":false,"usgs":false,"family":"Quicke","given":"Harold","email":"","middleInitial":"E.","affiliations":[{"id":82790,"text":"Environmental Science U.S. LLC","active":true,"usgs":false}],"preferred":false,"id":918296,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Price, Samuel J. 0000-0003-4172-4139","orcid":"https://orcid.org/0000-0003-4172-4139","contributorId":297001,"corporation":false,"usgs":true,"family":"Price","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918298,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260886,"text":"70260886 - 2024 - Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance","interactions":[],"lastModifiedDate":"2025-03-11T14:49:17.072232","indexId":"70260886","displayToPublicDate":"2024-11-11T08:52:40","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance","docAbstract":"The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.
","language":"English","publisher":"Sage","doi":"10.1177/87552930241280401","usgsCitation":"Porter, K., Milner, K.R., and Field, E.H., 2024, Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance: Earthquake Spectra, v. 41, no. 1, p. 636-653, https://doi.org/10.1177/87552930241280401.","productDescription":"19 p.","startPage":"636","endPage":"653","ipdsId":"IP-161498","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":464026,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-11-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Porter, Keith","contributorId":191074,"corporation":false,"usgs":false,"family":"Porter","given":"Keith","affiliations":[],"preferred":false,"id":918429,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milner, Kevin R.","contributorId":194141,"corporation":false,"usgs":false,"family":"Milner","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":918430,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":918431,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263970,"text":"70263970 - 2024 - Length in assessing status of freshwater fish populations: A review","interactions":[],"lastModifiedDate":"2025-03-04T15:50:34.260958","indexId":"70263970","displayToPublicDate":"2024-11-10T09:39:34","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Length in assessing status of freshwater fish populations: A review","docAbstract":"Effective policy formulation regarding the conservation of freshwater fish necessitates an understanding of water‐specific prevailing conditions and trends. Assessing fish populations in inland waters is difficult and expensive because there are many independent systems that need to be evaluated. Therefore, numerous freshwater systems are beset by insufficient data and the lack of systematic assessments of their status. To alleviate this deficiency, the objective of this study was to review length‐based metrics that may have utility in evaluating the well‐being of freshwater fish populations.
Length measurements can serve as proxies for a range of ecological and population dynamics attributes that are essential for the effective management of fish and associated fisheries. A review of the historical development of length measurements in fish conservation is provided, along with an examination of the potential biases that may arise from the use of lengths in practical contexts. In addition, we examine techniques that enable the spatial and temporal visualization of length data sets, as well as a range of indices and metrics that can be computed using length measurements.
Building populations assessments around length may be a cost‐effective strategy that allows a first cut at managing a large number of waters. Length‐based assessments can signal if management intervention is necessary, if management policies are yielding the intended outcome, or if surveys beyond mere length are necessary.
Our review indicates that length offers a straightforward and efficient approach to evaluate the status of fish populations in inland systems. We encourage pursuing additional study and to this end propose specific areas for investigation.
Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Hydrologic connectivity, the network of water pathways linking aquatic habitats, is vital for the exchange of organisms and abiotic materials between rivers and adjacent waterbodies. This study quantified hydrologic connectivity for 1,283 lakes in the Lower Mississippi River floodplain using satellite imagery, streamgauge data, and geospatial information. We aimed to assess connection frequency patterns between lakes and streams. Eight metrics describing temporal aspects of hydrologic connectivity were estimated, identifying trends by lake features and by stream size. Each lake exhibited a distinct pattern of connection, with specific months of connectivity followed by disconnection, likely influenced by lake characteristics and seasonal precipitation. Larger lakes showed increased connectivity, likely due to their surface area and volume, while smaller lakes were more prone to isolation, especially during dry periods. Lakes connected to large streams exhibited more prolonged and recurring connections, with less seasonal variation. In contrast, lakes near agricultural areas experienced reduced connectivity. However, local factors such as levees and artificial channels often disrupted these general trends. This hydrologic connectivity analysis can provide insight to support floodplain management, facilitate development of frameworks that restore connectivity, promote preservation of ecological integrity, and support management of invasive species spread in agricultural floodplains.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2024.112808","usgsCitation":"Ahmad, H., Miranda, L.E., Dunn, C.G., Boudreau, M., and Colvin, M.E., 2024, Connectivity patterns between floodplain lakes and neighboring streams in the historical floodplain of the Lower Mississippi River: Ecological Indicators, v. 169, 112808, 12 p., https://doi.org/10.1016/j.ecolind.2024.112808.","productDescription":"112808, 12 p.","ipdsId":"IP-168197","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490657,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2024.112808","text":"Publisher Index Page"},{"id":490406,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1QIH9NJ","text":"USGS data release","linkHelpText":"Code for Connectivity patterns between floodplain lakes and neighboring streams in the historical floodplain of the Lower Mississippi River"},{"id":489294,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lower Mississippi River floodplain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.30878420635052,\n 38.86158462464857\n ],\n [\n -92.32018351048195,\n 38.86158462464857\n ],\n [\n -92.32018351048195,\n 28.20085112656909\n ],\n [\n -88.30878420635052,\n 28.20085112656909\n ],\n [\n -88.30878420635052,\n 38.86158462464857\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"169","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ahmad, Hafez","contributorId":353774,"corporation":false,"usgs":false,"family":"Ahmad","given":"Hafez","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":938775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":938776,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":938777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boudreau, Melanie R.","contributorId":353778,"corporation":false,"usgs":false,"family":"Boudreau","given":"Melanie R.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":938778,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938779,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260707,"text":"sir20235064I - 2024 - Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","interactions":[{"subject":{"id":70260707,"text":"sir20235064I - 2024 - Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","indexId":"sir20235064I","publicationYear":"2024","noYear":false,"chapter":"I","displayTitle":"Peak Streamflow Trends in South Dakota and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020"},"predicate":"IS_PART_OF","object":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"id":1}],"isPartOf":{"id":70251152,"text":"sir20235064 - 2024 - Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin","indexId":"sir20235064","publicationYear":"2024","noYear":false,"title":"Peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin"},"lastModifiedDate":"2025-12-22T21:31:08.991933","indexId":"sir20235064I","displayToPublicDate":"2024-11-08T10:53:13","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5064","chapter":"I","displayTitle":"Peak Streamflow Trends in South Dakota and Their Relation to Changes in Climate, Water Years 1921–2020","title":"Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020","docAbstract":"Peak-flow (flood) frequency analysis is essential to water-resources management applications, including the design of critical infrastructure such as bridges and culverts, and floodplain mapping. Federal guidelines for performing peak-flow 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, which documents the guidelines for determining annual peak streamflow frequency, is that, for basins without major hydrologic alterations (for example, regulation, diversion, and urbanization), statistical properties of the distribution of annual peak streamflows are stationary; that is, the mean, variance, and skew are constant through time. Nonstationarity is a statistical property of a peak-flow series such that the long-term (on the order of decades) distributional properties change one or more times either gradually or abruptly through time. Individual nonstationarities may be attributed to one source such as flow regulation, land-use change, or climate but are often the result of a combination of sources, making detection and attribution of nonstationarities challenging.
In response to a growing concern regarding nonstationarity in peak streamflows in the region, 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, assessed the potential nonstationarity in peak streamflows in the north-central United States. This chapter characterizes the effects of natural hydroclimatic shifts and potential climate change on annual peak streamflows in the State of South Dakota. Annual peak and daily streamflow as well as model-simulated gridded climatic data were examined for temporal monotonic trends, change points, and other statistical properties indicative of changing climatic and environmental conditions.
Changes in annual peak and daily flows were evaluated among 13, 35, and 81 qualifying U.S. Geological Survey streamgages for the 75-, 50-, and 30-year trend periods through water year 2020 (the period from October 1, 2019, to September 30, 2020) in South Dakota, respectively. No qualifying streamgages were in the 100-year trend period in the State. Statistical tests for autocorrelation (independent and identically distributed assumption), monotonic trends, and change points in the median and scale are analyzed to evaluate potential stationarity violations (nonstationarity) for performing at-site peak-flow flood-frequency analysis. The trends are reported using a likelihood approach as an alternative to simply reporting significant trends with an arbitrary p-value cutoff point.
A distinct east-west spatial pattern of likely upward and downward monotonic trends and change points, respectively, was detected in 75- and 50-year trend periods, but an inconsistent spatial pattern was detected in the 30-year trend period. Additionally, change points in the median annual peak streamflows were detected in the late 1970s and early 1980s in the western part of the State, but in the east, the change point was more commonly detected in 1992–93. A similar east-west spatial pattern of likely upward and downward trends was detected in the annual peak-flow timing, the day of the year of the annal peak streamflow. In the western part of the State, the annual peak streamflows are arriving earlier, but in the east, the annual peak streamflows are arriving later. A peaks-over-threshold (POT) analysis where, on average, there are two events per year (POT2) and four events per year (POT4) was also used to evaluate changes in the frequency (count) of daily streamflows exceeding the threshold. Similar to detected changes in the annual peak streamflow, an east-west likely upward or downward change corresponding to an increase or decrease, respectively, in the frequency of daily streamflow greater than a POT2 and POT4 threshold was detected.
A monthly water-balance model was used to evaluate hydroclimatic variation in annual and seasonal precipitation, snowfall, potential evapotranspiration, and soil moisture storage for all qualifying streamgages in the 75-, 50-, and 30-year trend periods. Detected trends in the annual hydroclimatic metrics for the 75- and 50-year trend periods indicate a spatially consistent statewide increase in precipitation, decrease in snowfall, increase in potential evapotranspiration, and increase in soil moisture storage. Furthermore, detected trends in seasonal precipitation in the 75- and 50-year trend periods highlight a pronounced change in precipitation in winter and later into the summer season, especially in the 50-year trend period in the eastern part of the State. Statewide increases in seasonal soil moisture storage were also detected, highlighting year-round increasing flood magnitudes, particularly in the eastern part of the State.
Based on the results of these stationarity tests for the qualifying streamgages in South Dakota among the 75-, 50-, and 30-year trend periods, consistent temporal and spatial patterns of nonstationarity were detected among the 75- and 50-year trend periods. Furthermore, when nonstationarity is detected in daily streamflow, increased streamflow and volume (increasing frequency in POT), as well as potentially bridge scour, may have implications on culvert and highway design in the eastern part of South Dakota. Thus, when performing at-site peak-flow flood-frequency analyses in South Dakota, potential nonstationarities and alternative approaches are important considerations.
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U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Fluid inclusion microthermometry and Raman spectroscopy of fluid inclusions in quartz veins from the Pennsylvanian rocks of the Anthracite belt, eastern Pennsylvania support a deep burial model of coalification in favor of focused orogenic hot fluid flow. High-temperature (250 to 255 °C) trapping of CH4 ± CO2 saturated aqueous fluids and CH4 ± CO2 inclusions indicate fluid trapping at depths of 11.5 to 13.4 km under a cover of Pennsylvanian to Permian(?) syntectonic load. In the folded rocks to the south of the Anthracite belt, CH4 ± CO2 fluid inclusions indicate a sediment load that was up to 16.3 km thick. Re-equilibrated aqueous fluid inclusions from veins in Silurian through Devonian rocks give the same range of trapping conditions but a wide range of fluid salinities suggesting that folding, fracturing, and meteoric recharge resulted in the intermixing of fluids from throughout the stratigraphic succession.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2024.104646","usgsCitation":"Evans, M.A., and Jubb, A., 2024, Deep syntectonic burial of the Anthracite belt, Eastern Pennsylvania: International Journal of Coal Geology, v. 295, 104646, 27 p., https://doi.org/10.1016/j.coal.2024.104646.","productDescription":"104646, 27 p.","ipdsId":"IP-164265","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":463907,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75,\n 41.75\n ],\n [\n -80,\n 41.75\n ],\n [\n -80,\n 39.5\n ],\n [\n -75,\n 39.5\n ],\n [\n -75,\n 41.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"295","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Evans, Mark A.","contributorId":197411,"corporation":false,"usgs":false,"family":"Evans","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":918370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":918369,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70270845,"text":"70270845 - 2024 - Biological feasibility of introducing bighorn sheep to the Jicarilla Apache Nation","interactions":[],"lastModifiedDate":"2025-08-28T15:11:50.278531","indexId":"70270845","displayToPublicDate":"2024-11-08T09:59:02","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"CSS-159-2024","title":"Biological feasibility of introducing bighorn sheep to the Jicarilla Apache Nation","docAbstract":"The biological feasibility of introducing Rocky Mountain bighorn sheep (Ovis canadensis canadensis) to the Dulce area of the Jicarilla Apache Nation (JAN) depends on availability and condition of potential habitat and the potential for disease risk, as pneumonia is the largest current threat to wild sheep populations. We modeled quality and quantity of potential bighorn sheep habitat incorporating the three most recent fire scars around Dulce, determined potential winter range within preferred habitat, assessed on the ground vegetation characteristics, and examined potential for disease transmission via risk of contact with domestic sheep and goats. Most of the area of interest for this study has a suitability value ≥ 50%, with approximately 23-29% of the study area considered preferred, or high-quality habitat for bighorn sheep. High-quality habitat for Rocky Mountain bighorn sheep is defined as being within 300 m of escape terrain, within 1.6 km of water, and containing ≤ 30% shrub and tree cover. Of this, approximately 43-56% of potential preferred habitat qualifies as winter range, which is mostly concentrated in the narrow valley bottoms where roads are commonly located and the south-facing slopes surrounding valleys. Analysis of field-collected vegetation data indicate most of the existing forage within the surveyed area to be of moderate or high forage value to bighorn sheep, but horizontal visibility, predominantly in the form of shrubs, is more obscured than what bighorn sheep prefer for most of the area of interest. Maximum shrub and tree cover is also the most limiting factor in the suitability model, primarily due to the prevalence of dense shrub regeneration, particularly Gambel oak, which occurs after high severity burns. The largest quantities of high-quality potential bighorn sheep habitat within the study area occur in unburned areas or those burnt by the predominantly low-moderate severity Amargo fire in 2021. Relative to risk of contact with domestic sheep and goats that can transmit lethal pneumonia-causing pathogens, potentially causing an introduction effort to fail, there is high risk because of the proximity to two hobby-subsistence herds (< 3 km away).
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/10.3996/css73616801","usgsCitation":"Thompson, C.J., and Cain, J.W., 2024, Biological feasibility of introducing bighorn sheep to the Jicarilla Apache Nation: Cooperator Science Series CSS-159-2024, 80 p., https://doi.org/10.3996/10.3996/css73616801.","productDescription":"80 p.","ipdsId":"IP-167003","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":494875,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/biological-feasibility-introducing-bighorn-sheep-jicarilla-apache-nation","linkFileType":{"id":5,"text":"html"}},{"id":495006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Jicarilla Apache Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.01771249033892,\n 36.99249959403626\n ],\n [\n -107.5487950989812,\n 36.99249959403626\n ],\n [\n -107.5487950989812,\n 36.05621273485714\n ],\n [\n -106.01771249033892,\n 36.05621273485714\n ],\n [\n -106.01771249033892,\n 36.99249959403626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Thompson, Cara J.","contributorId":360559,"corporation":false,"usgs":false,"family":"Thompson","given":"Cara","middleInitial":"J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":947210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, James W. III 0000-0003-4743-516X jwcain@usgs.gov","orcid":"https://orcid.org/0000-0003-4743-516X","contributorId":4063,"corporation":false,"usgs":true,"family":"Cain","given":"James","suffix":"III","email":"jwcain@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":947211,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70260845,"text":"70260845 - 2024 - Riparian methylmercury production increases riverine mercury flux and food web concentrations","interactions":[],"lastModifiedDate":"2025-02-07T16:28:17.344914","indexId":"70260845","displayToPublicDate":"2024-11-08T09:57:15","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Riparian methylmercury production increases riverine mercury flux and food web concentrations","docAbstract":"The production and uptake of toxic methylmercury (MeHg) impacts aquatic ecosystems globally. Rivers can be dynamic and difficult systems to study for MeHg production and bioaccumulation, hence identifying sources of MeHg to these systems is both challenging and important for resource management within rivers and main-stem reservoirs. Riparian zones, which are known biogeochemical hotspots for MeHg production, are understudied as potential sources of MeHg to rivers. Here, we present a comprehensive quantification of the hydrologic and biogeochemical processes governing MeHg concentrations, loads, and bioaccumulation at 16 locations along 164 km of the agriculturally intensive Snake River (Idaho, Oregon USA) during summer baseflow conditions, with emphasis on riparian production of MeHg. Approximately one-third of the MeHg load of the Snake River could not be attributed to inflowing waters (upgradient, tributaries, or irrigation drains). Across the study reach, increases in MeHg loads in surface waters were significantly correlated with MeHg concentrations in riparian porewaters, suggesting riparian zones were likely an important source of MeHg to the Snake River. Across all locations, MeHg concentrations in surface waters positively correlated with MeHg concentrations in benthic snails and clams, supporting that riparian produced MeHg was assimilated into local aquatic food webs. This study contributes new insights into riparian MeHg production within rivers which can inform mitigation efforts to reduce MeHg bioaccumulation in fish.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.4c08585","usgsCitation":"Krause, V., Baldwin, A.K., Peterson, B.D., Krabbenhoft, D.P., Janssen, S., Willacker, J., Eagles-Smith, C., and Poulin, B., 2024, Riparian methylmercury production increases riverine mercury flux and food web concentrations: Environmental Science & Technology, v. 58, no. 46, p. 20490-20501, https://doi.org/10.1021/acs.est.4c08585.","productDescription":"12 p.","startPage":"20490","endPage":"20501","ipdsId":"IP-168495","costCenters":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":463875,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":466774,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.4c08585","text":"Publisher Index Page"}],"country":"United States","state":"Idaho, Oregon","otherGeospatial":"Snake River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.76519965515584,\n 44.99304074681157\n ],\n [\n -117.75863076747619,\n 42.94336107731144\n ],\n [\n -116.17776769472738,\n 42.9364463608284\n ],\n [\n -116.25927931073849,\n 44.985691191051046\n ],\n [\n -117.76519965515584,\n 44.99304074681157\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","issue":"46","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Krause, Virginia","contributorId":346163,"corporation":false,"usgs":false,"family":"Krause","given":"Virginia","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":918280,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918281,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Benjamin D.","contributorId":328487,"corporation":false,"usgs":false,"family":"Peterson","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":918282,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918283,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918284,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Willacker, James 0000-0002-6286-5224","orcid":"https://orcid.org/0000-0002-6286-5224","contributorId":221744,"corporation":false,"usgs":true,"family":"Willacker","given":"James","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918285,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":918286,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Poulin, Brett A.","contributorId":328488,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett A.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":918287,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70261200,"text":"70261200 - 2024 - Near-term ecological forecasting for climate change action","interactions":[],"lastModifiedDate":"2024-12-10T15:40:21.945944","indexId":"70261200","displayToPublicDate":"2024-11-08T08:55:08","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Near-term ecological forecasting for climate change action","docAbstract":"A substantial increase in predictive capacity is needed to anticipate and mitigate the widespread change in ecosystems and their services in the face of climate and biodiversity crises. In this era of accelerating change, we cannot rely on historical patterns or focus primarily on long-term projections that extend decades into the future. In this Perspective, we discuss the potential of near-term (daily to decadal) iterative ecological forecasting to improve decision-making on actionable time frames. We summarize the current status of ecological forecasting and focus on how to scale up, build on lessons from weather forecasting, and take advantage of recent technological advances. We also highlight the need to focus on equity, workforce development, and broad cross-disciplinary and non-academic partnerships.
","language":"English","publisher":"Nature","doi":"10.1038/s41558-024-02182-0","usgsCitation":"Dietze, M., White, E.P., Abeyta, A., Boettiger, C., Bueno Watts, N., Carey, C.C., Chaplin-Kramer, R., Emanuel, R.E., Ernest, S.M., Figueiredo, R., Gerst, M., Johnson, L.R., Kenney, M.A., McLachlan, J.S., Paschalidis, I., Peters, J., Rollinson, C.R., Simonis, J., Sullivan-Wiley, K., Thomas, R.Q., Wardle, G.M., Willson, A., and Zwart, J.A., 2024, Near-term ecological forecasting for climate change action: Nature Climate Change, v. 14, p. 1236-1244, https://doi.org/10.1038/s41558-024-02182-0.","productDescription":"9 p.","startPage":"1236","endPage":"1244","ipdsId":"IP-151657","costCenters":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":489045,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/10919/122612","text":"External Repository"},{"id":464589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Dietze, Michael","contributorId":248349,"corporation":false,"usgs":false,"family":"Dietze","given":"Michael","affiliations":[],"preferred":false,"id":919605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Ethan P.","contributorId":190112,"corporation":false,"usgs":false,"family":"White","given":"Ethan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":919606,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abeyta, Antoinette","contributorId":346577,"corporation":false,"usgs":false,"family":"Abeyta","given":"Antoinette","email":"","affiliations":[{"id":82890,"text":"University of New Mexico Gallup","active":true,"usgs":false}],"preferred":false,"id":919607,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boettiger, Carl 0000-0002-1642-628X","orcid":"https://orcid.org/0000-0002-1642-628X","contributorId":332018,"corporation":false,"usgs":false,"family":"Boettiger","given":"Carl","email":"","affiliations":[{"id":79359,"text":"Department of Environmental Science, Policy and Management, University of California Berkeley, Berkeley, CA","active":true,"usgs":false}],"preferred":false,"id":919608,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bueno Watts, Nievita","contributorId":346578,"corporation":false,"usgs":false,"family":"Bueno Watts","given":"Nievita","email":"","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":919609,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carey, Cayelan C.","contributorId":130969,"corporation":false,"usgs":false,"family":"Carey","given":"Cayelan","email":"","middleInitial":"C.","affiliations":[{"id":7185,"text":"Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA","active":true,"usgs":false}],"preferred":false,"id":919610,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chaplin-Kramer, Rebecca 0000-0002-1539-5231","orcid":"https://orcid.org/0000-0002-1539-5231","contributorId":213447,"corporation":false,"usgs":false,"family":"Chaplin-Kramer","given":"Rebecca","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":919611,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Emanuel, Ryan E.","contributorId":346579,"corporation":false,"usgs":false,"family":"Emanuel","given":"Ryan","email":"","middleInitial":"E.","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":919612,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ernest, S.K. 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Initial reproductive success post-translocation is important for establishing short-lived species such as quail, but factors influencing reproductive success are poorly understood. We evaluated the effect of source population and variation in delayed release strategy (1−9 weeks) on nest initiation and nest survival of wild-caught, translocated scaled quail. We trapped and translocated scaled quail in 2016–2017 from source populations in the Edwards Plateau and Rolling Plains ecoregions of Texas, USA, to a large contiguous (>40,000 ha) release site in Knox County, Texas. We used a multi-state mark-recapture model with state uncertainty to test for effects of release treatment, source population, age, release location, and year on nest initiation and survival. Increased length of holding time decreased re-nesting effort. Yearlings were more likely to initiate nests than adults and the probability of re-nesting was lower during the year with drought conditions. There was no effect of source population on any of the parameters we evaluated. Future scaled quail reintroduction efforts may benefit from prioritizing translocation of yearlings and conducting translocations when drought conditions are not forecasted.
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From 2018 through 2020 the U.S. Geological Survey and U.S. Army Corps of Engineers led a series of calls and meetings, and a workshop to develop a draft UMRS hydrogeomorphic change conceptual model and hierarchical classification scheme. This project was funded through an Upper Mississippi River Restoration 2018 science in support of restoration proposal entitled, “Conceptual Model and Hierarchical Classification of Hydrogeomorphic Settings in the Upper Mississippi River System.” This report documents the background leading up to and the major findings from the workshop. The resulting conceptual model focuses on the drivers and boundary conditions that affect the major hydrogeomorphic processes along the valley corridor using a continuum of spatial and temporal scales and resolutions. The draft hierarchical classification was based on three existing and three new nested geospatial datasets that ultimately can be used to characterize hydrogeomorphic settings that span the UMRS valley corridor. The conceptual model and hierarchical classification will help characterize recent (mid-1990s through mid-2010s) decadal-scale processes and sources for potential hydrogeomorphic change that span a range of spatial scales from watershed hydrology and sediment sources to channel hydraulics and sediment transport.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241051","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Fitzpatrick, F.A., Rogala, J.T., Hendrickson, J.S., Sawyer, L., Stone, J., Erwin, S., Brauer, E.J., and Vaughan, A.A., 2024, Upper Mississippi River System hydrogeomorphic change conceptual model and hierarchical classification: U.S. Geological Survey Open-File Report 2024–1051, 24 p., https://doi.org/10.3133/ofr20241051.","productDescription":"vi, 24 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154820","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":463608,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1051/ofr20241051.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024–1051"},{"id":463607,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1051/coverthb.jpg"},{"id":463611,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241051/full"},{"id":463609,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1051/ofr20241051.XML"},{"id":463610,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1051/images/"},{"id":497918,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117772.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois, Indiana, Iowa, Minnesota, Missouri, South Dakota, Wisconsin","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.50342683246095,\n 40.74721296729754\n ],\n [\n -86.22485822523954,\n 41.12212957640983\n ],\n [\n -86.47633619015835,\n 41.49085772032035\n ],\n [\n -87.70997806528162,\n 41.54161184649007\n ],\n [\n -87.96780499446993,\n 42.13710516972478\n ],\n [\n -88.45256695171824,\n 43.2601947483673\n ],\n [\n -88.90796053029793,\n 43.953704040844826\n ],\n [\n -89.31966888436784,\n 43.88619768580165\n ],\n [\n -88.82098034404291,\n 45.84620970391856\n ],\n [\n -89.77751644898966,\n 46.14284357021026\n ],\n [\n -92.3836871160787,\n 46.36717699384113\n ],\n [\n -93.57654031001726,\n 47.5843117955113\n ],\n [\n -96.69363739805445,\n 47.520997934475815\n ],\n [\n -96.5298693029927,\n 46.26717241479707\n ],\n [\n -97.88294379082475,\n 46.288663271101996\n ],\n [\n -96.96809715353103,\n 45.32804185048016\n ],\n [\n -95.79932895452089,\n 43.51835880034011\n ],\n [\n -93.73471399415848,\n 39.80187490699902\n ],\n [\n -90.99752932951242,\n 36.93622008574626\n ],\n [\n -89.6631770431625,\n 36.64968232220457\n ],\n [\n -89.28540446277691,\n 37.166100746132656\n ],\n [\n -87.50342683246095,\n 40.74721296729754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"The NASA Perseverance rover discovered light-toned float rocks scattered across the surface of Jezero crater that are particularly rich in alumina ( ~ 35 wt% Al2O3) and depleted in other major elements (except silica). These unique float rocks have heterogeneous mineralogy ranging from kaolinite/halloysite-bearing in hydrated samples, to spinel-bearing in dehydrated samples also containing a dehydrated Al-rich phase. Here we describe SuperCam and Mastcam-Z observations of the float rocks, including the first in situ identification of kaolinite or halloysite on another planet, and dehydrated phases including spinel and apparent partially dehydroxylated kaolinite. The presence of spinel in these samples is likely detrital in origin, surviving kaolinitization, pointing to an ultramafic origin. However, the association of low hydration with increased Al2O3 abundances suggests heating-induced dehydration which could have occurred during the lithification or impact excavation of these rocks. Given the orbital context of kaolinite-bearing megabreccia in the Jezero crater rim, we propose an origin for these rocks involving intense aqueous alteration of the parent material, followed by dehydration/lithification potentially through impact processes, and dispersion into Jezero crater through flood or impact-related processes.
","language":"English","publisher":"Nature","doi":"10.1038/s43247-024-01837-2","usgsCitation":"Royer, C., Bedford, C., Johnson, J., Horgan, B., Broz, A., Forni, O., Connell, S., Wiens, R., Mandon, L., Kathir, B., Hausrath, E., Udry, A., Madariaga, J., Dehouck, E., Anderson, R.B., Beck, P., Beyssac, O., Clavé, É., Clegg, S., Cloutis, E., Fouchet, T., Gabriel, T.S., Garczynski, B., Klidaras, A., Manelski, H., Mayhew, L., Nunez, J., Ollila, A., Schröder, S., Simon, J., Wolf, U., Stack, K., Cousin, A., and Maurice, S., 2024, Intense alteration on early Mars revealed by high-aluminum rocks at Jezero Crater: Communications Earth & Environment, v. 5, 671, 13 p., https://doi.org/10.1038/s43247-024-01837-2.","productDescription":"671, 13 p.","ipdsId":"IP-159028","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":466775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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inclusions","interactions":[],"lastModifiedDate":"2024-12-10T15:38:41.563856","indexId":"70260964","displayToPublicDate":"2024-11-07T09:57:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Depths in a day - A new era of rapid-response Raman-based barometry using fluid inclusions","docAbstract":"Rapid-response petrological monitoring is a major advance for volcano observatories, allowing them to build and validate models of plumbing systems that supply eruptions in near-real-time. The depth of magma storage has recently been identified as high-priority information for volcanic observatories, yet this information is not currently obtainable via petrological monitoring methods on timescales relevant to eruption response. Fluid inclusion barometry (using micro-thermometry or Raman spectroscopy) is a well-established petrological method to estimate magma storage depths and has been proposed to have potential as a rapid-response monitoring tool, although this has not been formally demonstrated. To address this deficiency, we performed a near-real-time rapid-response simulation for the September 2023 eruption of Kīlauea, Hawaiʻi. We show that Raman-based fluid inclusion barometry can robustly determine reservoir depths within a day of receiving samples — a transformative timescale that has not previously been achieved by petrological methods. Fluid inclusion barometry using micro-thermometric techniques has typically been limited to systems with relatively deep magma storage (>0.4 g/cm3 or >7 km) where measurements of CO2 density are easy and accurate because the CO2 fluid homogenizes into the liquid phase. Improvements of the accuracy of Raman spectroscopy measurements of fluids with low CO2 density over the past couple of decades has enabled measurements of fluid inclusions from shallower magmatic systems. However, one caveat of examining shallower systems is that the fraction of H2O in the fluid may be too high to reliably convert CO2 density to pressure. To test the global applicability of rapid response fluid inclusion barometry, we compiled a global melt inclusion dataset (>4000 samples) and calculate the fluid composition at the point of vapor saturation (XH2O). We show that fluid inclusions in crystal-hosts from mafic compositions (<57 wt. % SiO2) — likely representative of magmas recharging many volcanic systems worldwide — trap fluids with XH2O low enough to make fluid inclusion barometry useful at many of the world’s most active and hazardous mafic volcanic systems (e.g., Iceland, Hawaiʻi, Galápagos Islands, East African Rift, Réunion, Canary Islands, Azores, Cabo Verde).
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egae119","usgsCitation":"DeVitre, C., Wieser, P.E., Bearden, A.T., Richie, A., Rangel, B., Gleeson, M., Grimsich, J., Lynn, K.J., Downs, D.T., Deligne, N.I., and Mulliken, K.M., 2024, Depths in a day - A new era of rapid-response Raman-based barometry using fluid inclusions: Journal of Petrology, v. 65, no. 11, egae119, 15 p., https://doi.org/10.1093/petrology/egae119.","productDescription":"egae119, 15 p.","ipdsId":"IP-158109","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466776,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/petrology/egae119","text":"Publisher Index Page"},{"id":464235,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.2575579892722,\n 19.41802727097236\n ],\n [\n -155.2575579892722,\n 19.40813592330987\n ],\n [\n -155.2414055520364,\n 19.40813592330987\n ],\n [\n -155.2414055520364,\n 19.41802727097236\n ],\n [\n -155.2575579892722,\n 19.41802727097236\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"65","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"DeVitre, Charlotte","contributorId":346229,"corporation":false,"usgs":false,"family":"DeVitre","given":"Charlotte","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":918713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wieser, Penny E. 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Berkeley","active":true,"usgs":false}],"preferred":false,"id":918716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rangel, Berenise","contributorId":346222,"corporation":false,"usgs":false,"family":"Rangel","given":"Berenise","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":918717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gleeson, Matthew","contributorId":346331,"corporation":false,"usgs":false,"family":"Gleeson","given":"Matthew","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":918718,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grimsich, John","contributorId":346332,"corporation":false,"usgs":false,"family":"Grimsich","given":"John","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":918719,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":918720,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Downs, Drew T. 0000-0002-9056-1404 ddowns@usgs.gov","orcid":"https://orcid.org/0000-0002-9056-1404","contributorId":173516,"corporation":false,"usgs":true,"family":"Downs","given":"Drew","email":"ddowns@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":918721,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Deligne, Natalia I. 0000-0001-9221-8581","orcid":"https://orcid.org/0000-0001-9221-8581","contributorId":257389,"corporation":false,"usgs":true,"family":"Deligne","given":"Natalia","email":"","middleInitial":"I.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":918722,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mulliken, Katherine M. 0000-0003-4190-5060","orcid":"https://orcid.org/0000-0003-4190-5060","contributorId":217810,"corporation":false,"usgs":false,"family":"Mulliken","given":"Katherine","email":"","middleInitial":"M.","affiliations":[{"id":16126,"text":"Alaska Division of Geological and Geophysical Surveys","active":true,"usgs":false}],"preferred":false,"id":918723,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70261191,"text":"70261191 - 2024 - Indigenous knowledge in climate adaptation planning: Reflections from initial efforts","interactions":[],"lastModifiedDate":"2024-11-29T16:02:54.137345","indexId":"70261191","displayToPublicDate":"2024-11-07T08:54:19","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7749,"text":"Frontiers in Climate","active":true,"publicationSubtype":{"id":10}},"title":"Indigenous knowledge in climate adaptation planning: Reflections from initial efforts","docAbstract":"There are increasing calls to incorporate indigenous knowledge (IK) into climate adaptation planning (CAP) and related projects. However, given unique attributes of IK and the positionality of tribal communities to scientific research, several considerations are important to ensure CAP efforts with IK are ethical and effective. While such topics have been thoroughly explored conceptually, incorporation of IK into CAP is a nascent field only beginning to report findings and improve science production and delivery. Based on recent work with Ute Mountain Ute (UMU) resource managers and knowledge holders, we reflect on key considerations for incorporating IK into CAP: the importance of sustained and multi-level tribal engagement, operational approaches to IK incorporation, cross-cultural challenges with risk-based approaches, and how CAP can support existing tribal priorities. We hope exploring these considerations can help set appropriate expectations, promote ethical interactions, and increase the effectiveness of tribal CAP and related efforts.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fclim.2024.1393354","usgsCitation":"Ciocco, T.W., Miller, B.W., Tangen, S.G., Crausbay, S.D., Oldfather, M.F., and Bamzai-Dodson, A., 2024, Indigenous knowledge in climate adaptation planning: Reflections from initial efforts: Frontiers in Climate, v. 6, 1393354, 8 p., https://doi.org/10.3389/fclim.2024.1393354.","productDescription":"1393354, 8 p.","ipdsId":"IP-163417","costCenters":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":466777,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fclim.2024.1393354","text":"Publisher Index Page"},{"id":464596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2024-11-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Ciocco, Tony W. 0000-0002-5849-888X","orcid":"https://orcid.org/0000-0002-5849-888X","contributorId":306365,"corporation":false,"usgs":true,"family":"Ciocco","given":"Tony","email":"","middleInitial":"W.","affiliations":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":919586,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":919587,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tangen, Stefan Gabriel 0000-0002-6628-6094","orcid":"https://orcid.org/0000-0002-6628-6094","contributorId":346572,"corporation":false,"usgs":true,"family":"Tangen","given":"Stefan","email":"","middleInitial":"Gabriel","affiliations":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":919588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crausbay, Shelley D. 0000-0003-3028-801X","orcid":"https://orcid.org/0000-0003-3028-801X","contributorId":346573,"corporation":false,"usgs":false,"family":"Crausbay","given":"Shelley","email":"","middleInitial":"D.","affiliations":[{"id":82887,"text":"U.S.D.A. Forest Service, Office of Sustainability and Climate","active":true,"usgs":false}],"preferred":false,"id":919589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oldfather, Meagan Ford 0000-0003-3256-4786","orcid":"https://orcid.org/0000-0003-3256-4786","contributorId":331767,"corporation":false,"usgs":true,"family":"Oldfather","given":"Meagan","email":"","middleInitial":"Ford","affiliations":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":919590,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bamzai-Dodson, Aparna 0000-0002-2444-9051","orcid":"https://orcid.org/0000-0002-2444-9051","contributorId":303866,"corporation":false,"usgs":true,"family":"Bamzai-Dodson","given":"Aparna","email":"","affiliations":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":919591,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260482,"text":"sir20245095 - 2024 - Real-time pier scour monitoring and observations at three scour-critical sites in Idaho, water years 2020–22","interactions":[],"lastModifiedDate":"2025-12-22T21:36:02.002108","indexId":"sir20245095","displayToPublicDate":"2024-11-06T13:33:30","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5095","displayTitle":"Real-Time Pier Scour Monitoring and Observations at Three Scour-Critical Sites in Idaho, Water Years 2020–22","title":"Real-time pier scour monitoring and observations at three scour-critical sites in Idaho, water years 2020–22","docAbstract":"To observe real-time pier scour at three scour-critical sites in Idaho, the U.S. Geological Survey, in cooperation with Idaho Transportation Department, installed and operated fixed real-time (15-minute interval) bed elevation scour sonar sensors at three bridge locations associated with U.S. Geological Survey streamflow gaging stations for water years 2020 through 2022. Daily mean and peak streamflow conditions during the 3-year study were at or below average except for the peak flow in 2022. Each of the three sites included in the study had a coarse bed with an armored channel. Observed pier scour at each of the three sites was less than 20 percent than the stated minimum depth to the pier pile tip. The below average daily mean and peak streamflow during the study period may have resulted in below average scour.
Observed pier scour data during spring runoff (water years 2020–22) were compared to both Coarse Bed and Hydraulic Engineering Circular 18 (HEC-18) general pier scour design equation estimates to better understand how the observed pier scour data compared to design pier scour equation estimates during the same observational periods. For the 3-year study period, the Coarse Bed design equation generally overpredicted scour by about 2.5 times less than the HEC-18 general pier scour equation. The risk associated with each design equation was summarized using a reliability index to describe how each prediction might be expected to reliably overestimate scour depth. Overall, the Coarse Bed design scour equation provided more reasonable scour depth estimates than the HEC-18 general pier scour equation but with more risk to underestimating scour depth. Because these data are limited (3 sites, 3 years, and during average streamflow conditions), further research is needed to compare observed scour data to estimates predicted by the Coarse Bed design equation and other design equations.
This study demonstrated that real-time pier scour monitoring is a useful method and countermeasure at critical bridge sites. A recently developed rapid deployment real-time pier scour monitoring method may be a useful method to consider for future studies. Real-time monitoring at scour critical sites may be a useful tool to confirm previous scour evaluation estimates where site inspection scour observations conflict with the scour evaluation estimates. Considering alternative scour monitoring and evaluation methods, including the rapid estimation method, and updating pier scour calculations using the most recent coarse-bed pier scour equation may offer a more cost-effective solution to identifying and updating scour critical coding for bridges in Idaho. For scour critical bridge sites, the real-time pier scour monitoring methods used for this study provided an effective real-time local pier scour monitoring countermeasure.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245095","collaboration":"Prepared in cooperation with the Idaho Transportation Department","usgsCitation":"Fosness, R.L., and Schauer, P.V., 2024, Real-time pier scour monitoring and observations at three scour-critical sites in Idaho, water years 2020–22: U.S. Geological Survey Scientific Investigations Report 2024–5095, 23 p., https://doi.org/10.3133/sir20245095.","productDescription":"Report; vii, 23 p.p.; Data Release","onlineOnly":"Y","ipdsId":"IP-128131","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":497921,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117770.htm","linkFileType":{"id":5,"text":"html"}},{"id":463605,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5095/images"},{"id":463604,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90332LD","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydraulic assessment summary at selected real-time pier scour monitoring sites in Idaho, 2020–2022"},{"id":463603,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245095/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5095"},{"id":463602,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5095/sir20245095.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5095"},{"id":463601,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5095/sir20245095.jpg"},{"id":463606,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5095/sir20245095.XML"}],"country":"United States","state":"Idaho","otherGeospatial":"Boise River, Payette River, St. Joe River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.19181903119929,\n 47.27634704869766\n ],\n [\n -116.19181903119929,\n 47.2713170479783\n ],\n [\n -116.18399082696462,\n 47.2713170479783\n ],\n [\n -116.18399082696462,\n 47.27634704869766\n ],\n [\n -116.19181903119929,\n 47.27634704869766\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.98113730832642,\n 43.79475425455084\n ],\n [\n -116.98113730832642,\n 43.738517550064955\n ],\n [\n -116.90322501094207,\n 43.738517550064955\n ],\n [\n -116.90322501094207,\n 43.79475425455084\n ],\n [\n -116.98113730832642,\n 43.79475425455084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.64141007600492,\n 43.905644822917225\n ],\n [\n -116.64141007600492,\n 43.88897692930604\n ],\n [\n -116.61377308255302,\n 43.88897692930604\n ],\n [\n -116.61377308255302,\n 43.905644822917225\n ],\n [\n -116.64141007600492,\n 43.905644822917225\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4250
Temporally variable climates are expected to drive the evolution of thermal physiological traits that enable performance across a wider range of temperatures (i.e. climate variability hypothesis, CVH). Spatial thermal variability, however, may mediate this relationship by providing ectotherms with the opportunity to behaviourally select preferred temperatures (i.e. the Bogert effect). These antagonistic forces on thermal physiological traits may explain the mixed support for the CVH within species despite strong support among species at larger geographical scales. Here, we test the CVH as it relates to plasticity in physiological upper thermal limits (critical thermal maximum—CTmax) among populations of coastal tailed frogs (Ascaphus truei). We targeted populations that inhabit spatially homogeneous environments, reducing the potentially confounding effects of behavioural thermoregulation. We found that populations experiencing greater temporal thermal variability exhibited greater plasticity in CTmax, supporting the CVH. Interestingly, we identified only one site with spatial temperature variability and tadpoles from this site demonstrated greater plasticity than expected, suggesting the opportunity for behavioural thermoregulation can reduce support for the CVH. Overall, our results demonstrate one role of climate variability in shaping thermal plasticity among populations and provide a baseline understanding of the impact of the CVH in spatially homogeneous thermal landscapes.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rspb.2024.1628","usgsCitation":"Cicchino, A.S., Ghalambor, C.K., Forester, B.R., Dunham, J., and Funk, W., 2024, Greater plasticity in CTmax with increased climate variability among populations of tailed frogs: Proceedings of the Royal Society B, v. 291, no. 2034, 20241628, https://doi.org/10.1098/rspb.2024.1628.","productDescription":"20241628","ipdsId":"IP-169449","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":497360,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11537758/","text":"External Repository"},{"id":464535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"291","issue":"2034","noUsgsAuthors":false,"publicationDate":"2024-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Cicchino, Amanda S. 0000-0003-0170-829X","orcid":"https://orcid.org/0000-0003-0170-829X","contributorId":306171,"corporation":false,"usgs":false,"family":"Cicchino","given":"Amanda","email":"","middleInitial":"S.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":919451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ghalambor, Cameron K.","contributorId":93722,"corporation":false,"usgs":false,"family":"Ghalambor","given":"Cameron","email":"","middleInitial":"K.","affiliations":[{"id":6998,"text":"Department of Biology, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":919452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forester, Brenna R.","contributorId":261215,"corporation":false,"usgs":false,"family":"Forester","given":"Brenna","email":"","middleInitial":"R.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":919453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":919454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Funk, W. Chris 0000-0002-9254-6718","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":189580,"corporation":false,"usgs":false,"family":"Funk","given":"W. Chris","affiliations":[],"preferred":false,"id":919455,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260413,"text":"sir20245035 - 2024 - Potential corrosivity of untreated groundwater in Louisiana","interactions":[],"lastModifiedDate":"2025-12-22T21:37:33.869696","indexId":"sir20245035","displayToPublicDate":"2024-11-06T10:30:11","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5035","displayTitle":"Potential Corrosivity of Untreated Groundwater in Louisiana","title":"Potential corrosivity of untreated groundwater in Louisiana","docAbstract":"Corrosive groundwater can cause lead, copper, and other metals to leach from pipes and plumbing fixtures in water distribution systems. Metals, if ingested, could lead to serious health implications to the nearly 2.9 million people in Louisiana who obtain their drinking water from groundwater sources. Four indices—the Langelier Saturation Index (LSI), Ryznar Stability Index (RSI), Puckorius Scaling Index (PSI), and the Potential to Promote Galvanic Corrosion (PPGC)—in addition to an analysis which normalized the results from the existing indices, the Combined Index (CI), were used to assess the corrosivity of groundwater in Louisiana and identify areas within eight major aquifers and aquifer systems with moderate to high corrosivity potential. The purpose of this study is to provide State and local governments, public water system managers, and the nearly 500,000 private well owners in Louisiana with information needed to manage drinking-water supplies and mitigate potential health risks related to leaching of metals from water pipes and fixtures.
The average scores of untreated groundwater samples from approximately 375 wells by index are as follows: LSI, −1.28; RSI, 9.78; PSI, 9.34; and CI, 4.14. The PPGC does not produce a numerical score, but the total percentage of class counts can be used to assign a classification; overall, samples in Louisiana were classified as significant concern. The percentages of groundwater samples from wells classified as potentially corrosive, by index, are as follows: LSI, 53 percent; RSI, 94 percent; PSI, 81 percent; PPGC, 98 percent; and CI, 81 percent. The percentages of samples classified as indeterminate, by index, are as follows: LSI, 46 percent; RSI, 5 percent; PSI, 12 percent; PPGC, 0 percent; and CI, 18 percent.
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"nation\":\"USA \"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
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","tableOfContents":"Rocks dredged from water depths of 1,605, 2,500, 3,300, and 3,400 m in the Arctic Ocean included Paleozoic continental rocks pervasively mineralized during the Neogene by hydrothermal Fe and Mn oxides. Samples were recovered in three dredge hauls from the Chukchi Borderland and one from Mendeleev Ridge north of Alaska and eastern Siberia, respectively. Many of the rocks were so pervasively altered that the protolith could not be identified, while others had volcanic, plutonic, and metamorphic protoliths. The mineralized rocks were cemented and partly to wholly replaced by the hydrothermal oxides. The Amerasia Basin, where the Chukchi Borderland and Mendeleev Ridge occur, supports a series of faults and fractures that serve as major zones of crustal weakness. We propose that the stratabound hydrothermal deposits formed through the flux of hydrothermal fluids along Paleozoic and Mesozoic faults related to block faulting along a rifted margin during minor episodes of Neogene tectonism and were later exposed at the seafloor through slumping or other gravity processes. Tectonically driven hydrothermal circulation most likely facilitated the pervasive mineralization along fault surfaces via frictional heating, hydrofracturing brecciation, and low- to moderate temperature Fe- and Mn-rich hydrothermal fluids, which mineralized the crushed, altered, and brecciated rocks.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023GC010996","usgsCitation":"Hein, J.R., Mizell, K., and Gartman, A., 2024, Neogene hydrothermal Fe- and Mn-oxide mineralization of Paleozoic continental rocks, Amerasia Basin, Arctic Ocean: Geochemistry, Geophysics, Geosystems, v. 25, no. 11, e2023GC010996, 27 p., https://doi.org/10.1029/2023GC010996.","productDescription":"e2023GC010996, 27 p.","ipdsId":"IP-167891","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466778,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023gc010996","text":"Publisher Index Page"},{"id":463785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Amerasia basin, Arctic Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -150,\n 72\n ],\n [\n -179.9,\n 74.5\n ],\n [\n -179.9,\n 85\n ],\n [\n -137.09374278427933,\n 80.73796302105899\n ],\n [\n -115,\n 73\n ],\n [\n -150,\n 72\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 179.9,\n 85\n ],\n [\n 165,\n 85\n ],\n [\n 172,\n 74.5\n ],\n [\n 179.9,\n 74.5\n ],\n [\n 179.9,\n 85\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"11","noUsgsAuthors":false,"publicationDate":"2024-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":918141,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mizell, Kira 0000-0002-5066-787X kmizell@usgs.gov","orcid":"https://orcid.org/0000-0002-5066-787X","contributorId":4914,"corporation":false,"usgs":true,"family":"Mizell","given":"Kira","email":"kmizell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":918142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gartman, Amy 0000-0001-9307-3062 agartman@usgs.gov","orcid":"https://orcid.org/0000-0001-9307-3062","contributorId":177057,"corporation":false,"usgs":true,"family":"Gartman","given":"Amy","email":"agartman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":918143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263425,"text":"70263425 - 2024 - Assessing and implementing the concept of Blue Economy in Laurentian Great Lakes fisheries: Lessons from coupled human and natural systems","interactions":[],"lastModifiedDate":"2025-02-11T15:30:07.537954","indexId":"70263425","displayToPublicDate":"2024-11-06T08:22:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":865,"text":"Aquatic Ecosystem Health & Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessing and implementing the concept of Blue Economy in Laurentian Great Lakes fisheries: Lessons from coupled human and natural systems","docAbstract":"Inland fisheries often receive little to no attention in global discussions about sustainable development. The consequences of overlooking inland fisheries in sustainability dialogues are increasingly problematic as fisheries stressors (e.g., overharvest, species invasion, climate change, habitat modification) intensify. Elevating the global profile of inland fisheries requires an approach for quantifying and clearly conveying the ecological, economic, and societal values of these systems. One such approach involves the Blue Economy, a multifaceted concept initially used to describe the intersection of marine conservation and sustainable use of marine resources for economic growth. Although conceptually powerful, the Blue Economy has rarely been applied to inland waters and fisheries. To address this knowledge gap, we conceptualized Laurentian Great Lakes fisheries from a Blue Economy perspective. In particular, we evaluated the utility of the coupled human and natural systems (CHANS) framework for characterizing the ecological, economic, and societal values of Laurentian Great Lakes fisheries and associated contributions to the Blue Economy (e.g., human livelihoods, food security, recreation, conservation, economic prosperity). There are numerous opportunities to leverage CHANS methods (e.g., metacoupling, telecoupling) and associated mathematical models to advance fisheries science, inform fisheries management, and ultimately move toward a Blue Economy in the Laurentian Great Lakes. To that end, we demonstrated applications of CHANS methods, discussed strategies for communicating with stakeholders, and provided insights for navigating challenges to developing a Blue Economy in the Laurentian Great Lakes—a model that could be used in the African Great Lakes and other large ecosystems in the world.","language":"English","publisher":"BioOne","doi":"10.14321/aehm.027.02.74","usgsCitation":"Carlson, A.K., Leonard, N., Munawar, M., and Taylor, W., 2024, Assessing and implementing the concept of Blue Economy in Laurentian Great Lakes fisheries: Lessons from coupled human and natural systems: Aquatic Ecosystem Health & Management, v. 27, no. 2, p. 74-84, https://doi.org/10.14321/aehm.027.02.74.","productDescription":"11 p.","startPage":"74","endPage":"84","ipdsId":"IP-154893","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":481930,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Laurentian Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.35414421298296,\n 47.69798628255907\n ],\n [\n -92.55498641328694,\n 46.29425302711437\n ],\n [\n -86.95944652656331,\n 46.00505185703939\n ],\n [\n -88.62282303782777,\n 43.92021164632037\n ],\n [\n -87.50058525109819,\n 41.25347232284972\n ],\n [\n -85.72809349640711,\n 42.11694323111757\n ],\n [\n -85.91733849617773,\n 43.493974004776575\n ],\n [\n -84.89672932891068,\n 44.873597615031386\n ],\n [\n -83.29102906108528,\n 43.6549891230233\n ],\n [\n -83.78159647699495,\n 41.31847374004327\n ],\n [\n -79.95408136104199,\n 41.39215071916226\n ],\n [\n -75.87519895574565,\n 43.702579861752696\n ],\n [\n -79.58470723400637,\n 45.3214766230865\n ],\n [\n -84.23758896005683,\n 48.14783853442674\n ],\n [\n -88.84558873081599,\n 49.05585075889549\n ],\n [\n -91.35414421298296,\n 47.69798628255907\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-04-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Andrew Kenneth 0000-0002-6681-0853","orcid":"https://orcid.org/0000-0002-6681-0853","contributorId":340581,"corporation":false,"usgs":true,"family":"Carlson","given":"Andrew","email":"","middleInitial":"Kenneth","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":926955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leonard, Nancy J.","contributorId":350769,"corporation":false,"usgs":false,"family":"Leonard","given":"Nancy J.","affiliations":[{"id":20304,"text":"Pacific States Marine Fisheries Commission","active":true,"usgs":false}],"preferred":false,"id":926956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munawar, Mohiuddin","contributorId":350770,"corporation":false,"usgs":false,"family":"Munawar","given":"Mohiuddin","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":926957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, William W.","contributorId":350772,"corporation":false,"usgs":false,"family":"Taylor","given":"William W.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":926958,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70261286,"text":"70261286 - 2024 - GNSS reflectometry from low-cost sensors for continuous in situ contemporaneous glacier mass balance and flux divergence","interactions":[],"lastModifiedDate":"2024-12-26T16:59:57.220714","indexId":"70261286","displayToPublicDate":"2024-11-06T08:03:04","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2328,"text":"Journal of Glaciology","active":true,"publicationSubtype":{"id":10}},"title":"GNSS reflectometry from low-cost sensors for continuous in situ contemporaneous glacier mass balance and flux divergence","docAbstract":"Recent advances in remote sensing have produced global glacier surface elevation change data. Parsing these elevation change signals into contributions from the climate (i.e. climatic mass balance) and glacier dynamics (i.e. flux divergence) is critical to enhance our process-based understanding of glacier change. In this study, we evaluate three approaches for direct, continuous measurements of the climatic mass balance, flux divergence, and elevation change at a site on Gulkana Glacier in Alaska using low-cost GNSS sensors, GNSS interferometric reflectometry (GNSS-IR), banded ablation stakes with time-lapse cameras, and combinations thereof. Cumulative climatic mass balance over the season was 4.85 m and the three approaches were within 0.08 m through early July before the snowpack melted, and within 0.28 m through mid-August. The flux divergence increased from 0.52 ± 0.03 cm d-1 before June 3 to roughly 0.73 cm d-1 after June 27. We demonstrate a single GNSS system fixed atop an ablation stake can measure contemporaneous climatic mass balance, flux divergence, and elevation change based on the antenna’s position and GNSS-IR techniques. The ability of these systems to measure glacier mass balance and flux divergence offers unique opportunities for year-round observations on mountain glaciers in the future.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/jog.2024.54","usgsCitation":"Wells, A., Rounce, D.R., Sass, L., Florentine, C., Garbo, A., Baker, E., and McNeil, C., 2024, GNSS reflectometry from low-cost sensors for continuous in situ contemporaneous glacier mass balance and flux divergence: Journal of Glaciology, v. 70, e5, 12 p., https://doi.org/10.1017/jog.2024.54.","productDescription":"e5, 12 p.","ipdsId":"IP-164695","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":466780,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/jog.2024.54","text":"Publisher Index Page"},{"id":464746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulkana Glacier","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -145.68362267602475,\n 63.35411541798791\n ],\n [\n -145.68362267602475,\n 63.196253345505795\n ],\n [\n -145.0204214654105,\n 63.196253345505795\n ],\n [\n -145.0204214654105,\n 63.35411541798791\n ],\n [\n -145.68362267602475,\n 63.35411541798791\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"70","noUsgsAuthors":false,"publicationDate":"2024-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Albin","contributorId":346929,"corporation":false,"usgs":false,"family":"Wells","given":"Albin","email":"","affiliations":[{"id":12943,"text":"Carnegie Mellon University","active":true,"usgs":false}],"preferred":false,"id":920224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounce, David R.","contributorId":290361,"corporation":false,"usgs":false,"family":"Rounce","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":920225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":920226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Florentine, Caitlyn 0000-0002-7028-0963","orcid":"https://orcid.org/0000-0002-7028-0963","contributorId":205964,"corporation":false,"usgs":true,"family":"Florentine","given":"Caitlyn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":920227,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garbo, Adam","contributorId":346930,"corporation":false,"usgs":false,"family":"Garbo","given":"Adam","email":"","affiliations":[{"id":39169,"text":"University of Ottawa","active":true,"usgs":false}],"preferred":false,"id":920228,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baker, Emily 0000-0002-0938-3496 ehbaker@usgs.gov","orcid":"https://orcid.org/0000-0002-0938-3496","contributorId":200570,"corporation":false,"usgs":true,"family":"Baker","given":"Emily","email":"ehbaker@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":920229,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":920230,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70261558,"text":"70261558 - 2024 - Insights on arc magmatic systems drawn from natural melt inclusions and crystallization experiments at PH2O=800 MPa under oxidizing conditions","interactions":[],"lastModifiedDate":"2024-12-16T14:12:30.156142","indexId":"70261558","displayToPublicDate":"2024-11-06T06:57:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Insights on arc magmatic systems drawn from natural melt inclusions and crystallization experiments at PH2O=800 MPa under oxidizing conditions","title":"Insights on arc magmatic systems drawn from natural melt inclusions and crystallization experiments at PH2O=800 MPa under oxidizing conditions","docAbstract":"Whole rock compositions at Buldir Volcano, western Aleutian arc, record a strong, continuous trend of iron depletion with decreasing MgO, classically interpreted as a calc-alkaline liquid line of descent. In contrast, olivine-hosted melt inclusions have higher total iron (FeO*) than whole rocks and show little change in FeO* with decreasing MgO. To investigate this discrepancy and determine the conditions required for strong iron depletion, we conducted oxygen fugacity (ƒO2) buffered, water-saturated crystallization experiments at 800 MPa and ƒO2 = QFM + 1.6 ± 0.4 (1σ) (where QFM refers to the quartz-fayalite-magnetite buffer) on a high-Al, basaltic starting material modeled after a Buldir lava. Experimental conditions were informed by olivine-hosted melt inclusions that record minimum entrapment pressures as high as 570 MPa, >6 wt % H2O, and ƒO2 of QFM + 1.4 (±0.2), making Buldir one of the most oxidized and wettest arc volcanoes documented globally. The experiments produce melts with Si-enrichment and Fe-depletion signatures characteristic of evolved, calc-alkaline magmas at the lowest MgO, although FeO* remains roughly constant over most of the experimental temperature range. Experiments saturate CrAl-spinel and olivine at 1160°C, followed by clinopyroxene and Al-spinel at 1085°C, hornblende at 1060°C, and, finally, plagioclase and magnetite between 1040°C and 960°C. Hornblende crystallization, not magnetite, generates the largest increase in SiO2 and largest decrease in FeO* in coexisting melts. Compositions of melt inclusions are consistent with experimental melts and reflect crystallization of a basaltic parent magma at high PH2O. In contrast, the whole rock compositional trends are influenced by magma mixing and phenocryst redistribution and accumulation. The crystallization experiments and natural liquids (melt inclusions and groundmass glass) from Buldir suggest that for an oxidized, hydrous primary basalt starting composition, significant Fe depletion from the melt will not occur until intermediate to late stages of magma crystallization (< ~4.5 wt % MgO). We conclude that the Buldir whole rock trend cannot be reproduced by crystallization at arc-relevant oxygen fugacities and is not a true liquid line of descent, warranting caution when interpreting volcanic trends globally.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/petrology/egae117","usgsCitation":"Andrys, J.L., Cottrell, E., Kelley, K., Waters, L.E., and Coombs, M.L., 2024, Insights on arc magmatic systems drawn from natural melt inclusions and crystallization experiments at PH2O=800 MPa under oxidizing conditions: Journal of Petrology, v. 65, no. 12, egae117, 23 p., https://doi.org/10.1093/petrology/egae117.","productDescription":"egae117, 23 p.","ipdsId":"IP-166029","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":465141,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"12","noUsgsAuthors":false,"publicationDate":"2024-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Andrys, Janine L.","contributorId":347200,"corporation":false,"usgs":false,"family":"Andrys","given":"Janine","email":"","middleInitial":"L.","affiliations":[{"id":52668,"text":"Boise State","active":true,"usgs":false}],"preferred":false,"id":921044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cottrell, Elizabeth","contributorId":347203,"corporation":false,"usgs":false,"family":"Cottrell","given":"Elizabeth","affiliations":[{"id":36606,"text":"Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":921045,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kelley, Katherine A.","contributorId":347206,"corporation":false,"usgs":false,"family":"Kelley","given":"Katherine A.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":921046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waters, Laura E.","contributorId":347209,"corporation":false,"usgs":false,"family":"Waters","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":34868,"text":"New Mexico Institute of Mining and Technology","active":true,"usgs":false}],"preferred":false,"id":921047,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":921048,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}