The monarch butterfly is a flagship species and pollinator whose populations have declined by 85% in the recent two decades. Their largest population overwinters in Mexico, then disperses across eastern North America during March to August. During September-December, they return south using two flyways, one that spans the central United States and another that follows the Atlantic coast. Migrating monarchs fly diurnally and roost in groups nocturnally. We sought to determine the criteria this species uses to select roost sites, and the landscape context where those sites are found. We developed species distribution models of the landscape context of Atlantic flyway roost sites via citizen scientist observations and environmental variables that affect monarchs in the adult stage prior to migration, using two algorithms (Maximum Entropy and Genetic Algorithm for Ruleset Prediction). We developed two model validation methods: a citizen scientist smartphone application and peer-informed comparisons with aerial imagery. Proximity to surface water, elevation, and vegetative cover were the most important criteria for monarch roost site selection. Our model predicted 2.6 million ha (2.9% of the study area) of suitable roosting habitat in the Atlantic flyway, with the greatest availability along the Atlantic coastal plain and Appalachian Mountain ridges. Conservation of this species is difficult, as monarchs range over both large areas and various habitat types, and most current monarch research and conservation efforts are focused on the breeding and overwintering periods. These models can serve to help prioritize surveys of roosting sites and conservation efforts during the monarchs’ fall migration.
","language":"English","publisher":"Springer","doi":"10.1007/s10905-023-09844-5","usgsCitation":"Boxler, B., Loftin, C., and Sutton, W.B., 2024, Monarch butterfly (Danaus plexippus) roost site-selection criteria and locations east of the Appalachian Mountains, U.S.A.: Journal of Insect Behavior, v. 37, p. 22-48, https://doi.org/10.1007/s10905-023-09844-5.","productDescription":"27 p.","startPage":"22","endPage":"48","ipdsId":"IP-122336","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationDate":"2024-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Boxler, Brandon M.","contributorId":349226,"corporation":false,"usgs":false,"family":"Boxler","given":"Brandon M.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":924154,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":924153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutton, William B.","contributorId":88256,"corporation":false,"usgs":true,"family":"Sutton","given":"William","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":924155,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70263320,"text":"70263320 - 2024 - Monarch butterfly (Danaus plexippus) roost site-selection criteria and locations east of the Appalachian Mountains, U.S.A.","interactions":[],"lastModifiedDate":"2025-02-06T16:49:39.815475","indexId":"70263320","displayToPublicDate":"2024-02-23T10:46:37","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":19915,"text":"Journal of Insect Behavior","active":true,"publicationSubtype":{"id":10}},"title":"Monarch butterfly (Danaus plexippus) roost site-selection criteria and locations east of the Appalachian Mountains, U.S.A.","docAbstract":"The monarch butterfly is a flagship species and pollinator whose populations have declined by 85% in the recent two decades. Their largest population overwinters in Mexico, then disperses across eastern North America during March to August. During September-December, they return south using two flyways, one that spans the central United States and another that follows the Atlantic coast. Migrating monarchs fly diurnally and roost in groups nocturnally. We sought to determine the criteria this species uses to select roost sites, and the landscape context where those sites are found. We developed species distribution models of the landscape context of Atlantic flyway roost sites via citizen scientist observations and environmental variables that affect monarchs in the adult stage prior to migration, using two algorithms (Maximum Entropy and Genetic Algorithm for Ruleset Prediction). We developed two model validation methods: a citizen scientist smartphone application and peer-informed comparisons with aerial imagery. Proximity to surface water, elevation, and vegetative cover were the most important criteria for monarch roost site selection. Our model predicted 2.6 million ha (2.9% of the study area) of suitable roosting habitat in the Atlantic flyway, with the greatest availability along the Atlantic coastal plain and Appalachian Mountain ridges. Conservation of this species is difficult, as monarchs range over both large areas and various habitat types, and most current monarch research and conservation efforts are focused on the breeding and overwintering periods. These models can serve to help prioritize surveys of roosting sites and conservation efforts during the monarchs’ fall migration.
","language":"English","publisher":"Springer","doi":"10.1007/s10905-023-09844-5","usgsCitation":"Boxler, B., Loftin, C., and Sutton, W.B., 2024, Monarch butterfly (Danaus plexippus) roost site-selection criteria and locations east of the Appalachian Mountains, U.S.A.: Journal of Insect Behavior, v. 37, p. 22-48, https://doi.org/10.1007/s10905-023-09844-5.","productDescription":"27 p.","startPage":"22","endPage":"48","ipdsId":"IP-123861","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationDate":"2024-02-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Boxler, Brandon M.","contributorId":349226,"corporation":false,"usgs":false,"family":"Boxler","given":"Brandon M.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":926324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":926323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutton, William B.","contributorId":88256,"corporation":false,"usgs":true,"family":"Sutton","given":"William","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":926325,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70256504,"text":"70256504 - 2024 - Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA","interactions":[],"lastModifiedDate":"2024-09-09T17:01:27.882316","indexId":"70256504","displayToPublicDate":"2024-02-23T06:11:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA","docAbstract":"Grass carp (Ctenopharyngodon idella), an invasive cyprinid within the Laurentian Great Lakes, is naturally reproducing in several Lake Erie tributaries, which has raised concerns of the species’ spread throughout Lake Erie and the other Great Lakes. Knowledge of the recent invasion extent outside of the western basin of Lake Erie, particularly in eastern tributaries and nearshore waters, is limited. Understanding the invasion extent would improve the efficacy of ongoing coordinated multi-agency control efforts. Molecular tools, such as environmental DNA (eDNA), have shown promise for early detection of aquatic invasive species. In this study, water samples (N = 476) were collected for grass carp eDNA monthly between May and November in 2018 and 2019, at three sites in the Michigan waters of Lake Erie and the Detroit River. We fit Bayesian multi-scale occupancy models to determine differences in eDNA capture and detection probability among grass carp qPCR assays, sampling sites, and across time. To determine whether grass carp were physically present, and to validate eDNA samples, we quantified recent grass carp presence in sampled areas using an existing acoustic telemetry and field sampling framework. Our results indicate that grass carp eDNA capture probability differed among sites, but there was no difference among months. Positive grass carp eDNA detections were observed across multiple months at each site, with 69% of site-specific sampling events testing positive for grass carp eDNA on at least one assay and replicate. The majority (65%) of weeks where positive eDNA sampling detections occurred also concurrently had one or more grass carp detected via acoustic telemetry 1–6 days prior. Our results highlight the potential utility of using eDNA to monitor the invasion extent of grass carp within the nearshore waters of Lake Erie. However, further evaluation of the factors that influence grass carp eDNA characteristics among sites within Lake Erie are needed to determine its efficacy for surveillance protocols by natural resource management agencies.
","language":"English","publisher":"Reabic","doi":"10.3391/mbi.2024.15.1.04","usgsCitation":"Bopp, J., Nathan, L.R., Robinson, J.D., Kanefsky, J., Scribner, K., Herbst, S., and Robinson, K.F., 2024, Assessing grass carp (Ctenopharyngodon idella) occupancy and detection probability within Lake Erie from environmental DNA: Management of Biological Invasions, v. 15, no. 1, p. 51-72, https://doi.org/10.3391/mbi.2024.15.1.04.","productDescription":"22 p.","startPage":"51","endPage":"72","ipdsId":"IP-153893","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":440334,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2024.15.1.04","text":"Publisher Index Page"},{"id":433635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.49486489590893,\n 42.187220486618514\n ],\n [\n -83.49486489590893,\n 41.38443575807409\n ],\n [\n -82.35228677090853,\n 41.38443575807409\n ],\n [\n -82.35228677090853,\n 42.187220486618514\n ],\n [\n -83.49486489590893,\n 42.187220486618514\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bopp, Justin","contributorId":340933,"corporation":false,"usgs":false,"family":"Bopp","given":"Justin","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907700,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nathan, Lucas R.","contributorId":340934,"corporation":false,"usgs":false,"family":"Nathan","given":"Lucas","email":"","middleInitial":"R.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907701,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robinson, John D.","contributorId":340936,"corporation":false,"usgs":false,"family":"Robinson","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907702,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kanefsky, Jeanette","contributorId":340938,"corporation":false,"usgs":false,"family":"Kanefsky","given":"Jeanette","email":"","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907703,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scribner, Kim T.","contributorId":340939,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim T.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":907704,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herbst, Seth","contributorId":340940,"corporation":false,"usgs":false,"family":"Herbst","given":"Seth","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":907705,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Robinson, Kelly Filer 0000-0001-8109-9492","orcid":"https://orcid.org/0000-0001-8109-9492","contributorId":340631,"corporation":false,"usgs":true,"family":"Robinson","given":"Kelly","email":"","middleInitial":"Filer","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907706,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70264388,"text":"70264388 - 2024 - Ensemble2: Scenarios ensembling for communication and performance analysis","interactions":[],"lastModifiedDate":"2025-03-14T14:40:51.762475","indexId":"70264388","displayToPublicDate":"2024-02-22T09:37:18","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5213,"text":"Epidemics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Ensemble2: Scenarios ensembling for communication and performance analysis","title":"Ensemble2: Scenarios ensembling for communication and performance analysis","docAbstract":"Throughout the COVID-19 pandemic, scenario modeling played a crucial role in shaping the decision-making process of public health policies. Unlike forecasts, scenario projections rely on specific assumptions about the future that consider different plausible states-of-the-world that may or may not be realized and that depend on policy interventions, unpredictable changes in the epidemic outlook, etc. As a consequence, long-term scenario projections require different evaluation criteria than the ones used for traditional short-term epidemic forecasts. Here, we propose a novel ensemble procedure for assessing pandemic scenario projections using the results of the Scenario Modeling Hub (SMH) for COVID-19 in the United States (US). By defining a “scenario ensemble” for each model and the ensemble of models, termed “Ensemble
Landscape context structures fish abundance and dynamics, and understanding trends in fish abundance across the landscape is often prerequisite for effective conservation. In this study, we evaluated the status and trends of Brook Trout Salvelinus fontinalis in Shenandoah National Park to understand how these are structured across bedrock geology, elevation, and stream size.
We used long-term monitoring data from 94 sites in Shenandoah National Park to evaluate trends in Brook Trout abundance over a 27-year period (1996–2022) and assess the importance of local environmental covariates using a hierarchical Bayesian N-mixture model based on depletion sampling. Focal covariates were chosen for their demonstrated importance in structuring fish populations in Shenandoah National Park and elsewhere. Bedrock geology controls sensitivity to acid deposition, watershed area is related to stream habitat features such as complexity and flow variability, and elevation creates gradients in temperature.
Models revealed significant decreases in adult Brook Trout abundance over time (95% credible intervals < 0) for 31 of 94 sites (33%), and at least three sites exhibited apparent extirpations over the study period. Estimated Brook Trout abundance declined by 50% or more in approximately 70% of streams across the park over the study period. Sites with the warmest water temperatures exhibited the fastest declines in abundance. However, large watersheds on poorly buffered bedrock exhibited significant gains in abundance over time, suggesting some recovery from acid deposition due to improvements in air quality.
Our analysis revealed large and divergent changes in Brook Trout abundance over recent decades and suggests the importance of local water temperature and acid sensitivity as probable causal mechanisms. These results highlight the importance of considering local factors when evaluating long-term trends in stream fish populations. Results of this study can assist the development of targeted conservation actions within Shenandoah National Park and elsewhere.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10460","usgsCitation":"Childress, E., Demarest, D., Wofford, J.E., Hitt, N.P., and Letcher, B., 2024, Strong variation in Brook Trout trends across geology, elevation, and stream size in Shenandoah National Park: Transactions of the American Fisheries Society, v. 153, no. 2, p. 250-263, https://doi.org/10.1002/tafs.10460.","productDescription":"14 p.","startPage":"250","endPage":"263","ipdsId":"IP-150752","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499264,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10460","text":"Publisher Index Page"},{"id":426485,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.5730072818129,\n 37.84539890269417\n ],\n [\n -77.41219734606564,\n 37.84539890269417\n ],\n [\n -77.41219734606564,\n 39.434228970300325\n ],\n [\n -79.5730072818129,\n 39.434228970300325\n ],\n [\n -79.5730072818129,\n 37.84539890269417\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"153","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-02-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Childress, Evan S.","contributorId":214287,"corporation":false,"usgs":false,"family":"Childress","given":"Evan S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":896226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demarest, David E","contributorId":334666,"corporation":false,"usgs":false,"family":"Demarest","given":"David E","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":896227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wofford, John E.B.","contributorId":334667,"corporation":false,"usgs":false,"family":"Wofford","given":"John","email":"","middleInitial":"E.B.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":896228,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":238185,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"","middleInitial":"P.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":896229,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":896230,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70252746,"text":"70252746 - 2024 - Nitrate exposure from drinking water and dietary sources among Iowa farmers using private wells","interactions":[],"lastModifiedDate":"2024-04-04T14:33:34.378743","indexId":"70252746","displayToPublicDate":"2024-02-16T09:16:23","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17043,"text":"Science of the Total Envionrment","active":true,"publicationSubtype":{"id":10}},"title":"Nitrate exposure from drinking water and dietary sources among Iowa farmers using private wells","docAbstract":"Nitrate levels are increasing in water resources across the United States and nitrate ingestion from drinking water has been associated with adverse health risks in epidemiologic studies at levels below the maximum contaminant level (MCL). In contrast, dietary nitrate ingestion has generally been associated with beneficial health effects. Few studies have characterized the contribution of both drinking water and dietary sources to nitrate exposure. The Agricultural Health Study is a prospective cohort of farmers and their spouses in Iowa and North Carolina. In 2018–2019, we assessed nitrate exposure for 47 farmers who used private wells for their drinking water and lived in 8 eastern Iowa counties where groundwater is vulnerable to nitrate contamination. Drinking water and dietary intakes were estimated using the National Cancer Institute Automated Self-Administered 24-Hour Dietary Assessment tool. We measured nitrate in tap water and estimated dietary nitrate from a database of food concentrations. Urinary nitrate was measured in first morning void samples in 2018–19 and in archived samples from 2010 to 2017 (minimum time between samples: 2 years; median: 7 years). We used linear regression to evaluate urinary nitrate concentrations in relation to total nitrate, and drinking water and dietary intakes separately. Overall, dietary nitrate contributed the most to total intake (median: 97 %; interquartile range [IQR]: 57–99 %). Among 15 participants (32 %) whose drinking water nitrate concentrations were at/above the U.S. Environmental Protection Agency MCL (10 mg/L NO3-N), median intake from water was 44 % (IQR: 26–72 %). Total nitrate intake was the strongest predictor of urinary nitrate concentrations (R2 = 0.53). Drinking water explained a similar proportion of the variation in nitrate excretion (R2 = 0.52) as diet (R2 = 0.47). Our findings demonstrate the importance of both dietary and drinking water intakes as determinants of nitrate excretion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2024.170922","usgsCitation":"Skalaban, T., Thompson, D., Madrigal, J., Blount, B., Espinosa, M., Kolpin, D., Deziel, N., Jones, R., Freeman, L., Hofmann, J., and Ward, M., 2024, Nitrate exposure from drinking water and dietary sources among Iowa farmers using private wells: Science of the Total Envionrment, v. 919, 170922, 8 p., https://doi.org/10.1016/j.scitotenv.2024.170922.","productDescription":"170922, 8 p.","ipdsId":"IP-158584","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":467031,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11665930","text":"External Repository"},{"id":427395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Buchanan County, Cedar County, Delaware 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As adult Atlantic sturgeon spend much of their lives broadly distributed in marine and estuarine environments, it is challenging to collect data needed to estimate these demographic parameters in the adult population. Alternatively, data collected from juveniles and subadults before emigration may be used to calculate indices of abundance and provide insights into recruitment dynamics and stage-specific survival. However, uncertainty about stock mixture during early life stages may limit the use of juvenile and subadult data for monitoring recovery. To better understand early life stage stock composition, we conducted a genetic mixed-stock analysis of over 500 juvenile and subadult Atlantic sturgeon captured in an overwintering area in the Hudson River, New York, USA, from 2017 to 2022. The majority of Atlantic sturgeon in our study were natal to the Hudson River population, regardless of sex, size, or age. As such, indices of relative abundance estimated from survey data are expected to primarily characterize the demographic trends of Hudson River juvenile and subadult Atlantic sturgeon. We also found a small proportion of individuals that were most likely to have originated from more distantly located rivers, highlighting the potential for long-distance migration in juvenile and subadult Atlantic sturgeon. Results of this study strengthen our understanding of juvenile and subadult Atlantic sturgeon habitat use in the Hudson River and improve our ability to use data from early age classes to monitor recovery and stage-specific survival.
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Some have proposed that forest-based natural climate solutions can be strengthened via a number of strategies, including increases in the production of forest biomass energy. We used output from a forest dynamics model (SORTIE-ND) in combination with a GHG accounting tool (ForGATE) to estimate the carbon consequences of current and intensified timber harvest regimes in the Northeastern United States. We considered a range of carbon pools including forest ecosystem pools, forest product pools, and waste pools, along with different scenarios of feedstock production for biomass energy. The business-as-usual (BAU) scenario, which represents current harvest practices derived from the analysis of U.S. Forest Service Forest Inventory and Analysis data, sequestered more net CO2 equivalents than any of the intensified harvest and feedstock utilization scenarios over the next decade, the most important time period for combatting climate change. Increasing the intensity of timber harvest increased total emissions and reduced landscape average forest carbon stocks, resulting in reduced net carbon sequestration relative to current harvest regimes. Net carbon sequestration “parity points,” where the regional cumulative net carbon sequestration from alternate intensified harvest scenarios converge with and then exceed the BAU baseline, ranged from 12 to 40 years. A “no harvest” scenario provides an estimate of an upper bound on forest carbon sequestration in the region given the expected successional dynamics of the region's forests but ignores leakage. Regional net carbon sequestration is primarily influenced by (1) the harvest regime and amount of forest biomass removal, (2) the degree to which bioenergy displaces fossil fuel use, and (3) the proportion of biomass diverted to energy feedstocks versus wood products.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.4758","usgsCitation":"Brown, M.L., Canham, C., Buchholz, T., Gunn, J.S., and Donovan, T.M., 2024, Net carbon sequestration implications of intensified timber harvest in Northeastern U.S. forests: Ecosphere, v. 15, no. 2, e4758, 17 p., https://doi.org/10.1002/ecs2.4758.","productDescription":"e4758, 17 p.","ipdsId":"IP-145783","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":486940,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4758","text":"Publisher Index Page"},{"id":433270,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island, Vermont","otherGeospatial":"Northeastern United 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\"}}]}","volume":"15","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-02-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Michelle L.","contributorId":342622,"corporation":false,"usgs":false,"family":"Brown","given":"Michelle","email":"","middleInitial":"L.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":910228,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Canham, Charles D.","contributorId":342623,"corporation":false,"usgs":false,"family":"Canham","given":"Charles D.","affiliations":[{"id":36248,"text":"Cary Institute of Ecosystem Studies","active":true,"usgs":false}],"preferred":false,"id":910229,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchholz, Thomas","contributorId":342627,"corporation":false,"usgs":false,"family":"Buchholz","given":"Thomas","email":"","affiliations":[{"id":81895,"text":"Spatial Informatics Group","active":true,"usgs":false}],"preferred":false,"id":910230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gunn, John S.","contributorId":342628,"corporation":false,"usgs":false,"family":"Gunn","given":"John","email":"","middleInitial":"S.","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":910231,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910232,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271292,"text":"70271292 - 2024 - Mercury bioaccumulation and Hepatozoon spp. infections in two syntopic watersnakes in South Carolina","interactions":[],"lastModifiedDate":"2025-09-03T15:51:45.469464","indexId":"70271292","displayToPublicDate":"2024-02-08T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Mercury bioaccumulation and Hepatozoon spp. infections in two syntopic watersnakes in South Carolina","docAbstract":"Mercury (Hg) is a ubiquitous environmental contaminant known to bioaccumulate in biota and biomagnify in food webs. Parasites occur in nearly every ecosystem and often interact in complex ways with other stressors that their hosts experience. Hepatozoon spp. are intraerythrocytic parasites common in snakes. The Florida green watersnake (Nerodia floridana) and the banded watersnake (Nerodia fasciata) occur syntopically in certain aquatic habitats in the Southeastern United States. The purpose of this study was to investigate relationships among total mercury (THg) concentrations, body size, species, habitat type and prevalence and parasitemia of Hepatozoon spp. infections in snakes. In the present study, we sampled N. floridana and N. fasciata from former nuclear cooling reservoirs and isolated wetlands of the Savannah River Site in South Carolina. We used snake tail clips to quantify THg and collected blood samples for hemoparasite counts. Our results indicate a significant, positive relationship between THg and snake body size in N. floridana and N. fasciata in both habitats. Average THg was significantly higher for N. fasciata compared to N. floridana in bays (0.22 ± 0.02 and 0.08 ± 0.006 mg/kg, respectively; p < 0.01), but not in reservoirs (0.17 ± 0.02 and 0.17 ± 0.03 mg/kg, respectively; p = 0.29). Sex did not appear to be related to THg concentration or Hepatozoon spp. infections in either species. We found no association between Hg and Hepatozoon spp. prevalence or parasitemia; however, our results suggest that species and habitat type play a role in susceptibility to Hepatozoon spp. infection.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10646-024-02736-0","usgsCitation":"Brown, M.K., Haskins, D., Pilgrim, M.A., and Tuberville, T.D., 2024, Mercury bioaccumulation and Hepatozoon spp. infections in two syntopic watersnakes in South Carolina: Ecotoxicology, v. 33, p. 164-176, https://doi.org/10.1007/s10646-024-02736-0.","productDescription":"13 p.","startPage":"164","endPage":"176","ipdsId":"IP-151574","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":495185,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/2350673","text":"External Repository"},{"id":495154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","otherGeospatial":"Savannah River Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.58754725444848,\n 33.32644054240569\n ],\n [\n -81.58754725444848,\n 33.224172586552555\n ],\n [\n -81.46162826301534,\n 33.224172586552555\n ],\n [\n -81.46162826301534,\n 33.32644054240569\n ],\n [\n -81.58754725444848,\n 33.32644054240569\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2024-02-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, M. Kyle","contributorId":360889,"corporation":false,"usgs":false,"family":"Brown","given":"M.","middleInitial":"Kyle","affiliations":[{"id":86116,"text":"University of Georgia's Savannah River Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":947870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haskins, David Lee 0000-0002-6692-3225","orcid":"https://orcid.org/0000-0002-6692-3225","contributorId":357996,"corporation":false,"usgs":true,"family":"Haskins","given":"David Lee","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":947871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pilgrim, Melissa A.","contributorId":360890,"corporation":false,"usgs":false,"family":"Pilgrim","given":"Melissa","middleInitial":"A.","affiliations":[{"id":86119,"text":"University of South Carolina Upstate","active":true,"usgs":false}],"preferred":false,"id":947872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tuberville, Tracey D.","contributorId":360891,"corporation":false,"usgs":false,"family":"Tuberville","given":"Tracey","middleInitial":"D.","affiliations":[{"id":86116,"text":"University of Georgia's Savannah River Ecology Laboratory","active":true,"usgs":false}],"preferred":false,"id":947873,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70251323,"text":"sir20235128 - 2024 - An update of hydrologic conditions and distribution of selected constituents in water, eastern Snake River aquifer and perched groundwater zones, Idaho National Laboratory, Idaho, emphasis 2019–21","interactions":[],"lastModifiedDate":"2026-01-30T19:23:32.558092","indexId":"sir20235128","displayToPublicDate":"2024-02-06T10:35:55","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":"2023-5128","displayTitle":"An Update of Hydrologic Conditions and Distribution of Selected Constituents in Water, Eastern Snake River Aquifer and Perched Groundwater Zones, Idaho National Laboratory, Idaho, Emphasis 2019–21","title":"An update of hydrologic conditions and distribution of selected constituents in water, eastern Snake River aquifer and perched groundwater zones, Idaho National Laboratory, Idaho, emphasis 2019–21","docAbstract":"Since 1952, wastewater discharged to infiltration ponds (also called “percolation ponds”) and disposal wells at the Idaho National Laboratory (INL) has affected water quality in the eastern Snake River Plain (ESRP) aquifer and perched groundwater zones underlying the INL. The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy (DOE), maintains groundwater-monitoring networks at the INL to determine hydrologic trends and to delineate the movement of radiochemical and chemical wastes in both the aquifer and perched groundwater zones. This report presents an analysis of water-level and water-quality data collected from the ESRP aquifer and perched groundwater wells from the USGS groundwater monitoring networks during 2019–21.
From March–May 2018 to March–May 2021, water levels in wells completed in the ESRP aquifer increased in the northern part of the INL and decreased in the southwestern part. Water-level increases ranged from 0.02 to 1.04 feet in the northern part and decreases ranged from 0.03 to 2.94 feet in the southwestern part of the INL.
Detectable concentrations of radiochemical constituents in water samples from wells in the ESRP aquifer at the INL generally decreased or remained constant during 2019–21. Decreases in concentrations were attributed to radioactive decay, changes in waste-disposal methods, and dilution from recharge and underflow.
In 2021, tritium was detected above reporting levels in water samples collected from 46 of 105 aquifer wells and ranged from 150±50 to 4,280±150 picocuries per liter (pCi/L). Tritium concentrations from eight wells completed in deep perched groundwater near the Advanced Test Reactor Complex (ATRC) generally were greater than or equal to the reporting level during at least one sampling event during 2019–21, and concentrations ranged from 160±50 to 2,097±107 pCi/L. Concentrations of strontium-90 in water from 12 of 45 aquifer wells sampled in 2021 exceeded the reporting level, and concentrations ranged from 2.5±0.7 to 299±6 pCi/L. During 2021, concentrations of strontium-90 from five wells completed in deep perched groundwater at the ATRC equaled or exceeded the reporting levels, and concentrations ranged from 3±0.9 pCi/L to 27.8±1.3 pCi/L. Concentrations of cesium-137 were less than the reporting level in all but one aquifer well, and concentrations of plutonium-238, plutonium-239, -240 (undivided), and americium-241 were less than the reporting level in water samples from all aquifer wells sampled during this study period.
Dissolved chromium concentrations in water samples from 64 ESRP aquifer wells ranged from less than (<) 0.5 to 76.4 micrograms per liter (μg/L). During 2019–21, dissolved chromium was detected in water from wells completed in deep perched groundwater above the ESRP aquifer at the ATRC, and concentrations ranged from <1 to 82.1 μg/L.
In 2021, concentrations of dissolved sodium in water from most ESRP aquifer wells in the southern part of the INL were greater than the western tributary groundwater background concentration of 8.3 milligrams per liter (mg/L). During 2021, dissolved sodium concentrations in water from 15 wells completed in deep perched groundwater ranged from 11.7 to 122.5 mg/L. Variations in sodium concentrations in aquifer wells and perched groundwater zones are attributed to either migration of remnant water from the former chemical-waste ponds or disposal volume and composition variability in percolation ponds installed in 2008.
In 2021, concentrations of chloride in most water samples from ESRP aquifer wells south of the Idaho Nuclear Technology and Engineering Center (INTEC) and at the Central Facilities Area (CFA) exceeded background concentrations. Chloride concentrations in water from wells south of the INTEC have generally decreased because of discontinued chloride disposal to the legacy percolation ponds since 2002 when the discharge of wastewater was discontinued. During 2019–21, dissolved chloride concentrations in deep perched groundwater above the ESRP aquifer from 18 wells at the ATRC ranged from 8.15 to 231 mg/L.
In 2021, sulfate concentrations in water samples from ESRP aquifer wells in the south-central part of the INL that exceeded the background concentration of sulfate, ranged from 21 to 141 mg/L. The greater-than-background concentrations in water from these wells are attributed to sulfate disposal at the ATRC infiltration ponds or the legacy INTEC percolation ponds. In 2021, sulfate concentrations in water samples from aquifer wells near the Radioactive Waste Management Complex (RWMC) were mostly greater than background concentrations. The maximum dissolved sulfate concentration in shallow perched groundwater near the ATRC was 575 mg/L in 2021. During 2021, dissolved sulfate concentrations in water from wells completed in deep perched groundwater near the cold waste ponds at the ATRC ranged from 22.3 to 519 mg/L.
In 2021, concentrations of nitrate in water from most ESRP aquifer wells at and near the INTEC exceeded the western tributary groundwater background concentration of 0.655 mg/L. Concentrations of nitrate in aquifer wells southwest of INTEC and farther away from the influence of disposal areas and the Big Lost River, in intermittent source of surface water recharge to the aquifer, show a general decrease in nitrate concentration over time. Two aquifer wells south of INTEC show increasing trends that could result from wastewater beneath the INTEC tank farm being mobilized to the aquifer.
During 2019–21, water samples from several ESRP aquifer wells were collected and analyzed for volatile organic compounds (VOCs). Twelve VOCs were detected, and 1–4 VOCs were detected in water samples from 10 wells. The most frequently detected VOCs include carbon tetrachloride (tetrachloromethane), trichloromethane, tetrachloroethene, 1,1,1-trichloroethane, and trichloroethene. In 2019–21, concentrations for all VOCs were less than their respective maximum contaminant levels (MCLs) for drinking water, except carbon tetrachloride in one well, trichloroethene in two wells, and vinyl chloride in one well.
During 2019–21, variability and bias were evaluated from 34 replicate and 14 blank quality-assurance samples. Results from replicate analyses were investigated to evaluate sample variability. Constituents with acceptable reproducibility were major ions, trace elements, nutrients, and VOCs. All radiochemical constituents including gross alpha- and beta- radioactivity, strontium-90, cesium-137, and tritium, had acceptable reproducibility. Bias from sample contamination was evaluated from equipment, field, and source-solution blanks. Chloride and sulfate were detected slightly above their respective method detection limits in equipment and field blanks, but at concentrations well below the co-collected sample for that well. These chloride and sulfate detections in the field and equipment blanks were inconsequential because they weren’t detected above the analysis-specific variability for those constituents as determined by replicate sample result evaluation. None of the detections of nutrients and trace inorganic constituents were high enough to indicate environmental sample or analytical procedure bias.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235128","collaboration":"DOE/ID-22261Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Detailed understanding of crustal components and tectonic history of forearcs is important due to their geological complexity and high seismic hazard. The principal component of the Cascadia forearc is Siletzia, a composite basaltic terrane of oceanic origin. Much is known about the lithology and age of the province. However, glacial sediments blanketing the Puget Lowland obscure its lateral extent and internal structure, hindering our ability to fully understand its tectonic history and its influence on modern deformation. In this study, we apply map-view interpretation and two-dimensional modeling of aeromagnetic and gravity data to the magnetically stratified Siletzia terrane revealing its internal structure and characterizing its eastern boundary. These analyses suggest the contact between Siletzia (Crescent Formation) and the Eocene accretionary prism trends northward under Lake Washington. North of Seattle, this boundary dips east where it crosses the Kingston arch, whereas south of Seattle the contact dips west where it crosses the Seattle uplift (SU). This westward dip is opposite the dip of the Eocene subduction interface, implying obduction of Siletzia upper crust at this southern location. Elongate pairs of high and low magnetic anomalies over the SU suggest imbrication of steeply-dipping, deeply rooted slices of Crescent Formation within Siletzia. We hypothesize these features result from duplication of Crescent Formation in an accretionary fold-thrust belt during the Eocene. The active Seattle fault divides this Eocene fold-thrust belt into two zones with different structural trends and opposite frontal ramp dips, suggesting the Seattle fault may have originated as a tear fault during accretion.
Fishes exhibit a diverse range of traits encompassing life-history strategies, feeding behaviours and spawning behaviours. These traits mediate fish population responses to changing environmental conditions such as those caused by anthropogenic stressors. The Conasauga River, located in northwestern Georgia and southeastern Tennessee, USA, hosts a diverse assemblage of over 75 species of freshwater fish, some of which are locally or regionally endemic, and many of which are imperilled. Annual monitoring data have shown population declines in multiple fish species of conservation concern in the Conasauga River since at least the 1990s, raising the possibility that other taxa could be declining as well. We quantified temporal changes in fish communities at six shoal sites sampled annually in most years from 1996 to 2022, and asked whether species traits hypothesized to underlie population vulnerability to environmental alteration were correlated with species-specific trends for 32 taxa. We estimated that total counts of fish in annual samples declined by ~2% per year, although declines were uneven among species and generally greater for less abundant taxa. Tests for species traits corresponding to temporal population trends provided evidence that crevice-spawning minnows and smaller-bodied taxa had steeper declines compared with broadcast spawners and larger, longer-lived, more fecund taxa. Lower abundance, reliance on a particular habitat feature, and life-history traits that may limit population resilience to disturbance may all prove useful for identifying riverine fishes at particular risk of future population decline.
Adverse ecological and water-quality effects associated with industrial land-use changes are common for littoral wetlands connected to river mouth ecosystems in the Grand Calumet River-Indiana Harbor Canal Area of Concern. These effects can be exacerbated by recent high Lake Michigan water levels that are problematic for wetland restoration. Wetlands in the adjacent Clark and Pine Nature Preserve and Pine Station Nature Preserve are intended to mitigate wetland destruction in the area of concern by restoring residual dune-and-swale wetlands and preserving habitat for endangered and threatened plant species. Physical hydrology and water-quality monitoring of restored wetland cells at the preserves were initiated during 2019 to evaluate changes after wetland restoration efforts in 2015 and near record-low water levels in early 2013. Lake Michigan water levels rose steadily between late 2013 and 2018 to record-high water levels in 2019 and 2020. In this report, precipitation, evapotranspiration, and groundwater and surface-water levels are analyzed to better understand wetland inundation controls and flow directions in restored northern dune-and-swale wetland settings relative to the Grand Calumet River. Continuous specific conductance data and discrete water-quality samples were collected and analyzed to provide a synoptic view of water quality for the restored wetlands.
High Lake Michigan water levels affected Grand Calumet River stage and shallow groundwater elevations in the study area after the onset of peak lake levels in June 2019, that persisted through summer 2020, before finally receding in September 2020. Grand Calumet River stage peaked soon after lake levels in July 2019, whereas groundwater elevations in the study area peaked in October 2019. Specific conductance values in closed-basin wetland cells in the western and central parts of the nature preserves indicated a dilution trend and contrasted those of interconnected wetland cells along an eastern corridor, where alterations to wetland cells were more pronounced. Monitoring results indicate that varying seasonal wetland inundation trends with low stands in autumn have returned after high water table conditions owing to high water levels on Lake Michigan. Wetland water balance results during the study period indicated that the wetland ecosystem partially moderated flooding during high lake levels through summer evapotranspiration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235122","collaboration":"Prepared in cooperation with the Indiana Department of Natural Resources","usgsCitation":"Naylor, S., and Gahala, A.M., 2024, Hydrology and water quality of a dune-and-swale wetland adjacent to the Grand Calumet River, Indiana, 2019–22: U.S. Geological Survey Scientific Investigations Report 2023–5122, 29 p., https://doi.org/10.3133/sir20235122.","productDescription":"Report: vii, 29 p.; Dataset","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-149471","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":499387,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116023.htm","linkFileType":{"id":5,"text":"html"}},{"id":425295,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the nation"},{"id":425294,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5122/images/"},{"id":425293,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5122/sir20235122.XML"},{"id":425292,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235122/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5122"},{"id":425291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5122/sir20235122.pdf","text":"Report","size":"3.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5122"},{"id":425290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5122/coverthb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Grand Calumet River-Indiana Harbor Canal Area of Concern","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.4167,\n 41.6278\n ],\n [\n -87.4167,\n 41.6056\n ],\n [\n -87.35,\n 41.6056\n ],\n [\n -87.35,\n 41.6278\n ],\n [\n -87.4167,\n 41.6278\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229
Resin-coated proppants (RCPs) are used in hydraulic fracturing of oil and gas wells to improve well performance; however, these proppants could be a cause for environmental concern if they are disposed of improperly. In this study, we investigate the water-leachable organic and inorganic constituents from proppants collected from surficial releases of RCPs in southeastern New Mexico. Significant concentrations of nonvolatile dissolved organic matter (>100 mg C/L) and phenolic compounds (>50 mg phenol/L) were identified in one of the proppant leachates, with further gas chromatography–mass spectrometry analysis identifying isomers of bisphenol F, a known endocrine disruptor analogous to bisphenol A, as the main organic constituents within this leachate. Fluorescence excitation–emission matrices analyses of proppant leachates identified several peaks associated with phenolic compounds, similar to previously studied oilfield wastewaters. Precursors of polyurethane production, including the inhalation sensitizer methylene diphenyl diisocyanate, were identified in the leachate from another proppant sample. An understanding of leachable compounds from RCPs is vital to management of environmental contamination from surficial releases, protecting the public and industry workers from associated hazards, and identifying the sources of organic compounds in oilfield wastewaters.
Kīlauea Volcano experiences centuries-long cycles of explosive and effusive eruptive behavior, but the relation, if any, between these eruptive styles and changing conditions in the magma plumbing system remains poorly known. We analyze olivine-hosted melt and fluid inclusions to determine magma storage depths during the explosive-era Keanakākoʻi Tephra eruptions (∼1500–1840 CE) and compare these results to modern effusive-era Kīlauea eruptions (1959 Kīlauea Iki, 1960 Kapoho, 2018 lower East Rift Zone). We find that shallow (1–3 km) magma storage has persisted for centuries at Kīlauea, spanning both explosive and effusive periods. In contrast, mid-crustal zones of magma storage shallowed over time, from 5 to 8 km during the Keanakākoʻi sequence to 3–5 km during the modern effusive period. Melt and fluid inclusions in high-forsterite olivine (Fo86–89) trapped at shallow depths indicate that high-temperature magmas (1200 to ∼1300 °C) commonly reach depths of ≤3 km. CO2-rich fluid inclusions are present in olivine from all investigated Kīlauea eruptions but are larger and much more abundant in Keanakākoʻi units, which we interpret as indicating that a greater volume fraction of exsolved CO2-rich fluid was present in pre-eruptive Keanakākoʻi melts. Increased amounts of CO2-rich fluids in the Keanakākoʻi-era magmas would have increased magma buoyancy and driven rapid magma ascent, thereby increasing eruption energy and enhancing near-surface magma-water interactions compared to the current effusive period.
Metrosideros polymorpha (‘ōhi‘a, ‘ōhi‘a lehua) is an important foundation species in Hawaiian forest habitats. The genus originated in New Zealand and was dispersed to the Hawaiian archipelago approximately 3.9 million years ago. It evolved into five distinct endemic species and one of these, Metrosideros polymorpha, further differentiated into eight varieties across what are now the main Hawaiian Islands. ‘Ōhi‘a is a tree that has great significance in indigenous Hawaiian culture. It is considered a physical manifestation of several principal Hawaiian deities, and serves a broad range of uses in Hawaiian material culture. It occupies a wide diversity of habitats, extending from sea level to over 2,200 m elevation, occupying habitats that range from extremely wet to dry rainfall zones. It is the dominant or co-dominant tree species in wet and mesic forests and is also one of the first woody species to become established on young lava flows. Although ‘ōhi‘a is a dominant forest tree it also exhibits many characteristics of a pioneer species. ‘Ōhi‘a provides the matrix for a wide diversity of endemic plants and animals found in these habitats and functions as the primary vegetation cover on native Hawaiian watersheds, facilitating groundwater recharge and regulating surface runoff. ‘Ōhi‘a has shown remarkable resilience by recolonizing forests that were opened up by disturbance, such as the widespread ‘ōhi‘a canopy dieback that occurred on East Maui in the 1900s and on the east side of the Island of Hawai‘i in the 1970s. Several human-related conditions threaten the continued stability of Hawaii’s native ecosystems, including invasive plants, plant diseases, introduced animals, and changing climate. The research and conservation legacy of Dr. Dieter Mueller-Dombois helped to expand our knowledge of the ecology and importance of ‘ōhi‘a forests, and to increase awareness and appreciation of the remarkable Hawaiian ecosystems that are unique to the world.
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\"}}]}","volume":"77","issue":"2-3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":919264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boehmer, Hans Juergen","contributorId":207895,"corporation":false,"usgs":false,"family":"Boehmer","given":"Hans","email":"","middleInitial":"Juergen","affiliations":[{"id":37652,"text":"School of Geography, University of the South Pacific, Suva, Fiji","active":true,"usgs":false}],"preferred":false,"id":919265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":919266,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gon III, Samuel M. ‘Ohukaniʻōhiʻa","contributorId":346476,"corporation":false,"usgs":false,"family":"Gon III","given":"Samuel M. ‘Ohukaniʻōhiʻa","affiliations":[{"id":82869,"text":"The Nature Conservancy of Hawai`i","active":true,"usgs":false}],"preferred":false,"id":919267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mertelmeyer, Linda","contributorId":214407,"corporation":false,"usgs":false,"family":"Mertelmeyer","given":"Linda","email":"","affiliations":[{"id":39035,"text":"Technical University of Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":919268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Price, Jonathan","contributorId":187456,"corporation":false,"usgs":false,"family":"Price","given":"Jonathan","affiliations":[],"preferred":false,"id":919269,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70254428,"text":"70254428 - 2024 - Earthquake rupture forecast model construction for the 2023 U.S. 50‐State National Seismic Hazard Model Update: Central and eastern U.S. fault‐based source model","interactions":[],"lastModifiedDate":"2024-05-24T11:59:35.15136","indexId":"70254428","displayToPublicDate":"2024-01-31T06:56:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake rupture forecast model construction for the 2023 U.S. 50‐State National Seismic Hazard Model Update: Central and eastern U.S. fault‐based source model","docAbstract":"As part of the U.S. Geological Survey’s 2023 50‐State National Seismic Hazard Model (NSHM), we make modest revisions and additions to the central and eastern U.S. (CEUS) fault‐based seismic source model that result in locally substantial hazard changes. The CEUS fault‐based source model was last updated as part of the 2014 NSHM and considered new information from the Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn) Project. Since then, new geologic investigations have led to revised fault and fault‐zone inputs, and the release of databases of fault‐based sources in the CEUS. We have reviewed these databases and made minor revisions to six of the current fault‐based sources in the NSHM, as well as added five new fault‐based sources. Implementation of these sources follows the current NSHM methodology for CEUS fault‐based sources, as well as the incorporation of a new magnitude–area relationship and updated maximum magnitude and recurrence rate estimates following the methods used by the CEUS‐SSCn Project. Seismic hazard sensitivity calculations show some substantial local changes in hazard (−0.4g to 1.1g) due to some of these revisions and additions, especially from the addition of the central Virginia, Joiner ridge, and Saline River sources and revisions made to the Meers and New Madrid sources.
Many studies use landscape form to determine spatial patterns of tectonic deformation, and these are particularly effective when paired with independent measures of rock uplift and erosion. Here, we use morphometric analyses and 10Be catchment-averaged erosion rates, together with reverse slip rates from the Sierra Madre−Cucamonga fault zone, to reveal patterns in uplift, erosion, and fault activity in the range front of the San Gabriel Mountains in southern California, USA. Our analysis tests two prevailing hypotheses: (1) the range front of the San Gabriel Mountains is at steady state, in which rock uplift balances erosion and topographic elevations are stable throughout time, and (2) that west-to-east increases in elevation, relief, erosion rate, and stream-channel steepness across the interior of the massif reflect a parallel reverse-slip rate gradient on the range-bounding Sierra Madre−Cucamonga fault zone. We show that although deviations from steady state occur, the range-front hillslopes and stream channels are typically both well-connected and adjusted to patterns in Quaternary uplift driven by motion on the range-front fault network. Accordingly, landscape morphometrics, 10Be erosion rates, and model erosion rates effectively image spatial and temporal patterns in uplift. Interpreted jointly, these data reveal comparable peak slip rates on the Sierra Madre−Cucamonga fault zone and show that they do not monotonically increase from west to east. Thus, the eastward-increasing gradients developed within the interior of the massif are not solely related to reverse slip on the range-front faults. Evaluated on shorter length scales (<10 km), morphometric data corroborate earlier descriptions of the Sierra Madre−Cucamonga fault zone as multiple individual faults or fault sections, with slip rates tapering toward fault tips. We infer that these patterns imply the predominance of independent fault or fault section ruptures throughout the Quaternary, though data cannot rule out the possibility of large, connected Sierra Madre−Cucamonga fault zone ruptures. Deeper in the hanging wall of the Sierra Madre−Cucamonga fault zone, secondary faults accommodate range-front uplift. Motion on these faults may contribute to active uplift of the highest topography within the massif, in addition to partly reconciling differences between geologic and geodetic Sierra Madre−Cucamonga fault zone reverse-slip rates. This study provides a new, unified perspective on tectonics and landscape evolution in the San Gabriel Mountains.
Ocean acidification (OA) driven by eutrophication, riverine discharge, and other threats from local population growth that affect the inorganic carbonate system is already affecting the eastern Gulf of Mexico. Long-term declines in pH of ~ -0.001 pH units yr-1 have been observed in many southwest Florida estuaries over the past few decades. Coastal and estuarine waters of southwest Florida experience high biomass harmful algal blooms (HABs) of the dinoflagellate Karenia brevis nearly every year; and these blooms have the potential to impact and be impacted by seasonal to interannual patterns of carbonate chemistry. Sampling was conducted seasonally along three estuarine transects (Tampa Bay, Charlotte Harbor, Caloosahatchee River) between May 2020 and May 2023 to obtain baseline measurements of carbonate chemistry prior to, during, and following K. brevis blooms. Conductivity, temperature and depth data and discrete water samples for K. brevis cell abundance, nutrients, and carbonate chemistry (total alkalinity, dissolved inorganic carbonate (DIC), pCO2, and pHT were evaluated to identify seasonal patterns and linkages among carbonate system variables, nutrients, and K. brevis blooms. Karenia brevis blooms were observed during six samplings, and highest pCO2 and lowest pHT was observed either during or after blooms in all three estuaries. Highest average pH and lowest pCO2 were observed in Tampa Bay. In all three estuaries, average DIC and pHT were higher and pCO2 was lower during dry seasons than wet seasons. There was strong influence of net community calcification (NCC) and net community production (NCP) on the carbonate system; and NCC : NCP ratios in Tampa Bay, Charlotte Harbor, and the Caloosahatchee River were 0.83, 0.93, and 1.02, respectively. Linear relationships between salinity and dissolved ammonium, phosphate, and nitrate indicate strong influence of freshwater inflow from river input and discharge events on nutrient concentrations. This study is a first step towards connecting observations of high biomass blooms like those caused by K. brevis and alterations of carbonate chemistry in Southwest Florida. Our study demonstrates the need for integrated monitoring to improve understanding of interactions among the carbonate system, HABs, water quality, and acidification over local to regional spatial scales and event to decadal time scales.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmars.2024.1331285","usgsCitation":"Hall, E.R., Yates, K., Hubbard, K.A., Garrett, M., and Frankle, J., 2024, Nutrient and carbonate chemistry patterns associated with Karenia brevis blooms in three West Florida Shelf estuaries 2020-2023: Frontiers in Marine Science, v. 11, 1331285, 16 p., https://doi.org/10.3389/fmars.2024.1331285.","productDescription":"1331285, 16 p.","ipdsId":"IP-159102","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":440613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2024.1331285","text":"Publisher Index Page"},{"id":426239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Caloosahatchee River, Charlotte Harbor, Tampa Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.34832763337916,\n 28.08844843847784\n ],\n [\n -82.86256285263788,\n 28.08844843847784\n ],\n [\n -82.86256285263788,\n 27.473959773932535\n ],\n [\n -82.34832763337916,\n 27.473959773932535\n ],\n [\n -82.34832763337916,\n 28.08844843847784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.0334613261019,\n 26.994691244568983\n ],\n [\n -82.29301422823401,\n 26.99594814875003\n ],\n [\n -82.2944248418327,\n 26.644724858711314\n ],\n [\n -82.0334613261019,\n 26.643464039045767\n ],\n [\n -82.0334613261019,\n 26.994691244568983\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.835022542123,\n 26.624097850120123\n ],\n [\n -82.14513224054205,\n 26.624097850120123\n ],\n [\n -82.14513224054205,\n 26.367427637237768\n ],\n [\n -81.835022542123,\n 26.367427637237768\n ],\n [\n -81.835022542123,\n 26.624097850120123\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2024-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Emily R.","contributorId":229381,"corporation":false,"usgs":false,"family":"Hall","given":"Emily","email":"","middleInitial":"R.","affiliations":[{"id":41628,"text":"Mote Marine","active":true,"usgs":false}],"preferred":false,"id":895784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yates, Kimberly 0000-0001-8764-0358","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":202055,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":895785,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hubbard, Katherine A.","contributorId":334472,"corporation":false,"usgs":false,"family":"Hubbard","given":"Katherine","email":"","middleInitial":"A.","affiliations":[{"id":80154,"text":"Florida Fish & Wildlife Conservation Commission-FWRI","active":true,"usgs":false}],"preferred":false,"id":895786,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garrett, Matt","contributorId":334473,"corporation":false,"usgs":false,"family":"Garrett","given":"Matt","email":"","affiliations":[{"id":80154,"text":"Florida Fish & Wildlife Conservation Commission-FWRI","active":true,"usgs":false}],"preferred":false,"id":895787,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frankle, Jessica","contributorId":334474,"corporation":false,"usgs":false,"family":"Frankle","given":"Jessica","email":"","affiliations":[{"id":13147,"text":"Mote Marine Laboratory","active":true,"usgs":false}],"preferred":false,"id":895788,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70250850,"text":"ofr20231081 - 2024 - Water-level change from a multiple-well aquifer test in volcanic rocks, Umatilla Indian Reservation near Mission, northeastern Oregon, 2016","interactions":[],"lastModifiedDate":"2026-01-28T17:35:11.290065","indexId":"ofr20231081","displayToPublicDate":"2024-01-18T15:29:15","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1081","displayTitle":"Water-Level Change from a Multiple-Well Aquifer Test in Volcanic Rocks, Umatilla Indian Reservation near Mission, Northeastern Oregon, 2016","title":"Water-level change from a multiple-well aquifer test in volcanic rocks, Umatilla Indian Reservation near Mission, northeastern Oregon, 2016","docAbstract":"The U.S. Geological Survey, in cooperation with the Confederated Tribes of the Umatilla Indian Reservation (CTUIR), (1) estimated water-level change from a multiple-well aquifer test centered on CTUIR well number 422 and (2) evaluated hydraulic connections between the pumping and observation wells on the Umatilla Indian Reservation near Mission, northeastern Oregon to improve the understanding of aquifer characteristics and hydrologic flow boundaries. Water-level changes, or pumping responses, were determined by distinguishing the pumping signal from environmental fluctuations in groundwater levels using analytical water-level models. The pumping well produces water from basalt units from a depth of 450 to 1,057 feet below land surface and was intermittently pumped during February 1–April 18, 2016. Water-level responses to pumping were estimated in the pumping well and in seven observation wells within 4 miles (mi) of the pumping well. The observation wells are open to basalt and some observation wells are either separated from the pumping well by faults and other structural features, within structural zones, or adjacent to structural features. Pumping responses at the observation wells were classified as detected in two wells, ambiguous in one well, and not detected in four wells. Observation-well open-interval elevations overlapped with the pumping-well open interval in both wells with detected pumping responses. Observation wells with detections are 1.8 mi east of the pumping well and across a fault, and 1.4 mi south of the pumping well. The pumping response was classified as ambiguous in an observation well located 1.4 mi west of the pumping well, where the dip of the basalt unit steepens, and adjacent to the Agency syncline. Pumping responses were not detected in observation wells within 0.3 mi of the pumping well where observation-well open-interval elevations are above the top of the pumping well open interval. Analysis of pumping responses indicates (1) a more permeable zone of basalt is adjacent to the lower portion of the pumping-well open interval and extends eastward, (2) basalt adjacent to the upper portion of the pumping-well open-interval is less permeable than the lower portion or separated from the lower portion by a less permeable zone, and (or) (3) a less permeable zone limits vertical hydraulic connectivity between the pumping well and the overlying basalt.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231081","collaboration":"Prepared in cooperation with Confederated Tribes of the Umatilla Indian Reservation","usgsCitation":"Garcia, C.A., Kennedy, J.J., and Ely, K., 2024, Water-level change from a multiple-well aquifer test in volcanic rocks, Umatilla Indian Reservation near Mission, northeastern Oregon, 2016: U.S. Geological Survey Open-File Report 2023–1081, 16 p., https://doi.org/10.3133/ofr20231081.","productDescription":"Report: vii, 16 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-149402","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":499191,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115942.htm","linkFileType":{"id":5,"text":"html"}},{"id":424231,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1081/ofr20231081.XML"},{"id":424229,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q1122I","text":"USGS data release","description":"USGS data release","linkHelpText":"Multiple-well aquifer-test data and results, Umatilla Indian Reservation near Mission, northeastern Oregon"},{"id":424228,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231081/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1081"},{"id":424227,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1081/ofr20231081.pdf","text":"Report","size":"3.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1081"},{"id":424230,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1081/images"},{"id":424226,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1081/ofr20231081.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Umatilla Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.5,\n 45.44\n ],\n [\n -118.5,\n 45.36\n ],\n [\n -118.36,\n 45.36\n ],\n [\n -118.36,\n 45.44\n ],\n [\n -118.5,\n 45.44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director , Oregon Water Science Center
U.S. Geological Survey
601 SW 2nd Avenue, Suite 1950
Portland, OR 97204
The 1 September 1886 Charleston, South Carolina, earthquake was one of the largest preinstrumental earthquakes in eastern North America for which extensive contemporaneous observations were documented. The distribution of shaking was mapped shortly after the earthquake, and reconsidered by several authors in the late twentieth century, but has not been reconsidered with a modern appreciation for issues associated with macroseismic data interpretation. Detailed contemporary accounts have also never been used to map the distribution of numerical shaking intensities in the near field. In this study we reconsider macroseismic data from far‐field accounts as well as detailed accounts of damage in the near field, estimating modified Mercalli intensity values at 1297 locations including over 200 definite “not felt” reports that delineate the overall felt extent. We compare the results to the suite of ground‐motion models for eastern North America selected by the National Seismic Hazard Model, using a recently proposed mainshock rupture model and an average site condition for the locations at which intensities are estimated. The comparison supports the moment magnitude estimate, 7.3, from a recently proposed rupture model (Bilham and Hough, 2023). A ShakeMap constrained by model predictions and estimated intensities further illustrates this consistency, which we show is insensitive to rupture model details. Given the uncertainty of calibration relations for magnitudes close to 7, the overall intensity distribution provides a good characterization of shaking but cannot improve the independent moment magnitude estimate. We also identify a previously unrecognized early large aftershock that occurred 9–10 min after the mainshock, for which we estimate magnitude ∼5.6.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230224","usgsCitation":"Hough, S.E., and Bilham, R., 2024, The 1886 Charleston, South Carolina, earthquake: Intensities and ground motions: Bulletin of the Seismological Society of America, v. 114, no. 3, p. 1658-1679, https://doi.org/10.1785/0120230224.","productDescription":"22 p.","startPage":"1658","endPage":"1679","ipdsId":"IP-157642","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","city":"Charleston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.5,\n 33.3\n ],\n [\n -80.5,\n 32.65\n ],\n [\n -79.9,\n 32.65\n ],\n [\n -79.9,\n 33.3\n ],\n [\n -80.5,\n 33.3\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"114","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-01-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bilham, Roger","contributorId":225117,"corporation":false,"usgs":false,"family":"Bilham","given":"Roger","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":927606,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70250914,"text":"sir20235126 - 2024 - Flood of October 31 to November 3, 2019, in the East Canada Creek, West Canada Creek, and Sacandaga River basins in central New York","interactions":[],"lastModifiedDate":"2026-01-30T19:22:05.254094","indexId":"sir20235126","displayToPublicDate":"2024-01-17T07:10:00","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":"2023-5126","displayTitle":"Flood of October 31 to November 3, 2019, in the East Canada Creek, West Canada Creek, and Sacandaga River Basins in Central New York","title":"Flood of October 31 to November 3, 2019, in the East Canada Creek, West Canada Creek, and Sacandaga River basins in central New York","docAbstract":"Between October 31 and November 3, 2019, historic flooding in localized areas of the Mohawk Valley and southern Adirondack region in central New York State resulted in one fatality and an estimated $33 million in damages. Flooding resulted from high-intensity, hyperlocal rainfall in the region within a 24-hour period between October 31 and November 1, 2019, at the end of a much wetter than average October. In that 24-hour period, rainfall amounts largely ranged from 2 to 5 inches in the most heavily affected parts of the region, but a maximum rainfall amount for the region of 7 inches was recorded in Speculator, New York. This rainfall total for a 24-hour period for this location is estimated to have between a 200- and 500-year recurrence interval. The most severe flooding to result from the rainfall was mainly in the Sacandaga River basin, which is within the upper Hudson River basin, and in the East and West Canada Creek basins, which are within the Mohawk River basin.
Streamflow, stage, and reservoir elevation data, collected by the U.S. Geological Survey, are documented in this report. Flooding resulted in new peak streamflow records at five of six U.S. Geological Survey streamgages in the region that have periods of record of at least 20 years, including at three streamgages that have been in operation for about 100 years. At the sixth streamgage, this flooding resulted in the second highest peak streamflow in its 71-year period of record. For all six streamgages, estimates of flood magnitudes for selected annual exceedance probabilities were updated using the peak streamflows from the flooding. Additionally, the annual exceedance probabilities for the six respective peak streamflows were all estimated to be less than 1 percent (greater than a 100-year recurrence interval). At three of those six streamgages, however, previous annual peak streamflows of comparable magnitudes (within 10 percent) have also happened within the past 20 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235126","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Graziano, A.P., Gazoorian, C.L., Smith, T.L., and Lilienthal, A.G., III, 2024, Flood of October 31 to November 3, 2019, in the East Canada Creek, West Canada Creek, and Sacandaga River basins in central New York: U.S. Geological Survey Scientific Investigations Report 2023–5126, 37 p., https://doi.org/10.3133/sir20235126.","productDescription":"Report: vii, 37 p.; Data Release","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129517","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":499390,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115944.htm","linkFileType":{"id":5,"text":"html"}},{"id":424346,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SCOJ7M","text":"USGS data release","linkHelpText":"Flood-frequency data for six selected streamgages following the central New York flood of October 31–November 3, 2019"},{"id":424342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5126/sir20235126.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5126"},{"id":424341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5126/coverthb.jpg"},{"id":424345,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5126/images/"},{"id":424344,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5126/sir20235126.XML"},{"id":424343,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235126/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5126"}],"country":"United States","state":"New York","otherGeospatial":"East Canada Creek basin, West Canada Creek basin, Sacandaga River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.89510221171278,\n 42.85733224203008\n ],\n [\n -73.69783658671246,\n 42.85733224203008\n ],\n [\n -73.69783658671246,\n 44.15608967292573\n ],\n [\n -75.89510221171278,\n 44.15608967292573\n ],\n [\n -75.89510221171278,\n 42.85733224203008\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
Prices for battery-grade lithium have increased substantially since 2020, which is propelling the search for additional sources of this important element. Battery-grade lithium is predominately recovered from continental brines. Most crude oil and natural gas wells recover briny formation water, which may represent an additional source. Chemical analysis of these waters has been shown to indicate the presence of varying concentrations of lithium and related elements. This paper briefly reviews developments and literature supporting the presence of lithium in petroleum reservoir brines. It also describes the coverage and distribution of lithium data analyses in the United States Geological Survey National Produced Waters Geochemical Database (PWGD). It then addresses the question as to whether a lithium concentration can be accurately predicted using constituents of ion chemistry in produced brines from specific geologic formations. Four machine learning algorithms are employed to classify the commercial potential of lithium in oil field brines using data from oil wells recovering formation water from the Smackover Formation. The calibrated classification models are further applied to new (out-of-sample) data from the Marcellus Formation in the Appalachian Basin. Among the approaches considered, the predictive performance and wider applicability of the gradient boosted tree and the deep neural network models are determined to be the most promising. Finally, we discuss how the calibrated models could be applied to assure the quality of the data reported from chemical laboratory analysis and for imputation when lithium values are missing.
","language":"English","publisher":"Springer","doi":"10.1007/s13563-023-00409-8","usgsCitation":"Attanasi, E., Coburn, T., and Freeman, P., 2024, Machine learning approaches to identify lithium concentration in petroleum produced waters: Mineral Economics, v. 37, p. 477-497, https://doi.org/10.1007/s13563-023-00409-8.","productDescription":"21 p.","startPage":"477","endPage":"497","ipdsId":"IP-144611","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":424326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationDate":"2024-01-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":1809,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":891987,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coburn, Timothy","contributorId":333122,"corporation":false,"usgs":false,"family":"Coburn","given":"Timothy","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":891988,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":206294,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":891989,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70251132,"text":"70251132 - 2024 - Heterogeneous multi-stage accretionary orogenesis — Evidence from the Gunnison block in the Yavapai Province, southwest USA","interactions":[],"lastModifiedDate":"2024-01-24T13:12:49.893969","indexId":"70251132","displayToPublicDate":"2024-01-05T07:09:56","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneous multi-stage accretionary orogenesis — Evidence from the Gunnison block in the Yavapai Province, southwest USA","docAbstract":"Proterozoic rocks exposed in the southwestern U.S.A. represent one of the best examples of crustal growth by arc-related magmatism and accretionary orogenesis. Within the Southwest the 1.8–1.7 Ga Yavapai Province is widely regarded as a classic example of juvenile arc crust, however 1.8–2.5 Ga inherited zircon and Nd and Hf model ages have been recognized near Gunnison in central Colorado. These data have led to questions regarding the extent and nature of pre-1.8 Ga crustal material and the genesis of the Yavapai Province. We present evidence for a geochemically distinct, spatially restricted crustal block underlain by pre-1.8 Ga crust material (referred to here as the Gunnison block) in central to western Colorado within the Yavapai Province. The Gunnison block is characterized by 1.8–1.9 and 2.4–2.6 Ga inherited zircon, Pb isotopic systematics (μ = 9.8 ± 0.1, κ = 3.7 ± 0.1) elevated relative to 1.8 Ga depleted mantle values, 1.8–2.5 Ga Nd and Hf model ages, and a distinct pressure-temperature-time history. The geochemical data are consistent with mixing between juvenile 1.8 Ga and pre-1.8 Ga sources. The older crustal component is most similar to the isotopically enriched Mojave Province of eastern California and western Arizona, suggesting greater similarities between these provinces than previously recognized. Monazite and xenotime petrochronology indicate ca. 1.75–1.74, 1.72–1.69, 1.67, and 1.47–1.38 Ga tectono-metamorphic events. These data suggest that the Gunnison block accreted to other components of the Yavapai Province outboard of Laurentia at 1.75–1.74 Ga. The composite Yavapai Province was accreted to the margin of Laurentia during the 1.72–1.69 Ga Yavapai orogeny. Later overprinting is associated with the ∼1.68–1.60 Ga Mazatzal and ∼1.47–1.37 Ga Picuris orogenies. Identification of distinct crustal terranes within the Yavapai Province supports models involving multiple arcs and back-arcs that were progressively assembled prior to their accretion to Laurentia, perhaps akin to the present-day Banda Sea in Indonesia.
Accurate estimation and monitoring of wildlife population trends is foundational to evidence-based conservation. Here, we use hierarchical modelling to estimate population trends for six species of management interest (coyotes; red foxes, white-tailed deer, gray foxes; eastern wild turkey, and bobcats) while accounting for observation error from a long-term camera trap survey conducted across the State of New York. We were able to detect population level trends in occurrence and abundance and produce spatially explicit predictions for all six species using a combination of single-species occupancy models and Royle-Nichols models. Coyote (mean λ = 1.22, 95 % CI = 0.85–1.82) and red fox (mean λ = 1.17, 95 % CI = 0.95–1.46) populations were widely distributed with stable populations across the sampling period from 2014 to 2021. White-tailed deer populations were highly abundant and displayed an increasing population trend (mean λ = 1.85, 95 % CI = 1.54–2.10). Eastern wild turkey occupancy remained low across the state despite displaying a slight increase in occupancy over the sampling period (mean ψ = 0.16, 95 % CI = 0.07–0.25). Gray fox occupancy was also low (mean ψ = 0.22, 95 % CI = 0.12–0.29), consistent with growing concerns over the species across North America. Despite recent recoveries elsewhere, bobcat populations in New York State displayed very low occupancy (mean ψ = 0.07, 95 % CI = 0.02–0.12), highlighting the necessity of monitoring to inform conservation action. We provide empirically supported management implications for each species and demonstrate the efficacy of long-term camera trapping to provide robust evidence on population trends while accounting for imperfect detections, over scales meaningful to species management and conservation.