Polychlorinated biphenyls (PCBs) continue to impact the environment due to historic and ongoing anthropogenic sources (for example, industrial and agricultural), despite their ban. Contaminated stormwater has been identified as a vector for PCB transport to many estuaries impaired by PCBs. Management of these regulated discharges is typically achieved by best management practices (BMPs). This review focuses on PCB reduction practices and BMPs to assist management decision making and provide information on the current state of the science. Studies have quantitatively demonstrated the efficacy of green infrastructure BMPs and gray infrastructure improvements to reduce PCB loads, and other studies have demonstrated qualitative reductions for other BMP types. This review also highlights the disconnect between PCB load reduction and PCB bioavailability when selecting a remediation strategy. Additionally, the review evaluates modeling approaches to assess PCB load reduction to inform management decisions and suggests why there are still significant barriers to implementation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235074","usgsCitation":"Needham, T.P., Majcher, E., Foss, E., and Devereux, O.H., 2024, Evaluation and review of best management practices for the reduction of polychlorinated biphenyls to the Chesapeake Bay: U.S. Geological Survey Scientific Investigations Report 2023–5074, 18 p., https://doi.org/10.3133/sir20235074.","productDescription":"iv, 18 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135599","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":425826,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5074/sir20235074.XML"},{"id":425825,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5074/images/"},{"id":425824,"rank":3,"type":{"id":39,"text":"HTML 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U.S. Geological Survey
5522 Research Park Drive
Catonsville, Maryland 21228
Numerous factors influence the timing of spring migration in birds, yet the relative importance of intrinsic and extrinsic variables on migration initiation remains unclear. To test for interactions among weather, migration distance, parasitism, and physiology in determining spring departure date, we used the Dark-eyed Junco (Junco hyemalis) as a model migratory species known to harbor diverse and common haemosporidian parasites. Prior to spring migration departure from their wintering grounds in Indiana, USA, we quantified the intrinsic variables of fat, body condition (i.e., mass ~ tarsus residuals), physiological stress (i.e., ratio of heterophils to lymphocytes), cellular immunity (i.e., leukocyte composition and total count), migration distance (i.e., distance to the breeding grounds) using stable isotopes of hydrogen from feathers, and haemosporidian parasite intensity. We then attached nanotags to determine the timing of spring migration departure date using the Motus Wildlife Tracking System. We used additive Cox proportional hazard mixed models to test how risk of spring migratory departure was predicted by the combined intrinsic measures, along with meteorological predictors on the evening of departure (i.e., average wind speed and direction, relative humidity, and temperature). Model comparisons found that the best predictor of spring departure date was average nightly wind direction and a principal component combining relative humidity and temperature. Juncos were more likely to depart for spring migration on nights with largely southwestern winds and on warmer and drier evenings (relative to cooler and more humid evenings). Our results indicate that weather conditions at take-off are more critical to departure decisions than the measured physiological and parasitism variables.
Climate-induced expansion of invasive hybridization (breeding between invasive and native species) poses a significant threat to the persistence of many native species worldwide. In the northern U.S. Rocky Mountains, hybridization between native cutthroat trout and non-native rainbow trout has increased in recent decades due, in part, to climate-driven increases in water temperature. It has been postulated that invasive hybridization may enhance physiological tolerance to climate-induced thermal stress because laboratory studies indicate that rainbow trout have a higher thermal tolerance than cutthroat trout. Here, we assessed whether invasive hybridization improves cardiac performance response to acute water temperature stress of native wild trout populations. We collected trout from four streams with a wide range of non-native admixture among individuals and with different temperature and streamflow regimes in the upper Flathead River drainage, USA. We measured individual cardiac performance (maximum heart rate, “MaxHR”, and temperature at arrhythmia, “ArrTemp”) during laboratory trials with increasing water temperatures (10–28°C). Across the study populations, we observed substantial variation in cardiac performance of individual trout when exposed to thermal stress. Notably, we found significant differences in the cardiac response to thermal regimes among native cutthroat trout populations, suggesting the importance of genotype-by-environment interactions in shaping the physiological performance of native cutthroat trout. However, rainbow trout admixture had no significant effect on cardiac performance (MaxHR and ArrTemp) within any of the three populations. Our results indicate that invasive hybridization with a warmer-adapted species does not enhance the cardiac performance of native trout under warming conditions. Maintaining numerous populations across thermally and hydrologically diverse stream environments will be crucial for native trout to adapt and persist in a warming climate.
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":70251695,"text":"70251695 - 2024 - A biodynamic model predicting copper and cadmium bioaccumulation in caddisflies: Linkages between field studies and laboratory exposures","interactions":[],"lastModifiedDate":"2024-02-23T12:42:15.770548","indexId":"70251695","displayToPublicDate":"2024-02-22T06:40:12","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7774,"text":"PLoSOne","active":true,"publicationSubtype":{"id":10}},"title":"A biodynamic model predicting copper and cadmium bioaccumulation in caddisflies: Linkages between field studies and laboratory exposures","docAbstract":"Hydropsyche and Arctopsyche are filter-feeding caddisflies (Order: Trichoptera; Family: Hydropsychidae) that are commonly used to monitor metal exposures in rivers. While tissue residue concentrations provide important bioaccumulation data regarding metal bioavailability, they do not provide information regarding the mechanisms of uptake and loss, or exposure history. This study examined the physiological processes that control Cu and Cd uptake and loss using a biokinetic bioaccumulation model. Larvae of each taxon were experimentally exposed to either water or food enriched with stable isotopes (65Cu and 106Cd). Dissolved Cu uptake (ku) was similar between species (2.6–3.4 L-1g 1d-1), but Cd uptake was 3-fold higher in Hydropsyche than Arctopsyche (1.85 L-1g 1d-1 and 0.60 L-1g 1d-1, respectively). Cu and Cd efflux rates (ke) were relatively fast (0.14 d-1–0.24 d-1) in both species, and may explain, in part, their metal tolerance to mine-impacted rivers. Food ingestion rates (IR), assimilation efficiency (AE) of 65Cu and 106Cd from laboratory diets were also derived and used in a biodynamic model to quantify the relative contribution of dissolved and dietary exposure routes. Results from the biodynamic model were compared to tissue concentrations observed in a long-term field study and indicated that because dissolved Cu and Cd exposures accounted for less than 20% of body concentrations of either taxon, dietary exposure was the predominant metal pathway. An estimation of exposure history was determined using the model to predict steady state concentrations. Under constant exposure conditions (dissolved plus diet), steady state concentrations were reached in less than 30 days, an outcome largely influenced by rapid efflux (ke).
Declining body size in fishes and other aquatic ectotherms associated with anthropogenic climate warming has significant implications for future fisheries yields, stock assessments and aquatic ecosystem stability. One proposed mechanism seeking to explain such body-size reductions, known as the gill oxygen limitation (GOL) hypothesis, has recently been used to model future impacts of climate warming on fisheries but has not been robustly empirically tested. We used brook trout (Salvelinus fontinalis), a fast-growing, cold-water salmonid species of broad economic, conservation and ecological value, to examine the GOL hypothesis in a long-term experiment quantifying effects of temperature on growth, resting metabolic rate (RMR), maximum metabolic rate (MMR) and gill surface area (GSA). Despite significantly reduced growth and body size at an elevated temperature, allometric slopes of GSA were not significantly different than 1.0 and were above those for RMR and MMR at both temperature treatments (15°C and 20°C), contrary to GOL expectations. We also found that the effect of temperature on RMR was time-dependent, contradicting the prediction that heightened temperatures increase metabolic rates and reinforcing the importance of longer-term exposures (e.g. >6 months) to fully understand the influence of acclimation on temperature–metabolic rate relationships. Our results indicate that although oxygen limitation may be important in some aspects of temperature–body size relationships and constraints on metabolic supply may contribute to reduced growth in some cases, it is unlikely that GOL is a universal mechanism explaining temperature–body size relationships in aquatic ectotherms. We suggest future research focus on alternative mechanisms underlying temperature–body size relationships, and that projections of climate change impacts on fisheries yields using models based on GOL assumptions be interpreted with caution.
","language":"English","publisher":"The Company of Biologists Ltd","doi":"10.1242/jeb.246477","usgsCitation":"Lonthair, J., Wegner, N., Cheng, B.S., Fangue, N., O'Donnell, M.J., Regish, A.M., Swenson, J.D., Argueta, E., McCormick, S.D., Letcher, B., and Komoroske, L., 2024, Smaller body size under warming is not due to gill-oxygen limitation in a coldwater salmonid: Journal of Experimental Biology, v. 227, no. 4, jeb246477, 12 p., https://doi.org/10.1242/jeb.246477.","productDescription":"jeb246477, 12 p.","ipdsId":"IP-154954","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":488658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1242/jeb.246477","text":"Publisher Index Page"},{"id":484064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"227","issue":"4","noUsgsAuthors":false,"publicationDate":"2024-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Lonthair, Joshua K.","contributorId":352930,"corporation":false,"usgs":false,"family":"Lonthair","given":"Joshua K.","affiliations":[{"id":84305,"text":"Department of Environmental Conservation; 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University of Massachusetts at Amherst","active":true,"usgs":false}],"preferred":false,"id":932496,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932497,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"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":932498,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Komoroske, Lisa M","contributorId":152475,"corporation":false,"usgs":false,"family":"Komoroske","given":"Lisa M","affiliations":[{"id":18933,"text":"NOAA Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":932499,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70273289,"text":"70273289 - 2024 - Improving ecosystem health in highly altered river basins: A generalized framework and its application to the Mississippi-Atchafalaya River Basin","interactions":[],"lastModifiedDate":"2026-01-05T15:34:32.384968","indexId":"70273289","displayToPublicDate":"2024-02-21T09:25:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Improving ecosystem health in highly altered river basins: A generalized framework and its application to the Mississippi-Atchafalaya River Basin","docAbstract":"Continued large-scale public investment in declining ecosystems depends on demonstrations of “success”. While the public conception of “success” often focuses on restoration to a pre-disturbance condition, the scientific community is more likely to measure success in terms of improved ecosystem health. Using a combination of literature review, workshops and expert solicitation we propose a generalized framework to improve ecosystem health in highly altered river basins by reducing ecosystem stressors, enhancing ecosystem processes and increasing ecosystem resilience. We illustrate the use of this framework in the Mississippi-Atchafalaya River Basin (MARB) of the central United States (U.S.), by (i) identifying key stressors related to human activities, and (ii) creating a conceptual ecosystem model relating those stressors to effects on ecosystem structure and processes. As a result of our analysis, we identify a set of landscape-level indicators of ecosystem health, emphasizing leading indicators of stressor removal (e.g., reduced anthropogenic nutrient inputs), increased ecosystem function (e.g., increased water storage in the landscape) and increased resilience (e.g., changes in the percentage of perennial vegetative cover). We suggest that by including these indicators, along with lagging indicators such as direct measurements of water quality, stakeholders will be better able to assess the effectiveness of management actions. For example, if both leading and lagging indicators show improvement over time, then management actions are on track to attain desired ecosystem condition. If, however, leading indicators are not improving or even declining, then fundamental challenges to ecosystem health remain to be addressed and failure to address these will ultimately lead to declines in lagging indicators such as water quality. Although our model and indicators are specific to the MARB, we believe that the generalized framework and the process of model and indicator development will be valuable in an array of altered river basins.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2024.1332934","usgsCitation":"McLellan, E.L., Suttles, K.M., Bouska, K.L., Ellis, J., Flotemersch, J.E., Goff, M., Golden, H.E., Hill, R.A., Hohman, T.R., Keerthi, S., Keim, R.F., Kleiss, B.A., Lark, T.J., Piazza, B.P., Renfro, A.A., Robertson, D., Schilling, K.E., Schmidt, T.S., and Waite, I.R., 2024, Improving ecosystem health in highly altered river basins: A generalized framework and its application to the Mississippi-Atchafalaya River Basin: Frontiers in Environmental Science, v. 12, 1332934, 19 p., https://doi.org/10.3389/fenvs.2024.1332934.","productDescription":"1332934, 19 p.","ipdsId":"IP-159346","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":498453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2024.1332934","text":"Publisher Index 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Florida has the longest coastline of any State in the contiguous United States, and its coastal resources are one of the main drivers of its economic growth. High-quality elevation data are beneficial for use in emergency management, especially for hurricane response, recovery, and mitigation, as well as for coastal zone management, flood risk management, infrastructure planning, agriculture, forestry, and natural resources management. Having regional or statewide elevation data coverage that was collected at about the same time allows for improved results from in-depth modeling and more meaningful analysis to support the State’s Chief Science Officer, Geographic Information Officer, State agencies, water management districts, and local governments that will use these data for decision making. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.
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National Geospatial Program
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 511
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"The hydrological effects of climate change are documented in many regions; however, climate-driven impacts to the source and transport of river nutrients remain poorly understood. Understanding the factors controlling nutrient dynamics across river systems is critical to preserve ecosystem function yet challenging given the complexity of landscape and climate interactions. Here, we harness a large regional dataset of nitrate (NO3–) yield, concentration, and isotopic composition (δ15N and δ18O) to evaluate the strength of hydroclimate and landscape variables in controlling the seasonal source and transport of NO3–. We show that hydroclimate strongly influenced the seasonality of river NO3–, producing distinct, source-dependent NO3– regimes across rivers from two mountain ranges. Riverine responses to hydroclimate were also constrained by watershed-scale topographic features, demonstrating that while regional climate strongly influences the timing of river NO3– transport, watershed topography plays a distinct role in mediating the sensitivity of river NO3– dynamics to future change.
","language":"English","publisher":"Springer Nature","doi":"10.1038/s43247-024-01235-8","usgsCitation":"Elmstrom, E., Holtgrieve, G., Scheuerell, M.D., Andrew J. Schauer, and Leazer, K., 2024, Climate and landform interact to control the source and transport of nitrate in Pacific Northwest rivers: Communications Earth and Environment, v. 5, 90, 13 p., https://doi.org/10.1038/s43247-024-01235-8.","productDescription":"90, 13 p.","ipdsId":"IP-149744","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487967,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s43247-024-01235-8","text":"Publisher Index Page"},{"id":486521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Washington","otherGeospatial":"British Columbia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.87855871265536,\n 34.69978264689745\n ],\n [\n -113.87855871265536,\n 34.0589425188774\n ],\n [\n -113.23223159100554,\n 34.0589425188774\n ],\n [\n -113.23223159100554,\n 34.69978264689745\n ],\n [\n -113.87855871265536,\n 34.69978264689745\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.3245432375632,\n 49.988705305763744\n ],\n [\n -122.3245432375632,\n 45.99397202023496\n ],\n [\n -119.56144227480337,\n 45.99397202023496\n ],\n [\n -119.56144227480337,\n 49.988705305763744\n ],\n [\n -122.3245432375632,\n 49.988705305763744\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationDate":"2024-02-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Elmstrom, Elizabeth J.","contributorId":355859,"corporation":false,"usgs":false,"family":"Elmstrom","given":"Elizabeth J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtgrieve, Gordon W.","contributorId":355860,"corporation":false,"usgs":false,"family":"Holtgrieve","given":"Gordon W.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scheuerell, Mark David 0000-0002-8284-1254","orcid":"https://orcid.org/0000-0002-8284-1254","contributorId":288621,"corporation":false,"usgs":true,"family":"Scheuerell","given":"Mark","email":"","middleInitial":"David","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andrew J. 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Schauer","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Leazer, Karrin","contributorId":355862,"corporation":false,"usgs":false,"family":"Leazer","given":"Karrin","affiliations":[{"id":12723,"text":"Western Washington University","active":true,"usgs":false}],"preferred":false,"id":938287,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70252515,"text":"70252515 - 2024 - PFAS river export analysis highlights the urgent need for catchment-scale mass loading data","interactions":[],"lastModifiedDate":"2024-03-27T12:12:29.714027","indexId":"70252515","displayToPublicDate":"2024-02-19T07:11:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5022,"text":"Environmental Science & Technology Letters","onlineIssn":"2328-8930","active":true,"publicationSubtype":{"id":10}},"title":"PFAS river export analysis highlights the urgent need for catchment-scale mass loading data","docAbstract":"Source apportionment of per- and polyfluoroalkyl substances (PFAS) requires an understanding of the mass loading of these compounds in river basins. However, there is a lack of temporally variable and catchment-scale mass loading data, meaning identification and prioritization of sources of PFAS to rivers for management interventions can be difficult. Here, we analyze PFAS concentrations and loads in the River Mersey to provide the first temporally robust estimates of PFAS export for a European river system and the first estimates of the contribution of wastewater treatment works (WwTWs) to total river PFAS export. We estimate an annual PFAS export of 68.1 kg for the River Mersey and report that the yield of perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) in the catchment is among the highest recorded globally. Analysis of river and WwTW loads indicates approximately one-third of PFOA emitted from WwTWs is potentially stored in the catchment and approximately half of PFOS transported by the River Mersey may not originate from WwTWs. As governments move toward regulation of PFAS in WwTW effluents, our findings highlight the complexity of PFAS source apportionment and the need for catchment-scale mass loading data. This study indicates that strategies for reducing PFAS loading that focus solely on WwTW effluents may not achieve river water quality targets.
Water production from petroleum (oil and natural gas) wells is a topic of increasing environmental and economic importance, yet quantification efforts have been limited to date, and patterns between and within petroleum plays are largely unscrutinized. Additionally, classification of reservoirs as “unconventional” (also known as “continuous”) carries scientific and regulatory importance, but in some cases the distinction from \"conventional\" wells is unclear. Using water, oil, and gas production data, we calculated a set of quantitative metrics that elucidate trends in the water-to-petroleum ratio over the life of each producing well. The percent growth of the water-to-petroleum ratio quantifies the degree to which a well “waters out” over time; values calculated for 153,900 wells in 18 oil and gas plays show generally much higher values for conventional wells than for continuous/unconventional wells. Analysis of the percent growth along with the slope and median metrics reveals greater variation between conventional plays and between continuous (unconventional) plays than previously recognized. Further, an example from the Bakken Formation in the Williston Basin, USA, illustrates that, within a single play, the metrics provide insight into spatial variation of water production trends, as influenced by geology and reservoir characteristics. By quantifying the variability of water production trends within individual plays and between plays, including differences between conventional and continuous (unconventional) plays, these results provide a more nuanced view of water production from oil and gas wells than has previously been possible and they illustrate the degree to which water management considerations vary spatially and temporally.
The introduction of iterative ensemble smoothers (IES) for parameter calibration opens avenues for expanding parameter space in surface water hydrologic modeling. Here, we have introduced independent parameters into a model calibration experiment to estimate errors in rainfall forcing data. This approach has the potential to estimate rainfall errors using other hydrological observations and to improve model calibration. Using high-resolution rain gauge data, we estimated “real” rainfall errors across the Turkey River watershed at storm and daily scales. Tests on synthetic and real-world scenarios successfully estimated errors correlated with observed values – even at daily scales. However, a bias remained from model parameter compensation, and identifying errors was challenging for low precipitation and snowfall. Despite synthetic results showing good error correlation, the biases in parameter identification masked potential improvements in hydrological calibration. This study highlights the potential of IES to provide additional information on rainfall errors, even only using streamflow observations.
Summer water temperatures in the Skykomish, Snoqualmie, and Middle Fork Snoqualmie Rivers in western Washington have in recent decades exceeded the water temperature criteria for aquatic life uses set by the Washington Department of Ecology. This temperature increase is of particular concern because these rivers provide critical habitat for several salmonid populations, including Endangered Species Act-listed Chinook salmon (Onchorhynchus tshawytscha), steelhead trout (O. mykiss), and bull trout (Salvelinus confluentus), thus helping sustain Endangered Species Act-listed Southern Resident orcas (Orcinus orca). To inform salmonid restoration efforts within these rivers, this study used high-resolution thermal infrared (TIR) and three-band red, green, blue imagery acquired from repeated airborne surveys conducted in August 2020 and 2021 to (1) quantify longitudinal stream temperature profiles (LTPs) and (2) identify and characterize significant thermal features (STFs), including cold-water anomalies that could represent thermal refuges and serve as salmonid habitat. In addition, drag-probe water temperature surveys (“float surveys”) were performed on the Skykomish and Middle Fork Snoqualmie Rivers during August–September 2020 and on a segment of the Middle Fork Snoqualmie River in August 2021. These float surveys were intended to evaluate this thermal profiling method in comparison to airborne TIR surveys, by employing a novel method of processing float survey data to adjust for diurnal heating.
The Middle Fork Snoqualmie River warmed about 7 degrees Celsius (°C) from upstream to downstream in the 2020 airborne TIR survey and 9 °C in the 2021 airborne TIR survey, and the Snoqualmie River warmed about 4 °C in both surveys. The water temperature of the Skykomish River cooled in the 2020 and 2021 surveys, primarily because of cold inflow from the Sultan River. The overall shapes of airborne TIR LTPs of the same river were similar in the 2020 and 2021 surveys, with increasing and decreasing gradients in temperature tending to be nearly parallel over the same reaches and abrupt changes in temperature typically identified at the same locations. A total of 854 STFs were identified in the 2020 TIR imagery, and 732 STFs were identified in the 2021 TIR imagery. Interannual persistence was detected in 36.4 to 61.3 percent of lateral groundwater, side channel, and small tributary STFs, depending on the river surveyed, and in 14.8 to 28.7 percent of hyporheic and diffuse groundwater STFs. Hyporheic flow was commonly detected at the downstream end of a riffle, but not often detected directly downstream from large woody debris. Shade from riparian vegetation did not reduce water temperatures but rather maintained the water temperature recorded just upstream from the shaded section.
The adjusted average water temperature profiles from the float surveys were comparable to the LTPs derived from the airborne TIR surveys, with differences in temperature gradient primarily because the surveys were performed under different streamflow, radiation, and shading conditions. Though float surveys were found to be a valuable means of obtaining thermal profiles comparable to profiles obtained by airborne TIR surveys, one key advantage of airborne TIR surveys is that they may be used to precisely locate STFs over long distances, during a short survey duration, and in areas inaccessible to most watercraft.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235146","collaboration":"Prepared in cooperation with the Tulalip Tribes","usgsCitation":"Restivo, D.E., Diabat, M., Miwa, C., and Bright, V.A.L., 2024, Comparison of longitudinal stream temperature profiles and significant thermal features from airborne thermal infrared and float surveys of the Skykomish, Snoqualmie, and Middle Fork Snoqualmie Rivers, King and Snohomish Counties, Washington, summer 2020 and 2021: U.S. Geological Survey Scientific Investigations Report 2023–5146, 31 p., https://doi.org/10.3133/sir20235146.","productDescription":"Report: viii, 31 p.; Data Release","numberOfPages":"31","onlineOnly":"Y","ipdsId":"IP-139968","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":428021,"rank":3,"type":{"id":39,"text":"HTML 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Data Release","description":"Restivo, D.E., Diabat, M., Miwa, C., Bright, V.A.L., Seguin, C.M., Boucher, C.D., David, J.E., and Pouley, M., 2023, Water temperature mapping of the Skykomish, Snoqualmie, and Middle Fork Snoqualmie Rivers, Washington— Longitudinal stream temperature profiles, significant thermal features, and airborne thermal infrared and RGB imagery mosaics: U.S. Geological Survey data release, https://doi.org/10.5066/P9FJCM8N.","linkHelpText":"Water temperature mapping of the Skykomish, Snoqualmie, and Middle Fork Snoqualmie Rivers, Washington— Longitudinal stream temperature profiles, significant thermal features, and airborne thermal infrared and RGB imagery mosaics"}],"country":"United States","state":"Washington","county":"King County, Snohomish County","otherGeospatial":"Skykomish, Snoqualmie, and Middle Fork Snoqualmie 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Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
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 County, Dubuque County, Jackson County, Johnson County, Jones County, Linn 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Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"The chytrid insurance hypothesis: Integrating parasitic chytrids into a biodiversity–ecosystem functioning framework for phytoplankton–zooplankton population dynamics","docAbstract":"In temperate lakes, eutrophication and warm temperatures can promote cyanobacteria blooms that reduce water quality and impair food-chain support. Although parasitic chytrids of phytoplankton might compete with zooplankton, they also indirectly support zooplankton populations through the “mycoloop”, which helps move energy and essential dietary molecules from inedible phytoplankton to zooplankton. Here, we consider how the mycoloop might fit into the biodiversity–ecosystem functioning (BEF) framework. BEF considers how more diverse communities can benefit ecosystem functions like zooplankton production. Chytrids are themselves part of pelagic food webs and they directly contribute to zooplankton diets through spore production and by increasing host edibility. The additional way that chytrids might support BEF is if they engage in “kill-the-winner” dynamics. In contrast to grazers, which result in “eat-the-edible” dynamics, kill-the-winner dynamics can occur for host-specific infectious diseases that control the abundance of dominant (in this case inedible) hosts and thus limit the competitive exclusion of poorer (in this case edible) competitors. Thus, if phytoplankton diversity provides functions, and chytrids support algal diversity, chytrids could indirectly favour edible phytoplankton. All three mechanisms are linked to diversity and therefore provide some “insurance” for zooplankton production against the impacts of eutrophication and warming. In our perspective piece, we explore evidence for the chytrid insurance hypothesis, identify exceptions and knowledge gaps, and outline future research directions.
The effects of agriculture and flood control practices accrued over more than a century have impaired aquatic habitats and their fish communities in the Mississippi Alluvial Valley, the historic floodplain of the Lower Mississippi River prior to leveeing. As a first step to conservation planning and adaptive management, we developed and tested a conceptual model of how changes to this floodplain have affected stream environments and fish assemblages. The model is deliberately simple in structure because it needs to be understood by stakeholders ranging from engineers to farmers who must remain engaged to ensure effective conservation. Testing involved multivariate correlative analyses that included descriptors of land setting, water quality, and fish assemblages representing 376 stream samples taken over two decades and ranging in Strahler stream order from 1 to 8. The conceptual model was adequately corroborated by empirical data, but with unexplained variability that is not uncommon in field surveys where gear biases, temporal biases, and scale biases prevent accurate characterizations. Our conceptual model distinguishes three types of conservation actions relevant to large agricultural floodplains: reforestation of large parcels and riparian zone conservation, in-channel interventions and connectivity preservation, and flow augmentation. Complete restoration of the floodplain may not be an acceptable option to the agriculture community. However, in most cases the application of even the most basic measures can support the return of sensitive aquatic species. We suggest that together these types of conservation actions can bring improved water properties to impacted reaches, higher reach biodiversity, more intolerant species, and more rheophilic fishes.
Metabolism estimates organic carbon accumulation by primary productivity and removal by respiration. In rivers it is relevant to assessing trophic status and threats to river health such as hypoxia as well as greenhouse gas fluxes. We estimated metabolism in 17 rivers of the Illinois River basin (IRB) for a total of 15,176 days, or an average of 2.5 years per site. Daily estimates of gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem productivity (NEP), and the air-water gas exchange rate constant (K600) are reported, along with ancillary data such as river temperature and saturated dissolved oxygen concentration, barometric pressure, and river depth and discharge. Workflows for metabolism estimation and quality assurance are described including a new method for estimating river depth. IRB rivers are dominantly heterotrophic; however, autotrophy was common in river locations coinciding with reported harmful algal blooms (HABs) events. Metabolism of these regulated Midwestern U.S. rivers can help assess the causes and consequences of excessive algal blooms in rivers and their role in river ecological health.
Living shorelines with salt marsh species, rock breakwaters, and sand nourishment were built along the coastal areas in the Glenn Martin National Wildlife Refuge, Maryland, in 2016 in response to Hurricane Sandy (2012). The Fog Point living shoreline at Glenn Martin National Wildlife Refuge was designed with the “headland - breakwater - embayment” pattern. Scientists from the U.S. Geological Survey, Northeastern University, U.S. Fish and Wildlife Service, and Louisiana State University studied wave, current, and sediment dynamics to assess the effectiveness of the Fog Point living shoreline structures in terms of wave attenuation and erosion reduction. Wave gages, current meters, sediment traps, sediment tiles, and lateral erosion pins were deployed along the Fog Point shoreline during February 10–14, 2020. Because of COVID-19 pandemic travel restrictions, sensors were not retrieved until August 25, 2021, which was 18 months after field deployment, resulting in tremendous loss or damage of sensors and sediment measurements.
Monitoring data indicated that wave heights were substantially reduced at locations behind the breakwater (headland) compared to the wave heights in the offshore location, but not at the location in the control area (the embayment). Current patterns and current velocities at the location behind the breakwater were complex and changed dramatically compared to the current patterns and current velocities offshore. Sediments were blocked by the breakwater most of the time except during periods of storms with wave heights larger than 0.9 meter, when waves overtopped the breakwater and brought sediments to the tidal flat and salt marshes behind the breakwater. Behind the breakwater, both sediment deposition and erosion were observed during the 18 months of monitoring. Continued low elevation marsh edge erosion from wave undercutting along the embayment was observed, especially at the existing wave-cut gullies.
Monitoring results indicate that the “breakwater + marsh planting” structure along the Fog Point shoreline has limited shoreline protection capacity. Marsh edge erosion behind the breakwater was likely caused by the limited sediment supply from marine sources for transport and delivery, as well as the effects of circulation and current velocity on the settling and deposition of suspended sediments from eroded marshes. Marsh edge erosion continued in the embayment or control area where no shoreline restoration structures were implemented. Long-term (decadal scale) monitoring and adaptive management of living shoreline structures could help to assess the effectiveness of wave attenuation for reducing shoreline erosion and enhancing vegetation growth for trapping sediments and the effectiveness of marsh surface elevation growth for keeping pace with sea level rise.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20241004","issn":"2331-1258","collaboration":"Prepared in collaboration with Northeastern University, U.S. Fish and Wildlife Service, and Louisiana State University","usgsCitation":"Wang, H., Chen, Q., Capurso, W.D., Niemoczynski, L.M., Wang, N., Zhu, L., Snedden, G.A., Whitbeck, M., Wilson, C.A., and Brownley, M., 2024, Monitoring of wave, current, and sediment dynamics along the Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland: U.S. Geological Survey Open-File Report 2024–1004, 32 p., https://doi.org/10.3133/ofr20241004.","productDescription":"Report: x, 32 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-153204","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":499204,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116048.htm","linkFileType":{"id":5,"text":"html"}},{"id":425618,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TXZX5W","text":"USGS data release","linkHelpText":"Field observation of wind waves and current velocity (2020) along the Fog Point Living Shoreline, Maryland"},{"id":425617,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2024/1004/ofr20241004.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2024-1004 XML"},{"id":425616,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20241004/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2024-1004 HTML"},{"id":425615,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2024/1004/images"},{"id":425614,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2024/1004/ofr20241004.pdf","size":"5.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2024-1004"},{"id":425613,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2024/1004/coverthb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Glenn Martin National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.16645677294429,\n 38.13763711090462\n ],\n [\n -76.16645677294429,\n 37.8778983810208\n ],\n [\n -75.85669162075443,\n 37.8778983810208\n ],\n [\n -75.85669162075443,\n 38.13763711090462\n ],\n [\n -76.16645677294429,\n 38.13763711090462\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506–3152
Chemical changes in hot springs, as recorded by thermal waters and their deposits, provide a window into the evolution of the postglacial hydrothermal system of the Yellowstone Plateau Volcanic Field. Today, most hydrothermal travertine forms to the north and south of the ca. 631 ka Yellowstone caldera where groundwater flow through subsurface sedimentary rocks leads to calcite saturation at hot springs. In contrast, low-Ca rhyolites dominate the subsurface within the Yellowstone caldera, resulting in thermal waters that rarely deposit travertine. We investigated the timing and origin of five small travertine deposits in the Upper and Lower Geyser Basins to understand the conditions that allowed for travertine deposition. New 230Th-U dating, oxygen (δ18O), carbon (δ13C), and strontium (87Sr/86Sr) isotopic ratios, and elemental concentrations indicate that travertine deposits within the Yellowstone caldera formed during three main episodes that correspond broadly with known periods of wet climate: 13.9−13.6 ka, 12.2−9.5 ka, and 5.2−2.9 ka. Travertine deposition occurred in response to the influx of large volumes of cold meteoric water, which increased the rate of chemical weathering of surficial sediments and recharge into the hydrothermal system. The small volume of intracaldera travertine does not support a massive postglacial surge of CO2 within the Yellowstone caldera, nor was magmatic CO2 the catalyst for postglacial travertine deposition.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B37317.1","usgsCitation":"Harrison, L.N., Hurwitz, S., Paces, J., Whitlock, C., Peek, S., and Licciardi, J., 2024, Travertine records climate-induced transformations of the Yellowstone hydrothermal system from the late Pleistocene to the present: GSA Bulletin, v. 136, no. 9-10, p. 3605-3618, https://doi.org/10.1130/B37317.1.","productDescription":"14 p.","startPage":"3605","endPage":"3618","ipdsId":"IP-149989","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":440430,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/gsab.s.24891144","text":"External Repository"},{"id":428360,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Terrace Spring","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.854,\n 44.6583\n ],\n [\n -110.854,\n 44.641667\n ],\n [\n -110.841667,\n 44.641667\n ],\n [\n -110.841667,\n 44.6583\n ],\n [\n -110.854,\n 44.6583\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"136","issue":"9-10","noUsgsAuthors":false,"publicationDate":"2024-02-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Lauren N. 0000-0002-6621-5958","orcid":"https://orcid.org/0000-0002-6621-5958","contributorId":336192,"corporation":false,"usgs":false,"family":"Harrison","given":"Lauren","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":900110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":900111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paces, James B. 0000-0002-9809-8493","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":118216,"corporation":false,"usgs":true,"family":"Paces","given":"James B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":900112,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitlock, Cathy","contributorId":79745,"corporation":false,"usgs":false,"family":"Whitlock","given":"Cathy","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":900113,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":900114,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Licciardi, Joseph","contributorId":229595,"corporation":false,"usgs":false,"family":"Licciardi","given":"Joseph","affiliations":[{"id":41689,"text":"U. New Hampshire","active":true,"usgs":false}],"preferred":false,"id":900115,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70251288,"text":"sir20235143 - 2024 - Water-level and recoverable water in storage changes, High Plains Aquifer, predevelopment to 2019 and 2017 to 2019","interactions":[],"lastModifiedDate":"2026-01-30T19:56:30.550181","indexId":"sir20235143","displayToPublicDate":"2024-02-13T07:37:40","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":"2023-5143","displayTitle":"Water-Level and Recoverable Water in Storage Changes, High Plains Aquifer, Predevelopment to 2019 and 2017 to 2019","title":"Water-level and recoverable water in storage changes, High Plains Aquifer, predevelopment to 2019 and 2017 to 2019","docAbstract":"The High Plains aquifer underlies 111.8 million acres (about 175,000 square miles) in parts of eight States: Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. Water-level declines began in parts of the High Plains aquifer soon after the beginning of substantial groundwater irrigation (about 1950). This report presents water-level changes and change in recoverable water in storage in the High Plains aquifer from predevelopment (about 1950) to 2019 and from 2017 to 2019.
Water-level changes from predevelopment to 2019, by well, ranged from a rise of 86 feet to a decline of 265 feet; the range for 99 percent of the wells was from a rise of 42 feet to a decline of 203 feet. Water-level changes from 2017 to 2019, by well, ranged from a rise of 34 feet to a decline of 27 feet; the range for 99 percent of the wells was from a rise of 11 feet to a decline of 11 feet. The area-weighted, average water-level changes in the aquifer were an overall decline of 16.5 feet from predevelopment to 2019 and a rise of 0.1 foot from 2017 to 2019. Recoverable water in storage in the aquifer in 2019 was about 2.91 billion acre-feet, which was a decline of about 286.4 million acre-feet since predevelopment and a rise of 1.6 million acre-feet from 2017 to 2019.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235143","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"McGuire, V.L., and Strauch, K.R., 2024, Water-level and recoverable water in storage changes, High Plains Aquifer, predevelopment to 2019 and 2017 to 2019: U.S. Geological Survey Scientific Investigations Report 2023–5143, 15 p., https://doi.org/10.3133/sir20235143.","productDescription":"Report: vi, 15 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-117286","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":425299,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5143/images/"},{"id":425296,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5143/coverthb.jpg"},{"id":425298,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5143/sir20235143.XML"},{"id":425300,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WPP01S","text":"USGS data release","linkHelpText":"Data from maps of water-level changes in the High Plains aquifer in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming, predevelopment (about 1950) to 2019 and 2017 to 2019"},{"id":425301,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235143/full"},{"id":499405,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_116026.htm","linkFileType":{"id":5,"text":"html"}},{"id":425297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5143/sir20235143.pdf","text":"Report","size":"3.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5143"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106,\n 44\n ],\n [\n -106,\n 32\n ],\n [\n -96,\n 32\n ],\n [\n -96,\n 44\n ],\n [\n -106,\n 44\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Fluvial silicon (Si) plays a critical role in controlling primary production, water quality, and carbon sequestration through supporting freshwater and marine diatom communities. Geological, biogeochemical, and hydrological processes, as well as climate and land use, dictate the amount of Si exported by streams. Understanding Si regimes—the seasonal patterns of Si concentrations—can help identify processes driving Si export. We analyzed Si concentrations from over 200 stream sites across the Northern Hemisphere to establish distinct Si regimes and evaluated how often sites moved among regimes over their period of record. We observed five distinct regimes across diverse stream sites, with nearly 60% of sites exhibiting multiple regime types over time. Our results indicate greater spatial and interannual variability in Si seasonality than previously recognized and highlight the need to characterize the watershed and climate variables that affect Si cycling across diverse ecosystems.
Large dam removal can trigger changes to physical and biological processes that influence vegetation dynamics in former reservoirs, along river corridors downstream of former dams, and at a river’s terminus in deltas and estuaries. We present the first comprehensive review of vegetation response to major fluvial disturbance caused by the world’s largest dam removal. After being in place for nearly a century, two large dams were removed along the Elwha River, Washington, USA, between 2011 and 2014. The exposure, erosion, transport, and deposition of large volumes of sediment and large wood that were impounded behind the dams created new fluvial surfaces where plant colonization and growth have occurred. In the former reservoirs, dam removal exposed ~290 ha of unvegetated sediment distributed on three main landforms: valley walls, high terraces, and dynamic floodplains. In addition to natural revegetation in the former reservoirs, weed control and seeding and planting of desirable plants influenced vegetation trajectories. In early years following dam removal, ~20.5 Mt of trapped sediment were eroded from the former reservoirs and transported downstream. This sediment pulse, in combination with transport of large wood, led to channel widening, an increase in gravel bars, and floodplain deposition. The primary vegetation responses along the river corridor were a reduction in vegetated area associated with channel widening, plant establishment on new gravel bars, increased hydrochory, and altered plant community composition on gravel bars and floodplains. Plant species diversity increased in some river segments. In the delta, sediment deposition led to the creation of ~26.8 ha of new land surfaces and altered the distribution and dynamics of intertidal water bodies. Vegetation colonized ~16.4 ha of new surfaces: mixed pioneer vegetation colonized supratidal beach, river bars, and river mouth bars, and emergent marsh vegetation colonized intertidal aquatic habitats. In addition to the sediment-dominated processes that have created opportunities for plant colonization and growth, biological processes such as restored hydrochory and anadromous fish passage with associated delivery of marine-derived nutrients may influence vegetation dynamics over time. Rapid changes to landforms and vegetation growth were related to the large sediment pulse in the early years following dam removal, and the rate of change is expected to attenuate as the system adjusts to natural flow and sediment regimes.
Large variations in redox-related water parameters, like pH and dissolved oxygen (DO), have been documented in New Hampshire (United States) drinking-water wells over the course of a few hours under pumping conditions. These findings suggest that comparable sub-daily variability in dissolved concentrations of redox-reactive and toxic arsenic (As) also may occur, representing a potentially critical public-health data gap and a fundamental challenge for long-term As-trends monitoring. To test this hypothesis, discrete groundwater As samples were collected approximately hourly during one day in May and again in August 2019 from three New Hampshire drinking-water wells (2 public-supply, 1 private) under active pumping conditions. Collected samples were assessed by laboratory analysis (total As [AsTot], As(III), As(V)) and by field analysis (AsTot) using a novel integrated biosensor system. Laboratory analysis revealed sub-daily variability (range) in AsTot concentrations equivalent to 16 % – 36 % of that observed in the antecedent 3-year bimonthly trend monitoring. Thus, the results indicated that, along with previously demonstrated seasonality effects, the timing and duration of pumping are important considerations when assessing trends in drinking-water As exposures and concomitant risks. Results also illustrated the utility of the field sensor for monitoring and management of AsTot exposures in near-real-time.