Geospatial products of land use and land cover are broadly used in many applications. For example, the annual national greenhouse gas inventory uses the National Land Cover Database, the Coastal Change Analysis Program, Landscape Fire and Resource Management Planning Tools, the Forest Inventory and Analysis, and the National Resources Inventory to represent the land use and management base of the United States and attribute sources and sinks of greenhouse gas emissions. Federally produced land use and land cover datasets for the United States, including those from the Multi-Resolution Land Characteristics Consortium, set the foundation for developing and informing applications such as land change, conservation, greenhouse gas monitoring, urban planning, agricultural production, ecosystem functions, and water quantity and use. No single land use and land cover product is optimal for all land use and land cover applications. Approaches for defining and mapping land use and land cover classes differ across Federal map products, reflecting the tailoring of product specifications to match specific agency needs. These differing approaches present a challenge when attempting to integrate and harmonize multiple land use and land cover products into single analysis or application frameworks. Nuanced understanding of how these products are designed and produced may not be immediately evident to users; however, the availability of a diverse suite of products also represents an opportunity, providing multiple approaches for observing landscape change. In response to the National Strategy to Advance an Integrated U.S. Greenhouse Gas Measurement, Monitoring, and Information System, this Multi-Resolution Land Characteristics Consortium-led interagency report presents (1) the current status of U.S. Federal land use and land cover products (as of May 2024), (2) existing synergies and integration among these federally produced land use and land cover products, (3) inherent challenges of creating a single consistent framework, and (4) strategies for collectively tackling these challenges to improve coordination and collaboration among data producers and facilitate the adoption of land use and land cover products for greenhouse gas monitoring and a variety of other applications.
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U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
El Paso County is the second-most populous county in Colorado and is projected to grow another 15 percent by 2030. Within El Paso County is the Upper Black Squirrel Creek Designated Groundwater Basin (Black Squirrel Basin), an area where surface water is scarce and water users rely primarily on groundwater from five different aquifers (the Upper Black Squirrel Creek alluvial aquifer and four bedrock aquifers within the Denver Basin aquifer system: the lower Dawson, Denver, Arapahoe, and Laramie-Fox Hills aquifers) to meet their needs. Currently (2024), land within the Upper Black Squirrel Creek Basin is primarily used for rural grazing and agriculture; however, municipal development is ongoing.
In 2021, the U.S. Geological Survey, in cooperation with the Upper Black Squirrel Creek Ground Water Management District, began a study to establish a baseline dataset and assess the groundwater resources of the aquifers within the Black Squirrel Basin. A network of 39 wells was established in 2021; discrete groundwater-level measurements were made bimonthly. Nine of the 39 wells were equipped with pressure transducers to record hourly groundwater-level data. Seven wells had statistically significant seasonal trends, and trends at 3 wells were negative. For the discrete data, 16 wells had a significant trend for the study period, and 4 wells had negative trends. For the time-series data, 8 wells had significant trends, and 3 wells had negative trends.
Potentiometric surface maps were created for this study using discrete, static groundwater levels measured in April 2023. These maps showed the estimated groundwater flow direction from the north-northwest to the south-southeast in the alluvial aquifer and from the northwest to the east-southeast for the lower Dawson and Denver aquifer wells.
This study indicates the potential benefit of monitoring wells in the areas near municipal pumping. Additional monitoring could lead to a better understanding of connectivity between aquifers and be an important tool for assessing long-term sustainability of groundwater use.
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U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
The U.S. Geological Survey’s (USGS) National Water Monitoring Network is a network of networks that includes the Climate Response Network (CRN). The CRN is a network of wells selected to monitor the effects of climate variability, including droughts, on groundwater systems within the United States, Puerto Rico, and the U.S. Virgin Islands. The primary purpose of the CRN is to monitor these effects on groundwater levels in unconfined or near-surface confined aquifers that are minimally affected by pumping or other human-induced stresses.
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Visit https://www.usgs.gov/mission-areas/water-resources/observing-systems-division
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Groundwater drains to the land surface, generating the baseflow of streams, lakes, and wetlands. The hydrologic resilience of baseflow during prolonged dry periods and after disturbance can be assessed with evolving remote sensing analysis paired with localized monitoring of groundwater drainage features and creative model calibration strategies.
","language":"English","publisher":"Nature","doi":"10.1038/s44221-024-00376-6","usgsCitation":"Briggs, M., 2025, Enhanced hydrologic monitoring and characterization of groundwater drainage features: Nature Water, v. 3, p. 2-3, https://doi.org/10.1038/s44221-024-00376-6.","productDescription":"2 p.","startPage":"2","endPage":"3","ipdsId":"IP-172738","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":466645,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2025-01-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":923616,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70262095,"text":"ofr20241078 - 2025 - Review of the Lake Washington Ship Canal and Ballard Locks model, Seattle, Washington, 2014–20","interactions":[],"lastModifiedDate":"2025-07-10T15:35:39.574031","indexId":"ofr20241078","displayToPublicDate":"2025-01-13T14:18:55","publicationYear":"2025","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":"2024-1078","displayTitle":"Review of the Lake Washington Ship Canal and Ballard Locks Model, Seattle, Washington, 2014–20","title":"Review of the Lake Washington Ship Canal and Ballard Locks model, Seattle, Washington, 2014–20","docAbstract":"The Hiram M. Chittenden (Ballard) Locks and Lake Washington Ship Canal connect freshwater Lake Washington and saline Shilshole Bay of Puget Sound in Seattle, Washington. The locks and canal allow for ships to traverse this reach. Anadromous salmonids also migrate through, transitioning between saline and freshwater environments, and making use of a fish ladder at the locks when traveling upstream. WEST Consultants, Inc., constructed a two-dimensional hydrodynamic and water-quality model (CE-QUAL-W2) simulating flow, water temperature, and salinity for the Ballard Locks and the Lake Washington Ship Canal. An initial model was built for calendar years 2014–15, and the model was updated using a more recent and modern dataset for calendar years 2016–20. The U.S. Army Corps of Engineers requested that the U.S. Geological Survey review this model and its documentation to evaluate the technical aspects of its development and calibration. Findings from this review include the following:
Director, Oregon Water Science Center
U.S. Geological Survey
601 SW Second Avenue, Suite 1950
Portland, Oregon 97204
There is a growing need for consistent, large-scale estimates of water availability to identify and avoid potential conflicts among human and ecosystem uses of water. We present an assessment of water limitation, defined as the monthly balance (difference) between water supply (ws) and human consumptive water use (wc), for the conterminous United States (CONUS) during water years 2010–2020. We estimate that 26.7 million Americans, 8% of CONUS population, live in areas with chronic high or severe water limitation. Although ws greatly exceeds wc at the CONUS scale, water is limited locally or regionally due to spatial and temporal patterns in climate and wc. Our water limitation metric, the monthly supply and use index (SUI), peaked in 2012 during a widespread drought when 38% of the CONUS land area experienced elevated water stress. The central and southwestern U.S. experienced the highest SUI due to the combination of low ws and high wc, especially for crop irrigation. Spatial overlays of SUI and habitat ranges for fish species, including those of conservation concern, revealed that several species had notable proportions of their habitat exposed to high or severe water limitation during spawning season over the modeled time period, especially the Arkansas River shiner. Water supply (ws) was calculated from two CONUS, physically based, hydrologic models while wc was calculated from three CONUS models of water use for crop irrigation, thermoelectric power generation, and public supply. The ws and wc values were routed through a stream network and used to calculate water limitation for human populations and fish species at the scale of 12-digit hydrologic unit codes (HUC12s, 50-100 km2 catchments) and then analyzed using SUI. Evaluation of water availability at higher spatial and temporal resolution promotes more comprehensive analyses of the drivers of water availability and can be combined with complementary studies of water quality and water limiting thresholds to better understand the limitations on water availability.
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capability","interactions":[],"lastModifiedDate":"2025-03-06T20:35:44.371162","indexId":"70263419","displayToPublicDate":"2025-01-10T10:31:25","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesNumber":"PNNL-37047","title":"Integrated Hydro-terrestrial Modeling 2.0: Progress and path forward on building a national capability","docAbstract":"Growing societal pressures on U.S. water resources and the challenges inherent in understanding how future water risks may evolve are driving major investments to improve our knowledge of the integrated water cycle. This improved understanding as captured in innovations in our data, knowledge, and modeling capabilities, needs to be accelerated through better integration and coordination across scientific disciplines, programs, and U.S. agencies. The Integrated Hydro-Terrestrial Modeling (IHTM) community holds promise to accelerate the progress required to manage the U.S. water resources sustainably, equitably, and effectively. The U.S. Global Change Research Program (USGCRP) coordinates research on the impacts of global change on the water cycle through interagency collaboration. USGCRP agencies and their partners jointly held the IHTM 2.0 workshop for U.S. federal and non-federal scientists and managers in fall 2023, aiming to advance community modeling and integrated water resources management capabilities following open science principles. This workshop focused on developing both national and regional testbeds that employ state-of-the-art modeling approaches to explore gaps and opportunities for improving the representation and extensibility of hydrologic processes and modeling. Integrated regional testbeds in Mid-Atlantic, Great Lakes, Colorado River Basin, and Gulf Coast/Mississippi regions were proposed to leverage existing investments and seek actionable collaboration on issues such as water extremes, water quality, water use, and urbanization. Collaborations focused on advancing iterative cycles of model development and testing offer a means for regional scale studies to inform national scale modeling applications and yield nationally consistent modeling frameworks that are also locally relevant. This presentation will highlight key takeaways, findings, and future directions for the IHTM community that have been laid out in the IHTM 2.0 workshop report.","language":"English","publisher":"Pacific Northwest National Laboratory","usgsCitation":"Skalak, K., Voisin, N., Read, P., and Reinfelder, Y., 2025, Integrated Hydro-terrestrial Modeling 2.0: Progress and path forward on building a national capability, 98 p.","productDescription":"98 p.","ipdsId":"IP-172814","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":481982,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.pnnl.gov/publications/integrated-hydro-terrestrial-modeling-20-progress-and-path-forward-building-national","linkFileType":{"id":5,"text":"html"}},{"id":481983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":926910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Voisin, Nathalie","contributorId":242715,"corporation":false,"usgs":false,"family":"Voisin","given":"Nathalie","email":"","affiliations":[{"id":38914,"text":"Pacific Northwest National Laboratory","active":true,"usgs":false}],"preferred":false,"id":926912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Read, Patrick","contributorId":350756,"corporation":false,"usgs":false,"family":"Read","given":"Patrick","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":926911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reinfelder, Ying Fan","contributorId":350757,"corporation":false,"usgs":false,"family":"Reinfelder","given":"Ying Fan","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":926913,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70263252,"text":"70263252 - 2025 - Geochemical processes related to mined, milled, or natural metal deposits in a rapidly changing global environment","interactions":[],"lastModifiedDate":"2025-03-11T15:00:46.273017","indexId":"70263252","displayToPublicDate":"2025-01-10T08:25:45","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1758,"text":"Geochemistry: Exploration, Environment, Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical processes related to mined, milled, or natural metal deposits in a rapidly changing global environment","docAbstract":"The demand for metals and raw materials, such as nickel and copper, has been projected to expand in the coming decades, driven by the global energy transition, the need for green technologies, and expanding infrastructure. Consequently, the increasing extraction and production of mining waste can have adverse impacts on surrounding environments and human health. The aim of this thematic collection is to fill critical knowledge gaps in the present-day cycles of metal(loid)s from source to larger sinks, and the effect of environmental management, anthropogenic development, and climate change. Altogether, the studies have been conducted in different natural settings around the world and comprise investigations in laterites, a soil-medicinal plant system, watersheds, and banded iron formations, among others. The geochemical applications in tracing mineralization, its secondary products, and/or potential impact on the immediate environment are highly diverse with applied tools ranging from isotope tracers to major and trace element systematics. Particularly the use of rare earth elements, their patterns and anomalies are methods employed by several studies in this collection. We summarize the findings to offer a potential future direction for the use of geochemical tracing techniques in resource exploration in the context of climate change and environmental challenges.
","language":"English","publisher":"GeoScienceWorld","doi":"10.1144/geochem2024-062","usgsCitation":"Parviainen, A., Beisner, K.R., Blake, J., O'Sullivan, E., Miller, C., and Rosca, C., 2025, Geochemical processes related to mined, milled, or natural metal deposits in a rapidly changing global environment: Geochemistry: Exploration, Environment, Analysis, v. 25, no. 1, geochem2024-062, 6 p., https://doi.org/10.1144/geochem2024-062.","productDescription":"geochem2024-062, 6 p.","ipdsId":"IP-172207","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":481606,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, China, Indonesia, Iran, United 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Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Stream discharge determinations using slug additions and specific conductance","docAbstract":"Stream discharge is often determined by wading the stream and measuring the velocity at fixed widths and depths. However, there are conditions when wading measurements are not safe or the measurements are poor because of high turbulence, rocky streambeds, shallow or sheet flow, aquatic plants, or inaccessibility due to ice. Under these conditions, it is often preferable to determine discharge using salt slug addition and downstream measurement of salt concentration with time. A new method for determining stream discharge using specific conductance as a surrogate for salt concentrations is presented. The method adapts an approach that accurately calculates the specific conductance by utilizing ionic molal conductivities to determine the concentration of salt. The method was applied at four mountainous stream sites where a total of twenty-nine slug-additions were performed. The discharge determined from the new method was compared to four alternative methods including discharge from continuous injection, slug addition with discrete sample calibration, wading measurements with velocity measurement, and a stream gage. The discharge ranged from 21.5 to 778 L/s and the median difference between the new method and the traditional methods was -0.01%. Additionally, the p-value (0.75) determined from a paired t-test indicates that there is no significant difference between the discharge determined from the new and alternative discharge methods. The primary advantage of the new method is that it obviates the need to collect and analyze discrete samples to accurately quantify the specific conductance-salt surrogate relationship allowing for rapid, low-cost determination of discharge.","language":"English","publisher":"Wiley","doi":"10.1029/2024WR037771","usgsCitation":"McCleskey, R., Runkel, R.L., Murphy, S.F., and Roth, D.A., 2025, Stream discharge determinations using slug additions and specific conductance: Water Resources Research, v. 61, no. 1, e2024WR037771, 12 p., https://doi.org/10.1029/2024WR037771.","productDescription":"e2024WR037771, 12 p.","ipdsId":"IP-165553","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":466658,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr037771","text":"Publisher Index Page"},{"id":466114,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.50673744826068,\n 37.831337921925794\n ],\n [\n -119.50673744826068,\n 37.773982085357346\n ],\n [\n -119.36841180865719,\n 37.773982085357346\n ],\n [\n -119.36841180865719,\n 37.831337921925794\n ],\n [\n -119.50673744826068,\n 37.831337921925794\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"61","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"McCleskey, R. Blaine 0000-0002-2521-8052","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":205663,"corporation":false,"usgs":true,"family":"McCleskey","given":"R. 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As such, the State of Illinois initiated efforts to curb nutrient runoff over the last several decades. To evaluate progress towards these reductions, water-quality data were used to estimate incremental loads and yields of nitrate plus nitrite (NO3) and total phosphorus (TP) from 1997–2022 for 49 Illinois watersheds, defined using eight-digit hydrologic unit codes (HUC8), draining to the Mississippi River Basin. To estimate changes in NO3 and TP loads, recent loads from the period 2018 through 2022 were compared to baseline loads from 1997 through 2011. Nonpoint and point source loads, dissolved phosphorus (DP) loads, and water yields were also estimated. The sum of the incremental NO3 loads from the 49 HUC8s decreased 9% despite a 19% increase in water yield. Much of this decline occurred in HUC8s that had NO3 yields greater than 17 pounds per acre per year (lbs/acre/yr) during a 1997–2011 baseline period. The sum of all incremental HUC8 TP loads increased 25% despite a 27% reduction in point source discharge. Loads and yields were substantially larger for both NO3 and TP in the Chicago area. Outside the Chicago area, central and northern Illinois had higher NO3 yields than southern Illinois and a reverse pattern for TP where higher yields occur in southern Illinois. Nonpoint sources made up an estimated 82% and 78% of the NO3 and TP yields, respectively, across the HUC8s. In general, point source yields have mostly decreased over time, while nonpoint source yields varied depending on location and reflect the changes in the total yield.
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F.","contributorId":189364,"corporation":false,"usgs":false,"family":"McIsaac","given":"Gregory","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":922674,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261984,"text":"sir20245120 - 2025 - Groundwater-storage change in the north Phoenix aquifer, Arizona, 2020–23","interactions":[],"lastModifiedDate":"2025-01-08T15:06:42.999733","indexId":"sir20245120","displayToPublicDate":"2025-01-07T14:39:14","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5120","displayTitle":"Groundwater-Storage Change in the North Phoenix Aquifer, Arizona, 2020–23","title":"Groundwater-storage change in the north Phoenix aquifer, Arizona, 2020–23","docAbstract":"The city of Phoenix, Arizona, relies primarily on surface water for municipal water supply. The city also maintains wells to withdraw groundwater, particularly in times of drought and reduced surface-water supply, and to recharge groundwater when excess surface water is available. As of 2023, withdrawals from the aquifer in the northeastern part of the city are a small volume of water, less than 3,000 acre-feet in most years. Each year a similar volume of water is recharged through injection wells. The withdrawal wells are permitted to produce in total more than 20,000 acre-feet per year; increased pumping could lead to future groundwater-storage declines.
To better understand groundwater-storage change in the north Phoenix aquifer, a repeat microgravity monitoring network was established in 2020. Measurements of changes in Earth’s gravity provide a direct, non-invasive measurement of subsurface mass change. Groundwater-storage changes were small during the 2020–23 study period, consistent with the relatively small volumes of pumping and recharge. Groundwater levels measured in monitoring wells were stable or increased slightly during this period, although the number of monitoring wells within the area of the gravity monitoring network is sparse. In total, about 15,000 acre-feet of water were pumped and 31,000 acre-feet recharged through injection in the north Phoenix aquifer during the 2020–22 period. Within the monitored area, groundwater storage increased by a small amount, about 1,000 acre-feet, in 2020, and decreased by a larger amount, about 6,000 acre-feet, each year in 2021 and 2022. Storage decreased at 89 of 102 stations from 2020 to 2023. Groundwater-storage decreases greater than the volume of net pumping indicate down-gradient subflow from the aquifer is greater than recharge plus incoming subflow, drying of the unsaturated zone resulting from decreased land-surface recharge, or both.
At present (2023), the aquifer appears able to store and supply the relatively small amounts of water needed without excessive drawdown or harmful effects, such as land subsidence and surface inundation. If pumping or recharge increases in the future, the established repeat microgravity network is well suited to capture the spatial extent and magnitude of groundwater-storage changes in the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245120","collaboration":"Prepared in cooperation with the city of Phoenix Water Services","usgsCitation":"Kennedy, J.R., 2025, Groundwater-storage change in the north Phoenix aquifer, Arizona, 2020–23: U.S. Geological Survey Scientific Investigations Report 2024–5021, 18 p., https://doi.org/10.3133/sir20245120.","productDescription":"v, 18 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-160459","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":466450,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96Q1OZG","text":"USGS data release","linkHelpText":"Repeat microgravity data from Phoenix, Arizona, 2020-2023"},{"id":465834,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5120/covrthb.jpg"},{"id":465835,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5120/sir20245120.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"North Phoenix aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.1,\n 33.8667\n ],\n [\n -112.1,\n 33.6\n ],\n [\n -111.8,\n 33.6\n ],\n [\n -111.8,\n 33.8667\n ],\n [\n -112.1,\n 33.8667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Evaluating how weather, farm management, and soil conditions impact phosphorus (P) loss from agricultural sites is essential for improving our waterways in agricultural watersheds. In this study, rainfall characteristics, manure application timing, tillage, surface condition, and soil test phosphorus (STP) were analyzed to determine their effects on total phosphorus (TP) and dissolved phosphorus (DP) loss using 125 site-years of runoff data collected by the University of Wisconsin Discovery Farms and Discovery Farms Minnesota. Three linear mixed models (LMMs) were then used to evaluate the influence of those factors on TP and DP losses: (1) a model that included all runoff events, (2) manured sites only, and (3) precipitation events only. Results show that the timing of manure application relative to the timing of a runoff event only had a marginal association with P loads and concentrations, although the majority of the runoff events were collected after 10 days of manure application. Tillage was as influential factor, with greater DP loads and concentrations associated with no-till, especially during frozen conditions. Fields in this study had high STP values, but the model results only showed positive associations between DP load and DP flow-weighted mean concentration (FWMC) loss at the 0- to 15-cm depth. The precipitation event LMM (which included precipitation characteristics) was the model that resulted in the largest R2 value. While the predictive capacity of the LMMs was low, they did illuminate the relative importance of management and environmental variables on P loss, and can be used to guide future research on P loss in this region.
","language":"English","publisher":"Wiley","doi":"10.1002/jeq2.20662","usgsCitation":"Krueger, K., Thompson, A., Li, Q., Radatz, A., Cooley, E., Stuntebeck, T.D., Winslow, C., Oldfield, E., and Ruark, M., 2025, Exploring management and environment effects on edge-of-field phosphorus losses with linear mixed models: Journal of Environmental Quality, v. 54, no. 2, p. 450-464, https://doi.org/10.1002/jeq2.20662.","productDescription":"15 p.","startPage":"450","endPage":"464","ipdsId":"IP-154553","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466661,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jeq2.20662","text":"Publisher Index Page"},{"id":466018,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.67253208931788,\n 46.453472239766626\n ],\n [\n -96.53357725011335,\n 43.52335979339341\n ],\n [\n -91.25197772229393,\n 43.462001703986346\n ],\n [\n -91.04740751323666,\n 42.83358085977116\n ],\n [\n -90.69567476916163,\n 42.6339355953327\n ],\n [\n -88.04201458813054,\n 42.48198884581308\n ],\n [\n -87.61145222121533,\n 43.8914402724194\n ],\n [\n -92.82542026317009,\n 45.7061001895253\n ],\n [\n -96.67253208931788,\n 46.453472239766626\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"54","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Krueger, Kelsey 0000-0002-2412-0694","orcid":"https://orcid.org/0000-0002-2412-0694","contributorId":347852,"corporation":false,"usgs":false,"family":"Krueger","given":"Kelsey","affiliations":[{"id":83262,"text":"University of Wisconsin -Madison","active":true,"usgs":false}],"preferred":false,"id":922651,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Anita 0000-0002-6202-1742","orcid":"https://orcid.org/0000-0002-6202-1742","contributorId":236844,"corporation":false,"usgs":false,"family":"Thompson","given":"Anita","email":"","affiliations":[{"id":18002,"text":"University of Wisconsin - Madison","active":true,"usgs":false}],"preferred":false,"id":922652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Li, Qiang","contributorId":197310,"corporation":false,"usgs":false,"family":"Li","given":"Qiang","email":"","affiliations":[],"preferred":false,"id":922653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Radatz, Amber","contributorId":217384,"corporation":false,"usgs":false,"family":"Radatz","given":"Amber","email":"","affiliations":[{"id":39612,"text":"UW Madison-Extension, UW Discovery Farms","active":true,"usgs":false}],"preferred":false,"id":922654,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooley, Eric","contributorId":151059,"corporation":false,"usgs":false,"family":"Cooley","given":"Eric","email":"","affiliations":[{"id":18174,"text":"University of Wisconsin-Extension Discovery Farms","active":true,"usgs":false}],"preferred":false,"id":922655,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stuntebeck, Todd D. 0000-0002-8405-7295 tdstunte@usgs.gov","orcid":"https://orcid.org/0000-0002-8405-7295","contributorId":902,"corporation":false,"usgs":true,"family":"Stuntebeck","given":"Todd","email":"tdstunte@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922656,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Winslow, Christopher J.","contributorId":347853,"corporation":false,"usgs":false,"family":"Winslow","given":"Christopher J.","affiliations":[{"id":83263,"text":"Ohio Sea Grant College Program","active":true,"usgs":false}],"preferred":false,"id":922657,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oldfield, Emily 0000-0002-6181-1267","orcid":"https://orcid.org/0000-0002-6181-1267","contributorId":347854,"corporation":false,"usgs":false,"family":"Oldfield","given":"Emily","affiliations":[{"id":15310,"text":"Environmental Defense Fund","active":true,"usgs":false}],"preferred":false,"id":922658,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ruark, Matthew","contributorId":151056,"corporation":false,"usgs":false,"family":"Ruark","given":"Matthew","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":922659,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262101,"text":"70262101 - 2025 - Post-fire sediment yield from a western Sierra Nevada watershed burned by the 2021 Caldor Fire","interactions":[],"lastModifiedDate":"2025-01-14T15:40:44.912559","indexId":"70262101","displayToPublicDate":"2025-01-07T09:27:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5026,"text":"Earth and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Post-fire sediment yield from a western Sierra Nevada watershed burned by the 2021 Caldor Fire","docAbstract":"Watershed sediment yield commonly increases after wildfire, often causing negative impacts to downstream infrastructure and water resources. Post-fire erosion is important to understand and quantify because it is increasingly placing water supplies, habitat, communities, and infrastructure at risk as fire regimes intensify in a warming climate. However, measurements of post-fire sediment mobilization are lacking from many regions. We measured sediment yield from a forested, heavily managed 25.4-km2 watershed in the western Sierra Nevada, California, over 2 years following the 2021 Caldor Fire, by repeat mapping of a reservoir where sediment accumulated from terrain with moderate to high soil burn severity. Sediment yield was less than the geochronology-derived long-term average in the first year post-fire (conservatively estimated at 21.8–28.0 t/km2), low enough to be difficult to measure with uncrewed airborne system (UAS) and bathymetric sonar survey methods that are most effective at detecting larger sedimentary signals. In the second year post-fire the sediment delivery was 1,560–2,010 t/km2, an order of magnitude above long-term values, attributable to greater precipitation and intensive salvage logging. Hillslope erosion simulated by the Water Erosion Prediction Project (WEPP) model overestimated the measured amount by a factor of 90 in the first year and in the second year by a factor (1.9) that aligned with previously determined model performance in northern California. We encourage additional field studies, and validation of erosion models where feasible, to further expand the range of conditions informing post-fire hazard assessments and management decisions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024EA003939","usgsCitation":"East, A.E., Logan, J.B., Dartnell, P., Dow, H.W., Lindsay, D.N., and Cavagnaro, D.B., 2025, Post-fire sediment yield from a western Sierra Nevada watershed burned by the 2021 Caldor Fire: Earth and Space Science, v. 12, no. 1, e2024EA003939, 23 p., https://doi.org/10.1029/2024EA003939.","productDescription":"e2024EA003939, 23 p.","ipdsId":"IP-168883","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024ea003939","text":"Publisher Index Page"},{"id":466216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"2021 Caldor Fire burn zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.667,\n 39\n ],\n [\n -120.75,\n 39\n ],\n [\n -120.75,\n 38.5\n ],\n [\n -119.667,\n 38.5\n ],\n [\n -119.667,\n 39\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"12","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":923095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":923096,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dartnell, Peter 0000-0002-9554-729X","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":208208,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":923097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dow, Helen Willemien 0000-0001-6386-5560","orcid":"https://orcid.org/0000-0001-6386-5560","contributorId":299290,"corporation":false,"usgs":true,"family":"Dow","given":"Helen","email":"","middleInitial":"Willemien","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":923098,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsay, Donald N.","contributorId":216337,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","email":"","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":923099,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cavagnaro, David B.","contributorId":267181,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":923100,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70264245,"text":"70264245 - 2025 - Prioritizing chemicals of emerging concern in the Great Lakes Basin using covariance of chemical concentrations and diverse biological responses from a variety of species","interactions":[],"lastModifiedDate":"2025-03-10T14:26:58.704938","indexId":"70264245","displayToPublicDate":"2025-01-07T09:22:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Prioritizing chemicals of emerging concern in the Great Lakes Basin using covariance of chemical concentrations and diverse biological responses from a variety of species","docAbstract":"The Great Lakes Restoration Initiative aims to protect and restore the nation’s largest freshwater resource, in part, by furthering our understanding of the effects of contaminants of emerging concern (CECs) and chemical mixtures on aquatic and terrestrial organisms. To address this goal, an interagency team conducted field studies at sites along the Maumee River in Ohio, USA, in 2016–2017, monitoring CEC levels along with diverse in vitro and in vivo biological effects in ecologically relevant species (fathead minnows, tree swallows, and golden clams). The objective of the present work was to prioritize the CECs in these studies for further monitoring and assessment by determining if there are patterns in chemical–bioeffect relations across data sets, species, and response types that indicate relatively high or low hazard to aquatic life from CEC exposure. Of the 748 monitored chemicals, 425 were detected and were analyzed for covariance with bioeffects. All 748 chemicals were placed into 10 bins based on their frequencies of monitoring, detection, and covariance with bioeffects across studies and species. We describe how chemicals can be prioritized across bins to aid monitoring and assessment efforts. Our approach using effects-based monitoring data is especially useful for prioritizing chemicals with little or no traditional toxicity testing data. Similar evidence-based prioritizations will allow agencies to more efficiently allocate limited resources to improve the ability to protect aquatic and terrestrial organisms from adverse impacts due to contaminant exposure.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgae094","usgsCitation":"Vitense, K., Loken, L.C., Maloney, E., Blackwell, B., Collette, T.W., Corsi, S., Custer, C.M., Davenport, E., Kohno, S., and Hummel, S.E., 2025, Prioritizing chemicals of emerging concern in the Great Lakes Basin using covariance of chemical concentrations and diverse biological responses from a variety of species: Environmental Toxicology and Chemistry, v. 44, no. 3, p. 764-776, https://doi.org/10.1093/etojnl/vgae094.","productDescription":"13 p.","startPage":"764","endPage":"776","ipdsId":"IP-165045","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":487746,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgae094","text":"Publisher Index Page"},{"id":483135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","otherGeospatial":"Maumee River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.4,\n 41.75\n ],\n [\n -83.9,\n 41.75\n ],\n [\n -83.9,\n 41.35\n ],\n [\n -83.4,\n 41.35\n ],\n [\n -83.4,\n 41.75\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-01-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Vitense, Kelsey","contributorId":195720,"corporation":false,"usgs":false,"family":"Vitense","given":"Kelsey","email":"","affiliations":[],"preferred":false,"id":930184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maloney, Erin C","contributorId":223418,"corporation":false,"usgs":false,"family":"Maloney","given":"Erin C","affiliations":[{"id":40713,"text":"USACE Chicago District","active":true,"usgs":false}],"preferred":false,"id":930186,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackwell, Brett R.","contributorId":173601,"corporation":false,"usgs":false,"family":"Blackwell","given":"Brett R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":930187,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Collette, Timothy W.","contributorId":217482,"corporation":false,"usgs":false,"family":"Collette","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":930188,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":930189,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":930190,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davenport, Erik","contributorId":245994,"corporation":false,"usgs":false,"family":"Davenport","given":"Erik","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":930191,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kohno, Satomi","contributorId":264174,"corporation":false,"usgs":false,"family":"Kohno","given":"Satomi","email":"","affiliations":[],"preferred":false,"id":930192,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hummel, Stephanie E.","contributorId":244149,"corporation":false,"usgs":false,"family":"Hummel","given":"Stephanie","email":"","middleInitial":"E.","affiliations":[{"id":25470,"text":"U.S. Fish & Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":930193,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70264792,"text":"70264792 - 2025 - Metal-rich lacustrine sediments from legacy mining perpetuate copper exposure to aquatic-riparian food webs","interactions":[],"lastModifiedDate":"2025-03-24T15:15:08.725175","indexId":"70264792","displayToPublicDate":"2025-01-06T10:12:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Metal-rich lacustrine sediments from legacy mining perpetuate copper exposure to aquatic-riparian food webs","docAbstract":"Historic copper mining left a legacy of metal-rich tailings resulting in ecological impacts along and within Torch Lake, an area of concern in the Keweenaw Peninsula, Michigan, USA. Given the toxicity of copper to invertebrates, this study assessed the influence of this legacy on present day nearshore aquatic and terrestrial ecosystems. We measured the metal (Co, Cu, Ni, Zn, Cd) and metalloid (As) concentrations in sediment, pore water, surface water, larval and adult insects, and two riparian spider taxa collected from Torch Lake and a nearby reference lake. Overall, elevated metal and metalloid concentrations, particularly Cu, were measured in all sediment samples and some surface and pore water samples collected from Torch Lake. For instance, Cu concentrations in the Torch Lake sediment were ∼200% higher than the reference lake and all measured concentrations exceeded predicted effects concentrations by at least ninefold. Within larval insect tissues, we observed 160% higher Cu concentrations than measured in the reference lake, and Cu was the only measured element above predicted effects concentrations in Torch Lake. Adult insects collected at both lakes had similar metal concentrations irrespective of exposure levels. Yet we found 100% higher copper concentrations in Torch Lake riparian spiders, demonstrating elevated exposure risk to insectivores across the aquatic-terrestrial boundary. Our results highlight that other metals in the mixture may not be as concerning to adjacent riparian ecosystems, but copper remains a contaminant of concern in Torch Lake 60 years after mining ceased.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/inteam/vjae023","usgsCitation":"Perrotta, B.G., Kidd, K.A., Campbell, K.M., Croteau, M.N., Kane, T., Marcarelli, A., McCleskey, R., Paterson, G., Stricker, C.A., and Walters, D., 2025, Metal-rich lacustrine sediments from legacy mining perpetuate copper exposure to aquatic-riparian food webs: Integrated Environmental Assessment and Management, v. 21, no. 2, p. 414-424, https://doi.org/10.1093/inteam/vjae023.","productDescription":"11 p.","startPage":"414","endPage":"424","ipdsId":"IP-162301","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://digitalcommons.mtu.edu/michigantech-p2/1420","text":"Publisher Index Page"},{"id":483716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Keweenaw Peninsula, Torch Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.39059185784572,\n 47.193929098280194\n ],\n [\n -88.40680733939881,\n 47.19487803718532\n ],\n [\n -88.4300122526558,\n 47.17473802981718\n ],\n [\n -88.45978723171494,\n 47.150306379141526\n ],\n [\n -88.46223353281127,\n 47.13961178665928\n ],\n [\n -88.4590882885447,\n 47.130818916798404\n ],\n [\n -88.45153970230429,\n 47.131101806232955\n ],\n [\n -88.43113056172831,\n 47.155728212429736\n ],\n [\n -88.41072142115289,\n 47.150310604906245\n ],\n [\n -88.40485029852168,\n 47.15439926382797\n ],\n [\n -88.39143058965003,\n 47.17910442718053\n ],\n [\n -88.39059185784572,\n 47.193929098280194\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Perrotta, Brittany G. 0000-0003-2669-3047","orcid":"https://orcid.org/0000-0003-2669-3047","contributorId":301929,"corporation":false,"usgs":true,"family":"Perrotta","given":"Brittany","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":931698,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kidd, Karen A.","contributorId":201554,"corporation":false,"usgs":false,"family":"Kidd","given":"Karen","email":"","middleInitial":"A.","affiliations":[{"id":25502,"text":"McMaster University","active":true,"usgs":false}],"preferred":false,"id":931699,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":931700,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Croteau, Marie Noele 0000-0003-0346-3580 mcroteau@usgs.gov","orcid":"https://orcid.org/0000-0003-0346-3580","contributorId":895,"corporation":false,"usgs":true,"family":"Croteau","given":"Marie","email":"mcroteau@usgs.gov","middleInitial":"Noele","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":931701,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kane, Tyler 0000-0003-2511-7312 tkane@usgs.gov","orcid":"https://orcid.org/0000-0003-2511-7312","contributorId":195588,"corporation":false,"usgs":true,"family":"Kane","given":"Tyler","email":"tkane@usgs.gov","affiliations":[],"preferred":true,"id":931702,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marcarelli, Amy M.","contributorId":272244,"corporation":false,"usgs":false,"family":"Marcarelli","given":"Amy M.","affiliations":[{"id":56375,"text":"isu","active":true,"usgs":false}],"preferred":false,"id":931703,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCleskey, R. 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This represents a challenge to environmental managers, who must prioritize chemicals for management actions (e.g., restriction, regulation, remediation) but are often hindered by resource limitations. To help facilitate prioritization efforts, this study presents several strategies for deriving environmental hazard concentrations using publicly accessible data and open-source computational tools. Using a Great Lakes tributaries aquatic monitoring dataset as a case study, environmental hazard concentrations were obtained or derived for 334 organic chemicals. These concentrations were based on (1) current water quality guidelines; (2) apical screening values; (3) apical and (4) nonapical effect concentrations from the ECOTOXicology Knowledgebase; (5) in vitro effect concentrations from the ToxCast database; (6) cytotoxic burst concentrations collated from the Comptox Dashboard; (7) “estimated screening values” derived from modeled or estimated data and available from various regulatory and nonregulatory agencies; (8) pharmaceutical potency estimates from the MaPPFAST database; and (9) quantitative structure-activity relationship (QSAR)–derived acute toxicity estimates. Environmental fate data included aquatic half-lives and bioconcentration factors collated from the Comptox Dashboard or estimated using QSARs. To identify patterns that could be used for characterization, availability of ecotoxicological concentrations and environmental fate data were evaluated. Furthermore, exceedances of hazard concentrations were evaluated and compared across diverse ecotoxicological data types. Altogether, by providing detailed methodology and practical examples generated with real monitoring data, this study demonstrated that these hazard concentration derivation strategies can be efficiently and effectively used with large, complex datasets and identified critical considerations for future prioritization efforts.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/etojnl/vgae002","usgsCitation":"Maloney, E., Corsi, S., Pronschinske, M.A., DeCicco, L.A., Nott, M.A., Frisch, J.R., Fuller, N.W., Baldwin, A.K., Kimbrough, K., Edwards, M., Hummel, S.L., Vinas, N., and Villeneuve, D.L., 2025, Derivation and characterization of environmental hazard concentrations for chemical prioritization: A case study in the Great Lakes tributaries: Environmental Toxicology and Chemistry, https://doi.org/10.1093/etojnl/vgae002.","ipdsId":"IP-160548","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":482440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": 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effluent","interactions":[],"lastModifiedDate":"2025-09-16T15:17:24.885811","indexId":"70271467","displayToPublicDate":"2025-01-06T08:09:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Potential for biological effects of per- and polyfluoroalkyl substances in Great Lakes tributaries and associations with land cover and wastewater effluent","docAbstract":"Surface water concentrations of per- and polyfluoroalkyl substances (PFAS) and potential for resulting biological effects were estimated in a study using polar organic chemical integrative samplers (POCIS) from 60 tributary sites within 20 watersheds in the Great Lakes Basin in 2018. Sites represented a range of urban to agricultural, forested, and wetland land uses and included a gradient of wastewater treatment effluent from zero to 44% of annual streamflow. Several sites also had airport influence. Twenty-one of 32 targeted PFAS compounds were detected in POCIS samplers, of which, 16 had available POCIS sampling rates, enabling time-weighted water concentration estimates and comparison with available effects data. Estimated water concentrations were compared with published water quality guidelines (available for nine PFAS), effect concentrations reported in primary literature within the ECOTOX Knowledgebase for apical endpoints (10 PFAS) and nonapical endpoints (10 PFAS), and in vitro high-throughput screening data from the U.S. Environmental Protection Agency Toxicity Forecaster (ToxCast; 14 PFAS). Based on a conservative evaluation approach that was also weighted for persistence and limitations in available toxicological information, five individual PFAS, including perfluorooctanesulfonic acid, perfluorohexanesulfonic acid, perfluorobutanesulfonic acid, perfluorooctanoic acid, and perfluorononanoic acid were identified as warranting additional investigation. Possible increased potency of PFAS mixtures over individual chemical effects, estimated by summation of exposure-activity ratios (EARs) for chemicals that influence common ToxCast assays and specified gene targets, indicated that EAR values increased up to 5.6-fold over individual chemicals, with up to 14 chemicals contributing to mixture effect predictions. Potential for biological effects from PFAS, as estimated by summed exposure-activity ratios, were correlated with urban land use and the proportion of streamflow contributed by wastewater effluent.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1093/etojnl/vgae053","usgsCitation":"Corsi, S., Loken, L.C., Ankley, G.T., Alvarez, D.A., and Villeneuve, D.L., 2025, Potential for biological effects of per- and polyfluoroalkyl substances in Great Lakes tributaries and associations with land cover and wastewater effluent: Environmental Toxicology and Chemistry, v. 44, no. 6, p. 1706-1722, https://doi.org/10.1093/etojnl/vgae053.","productDescription":"17 p.","startPage":"1706","endPage":"1722","ipdsId":"IP-159605","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":495738,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/etojnl/vgae053","text":"Publisher Index Page"},{"id":495602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United Staes","otherGeospatial":"Great Lakes tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.57691865567881,\n 49.80505886092908\n ],\n [\n -92.57691865567881,\n 40.630914911656845\n ],\n [\n -75.84891837004692,\n 40.630914911656845\n ],\n [\n -75.84891837004692,\n 49.80505886092908\n ],\n [\n -92.57691865567881,\n 49.80505886092908\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"44","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-01-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loken, Luke C. 0000-0003-3194-1498 lloken@usgs.gov","orcid":"https://orcid.org/0000-0003-3194-1498","contributorId":195600,"corporation":false,"usgs":true,"family":"Loken","given":"Luke","email":"lloken@usgs.gov","middleInitial":"C.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ankley, Gerald T.","contributorId":361472,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald","middleInitial":"T.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":948871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alvarez, David A. 0000-0002-6918-2709","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":220763,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":948872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Villeneuve, Daniel L.","contributorId":361475,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","middleInitial":"L.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":948873,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265972,"text":"70265972 - 2025 - Hydrologic variability and plant composition drive relative abundance of marsh birds at created and reference marshes in southeastern Louisiana, U.S.A.","interactions":[],"lastModifiedDate":"2025-04-22T17:24:42.248319","indexId":"70265972","displayToPublicDate":"2025-01-05T12:21:52","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic variability and plant composition drive relative abundance of marsh birds at created and reference marshes in southeastern Louisiana, U.S.A.","docAbstract":"Coastal marsh loss occurs at an alarming pace globally, with extremely high rates along the northern Gulf of Mexico, particularly in Louisiana. In Louisiana, marsh creation projects combat wetland loss; however, biotic responses of vegetation and wildlife receive little to no consideration during and after construction. Habitat characteristics such as hydrologic processes, plant composition, and habitat structure affect the abundance of marsh birds, and understanding these features is important when creating suitable habitat for marsh birds. Our study compared hydrologic characteristics, plant composition, and habitat structure between created (n = 10) and reference (n = 9) sites across southeastern Louisiana and determined the relationship of these habitat characteristics to marsh bird relative abundance. We performed bird surveys (n = 766), including call-back surveys for secretive marsh birds, at all sites across three breeding seasons (2021–2023). We used drone imagery to determine plant composition and used water level recording devices to assess hydrologic characteristics. Our results indicate that hydrologic variation and plant composition are drivers of marsh bird relative abundance regardless of whether a marsh is created or not. While some habitat features differed between created and reference sites, our results indicated that created marshes can support similar abundances of marsh birds as reference sites, depending on what habitat features are present at the site. Our study demonstrates the importance of creating marshes that promote hydrologic connectivity and water level variability, which in turn supports diverse emergent vegetation communities and provides suitable habitat for a variety of marsh bird species.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.14376","usgsCitation":"Lipford, A., Moran, L., Fowler, D., and King, S.L., 2025, Hydrologic variability and plant composition drive relative abundance of marsh birds at created and reference marshes in southeastern Louisiana, U.S.A.: Restoration Ecology, v. 33, no. 3, e14376, 14 p., https://doi.org/10.1111/rec.14376.","productDescription":"e14376, 14 p.","ipdsId":"IP-166318","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":488490,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.14376","text":"Publisher Index Page"},{"id":484855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.68365742439656,\n 30.64538637262305\n ],\n [\n -91.68365742439656,\n 28.66657042786551\n ],\n [\n -88.1916582539898,\n 28.66657042786551\n ],\n [\n -88.1916582539898,\n 30.64538637262305\n ],\n [\n -91.68365742439656,\n 30.64538637262305\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Lipford, Aylett","contributorId":353640,"corporation":false,"usgs":false,"family":"Lipford","given":"Aylett","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":934208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moran, Leah L.K.","contributorId":353641,"corporation":false,"usgs":false,"family":"Moran","given":"Leah L.K.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":934209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fowler, Drew Nathan 0000-0001-9347-4579","orcid":"https://orcid.org/0000-0001-9347-4579","contributorId":341123,"corporation":false,"usgs":true,"family":"Fowler","given":"Drew Nathan","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934210,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":934211,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70262012,"text":"70262012 - 2025 - Automating physics-based models to estimate thermoelectric-power water use","interactions":[],"lastModifiedDate":"2025-01-10T17:08:02.343623","indexId":"70262012","displayToPublicDate":"2025-01-05T11:02:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Automating physics-based models to estimate thermoelectric-power water use","docAbstract":"Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2024.106265","usgsCitation":"Harris, M.A., Diehl, T.H., Gorman Sanisaca, L.E., Galanter, A.E., Lombard, M.A., Skinner, K.D., Chamberlin, C.A., McCarthy, B.A., Niswonger, R.G., Stewart, J.S., and Valseth, K., 2025, Automating physics-based models to estimate thermoelectric-power water use: Environmental Modelling and Software, v. 185, 106265, 16 p., https://doi.org/10.1016/j.envsoft.2024.106265.","productDescription":"106265, 16 p.","ipdsId":"IP-156740","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":466666,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envsoft.2024.106265","text":"Publisher Index Page"},{"id":466004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harris, Melissa A. 0000-0003-2659-9763 mharris@usgs.gov","orcid":"https://orcid.org/0000-0003-2659-9763","contributorId":1903,"corporation":false,"usgs":true,"family":"Harris","given":"Melissa","email":"mharris@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diehl, Timothy H. 0000-0001-9691-2212 thdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9691-2212","contributorId":546,"corporation":false,"usgs":true,"family":"Diehl","given":"Timothy","email":"thdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorman Sanisaca, Lillian E. 0000-0003-1711-3864","orcid":"https://orcid.org/0000-0003-1711-3864","contributorId":210381,"corporation":false,"usgs":true,"family":"Gorman Sanisaca","given":"Lillian","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":922693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lombard, Melissa A. 0000-0001-5924-6556 mlombard@usgs.gov","orcid":"https://orcid.org/0000-0001-5924-6556","contributorId":198254,"corporation":false,"usgs":true,"family":"Lombard","given":"Melissa","email":"mlombard@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - 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2025 - Leveraging airborne imaging spectroscopy and multispectral satellite imagery to map glacial sediment plumes in Kachemak Bay, Alaska","interactions":[],"lastModifiedDate":"2025-01-06T15:27:04.639948","indexId":"70261932","displayToPublicDate":"2025-01-03T09:14:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Leveraging airborne imaging spectroscopy and multispectral satellite imagery to map glacial sediment plumes in Kachemak Bay, Alaska","docAbstract":"Red snapper (Lutjanus campechanus) is an iconic marine fish species along the southeast United States coast. Despite its ecological and economic importance, surprisingly little is known about red snapper biology and habitat use on the southeast United States Atlantic continental shelf (SEUS). We used data from a long-term baited trap and video survey (2011–2022), as well as from remotely operated vehicle (ROV) sampling (2021–2023), to quantify temporal changes in relative abundance, patterns of spatial distribution, and habitat use of red snapper in the SEUS. Using generalized additive models, we showed that red snapper increased in relative abundance from 2011 to 2022 by 960% in traps and 1,141% in video samples. Red snapper relative abundance was highest in mid-shelf waters off the east coast of Florida, Georgia, and, to a lesser extent, off the Outer Banks of North Carolina; red snapper were less common off southern North Carolina and South Carolina. Highest relative abundance of red snapper occurred in locations with a moderate amount of natural structured habitat and high seafloor complexity and were never observed at randomly selected ROV stations (n = 197) lacking structured habitat. These results increase our understanding of the spatial and temporal distribution of red snapper, improve our knowledge of red snapper habitat use, and can be used when scaling local density estimates to the entire SEUS.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2024.107200","usgsCitation":"Bacheler, N., Patterson III, W., Tarnecki, J., Shertzer, K., Buckel, J., Hostetter, N.J., Pacifici, K., Zulian, V., and Bubley, W., 2025, Spatiotemporal dynamics and habitat use of red snapper (Lutjanus campechanus) on the southeastern United States Atlantic continental shelf: Fisheries Research, v. 281, 107200, 13 p., https://doi.org/10.1016/j.fishres.2024.107200.","productDescription":"107200, 13 p.","ipdsId":"IP-160875","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":486926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2024.107200","text":"Publisher Index Page"},{"id":482442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","otherGeospatial":"southeastern United States Atlantic continental shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.92593395494507,\n 33.15275092248328\n ],\n [\n -81.99045643689327,\n 31.10056957805797\n ],\n [\n -80.87712766876851,\n 28.48701241069105\n ],\n [\n -80.3042465673629,\n 31.325404220996276\n ],\n [\n -76.71024593975332,\n 34.122762076854926\n ],\n [\n -76.22924401859534,\n 35.13912357508609\n ],\n [\n -79.92593395494507,\n 33.15275092248328\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.13968222172028,\n 19.755747085043822\n ],\n [\n -155.13968222172028,\n 19.69242312727401\n ],\n [\n -155.07419576383438,\n 19.69242312727401\n ],\n [\n -155.07419576383438,\n 19.755747085043822\n ],\n [\n -155.13968222172028,\n 19.755747085043822\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"281","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bacheler, Nathan M.","contributorId":351435,"corporation":false,"usgs":false,"family":"Bacheler","given":"Nathan M.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":928514,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Patterson III, William F.","contributorId":351436,"corporation":false,"usgs":false,"family":"Patterson III","given":"William F.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":928515,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tarnecki, Joseph H.","contributorId":351437,"corporation":false,"usgs":false,"family":"Tarnecki","given":"Joseph H.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":928516,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shertzer, Kyle W.","contributorId":351439,"corporation":false,"usgs":false,"family":"Shertzer","given":"Kyle W.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":928517,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buckel, Jeffrey A.","contributorId":351441,"corporation":false,"usgs":false,"family":"Buckel","given":"Jeffrey A.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928518,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":928519,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pacifici, Krishna","contributorId":351444,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928520,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zulian, Viviane","contributorId":351446,"corporation":false,"usgs":false,"family":"Zulian","given":"Viviane","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":928521,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bubley, Walter J.","contributorId":351447,"corporation":false,"usgs":false,"family":"Bubley","given":"Walter J.","affiliations":[{"id":35670,"text":"South Carolina Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":928522,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70261980,"text":"70261980 - 2025 - Advancing the science of headwater streamflow for global water protection","interactions":[],"lastModifiedDate":"2025-01-27T16:46:01.883887","indexId":"70261980","displayToPublicDate":"2025-01-02T08:54:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17124,"text":"Nature Water","active":true,"publicationSubtype":{"id":10}},"title":"Advancing the science of headwater streamflow for global water protection","docAbstract":"The protection of headwater streams faces increasing challenges, exemplified by limited global recognition of headwater contributions to watershed resiliency and a recent US Supreme Court decision limiting federal safeguards. Despite accounting for ~77% of global river networks, the lack of adequate headwaters protections is caused, in part, by limited information on their extent and functions—in particular, their flow regimes, which form the foundation for decision-making regarding their protection. Yet, headwater streamflow is challenging to comprehensively measure and model; it is highly variable and sensitive to changes in land use, management and climate. Modelling headwater streamflow to quantify its cumulative contributions to downstream river networks requires an integrative understanding across local hillslope and channel (that is, watershed) processes. Here we begin to address this challenge by proposing a consistent definition for headwater systems and streams, evaluating how headwater streamflow is characterized and advocating for closing gaps in headwater streamflow data collection, modelling and synthesis.
","language":"English","publisher":"Nature","doi":"10.1038/s44221-024-00351-1","usgsCitation":"Golden, H.E., Christiensen, J., McMillan, H., Kelleher, C.A., Lane, C., Husic, A., Li, L., Ward, A., Hammond, J., Seybold, E.C., Jaeger, K.L., Zimmer, M.A., Sando, R., Jones, C., Segura, C., Mahoney, D.T., Price, A.N., and Chang, F., 2025, Advancing the science of headwater streamflow for global water protection: Nature Water, v. 3, p. 16-26, https://doi.org/10.1038/s44221-024-00351-1.","productDescription":"11 p.","startPage":"16","endPage":"26","ipdsId":"IP-161519","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":498448,"rank":2,"type":{"id":41,"text":"Open 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This report reviews the literature on how climate change is influencing visitor use in the United States and how visitor use may be affected in the future. Our goal is to provide the current state of the literature for managers of public lands and waters and provide foundational information for the development of a climate change vulnerability assessment methodology for visitor use within the National Park Service (that may be applicable to other federal lands and waters). Specifically, we investigate how seven different climate change factors may affect visitor use on public lands and waters. These factors consist of increasing temperatures; flooding, drought, and increased variability of precipitation; decreasing snowpack and earlier spring runoff; wildfires, smoke, and air quality; coastal hazards: hurricanes and sea level rise; harmful algal blooms (HABs); and zoonotic and vector-borne disease. The current research indicates that these factors are already affecting visitors to public lands and waters and continued effects in the future are likely as the climate warms. Additionally, we summarize existing research on how visitors to U.S. public lands and waters are adapting to climate change. 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Report","active":false,"publicationSubtype":{"id":3}},"title":"Wind River subbasin restoration: Annual report of U.S. Geological Survey activities January 2023 through December 2023","docAbstract":"We sampled juvenile wild Oncorhynchus mykiss (Steelhead Trout) in headwater streams of the Wind River, WA, to characterize population attributes and investigate life-history metrics, particularly migratory patterns, and early life-stage survival. We used passive integrated transponder (PIT) tagging and a series of instream PIT-tag interrogation systems (PTISs) to track juveniles and adults. The Wind River subbasin is considered a wild Steelhead refuge by Washington Department of Fish and Wildlife (WDFW). No hatchery Steelhead Trout have been released in the Wind River subbasin since 1997, and hatchery adults are estimated at less than one percent of spawners in most years. Over twenty years of Steelhead Trout status and trend monitoring and research in the subbasin is contributing to understanding of population response to numerous restoration actions in the subbasin, including removal of Hemlock Dam from Trout Creek in 2009, which had an inadequate adult ladder and contributed to increased water temperatures.
Data from our study, and companion work by Washington Department of Fish and Wildlife, are contributing to the Columbia Basin Fish and Wildlife Program (2008) Research, Monitoring, and Evaluation (RM&E) Strategy of Fish Population Status Monitoring. Specifically, this work addresses the sub-strategies of 1) Assessing the Status and Trends of Diversity of Natural Origin Fish Populations and Uncertainties Research regarding differing life histories of a wild Steelhead Trout population, 2) Assessing the Status and Trend of Adult Natural Origin Fish Populations, and 3) Monitoring and Evaluating the Effectiveness of Tributary Habitat Actions Relative to Environmental, Physical, or Biological Performance Objectives.
During summer and fall 2023, we PIT-tagged 1,294 Steelhead Trout parr (age-0 and age-1), in the Trout Creek and upper Wind River watersheds. Age-0 parr were at high abundance due to a strong spawning run in 2023 (estimate of 814 adults from September snorkel survey compared to 22-year median of 450; Charlie Cochran, WDFW Fish Biologist, personal commun., 2022), but age-1 parr abundance was low following poor spawner numbers in 2022 (estimate of 159 adults from September snorkel survey). An additional 189 age-2 or older parr were tagged to provide fish for estimating detection efficiencies at PTISs. Steelhead Trout parr were recaptured and detected through repeat headwater sampling, smolt trapping, instream PTISs and Columbia River PIT-tag detection. We maintained and upgraded six instream PTISs to detect PIT-tagged Steelhead Trout parr, smolts, and adults, providing data for population assessments, and life-cycle research.
Detection data from PIT-tagged adult Steelhead Trout at PTISs allow assessment of adult escapement to tributary watersheds within the Wind River subbasin. Adult Steelhead Trout detection efficiency estimates at our primary PTIS in Trout Creek have been greater than 99 percent during seven of the past nine years and have exceeded 97% at our primary PTIS in the Wind River during eight of the past nine years. Adult escapement estimates to tributary watersheds are helping evaluate the efficacy of the 2009 removal of Hemlock Dam from rkm 2.0 of Trout Creek, where it had potential negative effects on Steelhead Trout populations due to hydrologic impairment, increased temperatures, and adult passage issues because of an inadequate fish ladder.
Detections at the instream PTISs have shown trends of age-0 and age-1 Steelhead Trout parr emigration from natal areas during summer and fall, in addition to the expected movement of parr and smolts in spring. Our data suggest that often most fish from a cohort that migrate downstream will do so at age-1 for additional rearing downstream of their natal areas. It is unknown if this is ingrained behavior or a result of lack of habitat capacity. We have estimated that from 15 to 56% of parr tagged as age-0 fish in headwater areas make downstream migrations at age-1 for additional rearing. We have estimated that up to 27% of Steelhead Trout parr, tagged as age-1 fish, make downstream migrations during fall: this is especially pronounced in the upper Wind River portion of the watershed. These findings raise questions about preferred parr rearing habitat and whether migrations are density- or habitat-quality driven, and answers to such questions are part of the long-term goals of this study as active and passive habitat restoration actions occur.
Repeat sampling at sites in the subbasin within and between years has enabled assessment of juvenile Steelhead Trout growth patterns. Growth rates (relative change in weight) of age-0 PIT-tagged parr during summer have been similar across the subbasin, though slightly lower in the Trout Creek watershed. Summer growth rates have been lower for age-1 parr in the Trout Creek watershed than the upper Wind River watershed. Yearly relative growth was similar across the subbasin for both age-0 and age-1 tagged parr.
Non-native Salvelinus fontinalis (Brook Trout) are present in the subbasin, chiefly the Trout Creek watershed, and repeat sampling provides an index of their prevalence. Mean percent-of-catch that is Brook Trout, at four sample sites in Trout Creek, has declined from the period 1998 – 2003 to the period 2011 – 2024. Percent-of-catch and number of Brook Trout at the Trout Creek sites from 2011 through 2022, though variable, have generally declined.
Evaluation and planning of habitat restoration efforts are critical to ensure efficient use of money and resources. Assessing Steelhead Trout life history variation in the Wind River subbasin informs research and tracking of many populations and habitat restoration and water allocation planning. Movement of Steelhead Trout parr from natal areas to other rearing areas raises questions regarding juvenile abundance, origin, and habitat use within watersheds. Improved PTISs and focused PIT-tagging of age-0 and age-1 Steelhead Trout parr allow investigation of such questions. Detailed viable salmonid population and life-history data, such as that provided by PIT-tagging and instream PTIS networks inform fisheries policy and management and enable assessment of long-term effects of habitat restoration actions such as the removal of Hemlock Dam on Trout Creek and proposed major instream habitat restoration in the upper Wind River.
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