Clear Lake volcanic field (CLVF) is the northernmost and youngest (~2.2 Ma to 8 ka) of the volcanic centers distributed along the San Andreas transform fault in western California. The initial phase of CLVF volcanism (interval one) occurred between ~2.2 and 1.3 Ma and extends ~35 km southeast of Clear Lake, forming a semi-continuous upland plateau capped by lava flows, with isolated volcanic remnants on the periphery. This volcanism is broadly characterized by geochemically primitive compositions that reflect three source compositions and conditions of melt generation. (1) Partial melting of upwelling asthenospheric mantle lherzolite at moderate pressures (1.2–1.4 GPa) and temperatures (1297–1329 °C) produced high-CaO (9.8–11.3 wt %) basalts with high Al2O3 (16.8–17.6 wt %), Mg#s (66–70), MgO (8–10 wt %), Ni (103–262 μg/g), and Cr (284–609 μg/g). These high-CaO basalts contain olivine (Fo87–91) phenocrysts with Cr-spinel inclusions ± subordinate plagioclase and crop out only in the southern part of the CLVF. (2) Partial melting of depleted sub-continental lithospheric mantle harzburgite at variable pressures (0.7–1.5 GPa) and temperatures (1097–1299 °C) produced a compositional continuum of med-K2O, calc-alkaline, high-MgO basalts through high-MgO andesites with high Mg#s (67–77), MgO (8–14 wt %) and high Ni and Cr abundances (154–439 and 340–1124 μg/g, respectively). Mineral assemblages are olivine (Fo88–93) with Cr-spinel inclusions ± subordinate clinopyroxene, orthopyroxene and plagioclase. Small (<2.5 cm) mantle harzburgite xenoliths and mantle olivine xenocrysts are also found in several of these samples. These high-MgO basalts through andesites represent the largest volume of primitive compositions and have erupted predominantly along the main, fault-controlled northwest-southeast trending axis of volcanism with peripheral outcrops to the north, west, and east. (3) Partial melting of the Gorda eclogite slab edge produced adakitic silicic slab melts with strong depletion in the heavy rare earth elements (Yb = 0.6 μg/g). Subsequent reaction of those melts with depleted ultramafic rocks during ascent imprinted the adakitic dacites with high Mg#s (65–78) and elevated Ni (117–210 μg/g) and Cr (191–283 μg/g). Phenocrysts of orthopyroxene (En87–94) with spinel inclusions (Cr# = 80–88) and extremely Ni-rich (9483 μg/g) olivine cores (Fo84–93) record those reactions. Small-volume outcrops of the adakites on the eastern periphery of the CLVF track the passing slab edge. The trio of melting sources recorded by early CLVF magmatism reflect the tectonically complex environment and the hot (1097–1329 °C), shallow (0.7–1.5 GPa) melting conditions for these primitive compositions and provide estimates of the heat delivered to the crust. Over time, this flux led to maturation of the CLVF magmatic system toward the more voluminous and silicic volcanism that characterizes the balance of its subsequent volcanic history and maintains the present-day anomalously high heat flow in the region. The current interval (interval four) of volcanic activity at CLVF is characterized by low-volume, fault-controlled eruptions of basaltic andesite and andesite suggestive of mantle magma and heat delivery to the crust, similar to interval one. This analogous activity provides motivation for the current study and begs the question of whether the system is undergoing thermal priming for renewed silicic volcanism.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egaf077","usgsCitation":"Blatter, D.L., and Burgess, S.D., 2025, Melt generation sources and conditions in the wake of a migrating slab window: Geochemistry and petrology of the million-year history of primitive volcanism at Clear Lake volcanic field, California: Journal of Petrology, v. 66, no. 9, egaf077, 43 p., https://doi.org/10.1093/petrology/egaf077.","productDescription":"egaf077, 43 p.","ipdsId":"IP-173749","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake volcanic field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.9635380144356,\n 39.14844575495471\n ],\n [\n -122.9635380144356,\n 38.917438489493804\n ],\n [\n -122.5731123436415,\n 38.917438489493804\n ],\n [\n -122.5731123436415,\n 39.14844575495471\n ],\n [\n -122.9635380144356,\n 39.14844575495471\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"66","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Blatter, Dawnika L. 0000-0002-7161-6844 dblatter@usgs.gov","orcid":"https://orcid.org/0000-0002-7161-6844","contributorId":4899,"corporation":false,"usgs":true,"family":"Blatter","given":"Dawnika","email":"dblatter@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":950370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgess, Seth D. 0000-0002-2128-9144","orcid":"https://orcid.org/0000-0002-2128-9144","contributorId":362359,"corporation":false,"usgs":true,"family":"Burgess","given":"Seth","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":950371,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271905,"text":"70271905 - 2025 - A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed","interactions":[],"lastModifiedDate":"2025-09-24T15:03:35.249606","indexId":"70271905","displayToPublicDate":"2025-09-01T07:53:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed","docAbstract":"Tsunami hazards are substantial threats to coastal communities across the United States (U.S.) and its territories. U.S. states and territories collaborate through the National Tsunami Hazard Mitigation Program (NTHMP) to develop their own tsunami-hazard information for outreach and evacuation planning. An effort to curate this tsunami-hazard information to support comprehensive risk analysis at the national level has not yet been completed. In support of this effort, the Federal Emergency Management Agency (FEMA) collaborated with the NTHMP, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) starting in 2023. This collaboration included the collection and analysis of existing tsunami hazard data and methods in the U.S. Tsunami subject matter experts identified and selected scientifically defensible methods for estimating the risks to buildings and populations in coastal communities. These efforts may support decision making regarding resilience policies, priorities, strategies and funding levels.
Tsunamis can be triggered by earthquakes, subaerial or submarine landslides, volcanic eruptions, glacial calving, near-earth objects, weather or other events. These events can cause severe destruction, injuries, and loss of life due to powerful currents and flooding. Tsunamis pose a substantial threat to the western United States and all U.S. territories, as described below.
■ Hawaii is threatened by distant tsunamis due to its central location in the Pacific Ocean basin and has a history of local events.
■ Alaska, particularly the Aleutian Islands, faces local tsunami threats due to proximity to the Alaska-Aleutian Subduction Zone, as well as distant tsunamis from around the Pacific Ocean basin.
■ The western coast of the U.S. is threatened by distant tsunamis from around the Pacific Ocean basin and local source tsunamis from earthquakes generated within the Cascadia Subduction Zone in the Pacific Northwest.
■ American Samoa faces local tsunami threats from earthquakes generated in the nearby Tonga Trench, as well as distant tsunami threats.
■ Guam and the Commonwealth of the Northern Mariana Islands are threatened by local tsunamis from the nearby Mariana Subduction Zone, as well as distant sources from around the Pacific Ocean Basin.
■ Puerto Rico and the United States Virgin Islands are threatened by multiple local and distant tsunami sources, such as the Puerto Rico Trench (PRT), given their location in the complex seismic region of the Caribbean Sea.
Several historical events stand out because of their catastrophic impacts.
■ In the Pacific Northwest, the 1700 Cascadia earthquake caused a tsunami that affected coastal Native American communities, though the extent of the damage is not fully documented (Ludwin, et al., 2005).
■ In Puerto Rico, the 1918 earthquake triggered a tsunami that caused $77 million in damage in 2022 dollars and 116 fatalities, primarily along the western coast (Coffman et al., 1982).
■ The 1946 Aleutian Islands earthquake triggered a massive tsunami that devastated Hilo, Hawaii, killing 158 people and resulting in approximately $375 million in damage (adjusted to 2022 dollars) (Fisher et al., 2023).
■ The 1964 Alaska earthquake (M 9.2) generated tsunamis that caused severe destruction in some communities across Alaska, Oregon, and California. This disaster led to a total of 124 fatalities and approximately $2.9 billion in property damage (adjusted to 2022 dollars) (Brocher et al., 2014) (Alaska Science Center, 2024).
■ In American Samoa, a tsunami generated by the 2009 Samoa earthquake (Mw 8.1) caused widespread devastation, resulting in 34 confirmed fatalities (Apatu et al., 2013) and economic losses exceeding $160 million (adjusted to 2022 dollars) (DHS, 2011).
More recent events, including the 2010 Chile earthquake, the 2011 Japan earthquake, and the 2022 Tonga volcanic eruption, resulted in millions of dollars in damage to numerous ports and harbors in the U.S. South Pacific territories, Hawaii, and along the west coast of the U.S. (Lynett, et al., 2022) (Wilson, et al., 2013). Since these events, the expansion of the built environment in lowlying areas along the coast has increased the exposure of buildings and people, thereby further escalating community risk from tsunamis.
This report provides a comprehensive national assessment of earthquake-generated tsunami risk. It does not include impacts from tsunamis generated by landslides, volcanic eruptions, glacial calving, near-earth objects, weather, or other events. This study is based on the best available hazard data from the U.S. Pacific Coast (California, Oregon and Washington), Alaska, Hawaii, U.S. Pacific Territories (American Samoa, Guam and Commonwealth of the Northern Mariana Islands) and Caribbean Territories (Puerto Rico and United States Virgin Islands). Tsunami risks associated with states along the East Coast, Gulf Coast, and Great Lakes are not included in this study because Hazus 6.1 software (FEMA 2024a) does not currently include the ability to analyze tsunami risk in those states. Once modeling capabilities and tsunami hazard data become available for additional states, FEMA may incorporate these data into future editions of this study.
","language":"English","publisher":"FEMA","collaboration":"NOAA","usgsCitation":"Sheehan, A., Zuzak, C., Wood, N.J., Bausch, D., Yeager, C.G., and McDougall, A., 2025, Estimated average annualized tsunami losses for the United States, xiv, 158 p.","productDescription":"xiv, 158 p.","startPage":"158","ipdsId":"IP-178510","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":496895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496887,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fema.gov/sites/default/files/documents/fema_hazus_p-2426_estimated-average-annualized-tsunami-losses-united-states_092025.pdf"}],"country":"Commonwealth of the Northern Marianas Islands, United States","state":"Alaska, California, Hawaii Oregon, Washington","otherGeospatial":"American Samoa, Guam, Puerto Rico, U.S. West Coast, U.S. Virgin Islands","geographicExtents":"{\n \"type\": 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]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sheehan, Anne","contributorId":330480,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":951001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zuzak, Casey","contributorId":287432,"corporation":false,"usgs":false,"family":"Zuzak","given":"Casey","affiliations":[{"id":61582,"text":"FEMA Risk Mgmt Directorate","active":true,"usgs":false}],"preferred":false,"id":951002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":951003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bausch, Doug","contributorId":195191,"corporation":false,"usgs":false,"family":"Bausch","given":"Doug","email":"","affiliations":[{"id":34169,"text":"Pacific Disaster Center","active":true,"usgs":false}],"preferred":false,"id":951004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yeager, Cadie Goulette 0009-0002-6966-1811","orcid":"https://orcid.org/0009-0002-6966-1811","contributorId":361919,"corporation":false,"usgs":false,"family":"Yeager","given":"Cadie","middleInitial":"Goulette","affiliations":[{"id":86387,"text":"Niyam IT","active":true,"usgs":false}],"preferred":false,"id":951005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDougall, Alice","contributorId":363052,"corporation":false,"usgs":false,"family":"McDougall","given":"Alice","affiliations":[{"id":86600,"text":"FACTOR","active":true,"usgs":false}],"preferred":false,"id":951006,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273980,"text":"70273980 - 2025 - 3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park","interactions":[],"lastModifiedDate":"2026-02-24T14:58:17.527534","indexId":"70273980","displayToPublicDate":"2025-09-01T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park","docAbstract":"The ongoing degradation of coral reef habitats is widely acknowledged to have adverse effects on the abundance and diversity of reef fish populations, yet the direct effects on ecosystem functions remain uncertain. This study used a quantitative approach to determine the mechanistic links between fish assemblages and ecological function. We investigated the effects of 3D habitat structure and coral morphology on the ecological, behavioral, and morphological functional traits of reef fish within a protected marine national park. Fish traits such as Gregariousness, Water Column Position, and Body Shape were identified to be highly influential in shaping the multidimensional fish functional space, which was categorized into 10 Fish Functional Groups (FFG). Furthermore, habitat complexity and coral morphology significantly explained the abundances of eight out of 10 FFG. Notably, the habitat complexity metrics of Slope and Surface Complexity, along with coral morphologies of Branching and Mounding types, emerged as the most influential habitat features across FFG. Pairing Compressiform species and Schooling Short/Deep species, for example, significantly increased in abundance on substrate with higher Slopes and increased percentages of branching coral cover. Additionally, Cryptic and Nocturnal species exhibited statistically significant associations with all coral morphologies and substrates with high trait values of Slope and Curvature. Elucidating ecological drivers of specific functional groups of reef fish is critical for determining how changes in reef composition and structure will alter fish assemblages. Broad scale patterns were also detected, suggesting that although structural complexity is important, live coral morphologies have a greater positive impact on reef fish functional groups. These findings have direct implications for conservation and monitoring efforts, offering valuable insights for predicting the impacts of environmental change on community dynamics and ecosystem functioning.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71992","usgsCitation":"Ferreira, S.B., Burns, J.H., Fukunaga, A., Raz, L., McKenna, S.A., Annandale, K., Monello, R.J., 2025, 3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park: Ecology and Evolution, v. 15, no. 9, e71992, 16 p., https://doi.org/10.1002/ece3.71992.","productDescription":"e71992, 16 p.","ipdsId":"IP-174520","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500601,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71992","text":"Publisher Index Page"},{"id":500436,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","city":"Kailua-Kona","otherGeospatial":"Kaloko-Honokohau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.0727322749224,\n 19.716285054970754\n ],\n [\n -156.0727322749224,\n 19.58261325737645\n ],\n [\n -155.92066431233505,\n 19.58261325737645\n ],\n [\n -155.92066431233505,\n 19.716285054970754\n ],\n [\n -156.0727322749224,\n 19.716285054970754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ferreira, Sofia B.","contributorId":366488,"corporation":false,"usgs":false,"family":"Ferreira","given":"Sofia","middleInitial":"B.","affiliations":[],"preferred":false,"id":955983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, John H.R.","contributorId":366489,"corporation":false,"usgs":false,"family":"Burns","given":"John","middleInitial":"H.R.","affiliations":[],"preferred":false,"id":955984,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fukunaga, Atsuko","contributorId":366490,"corporation":false,"usgs":false,"family":"Fukunaga","given":"Atsuko","affiliations":[],"preferred":false,"id":955985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raz, Lillian Joy Tuttle 0000-0002-5009-8080","orcid":"https://orcid.org/0000-0002-5009-8080","contributorId":354940,"corporation":false,"usgs":true,"family":"Raz","given":"Lillian Joy Tuttle","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":955986,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKenna, Sheila A.","contributorId":366491,"corporation":false,"usgs":false,"family":"McKenna","given":"Sheila","middleInitial":"A.","affiliations":[],"preferred":false,"id":955987,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Annandale, Kailea","contributorId":366492,"corporation":false,"usgs":false,"family":"Annandale","given":"Kailea","affiliations":[],"preferred":false,"id":955988,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monello, Ryan J.","contributorId":366493,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","middleInitial":"J.","affiliations":[],"preferred":false,"id":955989,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70270765,"text":"sir20255077 - 2025 - Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming","interactions":[],"lastModifiedDate":"2026-02-03T15:17:46.175988","indexId":"sir20255077","displayToPublicDate":"2025-08-29T11:03:01","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":"2025-5077","displayTitle":"Fluvial Sediment Dynamics in the Shoshone River and Tributaries Around Willwood Dam, Park County, Wyoming","title":"Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming","docAbstract":"Sedimentation affects many of the aging reservoirs in the United States. Dams and water diversions from rivers have been central elements of infrastructure supporting agricultural irrigation in the arid and semiarid regions of the Western United States for more than a century. The Willwood Irrigation District diversion dam (hereafter referred to as “Willwood Dam”) in Park County, Wyoming, is approximately 12 miles northeast of Cody, Wyo.; has a structural height of 70 feet; and impounds the Shoshone River for diversion into the Willwood Canal. Willwood Dam is part of a larger irrigation scheme supported by water storage in the much larger Buffalo Bill Dam, which is approximately 20 miles upstream. In October 2016, renovation construction activities at Willwood Dam and the Willwood Canal caused an unplanned evacuation of nearly 96,000 cubic yards of fine sediment.
The fine sediment release in 2016 raised concerns that ongoing sediment management at Willwood Dam could impose limits on the long-term health of the aquatic ecosystem and fish populations. The U.S. Geological Survey, in cooperation with Wyoming Department of Environmental Quality and Willwood Work Groups 2 and 3, initiated an investigation of the dynamics of sediment transport in the Shoshone River and selected tributaries between Buffalo Bill Dam and Willwood Dam. The goal of the study was to quantify sediment transport into and out of Willwood Dam on an annual, seasonal, and event basis to better understand the relative quantities of sediment coming from natural sources and human activities on the landscape. The study ran from March 2019 through October 2021 and used observations of streamflow, turbidity, and acoustic backscatter collected at streamgages upstream and downstream from Willwood Dam to quantify suspended-sediment loads into and out of the dam during irrigation and fallow seasons, precipitation-runoff events, and deliberate sediment releases. Each tributary’s relative contribution to the sediment load upstream from Willwood Dam was examined using discrete measurements of suspended-sediment concentration and bedload during irrigation and fallow seasons, precipitation events, and stable conditions.
Analysis of daily precipitation and temperature data indicated that conditions in the study area during the 2019 agricultural year were wetter and colder than period of record normal, and drier and near normal temperatures for the 2020 and 2021 agricultural years. Not all sediment load records between 2019 and 2021 are complete because of rejected observations (outliers), instrument failures or fouling, and instrument removal for calibrations.
Statistical modeling of suspended-sediment concentration using paired values of turbidity and acoustic backscatter produced four models that, after refinement, had coefficients of determination indicating that more than 84 percent of the variance was explained by either turbidity or acoustic backscatter. A system of rules was developed to select the model predictions based on the seasonal operations of Willwood Dam, assumptions about the grain sizes mobilized during these operations, and assumed accuracy of the models at the downstream streamgage (Shoshone River below Willwood Dam, near Ralston, Wyo. [streamgage 06284010]) under different operational conditions. The sediment budget between upstream and downstream estimates of loads was interpreted using the mean predicted values bound by their respective model prediction intervals. When mean predicted loads of one streamgage were contained in the prediction intervals of the other streamgage, and vice-versa, difference in the sediment budget were interpreted as “indeterminate.”
Modeled sediment load balances demonstrated the depositional and erosional behaviors expected from the conceptual model of dam operations whereby sediment tends to accumulate during irrigation seasons when the dam is spilling over the top, and sediment tends to evacuate during the fallow seasons when it is flowing through the sluice gates at the base of the dam. The sediment load calculations using the rules-based model criteria indicated that between 14,200 and 380,000 tons of suspended sediment moved through the Shoshone River around Willwood Dam during the irrigation seasons of 2019, 2020, and 2021; 380,000 tons of suspended sediment were transported during the cool, wet year of 2019, and 14,200 tons of suspended sediment were transported in 2020, which was relatively dry. During fallow seasons 2019, 2020, and 2021, which had fewer complete records, between 1,140 and 106,000 tons of suspended sediment was estimated to have moved through the river.
For all seasons except fallow season 2022, the models estimated that more sediment was released from the dam than entered the dam, but the modeled mean loads at each streamgage were nearly always within the prediction intervals of each other, making the sediment balance indeterminant. Examination of suspended-sediment loads during irrigation seasons indicated that between 65 and 85 percent of fine sediment was transported during annual high flows and storm events, with the remainder transported during steady, lower streamflows. Examination of suspended loads during fallow seasons indicated that deliberate sediment releases through Willwood Dam accounted for between 39 and 67 percent of the total sediment moved during the fallow seasons. Deliberate sediment releases from Willwood Dam had estimated net exports of between 1,360 and 22,400 tons.
Between August 2017 and July 2023, suspended-sediment concentration and bedload sediment samples were collected from 9 tributaries to the Shoshone River during 137 sampling events, including stable and precipitation-runoff conditions. During irrigation season precipitation events, the mean total sediment yields ranged from 0.33 to 9.51 tons per day per square mile; during fallow season precipitation events, the mean total yields ranged from 0.04 to 0.95 ton per day per square mile. The mean total sediment yield per unit area across all samples at each tributary site ranged from 0.26 to 3.08 tons per day per square mile. Bedload was a minor fraction of the total load, constituting a mean of 4 percent across all samples; 3 and 6 percent for events and nonevents, respectively, during irrigation season; and 3 and 1 percent for events and nonevents, respectively, during the fallow season. With the exception of one tributary, Dry Creek, these mean yield values were within the range of watershed-scale background sediment yield values estimated from reservoir surveys and previous suspended-sediment studies.
Imagery from irrigation seasons 2012, 2015, 2017, 2019, and 2022 was used to determine the planimetric backwater extent of the pool area in the Shoshone River behind Willwood Dam to identify any changes in sediment storage. Active river channel widths in the Shoshone River upstream from Willwood Dam were all similar between years except 2015, which was determined to be statistically different from all other years. Bathymetric data taken in the pool behind Willwood Dam during three different surveys between November 2017 and April 2022 indicated no statistically significant differences in bed elevations between the years. Results from the planimetric and bathymetric survey data provide multiple lines of evidence indicating that sediment did not accumulate behind the dam within the error of the methods used.
Examination of how precipitation affects sediment transport in the Shoshone River upstream from Willwood Dam indicated that accumulated rainfall from the natural runoff events captured during the study period varied from a trace to as much as 4.26 inches, with associated predicted suspended-sediment loads varying from 112 to 232,000 tons of suspended sediment. The behavior of the sediment loads relative to accumulated precipitation did not appear to change depending on irrigation or fallow season. A model of suspended-sediment concentrations relative to the 2-day accumulated precipitation indicated that suspended-sediment concentrations in the Shoshone River upstream from Willwood Dam increased exponentially for accumulations of 0.3 inch or more; such storms accounted for 10 percent or less of precipitation events observed during the 1981 to 2018 period of record.
The gaps in records, precision of the instrumentation, and large variation in grain sizes in suspended-sediment mixtures downstream from the dam made closing the sediment budgets for most seasons unattainable. The biggest recent change in sediment storage measured using the planimetric area of deposits behind Willwood Dam took place between 2015 and 2017. The main event between these two measurements was the installation of new Willwood Canal gates in October 2016, which resulted in the large unplanned sediment release. Because the sediment budgets were nearly always indeterminate and the planimetric and bathymetric data indicated little change in the bed and bank material, it is likely that the change in sediment storage behind the dam during the study period was small relative to the precision of the statistical models and other uncertainties.
This body of evidence suggests that, averaged during the 3-year study period, no major changes in storage took place, and that the current operations may be keeping storage at near-equilibrium. This condition could have been initiated because the middle sluice gate has now been operational since 2014, and the sediment release in October 2016 evacuated a large amount of legacy sediment from storage. Although the uncertainties are large, sluicing events allow for controlled releases of sediment that contributed to the near equilibrium conditions observed over an annual basis during this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255077","collaboration":"Prepared in cooperation with the Wyoming Department of Environmental Quality","usgsCitation":"Alexander, J.S., Brown, H., Eddy-Miller, C.A., Burckhardt, J., Burckhardt, L., Ellison, C., McIntyre, C., Moger, T., Patterson, L., Tavelli, C., Waterstreet, D., and Williams, M., 2025, Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming: U.S. Geological Survey Scientific Investigations Report 2025–5077, 70 p., https://doi.org/10.3133/sir20255077.","productDescription":"Report: x, 70 p.; Data Release; Dataset","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-164415","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":494651,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255077/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5077"},{"id":494674,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":494673,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13VHDRG","text":"USGS data release","linkHelpText":"Shapefiles of digitized backwater extent behind Willwood Dam on the Shoshone River, near Cody, Wyoming, derived from 2012, 2015, 2017, 2019, and 2022 National Agriculture Imagery Program imagery"},{"id":494652,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5077/images"},{"id":494654,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5077/sir20255077.XML","linkFileType":{"id":8,"text":"xml"}},{"id":494650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5077/sir20255077.pdf","text":"Report","size":"9.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5077"},{"id":494649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5077/coverthb.jpg"}],"country":"United States","state":"Wyoming","county":"Park County","otherGeospatial":"Shoshone River and tributaries around Willwood Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.66170194279013,\n 44.80967182289373\n ],\n [\n -109.31267227648169,\n 44.80967182289373\n ],\n [\n -109.31267227648169,\n 44.39309612019585\n ],\n [\n -108.66170194279013,\n 44.39309612019585\n ],\n [\n -108.66170194279013,\n 44.80967182289373\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
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Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally efficient method that enables the projection of daily stream water quality under varying hydrologic conditions using commonly available discrete monitoring data. WRTDS-P model performance was validated using 39 sites in the Delaware River Basin (DRB) and four key constituents: specific conductance (SC), nitrate (NO3−), magnesium (Mg2+) and calcium (Ca2+). Projections were tested against holdout data from the final 1 to 5 years of each time series, demonstrating robust predictive capability, with median Nash-Sutcliffe efficiencies of 0.67 for SC, 0.56 for NO3−, 0.65 for Ca2+, and 0.79 for Mg2+. Model uncertainty was correlated with indicators of hydrologic or geochemical mass-sinks, such as groundwater storage and adsorption in wetland soils. Drought scenario analyses for SC used ranges of reduced discharge including flows from the 1965 drought of record. Scenarios predicted widespread increases of SC, especially in southern DRB streams where baseline SC levels are already elevated. Fractional increases of SC were more uniformly distributed, indicating potential risk to sensitive ecosystems. Notably, drought-induced SC increases were positively correlated with interannual SC trends, indicating that hydrologic extremes could exacerbate ongoing salinization. This work provides a transferable and interpretable framework for projecting future water quality and assessing hydrologic risk to water resources and aquatic ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.180286","usgsCitation":"Green, C., Hirsch, R.M., Essaid, H., and Sanford, W.E., 2025, Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin: Science of the Total Environment, v. 999, 180286, 14 p., https://doi.org/10.1016/j.scitotenv.2025.180286.","productDescription":"180286, 14 p.","ipdsId":"IP-159069","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":496136,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.180286","text":"Publisher Index Page"},{"id":495782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.79788517502844,\n 39.713218235332164\n ],\n [\n -75.44918608740714,\n 38.663983307614814\n ],\n [\n -74.82016028228699,\n 38.99952921670035\n ],\n [\n -74.61504317192174,\n 39.81307746348011\n ],\n [\n -74.15695069541222,\n 41.998596289750736\n ],\n [\n -74.9227212407762,\n 42.30779251171998\n ],\n [\n -75.65430560107949,\n 41.9782683665571\n ],\n [\n -76.07821429583441,\n 41.159834427011475\n ],\n [\n -76.03035363674925,\n 40.632678412780365\n ],\n [\n -75.79788517502844,\n 39.713218235332164\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"999","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":949040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":949041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Essaid, Hedeff 0000-0003-0154-8628","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":361587,"corporation":false,"usgs":false,"family":"Essaid","given":"Hedeff","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":949042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":337084,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":949043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271299,"text":"70271299 - 2025 - Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA","interactions":[],"lastModifiedDate":"2025-09-03T15:29:49.125047","indexId":"70271299","displayToPublicDate":"2025-08-29T08:20:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA","docAbstract":"Rising chloride concentrations pose critical risks to freshwater stream ecosystems in temperate regions like the Delaware River Basin (DRB), USA, where winter deicer applications (i.e., road salt) are common. Increasing chloride concentrations have been documented in the region, but the extent to which chloride exceeds regulatory benchmarks remains unclear because detection of exceedances requires continuous monitoring of chloride (i.e., hourly or daily). A network of 82 non-tidal continuous specific conductance (SC) monitoring sites, spanning varied land use and geological settings, was established across the DRB to address this research need. First, a cluster analysis was conducted to group sites based on their watershed characteristics. Next, regression models for sites and clusters were developed to predict chloride using SC as a proxy. Finally, daily mean and hourly mean chloride concentration predictions were made for a three-year period (2020–2022) at the 82 study sites and analyzed to determine where and when chloride exceeded federal regulatory benchmarks. Chloride exceedance events occurred at 35% of the sites, all of which had 5% impervious cover or greater. Seasonally elevated chloride also was predicted at sites with less than 5% impervious cover. Variability in chloride patterns likely was influenced by deicer material types, winter weather patterns, geological settings, and gaps in data coverage. This study demonstrated the value of SC as a proxy for predicting chloride concentrations and showed how SC-chloride regression relationships vary across settings. More broadly, this study highlighted the value of continuous water quality monitoring to assess effects of freshwater salinization at a regional scale.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10661-025-14485-6","usgsCitation":"Fanelli, R.M., Morency, M., Fleming, B.J., Moore, J., Hardesty, D., and Shoda, M.E., 2025, Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA: Environmental Monitoring and Assessment, no. 197, 1056, 25 p., https://doi.org/10.1007/s10661-025-14485-6.","productDescription":"1056, 25 p.","ipdsId":"IP-175501","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":495182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-025-14485-6","text":"Publisher Index Page"},{"id":495151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.79184558063025,\n 41.902372822441464\n ],\n [\n -75.79184558063025,\n 38.41313507684677\n ],\n [\n -74.54201398019202,\n 38.41313507684677\n ],\n [\n -74.54201398019202,\n 41.902372822441464\n ],\n [\n -75.79184558063025,\n 41.902372822441464\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"197","noUsgsAuthors":false,"publicationDate":"2025-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":341844,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morency, Michelle 0009-0000-9027-7561","orcid":"https://orcid.org/0009-0000-9027-7561","contributorId":345367,"corporation":false,"usgs":false,"family":"Morency","given":"Michelle","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":947887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Joel","contributorId":49034,"corporation":false,"usgs":false,"family":"Moore","given":"Joel","affiliations":[],"preferred":false,"id":947889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardesty, Deanna 0000-0002-4924-2233","orcid":"https://orcid.org/0000-0002-4924-2233","contributorId":341845,"corporation":false,"usgs":true,"family":"Hardesty","given":"Deanna","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947890,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":947891,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271296,"text":"70271296 - 2025 - Dispersal and survival of sea lamprey in Lake Erie and connected waterways","interactions":[],"lastModifiedDate":"2026-01-05T16:40:02.610528","indexId":"70271296","displayToPublicDate":"2025-08-29T07:47:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Dispersal and survival of sea lamprey in Lake Erie and connected waterways","docAbstract":"Invasive sea lamprey inhabiting the North American Laurentian Great Lakes are the target of the world’s longest running vertebrate invasive species control program. However, metapopulation dynamics comprising survival and dispersal during the sea lampreys’ lake-resident life stages are poorly understood. We applied acoustic telemetry and continuous-time multistate capture-recapture modeling to address this knowledge gap in Lake Erie. We acoustic-tagged sea lamprey (n = 619) and deployed acoustic receivers into all known connected waterways containing larval sea lamprey rearing habitat (n = 23), including the Detroit River (connecting Lake Erie to Lake Huron) and distributaries to Lake Ontario. Distribution of tagged sea lamprey to putative spawning waterways was shaped by heterogeneous stream attractiveness and distance-limited dispersal. Using parameter estimates from our capture-recapture model and simulation, we predicted survival and dispersal outcomes for a hypothetical sea lamprey population evenly distributed throughout Lake Erie at the beginning of January (34% pre-spawn mortality, 45% dispersal into Lake Erie tributaries, 19% dispersal into the Detroit River, and 2% dispersal into Lake Ontario). The methodology we applied may be widely useful for investigating dispersal and survival of aquatic organisms.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2025-0103","usgsCitation":"Lewandoski, S.A., and Holbrook, C., 2025, Dispersal and survival of sea lamprey in Lake Erie and connected waterways: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-13, https://doi.org/10.1139/cjfas-2025-0103.","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-181833","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":495148,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496372,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2025-0103","text":"Publisher Index Page"}],"country":"Canada, United States","otherGeospatial":"Lake Erie, Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.70617488623432,\n 42.02384024551296\n ],\n [\n -83.62185164386733,\n 41.22531282546535\n ],\n [\n -80.95581262939565,\n 41.614162157533514\n ],\n [\n -78.44800562562105,\n 42.65436741270719\n ],\n [\n -78.07746378748234,\n 44.06396277336654\n ],\n [\n -79.76290535037472,\n 43.86046169412299\n ],\n [\n -83.70617488623432,\n 42.02384024551296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewandoski, Sean Alois 0000-0002-6801-5861","orcid":"https://orcid.org/0000-0002-6801-5861","contributorId":340324,"corporation":false,"usgs":true,"family":"Lewandoski","given":"Sean","email":"","middleInitial":"Alois","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":947884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":947885,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271378,"text":"70271378 - 2025 - Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper","interactions":[],"lastModifiedDate":"2025-09-10T14:44:00.057371","indexId":"70271378","displayToPublicDate":"2025-08-29T07:38:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper","docAbstract":"The Palila (Loxioides bailleui), the last member of the once speciose finch-billed Hawaiian honeycreeper clade (Drepanidinae) in the main Hawaiian Islands, faces critical conservation challenges as an endangered species. Understanding the drivers of its decline is essential for effective management. We used additive decomposition models to examine temporal trends in climatic variables (temperature, precipitation, drought) and Normalized Difference Vegetation Index (NDVI), a vegetation health metric hypothesized to be associated with long-term trends in Palila abundance at landscape (250 m) scales on the Island of Hawai'i. A breakpoint analysis identified 2005–2009 as critical years of Palila decline. Vegetation health metrics at the 250 m scale lined up well both spatially and temporally with trends in Palila declines, with a significant browning from January 2004 to January 2014. Given the strong correlation between vegetation health and drought metrics at the landscape scale (r = 0.75, p < 0.001), NDVI changes appeared driven by drought. To enable the future projection of habitat quality in this area, we explored a stepwise linear regression to explain the variation in MODIS NDVI in recent years. We found that 87 % of the variability in NDVI can be explained by wet season precipitation and vapor pressure deficit from the previous dry season. The model is largely driven by a strong positive correlation between wet season precipitation and NDVI (r = 0.72, adjusted p < 0.001). Areas that maintained a low likelihood of NDVI decline throughout the time series and experienced increases in predicted Palila count represent potential drought microrefugia for the species. This higher elevation microrefugia is likely resilient against decreases in wet season precipitation through supplemental water retention from fog drip. While NDVI rebounded after 2014, Palila have not recovered. Our analysis highlights the importance of trend decomposition for monitoring endangered species with limited rebound potential due to small population dynamics and indicate continued warm, dry conditions may prevent Palila recovery without intervention.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03831","usgsCitation":"Gallerani, E.M., Camp, R.J., Banko, P.C., Madson, A., Dong, C., Fortini, L., Ma, Z., and Gillespie, T.W., 2025, Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper: Global Ecology and Conservation, v. 62, e03831, 14 p., https://doi.org/10.1016/j.gecco.2025.e03831.","productDescription":"e03831, 14 p.","ipdsId":"IP-166687","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":495392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2025.e03831","text":"Publisher Index Page"},{"id":495277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.6511297931527,\n 19.916012794249554\n ],\n [\n -155.6511297931527,\n 19.716091807948942\n ],\n [\n -155.34902248798784,\n 19.716091807948942\n ],\n [\n -155.34902248798784,\n 19.916012794249554\n ],\n [\n -155.6511297931527,\n 19.916012794249554\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gallerani, Erica M.","contributorId":361171,"corporation":false,"usgs":false,"family":"Gallerani","given":"Erica","middleInitial":"M.","affiliations":[{"id":86232,"text":"University of California Los Angles","active":true,"usgs":false}],"preferred":false,"id":948318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":948319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":948320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madson, Austin","contributorId":304629,"corporation":false,"usgs":false,"family":"Madson","given":"Austin","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":948321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dong, Chunyu","contributorId":304633,"corporation":false,"usgs":false,"family":"Dong","given":"Chunyu","email":"","affiliations":[{"id":37968,"text":"Sun Yat-Sen University","active":true,"usgs":false}],"preferred":false,"id":948322,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":948323,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ma, Zhimin","contributorId":304634,"corporation":false,"usgs":false,"family":"Ma","given":"Zhimin","email":"","affiliations":[{"id":37968,"text":"Sun Yat-Sen University","active":true,"usgs":false}],"preferred":false,"id":948324,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gillespie, Thomas W.","contributorId":361172,"corporation":false,"usgs":false,"family":"Gillespie","given":"Thomas","middleInitial":"W.","affiliations":[{"id":86232,"text":"University of California Los Angles","active":true,"usgs":false}],"preferred":false,"id":948325,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70270434,"text":"sir20255069 - 2025 - Streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada","interactions":[],"lastModifiedDate":"2026-02-03T15:15:45.219139","indexId":"sir20255069","displayToPublicDate":"2025-08-27T11:06:10","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":"2025-5069","displayTitle":"Streamflow Extents and Hydraulic Characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada","title":"Streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada","docAbstract":"The former Stuart Ranch, now managed by the Bureau of Land Management, is transected by Meadow Valley Wash, where 4,600 feet of perennial stream and adjacent riparian vegetation provide critical habitat for several wildlife and aquatic species protected under the Endangered Species Act. The stream has been altered by prior construction of irrigation diversions, gravel mining, and removal of riparian vegetation, resulting in the loss of instream and riparian vegetation and disconnected floodplains. The stream alteration has also resulted in the loss of native species and increased non-native invasive species and changes in ecological cycles. With the goal of improving habitat extent and quality for native threatened and endangered species, the Bureau of Land Management (BLM) is considering establishing perennial streams through braided side channels by constructing beaver dam analogs, excavating side channel connectors, and grading an irrigation reservoir berm on the floodplain. The U.S. Geological Survey (USGS) provided hydraulic modeling to assist the BLM in evaluating how possible restoration modifications could affect the extent of aquatic, riparian, and other habitat types. Three two-dimensional (2-D) hydraulic models were developed to simulate 2021 conditions (when most of the topographic data were collected), minor restoration modifications (one excavated side channel and a beaver dam analog), and major restoration modifications (three excavated side channels, a beaver dam analog, and an excavated and graded area to remove the irrigation reservoir) to determine streamflow-inundation extents and hydraulic characteristics (depth and velocity) for base flow and various flood (50-, 20-, 10-, 4-, 2-, and 1-percent annual exceedance probability [AEP]) scenarios. An average summer base flow of 0.92 cubic feet per second was estimated based on data from a USGS streamgage in the study area. The 50-, 20-, 10-, 4-, 2-, and 1-percent AEP streamflows were estimated based on a flood-frequency analysis of data from the streamgage. The base flow and AEP floods were combined with surveyed topographic data to create a 2-D unsteady hydraulic model. The hydraulic model was used to simulate the base flow and flood-inundation extents and hydraulic characteristics under 2021 conditions and with two possible restoration modification scenarios. Under 2021 conditions, flow remains in a single channel until the most downstream end of the modeled reach, where flow then expands into slower velocity pools. During floods, streamflow begins to enter the side channels at the 50-percent flood, expands into the east floodplain at 20-percent flood, and flows in the irrigation reservoir at 4-percent flood. Compared to 2021 conditions with no terrain modification, base flow under the possible restoration modifications enters and remains in the side channels, thus increasing the likelihood of expanding riparian habitat. Additionally, during floods under the major restoration modifications, streamflow expands into the modified terrain surrounding the irrigation reservoir at 10-percent AEP, as opposed to 4-percent AEP under 2021 conditions. For all modeled streamflow scenarios, streamflow is deepest in the center of the main and side channels, as well as the downstream pooled areas. Streamflow is fastest in the narrow sections of the channels, especially in the upper 1,220 feet of the modeled reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255069","collaboration":"Prepared in cooperation with Bureau of Land Management","programNote":"Water Resources Mission Area","usgsCitation":"Dye, L.A., Morris, C.M., and Childres, H.K., 2025, Streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada: U.S. Geological Survey Scientific Investigations Report 2025–5069, 24 p., https://doi.org/10.3133/sir20255069.","productDescription":"Report: vi, 24 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124818","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":494320,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5069/images"},{"id":494319,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HQ6F7","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data, flood-frequency analysis, and surface-water model archive for streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada"},{"id":494317,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5069/sir20255069.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5069"},{"id":494316,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5069/coverthb.jpg"},{"id":494318,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5069"},{"id":494321,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5069/sir20255069.XML"}],"country":"United States","state":"Nevada","city":"Rox","otherGeospatial":"Meadow Valley Wash at Stuart Ranch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.6611,\n 36.84\n ],\n [\n -114.6611,\n 36.8278\n ],\n [\n -114.65,\n 36.8278\n ],\n [\n -114.65,\n 36.84\n ],\n [\n -114.6611,\n 36.84\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road, Suite 3
Carson City, Nevada 89701
Characterizing traffic-related air pollutants (TRAPs), which significantly impact health, and greenhouse gases (GHGs) can be challenging in urban environments. Mobile monitoring has the potential to capture the spatial distribution of these pollutants. We present results from a campaign using the Denver Mobile Monitoring Laboratory (DMML) in the summer of 2023 when we measured ultrafine particles (UFPs), black carbon (BC), ozone (O3), methane (CH4), and carbon dioxide (CO2) concentrations in Denver, CO. Despite our campaign being brief, we obtained several interesting results. We observed elevated UFP and BC concentrations on major roads. In contrast, O3 concentrations were higher on neighborhood streets and roads and in the industrial neighborhood of Commerce City. We consistently observed elevated CH4 concentrations (>2.5 ppm) on highway I-70, suggesting the presence of a previously unknown major source of CH4. The CH4 concentrations measured in our campaign did not align with those from an overlapping aerial campaign, suggesting that mobile monitoring is crucial to capture important, potentially intermittent CH4 hotspots in cities. We evaluated if trees mitigated pollution concentrations, as planting trees is a key policy initiative of the city of Denver. We observed significant negative associations between tree canopy coverage and UFPs, BC, and CH4, and a positive association with O3 when using linear mixed-effects regression models. Our work highlights the importance of investigating the role of tree canopy coverage to mitigate TRAPs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeaoa.2025.100364","usgsCitation":"deSouza, P., Crawford, B., Durant, J.L., Hudda, N., Ibsen, P.C., L'Orange, C., Jimenez, J., Graeber, B., Cicione, B., Mekonnen, R., Purushothama, S., Kahn, R., Kinney, P.L., and Volckens, J., 2025, High-resolution multi-pollutant mapping in Denver, Colorado: Atmospheric Environment X, v. 27, 100364, 10 p., https://doi.org/10.1016/j.aeaoa.2025.100364.","productDescription":"100364, 10 p.","ipdsId":"IP-177506","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":495723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeaoa.2025.100364","text":"Publisher Index Page"},{"id":495408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.32990609528034,\n 39.95761559533625\n ],\n [\n -105.32990609528034,\n 39.506686432213314\n ],\n [\n -104.5591800032328,\n 39.506686432213314\n ],\n [\n -104.5591800032328,\n 39.95761559533625\n ],\n [\n -105.32990609528034,\n 39.95761559533625\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"27","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"deSouza, Priyanka","contributorId":353306,"corporation":false,"usgs":false,"family":"deSouza","given":"Priyanka","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crawford, Benjamin 0000-0003-3820-7982","orcid":"https://orcid.org/0000-0003-3820-7982","contributorId":340464,"corporation":false,"usgs":false,"family":"Crawford","given":"Benjamin","affiliations":[{"id":81615,"text":"University of Colorado Denver, Deparment of Geography and Environmental Science","active":true,"usgs":false}],"preferred":false,"id":948615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Durant, John L.","contributorId":361323,"corporation":false,"usgs":false,"family":"Durant","given":"John","middleInitial":"L.","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":948616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hudda, Neelakshi","contributorId":361324,"corporation":false,"usgs":false,"family":"Hudda","given":"Neelakshi","affiliations":[{"id":6936,"text":"Tufts University","active":true,"usgs":false}],"preferred":false,"id":948617,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ibsen, 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SPAIN","active":true,"usgs":false}],"preferred":false,"id":948620,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Graeber, Brady","contributorId":361326,"corporation":false,"usgs":false,"family":"Graeber","given":"Brady","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948621,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cicione, Brendan","contributorId":361327,"corporation":false,"usgs":false,"family":"Cicione","given":"Brendan","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948622,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mekonnen, Ruth","contributorId":361328,"corporation":false,"usgs":false,"family":"Mekonnen","given":"Ruth","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948623,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Purushothama, Saadhana","contributorId":361329,"corporation":false,"usgs":false,"family":"Purushothama","given":"Saadhana","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948624,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kahn, Ralph","contributorId":353311,"corporation":false,"usgs":false,"family":"Kahn","given":"Ralph","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":948625,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kinney, Patrick L.","contributorId":361330,"corporation":false,"usgs":false,"family":"Kinney","given":"Patrick","middleInitial":"L.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":948626,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Volckens, John","contributorId":361331,"corporation":false,"usgs":false,"family":"Volckens","given":"John","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":948627,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70273979,"text":"70273979 - 2025 - Suspended sediment and fisheries: An exploration of empirical relationships","interactions":[],"lastModifiedDate":"2026-02-20T18:21:30.798822","indexId":"70273979","displayToPublicDate":"2025-08-26T11:18:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Suspended sediment and fisheries: An exploration of empirical relationships","docAbstract":"Objective:
Sediment has an important role in aquatic ecosystems, however, excess sediment can negatively impact fish and other aquatic life. Quantifying the response of aquatic life, particularly fish, to suspended sediment is important for natural resource managers tasked with developing sediment management guidelines to protect aquatic ecosystems. Our goal was to assess the ability of established, revised, and alternate severity of ill effect (SEV) dose-response models to predict the impact of suspended sediment on fish.
Methods: We synthesized existing literature to develop an expansive dataset that relates suspended sediment concentration and exposure duration to biological effects on fishes and assessed the predictive ability of established and revised SEV dose-response models. We investigated potential sources of variation in biological responses to suspended sediment dose and explored two alternative approaches for assessing the effects of suspended sediment on fish: 90th quantile SEV dose-response regression models and logistic SEV dose-response models.
Results: We found that both established and revised linear SEV dose-response models poorly quantify fish biological response to suspended sediment. Quantile SEV dose-response regressions also performed poorly. More promising are logistic dose-response models that identify sediment thresholds where major effects of sediment on fish can be expected to occur. We demonstrate that fish biological response to suspended sediment is modulated by sediment particle size, water temperature, and dissolved oxygen levels, suggesting additional environmental and biological variables to consider when evaluating the effects of suspended sediment on fish.
Conclusion: We contribute revised and novel empirically derived tools for predicting the effects of suspended sediment on fish and demonstrate how environmental variables and life stage may modulate fish biological response. Our work illustrates challenges associated with predictive modeling and some potential sources of variation. While empirical models integrating biological stress response to suspended sediment may help natural resource managers capture potential impacts of this stressor, a cautious approach that considers co-acting stressors may be most effective for sediment management that is protective of fish.
","language":"English","publisher":"American Fisheries Society","doi":"10.1093/najfmt/vqaf051","usgsCitation":"Pilkerton, A.M., McCullough, S.M., Patterson, L.S., Rahel, F., Walters, A.W., 2025, Suspended sediment and fisheries: An exploration of empirical relationships: North American Journal of Fisheries Management, v. 45, no. 5, p. 753-766, https://doi.org/10.1093/najfmt/vqaf051.","productDescription":"14 p.","startPage":"753","endPage":"766","ipdsId":"IP-174503","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-08-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Pilkerton, Ashleigh M.","contributorId":366479,"corporation":false,"usgs":false,"family":"Pilkerton","given":"Ashleigh","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":955978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCullough, Sara M.","contributorId":366480,"corporation":false,"usgs":false,"family":"McCullough","given":"Sara","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":955979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Lindsay S.","contributorId":366481,"corporation":false,"usgs":false,"family":"Patterson","given":"Lindsay","middleInitial":"S.","affiliations":[{"id":84900,"text":"Wyoming Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":955980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rahel, Frank J.","contributorId":337685,"corporation":false,"usgs":false,"family":"Rahel","given":"Frank J.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":955981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":955982,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270953,"text":"70270953 - 2025 - Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA","interactions":[],"lastModifiedDate":"2025-08-27T15:00:56.506199","indexId":"70270953","displayToPublicDate":"2025-08-26T07:55:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1828,"text":"Geothermics","active":true,"publicationSubtype":{"id":10}},"title":"Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA","docAbstract":"The U.S. Geological Survey (USGS) is updating the 2008 assessment of conventional hydrothermal resources for the Great Basin in the western United States. As part of this work, the workflow for hydrothermal resource favorability maps is being modified to integrate modern data-driven machine learning (ML) methods. Improvements include: [1] using new and refined evidence layers (features); [2] using an order of magnitude more training sites (labeled examples); [3] utilizing simple but non-linear supervised ML algorithms; [4] representing positive training sites (wells with measured heat flow) with their ordinal value proportional to the magnitude of convective upflow (i.e., low, high, or very high convective signals instead of past strategies using positive-negative labels); [5] supplementing training sites with additional sites with low convective signals to represent diverse under-sampled areas where hydrothermal systems are unlikely to exist; [6] comparing with competing approaches; and [7] utilizing Monte Carlo cross-validation to estimate and evaluate prediction uncertainty.
For the new favorability map, over half of the power-producing systems (i.e., 15 of 28) are predicted in the 99th percentile of most favorable locations (i.e., the highest 1 % of favorability, corresponding to 1 % of the map area), exceeding the performance of past models that have explicitly used power plants as training sites. Previous favorability maps predicted approximately half of the power-producing hydrothermal systems above the 80th percentile (i.e., 20 % of the map area). For the new favorability map, 93 % of power-producing systems (i.e., 26 of 28) are above the 80th percentile. The power-producing systems for which the new model does not perform well are either comparatively small, low-temperature systems or systems also not predicted well by prior modeling approaches, suggesting that these few systems are unusual when compared with most power-producing systems. Focusing research on these known, seemingly different systems may yield new insights and subsequent discovery of new prospects.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2025.103450","usgsCitation":"Mordensky, S.P., Burns, E., Lipor, J., and DeAngelo, J., 2025, Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA: Geothermics, v. 133, 103450, 24 p., https://doi.org/10.1016/j.geothermics.2025.103450.","productDescription":"103450, 24 p.","ipdsId":"IP-170174","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":495066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2025.103450","text":"Publisher Index Page"},{"id":494947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.0202610934917,\n 42.55970962212865\n ],\n [\n -119.8746500530377,\n 37.88790476539039\n ],\n [\n -116.94256843416173,\n 36.91537025154052\n ],\n [\n -113.73824592248651,\n 36.98857095813982\n ],\n [\n -111.99293303262,\n 42.55970962212865\n ],\n [\n -115.98687680320434,\n 42.23211305382921\n ],\n [\n -118.48297767228134,\n 42.58841357223409\n ],\n [\n -121.0202610934917,\n 42.55970962212865\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"133","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":947427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":225412,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":947428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lipor, John 0000-0002-0990-5493","orcid":"https://orcid.org/0000-0002-0990-5493","contributorId":292015,"corporation":false,"usgs":false,"family":"Lipor","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":947429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":947430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272689,"text":"70272689 - 2025 - The role of fire on Earth","interactions":[],"lastModifiedDate":"2026-01-07T17:36:21.383553","indexId":"70272689","displayToPublicDate":"2025-08-23T10:46:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"The role of fire on Earth","docAbstract":"Fire is a defining feature of our biosphere, having appeared when the first plants colonized the land, and it continues to occur across the planet at different frequencies and intensities. Fire has been and remains as an evolutionary force in many plant and animal lineages and contributes to explaining the variability of our biodiversity. Fire has also shaped the structure of many ecosystems and the distribution of biomes, and it is an important contributor to the global biogeochemical cycles. In addition, fire has been a key factor in human evolution, and, in turn, humans have modified fire regimes with important consequences for the biosphere. Consequently, fire is an intrinsic factor on our planet. Our challenge now is to understand and predict the role of fire in a densely populated, highly technological world that imposes significant changes on the Earth.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biaf132","usgsCitation":"Pausas, J.G., Keeley, J., and Bond, W.J., 2025, The role of fire on Earth: BioScience, v. 75, no. 12, p. 1028-1041, https://doi.org/10.1093/biosci/biaf132.","productDescription":"14 p.","startPage":"1028","endPage":"1041","ipdsId":"IP-176989","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":497116,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biaf132","text":"Publisher Index Page"},{"id":497067,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"12","noUsgsAuthors":false,"publicationDate":"2025-08-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Pausas, Juli G.","contributorId":363229,"corporation":false,"usgs":false,"family":"Pausas","given":"Juli","middleInitial":"G.","affiliations":[{"id":86660,"text":"Centro de Investigaciones sobre Desertificación, Consejo Superior de Investigaciones Científicas, Moncada, Spain","active":true,"usgs":false}],"preferred":false,"id":951336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeley, Jon 0000-0002-4564-6521","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":216485,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":951337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bond, William J.","contributorId":363230,"corporation":false,"usgs":false,"family":"Bond","given":"William","middleInitial":"J.","affiliations":[{"id":12665,"text":"University of Cape Town","active":true,"usgs":false}],"preferred":false,"id":951338,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70273328,"text":"70273328 - 2025 - Near-surface material and topography generate anomalous high-frequency ground motion amplification in Chugiak, Alaska","interactions":[],"lastModifiedDate":"2026-01-06T15:19:15.394653","indexId":"70273328","displayToPublicDate":"2025-08-22T09:12:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Near-surface material and topography generate anomalous high-frequency ground motion amplification in Chugiak, Alaska","docAbstract":"An ∼3 km long nodal array oriented approximately east–west was deployed in Chugiak, Alaska, by the U.S. Geological Survey during 2021. The array intersects with the permanent NetQuakes station NP.ARTY, where peak ground acceleration (PGA) value of 1.98g was recorded during the 2018 Mw 7.1 Anchorage, Alaska, earthquake, in sharp contrast to the PGA of ∼0.3g at a site just 4 km to the west. Seismic data for Mw 1.8–4.3 aftershocks from the Mw 7.1 event recorded by the nodal array confirm the anomalously large ground motions obtained at NP.ARTY as well as similar amplifications at nodes within ∼1 km to the east. Here, we performed 0–10 Hz 3D finite‐difference simulations, including high‐resolution surface topography, to explore the cause of the unexpectedly large amplification. As expected, the simulations computed with a regional 3D tomography velocity model severely underpredict the 0–10 Hz acceleration records at almost all sites. Adding a near‐surface low‐velocity taper to 300 m depth amplifies the accelerations by up to a factor of 5 and enables a reasonable match between the nodal data and simulations at sites to the west of NP.ARTY. However, this model still underpredicts the spectral energy in the area covered by glacial sediments by up to an order of magnitude. The addition of a till layer using a depth‐dependent shear‐wave velocity (Vs) profile along with a homogeneous, 8 m thick low‐velocity layer with Vs = 250 m/s representing the kame terraces improves the fit to data to within a factor of 2 at nodes located on top of the glacial sediments. Our study shows that the anomalously large high‐frequency amplification recorded at and near NP.ARTY can be explained by a combination of topographic effects and near‐surface low‐velocity material with amplification effects on the high‐frequency ground motion by up to about 40% and an order of magnitude, respectively.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120240283","usgsCitation":"Yeh, T., Olsen, K.B., Steidl, J.H., and Haeussler, P., 2025, Near-surface material and topography generate anomalous high-frequency ground motion amplification in Chugiak, Alaska: Bulletin of the Seismological Society of America, v. 115, no. 6, p. 2793-2808, https://doi.org/10.1785/0120240283.","productDescription":"16 p.","startPage":"2793","endPage":"2808","ipdsId":"IP-173630","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":498350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Chugiak","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.0449585780233,\n 61.579337610698786\n ],\n [\n -150.32779349821365,\n 61.579337610698786\n ],\n [\n -150.32779349821365,\n 60.81067946634249\n ],\n [\n -149.0449585780233,\n 60.81067946634249\n ],\n [\n -149.0449585780233,\n 61.579337610698786\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-08-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Yeh, Te-Yang 0000-0002-9146-6804","orcid":"https://orcid.org/0000-0002-9146-6804","contributorId":364872,"corporation":false,"usgs":false,"family":"Yeh","given":"Te-Yang","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":953357,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olsen, Kim B.","contributorId":364874,"corporation":false,"usgs":false,"family":"Olsen","given":"Kim","middleInitial":"B.","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":953358,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steidl, Jamison Haase 0000-0003-0612-7654","orcid":"https://orcid.org/0000-0003-0612-7654","contributorId":239709,"corporation":false,"usgs":true,"family":"Steidl","given":"Jamison","email":"","middleInitial":"Haase","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":953359,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haeussler, Peter J. 0000-0002-1503-6247","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":353464,"corporation":false,"usgs":false,"family":"Haeussler","given":"Peter J.","affiliations":[{"id":84407,"text":"USGS ASC retired","active":true,"usgs":false}],"preferred":false,"id":953360,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70270361,"text":"dr1214 - 2025 - Revised marine bird collision and displacement vulnerability index for U.S. Pacific Outer Continental Shelf offshore wind energy development","interactions":[],"lastModifiedDate":"2026-02-03T15:11:59.483763","indexId":"dr1214","displayToPublicDate":"2025-08-21T06:59:57","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1214","displayTitle":"Revised Marine Bird Collision and Displacement Vulnerability Index for U.S. Pacific Outer Continental Shelf Offshore Wind Energy Development","title":"Revised marine bird collision and displacement vulnerability index for U.S. Pacific Outer Continental Shelf offshore wind energy development","docAbstract":"The installation of offshore wind energy infrastructure (OWEI) at sea may affect marine birds by increasing the risk of mortality from collision with OWEI (Collision Vulnerability) and causing disturbance and displacement from important habitats (Displacement Vulnerability). In 2017, we published the first comprehensive database quantifying marine bird Collision Vulnerability and Displacement Vulnerability to potential OWEI in the region of the U.S. Pacific Outer Continental Shelf (POCS; waters within the Exclusive Economic Zone of California, Oregon, and Washington). We have updated this Vulnerability Index with new research and data, additional species present in the POCS, and an evolved understanding of the application and utility of the Index. Of the species assessed, phalaropes and Red-billed Tropicbird have the highest Collision Vulnerability, and gulls, terns, jaegers, skuas, and pelicans have moderately high Collision Vulnerability. Boobies, sea ducks, and pelicans have the greatest Displacement Vulnerability. The overall trends in ranked Vulnerability among marine birds in the POCS were consistent between Version 1 and Version 2 although new data and revised calculations updated the outcomes. Alcids, loons, storm-petrels, Brant, and phalaropes ranked higher for Collision Vulnerability in Version 2 compared to Version 1; sea ducks, cormorants, skua, and jaegers ranked lower for Collision Vulnerability in Version 2 compared to Version 1. Displacement Vulnerability ranks were higher in Version 2 for gulls, pelicans, sea ducks, and alcids and lower for albatrosses, terns, and loons. Vulnerability Index Version 2 is an up-to-date, representative, and transparent assessment of marine bird vulnerability to potential offshore wind energy development. This updated Vulnerability Index can assist resource managers and others in understanding and addressing potential interactions between OWEI and marine bird species that inhabit the POCS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1214","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Kelsey, E.C., Felis, J.J., Pereksta, D.M., and Adams, J., 2025, Revised marine bird collision and displacement vulnerability index for U.S. Pacific Outer Continental Shelf offshore wind energy development (ver. 1.1,\nNovember 2025): U.S. Geological Survey Data Report 1214, 32 p., https://doi.org/10.3133/dr1214.","productDescription":"viii, 32 p.","onlineOnly":"Y","ipdsId":"IP-167805","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":496435,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1214/dr1214.XML"},{"id":496432,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/dr/1214/VersionHistory.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":496434,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1214/images"},{"id":496433,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1OUOM9W","text":"USGS data release","description":"USGS data release","linkHelpText":"Data for the revised marine bird Collision and Displacement Vulnerability Index for Pacific Outer Continental Shelf offshore wind energy development"},{"id":496431,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1214/dr1214.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1214"},{"id":496429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1214/coverthb2.jpg"}],"country":"Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.11122811871701,\n 46.836231292523934\n ],\n [\n -133.66298337147504,\n 43.87312626189197\n ],\n [\n -135.1639174719598,\n 38.18991249267404\n ],\n [\n -124.75213428275356,\n 21.70090202972672\n ],\n [\n -117.3903149351834,\n 19.187148095597664\n ],\n [\n -108.20584860772473,\n 21.105959128505745\n ],\n [\n -110.47687143079384,\n 23.789215318067903\n ],\n [\n -114.73093128440786,\n 29.394483151806185\n ],\n [\n -116.81948042658601,\n 32.732895836344994\n ],\n [\n -120.58898983505466,\n 35.78436076311384\n ],\n [\n -123.50560199570324,\n 40.66753444650692\n ],\n [\n -123.11122811871701,\n 46.836231292523934\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: August 19, 2025; Version 1.1: November 17, 2025","contact":"Director, Western Ecological Research Center
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The U.S. Geological Survey (USGS) is using collaborative, interdisciplinary planning to develop data and tools needed to optimize the management of water resources and land use by resource management agencies during an ongoing, multidecadal drought in the Colorado River Basin. The USGS Actionable and Strategic Integrated Science and Technology team works to build relationships with resource management agencies and other stakeholders who can benefit from the use of USGS data and products. In 2023, the Actionable and Strategic Integrated Science and Technology team hosted a series of collaborative workshops to bring together representatives of resource management agencies and other stakeholders (any person or entity with interests in a resource or location) with USGS program managers, scientists, and multidisciplinary subject matter experts to codevelop concepts for interdisciplinary drought science and technology projects to address pressing needs related to drought in the Colorado River Basin. Workshop participants identified current and recent scientific data that could be shared through a centralized online data portal. Workshop participants also identified drought science and technology needs and developed project concepts to address those science needs. Participants categorized project concepts based on their potential to develop short-, mid-, and long-term drought science data and tools, provide for the spatial or temporal expansion of ongoing USGS science projects, and address high-priority science needs. Participants developed nine project concepts: (1) understanding shifting ecohydrologic baselines, (2) San Juan River Basin synthesis, (3) incorporating dynamic land cover into hydrologic models, (4) aridification compared to drought, (5) surface water-groundwater interactions, (6) cascading effects of drought on dust, (7) cascading effects of drought on water availability, (8) cascading effects of drought on socioeconomic factors, and (9) the value of water in the Colorado River Basin. This report provides an overview of the 2023 Codesign Workshop Series, synthesized outcomes from workshop materials and discussions, and science project concepts that emerged from the collaborative meetings that will continue to be refined into science project proposals through codevelopment processes. This report also highlights lessons learned and next steps needed to receive feedback and testing of the USGS Science Collaboration Portal, continue collaboration to develop detailed specifics and steps for short-term wins, develop interdisciplinary project proposals, and implement science planning and studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20251041","usgsCitation":"Anderson, P.J., Godaire, J.E., Jones, D.K., Andrews, W.J., Torregrosa, A.A., Bell, M.T., Holloway, J.M., Blakowski, M.A., Hevesi, J.A., and Qi, S.L., 2025, Collaborative drought science planning in the Colorado River Basin: U.S. Geological Survey Open-File Report 2025–1041, 32 p., https://doi.org/10.3133/ofr20251041.","productDescription":"vi, 32 p.","onlineOnly":"Y","ipdsId":"IP-165607","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":494357,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1041/ofr20251041.xml"},{"id":494378,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251041/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1041"},{"id":494325,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1041/ofr20251041.pdf","text":"Report","size":"9.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1041"},{"id":494356,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1041/images"},{"id":494324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1041/coverthb.jpg"}],"country":"Mexico, United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.23441985470737,\n 42.42360949558767\n ],\n [\n -110.0074572875208,\n 42.9273485741041\n ],\n [\n -110.88201818257588,\n 40.83215412591818\n ],\n [\n -112.09041488325958,\n 37.81270064609009\n ],\n [\n -113.86864235906498,\n 37.77076755792572\n ],\n [\n -113.94586057217214,\n 38.21912009189296\n ],\n [\n -115.10119317735365,\n 39.08121928179544\n ],\n [\n -115.47544949784407,\n 35.429353160164375\n ],\n [\n -115.29249888241867,\n 31.986896837542588\n ],\n [\n -110.42076682180414,\n 30.172954165166573\n ],\n [\n -108.95437388160886,\n 30.991312421045535\n ],\n [\n -108.56364522256465,\n 31.857948821439074\n ],\n [\n -107.84802514114666,\n 32.26017852956302\n ],\n [\n -107.22575341999277,\n 34.155285973008596\n ],\n [\n -107.68523996280838,\n 35.482296714195456\n ],\n [\n -106.46728549757393,\n 37.071939542790304\n ],\n [\n -105.6885671199549,\n 39.88037502712785\n ],\n [\n -106.23441985470737,\n 42.42360949558767\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
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Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland were carried out in July–August 1971 as part of a grant to the University of Oregon Center for Volcanology to refine the models of crystallization and differentiation of the intrusion, specifically to test whether the intrusion is underlain by dense rocks of a reservoir 20 kilometers (km) thick (referred to as a “hidden zone”). The Skaergaard intrusion is a source of platinum group elements that are critical mineral resources for many technologies, and because no new data have been collected these legacy datasets remain a valuable asset. The total-intensity aeromagnetic survey was flown in early July 1971 with a proton precession magnetometer at a constant barometric altitude of 1.5 km (5,000 feet) with a nominal line spacing of 1 km. Two gravimeters were used to acquire 168 stations of which 86 were at known altitudes (mainly sea level) and 82 had altitudes measured by altimetry in late July–August 1971. Finally, a north-south ground vertical-intensity magnetic traverse was completed across the intrusion together with collection of oriented hand specimens. The hand specimens were measured for remnant magnetization and density, along with density measurements of more specimens collected by expedition geologists for other purposes.
The intrusion is composed of layered gabbro with extensive crystal fractionation that is dense and strongly reversely polarized. After terrain correction and standard Bouguer gravity reduction, the gravity anomaly dataset was corrected for all rock above sea level using the density measurements of the various zones of the intrusion and the topographic and geologic maps (variable density Bouguer gravity reduction).
A large regional gradient in the gravity anomaly data was removed using orthogonal polynomial fitting to the gridded data. The zonal volumes of rock below sea level were calculated from the dipping polygonal layer gravity model of the intrusion below sea level and combined with elliptic cross–section cylinders for the various zones above sea level to approximate the original zonal volumes of the intrusion. The residual gravity anomaly of 18–20 milligals (mGal) was only about half of the expected anomaly if a large hidden zone proposed from petrologic considerations were present, and both two-dimensional and three-dimensional models imply that the exposed series of intrusion zones explain the gravity anomaly by their down-dip extension below sea level together with a small hidden-zone volume. A three-dimensional model of the exposed rocks and their down-dip extension below sea level also can account for the aeromagnetic anomaly with little or no requirement for hidden-zone rock. The middle and upper zone units of the intrusion contain the most magnetite and account for most of the aeromagnetic anomaly.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251030","programNote":"Mineral Resources Program","usgsCitation":"Gettings, M.E., 2025, Gravity and magnetic surveys of the Skaergaard intrusion, East Greenland: U.S. Geological Survey Open-File Report 2025–1030, 43 p., https://doi.org/10.3133/ofr20251030.","productDescription":"Report: ix, 43 p.; Data Release","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-126792","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":494352,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91OVG7G","text":"USGS data release","description":"Gettings, M.E., and Parks, H.L., 2025, Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland, 1971: U.S. Geological Survey data release, https://doi.org/10.5066/P91OVG7G.","linkHelpText":"Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland, 1971"},{"id":494347,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1030/coverthb.jpg"},{"id":494348,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1030/ofr20251030.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1030 PDF"},{"id":494349,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251030/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1030 HTML"},{"id":494350,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1030/ofr20251030.XML","description":"OFR 2025-1030 XML"},{"id":494351,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1030/images"}],"country":"Greenland","otherGeospatial":"Skaergaard intrusion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -32.1667,\n 68.3\n ],\n [\n -32.1677,\n 68\n ],\n [\n -31.1667,\n 68\n ],\n [\n -31.1667,\n 68.3\n ],\n [\n -32.1667,\n 68.3\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, and Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Conventional dietary assessments are challenging in hematophagous species, particularly in sea lamprey (Petromyzon marinus). However, recent technological developments and molecular approaches have provided an attractive alternative through the use of DNA metabarcoding. While DNA metabarcoding has been used for dietary analyses in numerous species, including lampreys, applications of universal primers that detect a diverse set of prey items can be limited by the amplification of predator DNA. In this study, we designed and tested eight blocking primers designed to suppress the amplification of sea lamprey DNA with vertebrate-universal primers targeting the mitochondrial 12S rRNA gene. This approach allowed for the use of a single marker to amplify a taxonomically diverse suite of host species, in contrast to previous studies that used multiple taxon-specific primer pairs (e.g., Salmonidae, Cyprinidae, and Catostomidae). Candidate blocking primers evaluated in this study differed in base pair length, end sequence modification, and purification method. Samples with different sea lamprey-to-host DNA ratios were subjected to multiple detection methods including gel electrophoresis, quantitative PCR, and DNA metabarcoding to assess the ability of each blocking primer to selectively suppress amplification of the sea lamprey 12S gene region. All blocking primers tested performed well and demonstrated high effectiveness, suppressing sea lamprey reads by > 99.9% in mock communities and improving host DNA sequence recovery across various sample types, including wild-caught lamprey. Results show that the blocking primers evaluated can facilitate molecular diet analysis in sea lamprey, allowing the amplification of a taxonomically diverse range of host fish species with universal primers.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71999","usgsCitation":"O'Kane, C., Johnson, N.S., Scribner, K.T., Kanefsky, J., Li, W., and Robinson, J.D., 2025, Development of PCR blocking primers enabling DNA metabarcoding analysis of dietary composition in hematophagous sea lamprey: Ecology and Evolution, v. 15, no. 8, e71999, 17 p., https://doi.org/10.1002/ece3.71999.","productDescription":"e71999, 17 p.","ipdsId":"IP-180902","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":495047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71999","text":"Publisher Index Page"},{"id":494536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.42859751371756,\n 46.71487752181625\n ],\n [\n -88.36277690371458,\n 45.01774821823912\n ],\n [\n -88.31731481855903,\n 41.21678815653618\n ],\n [\n -82.47857075519083,\n 40.921825838317346\n ],\n [\n -76.56443794208697,\n 42.71597391873013\n ],\n [\n -75.95858087681425,\n 44.662611421640634\n ],\n [\n -78.61421032535229,\n 45.36119897624181\n ],\n [\n -83.48488030611055,\n 47.11030206757272\n ],\n [\n -83.94723014044203,\n 48.52355518474724\n ],\n [\n -89.06406805799038,\n 49.4614460474032\n ],\n [\n -93.42859751371756,\n 46.71487752181625\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-08-20","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Kane, Conor","contributorId":360151,"corporation":false,"usgs":false,"family":"O'Kane","given":"Conor","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":946859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scribner, Kim T.","contributorId":360153,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim","middleInitial":"T.","affiliations":[{"id":85977,"text":"Michigan State Univesity","active":true,"usgs":false}],"preferred":false,"id":946860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kanefsky, Jeannette","contributorId":243198,"corporation":false,"usgs":false,"family":"Kanefsky","given":"Jeannette","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946862,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, John D.","contributorId":360155,"corporation":false,"usgs":false,"family":"Robinson","given":"John","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946863,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272186,"text":"70272186 - 2025 - Divergent trends in fluvial suspended-sediment concentrations following improved land-use practices, southwest Washington State","interactions":[],"lastModifiedDate":"2025-11-18T15:33:25.145266","indexId":"70272186","displayToPublicDate":"2025-08-20T09:20:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Divergent trends in fluvial suspended-sediment concentrations following improved land-use practices, southwest Washington State","docAbstract":"Improvements in logging practices since the mid-20th century are widely presumed to have reduced suspended sediment loads in streams across the Pacific Northwest. However, there have been few opportunities to directly assess this, particularly in larger rivers. We compare modern (2019–22) and historical (1960s) suspended sediment monitoring in three large, actively managed watersheds in western Washington with similar land-use histories. In the two watersheds draining the southern Olympic Mountains (Satsop and Wynoochee Rivers), modern sediment yields were around 300 t/km2/yr, two to three times lower than historical conditions. Most suspended sediment exiting these watersheds came from rolling terrain mantled by glacial deposits in the lower watersheds, not the steep headwaters. Modern sediment yields in the Chehalis River, draining the low-relief Willapa Hills, were lower (70 t/km2/yr), though this represented a 50 % increase relative to historical conditions. SSC-discharge relations in the Chehalis River were steady from 1961 to 1994, indicating this increase happened sometime after 1994. The Chehalis River headwaters were uniquely impacted by landsliding during a 2007 storm, though there is some evidence against that storm as the cause of the recent increase. Ultimately, improved land-use practices appear to have reduced suspended sediment loads in large rivers of the southern Olympic Mountains several-fold, consistent with prior findings in the western Olympic Mountains, primarily due to reduced sediment delivery from the lower watersheds. Countervailing SSC-discharge trends and lower yields in the Chehalis River underscore that background sediment delivery rates and sensitivity to land-use disturbance may vary substantially within a region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2025.109963","usgsCitation":"Anderson, S., Curran, C.A., Wilkerson, O., and Seguin, K., 2025, Divergent trends in fluvial suspended-sediment concentrations following improved land-use practices, southwest Washington State: Geomorphology, v. 488, 109963, 13 p., https://doi.org/10.1016/j.geomorph.2025.109963.","productDescription":"109963, 13 p.","ipdsId":"IP-159608","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":496732,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2025.109963","text":"Publisher Index Page"},{"id":496585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Chehalis River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124,\n 47.667\n ],\n [\n -124,\n 46.333\n ],\n [\n -122.333,\n 46.333\n ],\n [\n -122.333,\n 47.667\n ],\n [\n -124,\n 47.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"488","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W 0000-0002-6239-7352","orcid":"https://orcid.org/0000-0002-6239-7352","contributorId":344221,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott W","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkerson, Oscar A. 0000-0003-1786-5329","orcid":"https://orcid.org/0000-0003-1786-5329","contributorId":344222,"corporation":false,"usgs":true,"family":"Wilkerson","given":"Oscar","middleInitial":"A.","affiliations":[{"id":80400,"text":"Washington Water Science Center","active":true,"usgs":false}],"preferred":true,"id":950369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seguin, Katie","contributorId":362358,"corporation":false,"usgs":false,"family":"Seguin","given":"Katie","affiliations":[{"id":86510,"text":"USGS, WA WSC","active":true,"usgs":false}],"preferred":false,"id":950368,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70276403,"text":"70276403 - 2025 - Hidden legacies: Investigating buried pre-colonial stream corridors in the Mid-Atlantic Coastal Plain, Maryland, USA","interactions":[],"lastModifiedDate":"2026-06-04T15:10:31.066409","indexId":"70276403","displayToPublicDate":"2025-08-20T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Hidden legacies: Investigating buried pre-colonial stream corridors in the Mid-Atlantic Coastal Plain, Maryland, USA","docAbstract":"Within the Mid-Atlantic United States, widespread landscape disturbance during European colonization resulted in erosion and subsequent storage of legacy sediments within river valleys and floodplains, altering their form, function, and flora. Previous studies of precolonial river corridors have influenced river restoration designs and targets throughout the region, but the generalizability of these studies into other physiographic settings, such as the Coastal Plain, is unknown. Therefore, our study investigated the physical form and riparian vegetation of pre-colonial stream corridors located within the Coastal Plain of Anne Arundel County, Maryland, documenting changes from pre- to colonial and postcolonial time periods. Our study provides evidence of buried, precolonial riparian ecosystems with dates ranging between 750 years to 8000 years Before Present. These valley bottom ecosystems were likely a dynamic patch mosaic, largely dominated by dense Alnus (alder) scrub swamps with variable Poaceae (grass) and Cyperaceae (sedge) dominated meadows and both multi-threaded and single-threaded channel forms. These precolonial floodplains are buried by vast amounts of legacy sediment to the extent that pre-colonial sediments are largely not exposed in the modern valley bottom. Notably, the Coastal Plain precolonial corridors investigated in this study contrast to studies in the Piedmont physiographic region with precolonial sediments exposed in streambanks and with precolonial ecosystems described as herbaceous stream-wetlands. Our findings provide critical historical context as to the magnitude of alteration for modern stream channels and suggest an alternative precolonial ecosystem which can be used to inform restoration designs, management targets, and reestablishment of channel functional processes in areas of the Mid-Atlantic Coastal Plain.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2025.107771","usgsCitation":"Cashman, M.J., Clifton, Z.J., Landacre, B.D., Bernhardt, C.E., Wiedenhoeft, A.C., and Victoria, C.J., 2025, Hidden legacies: Investigating buried pre-colonial stream corridors in the Mid-Atlantic Coastal Plain, Maryland, USA: Ecological Engineering, v. 221, 107771, 24 p., https://doi.org/10.1016/j.ecoleng.2025.107771.","productDescription":"107771, 24 p.","ipdsId":"IP-160189","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":505057,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2025.107771","text":"Publisher Index Page"},{"id":504997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Mid-Atlantic Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.67198174426711,\n 39.16602363675844\n ],\n [\n -76.37085843168573,\n 39.16604634751161\n ],\n [\n -76.37085974704267,\n 38.66316241515625\n ],\n [\n -76.67198714447551,\n 38.66315266998711\n ],\n [\n -76.67198174426711,\n 39.16602363675844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"221","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cashman, Matthew J. 0000-0002-6635-4309","orcid":"https://orcid.org/0000-0002-6635-4309","contributorId":203315,"corporation":false,"usgs":true,"family":"Cashman","given":"Matthew","middleInitial":"J.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":962338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clifton, Zachary J. 0000-0002-8148-5454","orcid":"https://orcid.org/0000-0002-8148-5454","contributorId":220551,"corporation":false,"usgs":true,"family":"Clifton","given":"Zachary","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":962340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landacre, Bryan D. 0000-0002-0523-360X blandacre@usgs.gov","orcid":"https://orcid.org/0000-0002-0523-360X","contributorId":2722,"corporation":false,"usgs":true,"family":"Landacre","given":"Bryan","email":"blandacre@usgs.gov","middleInitial":"D.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":962390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernhardt, Christopher E. 0000-0003-0082-4731 cbernhardt@usgs.gov","orcid":"https://orcid.org/0000-0003-0082-4731","contributorId":2131,"corporation":false,"usgs":true,"family":"Bernhardt","given":"Christopher","email":"cbernhardt@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":962391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiedenhoeft, Alex C.","contributorId":371766,"corporation":false,"usgs":false,"family":"Wiedenhoeft","given":"Alex","middleInitial":"C.","affiliations":[{"id":88223,"text":"US Forest Service, Forest Products Laboratory","active":true,"usgs":false}],"preferred":false,"id":962342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Victoria, Christopher J.","contributorId":371767,"corporation":false,"usgs":false,"family":"Victoria","given":"Christopher","middleInitial":"J.","affiliations":[{"id":88224,"text":"Anne Arundel County, Bureatu of Watershed Protection and Restoration","active":true,"usgs":false}],"preferred":false,"id":962343,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267829,"text":"70267829 - 2025 - Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent","interactions":[],"lastModifiedDate":"2026-01-16T16:33:30.622156","indexId":"70267829","displayToPublicDate":"2025-08-19T10:30:56","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent","docAbstract":"The increased demand for clean energy technology and a significant reliance on foreign supply chains have given impetus to understanding critical mineral systems and locating potential resources within the United States. At least thirteen critical mineral-bearing systems have been identified throughout the U.S. southern Midcontinent (Hofstra and Kreiner, 2020) but much of the region’s geologic framework is concealed by vegetation and sedimentary cover that hinder traditional geologic mapping efforts. Airborne geophysical data provide an effective way to overcome these obstacles and to provide additional insight into the deeper structures that underlie shallow mineralization. However, legacy airborne magnetic and radiometric data were collected using now-outdated instruments and methods, inconsistent survey parameters, and large flight-line spacings resulting in low-resolution data that present challenges to regional-scale study and interpretation. Over the last decade, the U.S. Geological Survey Earth Mapping Resources Initiative (EMRI) and National Cooperative Geologic Mapping Program have conducted a series of high-resolution airborne magnetic and radiometric surveys across the southern Midcontinent (Fig. 1) as part of an effort to improve understanding of the geophysical framework and natural resource potential in the region. These surveys are designed using modern survey methods and instruments with consistent parameters for flight-line spacing and flight height relative to magnetic sources. The EMRI airborne surveys are planned in collaboration with State geological surveys based on focus areas (Dicken et al., 2022) according to the presence of or potential for critical mineral deposits. High-resolution airborne magnetic and radiometric data cover focus areas such as the southeast Missouri iron metallogenic province and South-Central iron-oxide-apatite (IOA) – iron-oxide-copper-gold (IOCG) province, the Magnet Cove alkaline-carbonatite complex, the Midwest Permian ultramafic dike district, the Illinois-Kentucky fluorspar district, and several Mississippi Valley-type lead-zinc deposits and districts (Fig. 1). These focus areas represent known deposits or prospective host systems of critical minerals including rare earth elements (REEs), platinum-group elements (PGEs), cobalt, lithium, fluorspar, niobium, titanium, vanadium, lead, zinc, gallium, germanium, and many more. Other significant geologic and geophysical features covered include the Reelfoot rift, the New Madrid seismic zone, the Illinois basin, the Arkoma basin, the South-Central magnetic lineament, and the Kentucky-Tennessee magnetic anomaly (Fig. 1). This presentation focuses on new airborne magnetic and radiometric data with continuous coverage across parts of six states, preliminary interpretations, examples of geologic mapping applications, and discussion of newly discovered magnetic anomalies and follow-up investigations.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geologic Mapping Forum 24/24 abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"University of Minnesota Twin Cities","usgsCitation":"Amaral, C.M., McCafferty, A.E., and Connell, D., 2025, Airborne geophysics for geologic mapping of critical mineral systems in the United States southern midcontinent, in Geologic Mapping Forum 24/24 abstracts, p. 15-16.","productDescription":"2 p.","startPage":"15","endPage":"16","ipdsId":"IP-173917","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":489447,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://hdl.handle.net/11299/275433"},{"id":498748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.25384608464034,\n 38.46574935812839\n ],\n [\n -93.61302912846105,\n 38.46574935812839\n ],\n [\n -93.61302912846105,\n 34.021659839091996\n ],\n [\n -86.25384608464034,\n 34.021659839091996\n ],\n [\n -86.25384608464034,\n 38.46574935812839\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2025-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Amaral, Chelsea Morgan 0000-0003-4632-4097","orcid":"https://orcid.org/0000-0003-4632-4097","contributorId":313539,"corporation":false,"usgs":true,"family":"Amaral","given":"Chelsea","email":"","middleInitial":"Morgan","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":939061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCafferty, Anne E. 0000-0001-5574-9201 anne@usgs.gov","orcid":"https://orcid.org/0000-0001-5574-9201","contributorId":1120,"corporation":false,"usgs":true,"family":"McCafferty","given":"Anne","email":"anne@usgs.gov","middleInitial":"E.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":939062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connell, Dylan Mark 0000-0001-8678-2776","orcid":"https://orcid.org/0000-0001-8678-2776","contributorId":292570,"corporation":false,"usgs":true,"family":"Connell","given":"Dylan Mark","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":939063,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70270458,"text":"70270458 - 2025 - Improved prediction of postfire debris flows through rainfall anomaly maps","interactions":[],"lastModifiedDate":"2025-08-20T14:53:20.297849","indexId":"70270458","displayToPublicDate":"2025-08-19T09:48:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Improved prediction of postfire debris flows through rainfall anomaly maps","docAbstract":"Predicting where runoff-generated debris flows might occur during rainfall on steep, recently burned terrain is challenging. Studies of mass-movement processes in unburned areas indicate that event locations are well-predicted by rainfall anomaly, R*, in which peak observed rainfall is normalized by local rainfall climatology. Here, we use remote and field methods to map debris flows triggered within the 2020 Dolan Fire burn area in coastal California, demonstrate that a short-duration R* metric predicts debris-flow occurrence more effectively than absolute peak intensity or longer-duration rainfall metrics, and show that incorporating an R* criterion into an existing debris-flow likelihood model can reduce false positive predictions and improve accuracy. We test R* at three other climatically distinct fires in California, demonstrating its utility for mapping likely debris-flow locations in different climates. We also consider how R* can benefit postfire debris-flow prediction given recent increases in climatological variability within individual burn perimeters.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL114791","usgsCitation":"Cavagnaro, D.B., McCoy, S.W., Thomas, M.A., Kostelnik, J., and Lindsay, D.N., 2025, Improved prediction of postfire debris flows through rainfall anomaly maps: Geophysical Research Letters, v. 52, no. 16, e2025GL114791, 12 p., https://doi.org/10.1029/2025GL114791.","productDescription":"e2025GL114791, 12 p.","ipdsId":"IP-170042","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":494967,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZGR6F","text":"USGS data release","linkHelpText":"Inventory of fluvial erosion and debris-flow activity following the 2020 Dolan Fire, California"},{"id":494458,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl114791","text":"Publisher Index Page"},{"id":494344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Callifornia","county":"Monterey County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.7,\n 36.2\n ],\n [\n -121.7,\n 35.9\n ],\n [\n -121.3,\n 35.9\n ],\n [\n -121.3,\n 36.2\n ],\n [\n -121.7,\n 36.2\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"16","noUsgsAuthors":false,"publicationDate":"2025-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavagnaro, David B.","contributorId":359920,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","middleInitial":"B.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":946432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Scott W.","contributorId":359922,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott","middleInitial":"W.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":946433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":946434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":946435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsay, Donald N.","contributorId":359924,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":946436,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270590,"text":"70270590 - 2025 - Potomac Tributary Summary: A summary of trends in tidal water quality and associated factors, 1985 - 2022","interactions":[],"lastModifiedDate":"2025-08-21T14:07:08.104178","indexId":"70270590","displayToPublicDate":"2025-08-19T08:53:54","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Potomac Tributary Summary: A summary of trends in tidal water quality and associated factors, 1985 - 2022","docAbstract":"The Potomac Tributary Summary outlines change over time for a suite of monitored tidal water quality parameters and associated potential drivers of those trends for the period of 1985 to 2022, and provides a brief description of the current state of knowledge explaining these observed changes. Water quality parameters described include surface (above pycnocline) total nitrogen (TN), surface total phosphorus (TP), surface water temperature (WTEMP), spring (March-May) and summer (July-September) surface chlorophyll a, summer bottom (below pycnocline) dissolved oxygen (DO) concentrations, and Secchi disk depth (a measure of water clarity). Results for annual bottom TP, bottom TN, surface ortho-phosphate (PO4), surface dissolved inorganic nitrogen (DIN), surface total suspended solids (TSS), and summer surface DO concentrations are provided in Appendix B. Drivers discussed include physiographic watershed characteristics, changes in TN, TP, and sediment loads from the watershed to tidal waters, expected effects of changing land use, and implementation of nutrient management and natural resource conservation practices. Factors internal to estuarine waters that also play a role as drivers are described including biogeochemical processes, physical forces such as wind driven mixing of the water column and increase in rainfall intensity and volume, and biological factors such as phytoplankton biomass and the presence of submerged aquatic vegetation. Continuing to track water quality response and investigating these influencing factors are important steps to understanding water quality patterns and changes in the Potomac River. The intended audiences for this report include, but are not limited to, 1) technical managers within jurisdictions who are looking at tidal water quality data and trying to understand why patterns are occurring, 2) local watershed organizations that are trying to understand these analyses and working to connect them to their local area(s), and 3) federal, state, and academic researchers. Figure 1 presents a conceptual model highlighting these intended audiences. Our goal is for the Tributary Summary documents to be sources of readily available background for change over time in tidal water quality observed with monitoring data. The intended purpose of the Tributary Summary documents is to help answer questions related to water quality, show how landscape factors drive water quality change over time, provide support for management decisions that may alter water quality trends and living resources conditions, and highlight where there may be information or knowledge gaps.","language":"English","publisher":"Chesapeake Bay Program","usgsCitation":"Sullivan, B.M., Gootman, K., Gunnerson, A., Betts, S., Duran, G., Johnson, C., Mason, C.A., Perry, E., Bhatt, G., Keisman, J.L., Webber, J.S., Harcum, J., Lane, M., Devereux, O., Zhang, Q., Murphy, R., Renee Karrh, Butler, T., and Wei, Z., 2025, Potomac Tributary Summary: A summary of trends in tidal water quality and associated factors, 1985 - 2022, 88 p.","productDescription":"88 p.","ipdsId":"IP-173187","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science 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