Groundwater-quality trend assessments identify aquifers that are responding to changes in pesticide use and the compounds that may pose a threat to water availability. The U.S. Geological Survey has been monitoring pesticide concentrations in groundwater for 25 principal aquifers across the conterminous United States since 1993. The groundwater well locations represent a range of soils, climate, and landforms. The wells are used to monitor groundwater underlying selected agricultural and urban settings and groundwater used for domestic supply. This study examined changes in relative concentrations, defined here as the percentage of wells with pesticide concentrations exceeding a human health benchmark (HHB). HHBs used in this report are legally enforceable drinking-water standards and nonenforceable drinking water levels. Relative pesticide concentration increases may lead to decreased water availability, as restrictions may be put in place for groundwater used as a drinking-water source.
This study focused on concentration changes in 22 pesticides that were included in laboratory analysis from 1993 to 2023. The analysis and interpretation of these pesticide concentrations in groundwater have been separated into approximate decadal intervals (decade 1 (1993–2001), decade 2 (2002–12), and decade 3 (2013–22). For one pesticide, 1,2-dibromo-3-chloropropane (DBCP), concentration data were also collected in decade 4 (2023–onward).
Atrazine, deethylatrazine, alachlor, prometon, and simazine were 5 pesticides detected at moderate concentrations (greater than 10 percent of the HHB but less than or equal to the HHB). The percentage of wells that had groundwater pesticide concentrations in the moderate concentration category decreased from 7 percent in decade 1 to 2 percent in decade 3. The agricultural networks had the highest percentages of wells with moderate concentrations, and these percentages decreased from 13 percent in decade 1 to 4 percent in decade 3. Moderate concentrations in the urban networks decreased between decades 1 and 2 from 4 percent to 0 percent. No moderate concentrations occurred in the urban networks in decade 3. The percentage of wells with moderate concentrations in the domestic supply networks (1 percent) was the lowest of all the network types and did not change across the three decades. Moderate atrazine or deethylatrazine concentrations occurred across all three decades in aggregated ecoregions representing similar soils, climate, and landforms in the Semiarid West, Midcontinent, and Northeastern United States. Moderate concentrations of prometon, alachlor, and simazine also occurred in the Midcontinent, Arid West, Northeast, South Atlantic Gulf, and Semiarid West regions, but the moderate concentrations did not persist across all three decades.
DBCP was the only pesticide that exceeded its respective HHB, and the exceedances occurred across all four decades. In this report, the DBCP analysis was limited to one well network in the Central Valley, California. Agricultural use of DBCP was suspended in 1977. Forty-five years after being banned, DBCP concentrations were greater than the maximum contaminant level of 2 micrograms per liter (μg/L), but the number of exceedances decreased from 50 percent to 15 percent of the samples between 1993 and 2023.
This assessment of decadal groundwater pesticide concentrations provides a characterization of changes in water availability because of pesticide contamination in areas where groundwater is used as a drinking-water source. The results highlight the importance of continued long-term monitoring and assessment of groundwater pesticides to identify locations and specific compounds that may pose a potential risk to human health.
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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
Wind erosion and sediment transport continue to increase in many parts of the world, leading to decreased soil quality, accelerated snow-melt, respiratory diseases, and traffic accidents. The processes that control sediment transport are well understood at small scales of mm to m but are less well understood at larger scales of km to hundreds of km. Here we test four approaches aimed at improving the variance explained in sediment transport measured in a network of 52 horizontal sediment flux collecting devices located on the Colorado Plateau, USA. First, switching from a regression tree to random forest statistical analysis increased the variance in sediment transport explained from 58% to 91%. Soil moisture as a single variable explained 52% of variation in sediment flux, but had a negligible effect on a random forest model with season (Winter, Spring, Summer), wind speed, and seasonal total precipitation. Similarly, adding four years of new data to an existing five-year dataset or adding measurements of soil roughness and grazing failed to improve variance explained. By explaining 91% of the variance in sediment transport, our model provides baseline model for understanding sediment transport on the landscape scale. Dust flux networks in new regions would likely need to collect at least 300-500 samples to describe variation in sediment transport values using random forest analyses of the effects of season, wind speed, seasonal rain and vegetation type.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0333166","usgsCitation":"Kulmatiski, A., Ozturk, M., Bladen, K.K., Brahney, J., and Duniway, M.C., 2025, Season, wind speed, and seasonal rain are major drivers of a regional aeolian sediment transport model: PLoS ONE, v. 20, no. 9, e0333166, 15 p., https://doi.org/10.1371/journal.pone.0333166.","productDescription":"e0333166, 15 p.","ipdsId":"IP-175885","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498292,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0333166","text":"Publisher Index Page"},{"id":498100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","volume":"20","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Kulmatiski, Andrew","contributorId":210408,"corporation":false,"usgs":false,"family":"Kulmatiski","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":952968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ozturk, Mehmet mozturk@usgs.gov","contributorId":196300,"corporation":false,"usgs":false,"family":"Ozturk","given":"Mehmet","email":"mozturk@usgs.gov","affiliations":[],"preferred":false,"id":952969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bladen, Kelvyn K.","contributorId":364634,"corporation":false,"usgs":false,"family":"Bladen","given":"Kelvyn","middleInitial":"K.","affiliations":[{"id":86880,"text":"Department of Mathematics and Statistics, Utah State University, Logan, UT, USA","active":true,"usgs":false}],"preferred":false,"id":952970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brahney, Janice","contributorId":269810,"corporation":false,"usgs":false,"family":"Brahney","given":"Janice","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":952971,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":219284,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":952972,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271978,"text":"70271978 - 2025 - Validation of gridded precipitation datasets for flood-typing in select conterminous U.S. basins","interactions":[],"lastModifiedDate":"2025-09-29T15:03:21.41738","indexId":"70271978","displayToPublicDate":"2025-09-26T07:58:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Validation of gridded precipitation datasets for flood-typing in select conterminous U.S. basins","docAbstract":"Gridded precipitation datasets are required for flood-typing historical annual peak streamflow events in basins across the Conterminous United States. Selected gridded precipitation datasets were validated over the period 1981–2013 through comparisons with gage data from the NOAA Global Historical Climatology Network daily (GHCNd). The ability of each gridded dataset to capture the spatiotemporal characteristics of daily precipitation, including multi-day extremes over six selected regions, was assessed using the Kling-Gupta Efficiency metric and its component statistics. Overall, the Parameter-elevation Regression on Independent Slopes Model and Livneh-unsplit were found to best match the spatiotemporal variability of the GHCNd precipitation data, including extremes. The Analysis of Record for Calibration was found to be the third best-performing dataset in most regions except in the western U.S. The performance of reanalysis datasets evaluated appears to be poor compared to gage-based datasets. The reanalysis datasets might not be able to skillfully capture precipitation amounts at the correct location and time. Gage- and radar-based datasets were found to have relatively small biases (within +/-10% on an annual basis), while reanalysis datasets were found to have larger positive apparent biases, especially in winter and spring in most regions. It is possible that the apparent overestimation of winter and spring precipitation in the reanalysis datasets might reflect snow undercatch at gages especially in the central U.S. An overall deterioration of performance for correlation and/or variability was also observed for the summer season compared to other seasons in the reanalysis datasets. Various precipitation datasets might need to be used for flood-typing during different periods from the late 19th century to present. Datasets from different sources have different biases and errors and might have to be homogenized using downscaling and bias-adjustment methods. Alternatively, precipitation thresholds used in some flood-typing schemes might have to be adjusted as a function of time.","language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/JHYEFF.HEENG-6500","usgsCitation":"Irizarry-Ortiz, M.M., and Murphy, S.Y., 2025, Validation of gridded precipitation datasets for flood-typing in select conterminous U.S. basins: Journal of Hydrologic Engineering, v. 30, no. 6, 04025042, 13 p., https://doi.org/10.1061/JHYEFF.HEENG-6500.","productDescription":"04025042, 13 p.","ipdsId":"IP-167576","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":496323,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/jhyeff.heeng-6500","text":"Publisher Index Page"},{"id":496227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous 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Article"},"seriesTitle":{"id":1445,"text":"Ecography","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying landscape-level biodiversity change in an island ecosystem: A 50-year assessment of shifts in the Hawaiian avian community","docAbstract":"Hawaii has experienced profound declines in native avifauna alongside the introduction of numerous bird species. While site-specific population studies are common, landscape-level analyses of avian population dynamics are rare, particularly in island ecosystems. To address this gap, we used a density surface model to create a spatio-temporal projection of population densities and distributions across the Island of Hawai‘i, spanning nearly five decades (1976–2023). We incorporated environmental covariates of habitat, precipitation, and elevation, to further refine our projections. Our analysis encompassed nine native and six non-native bird species, inhabiting a range of ecological niches. We found five out of nine native species have declined in density and range size while four were stable. For non-native species, two were stable, one was decreasing, and three were increasing in density and range size. Our landscape projections can inform management by suggesting areas critical for habitat preservation and land acquisition for conservation, identifying where range fragmentation is occurring, and pinpointing locations of multi-species declines that are likely driven by a common cause. Our study demonstrates how long-term, landscape-level monitoring and analyses can advance understanding and addressing biodiversity loss, particularly in vulnerable tropical island ecosystems.
","language":"English","publisher":"Nordic Society Oikos","doi":"10.1002/ecog.07907","usgsCitation":"Bak, T., Fortini, L., Hunt, N., Banko, P.C., Schnell, L., and Camp, R.J., 2025, Quantifying landscape-level biodiversity change in an island ecosystem: A 50-year assessment of shifts in the Hawaiian avian community: Ecography, v. 2025, no. 11, e07907, 18 p., https://doi.org/10.1002/ecog.07907.","productDescription":"e07907, 18 p.","ipdsId":"IP-177022","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":496739,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecog.07907","text":"Publisher Index Page"},{"id":496624,"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 -156.31156357630775,\n 20.24770610218596\n ],\n [\n -156.31156357630775,\n 18.872624778542928\n ],\n [\n -154.63317186924985,\n 18.872624778542928\n ],\n [\n -154.63317186924985,\n 20.24770610218596\n ],\n [\n -156.31156357630775,\n 20.24770610218596\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2025","issue":"11","noUsgsAuthors":false,"publicationDate":"2025-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Bak, Trevor","contributorId":292157,"corporation":false,"usgs":false,"family":"Bak","given":"Trevor","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":950519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":950520,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Noah","contributorId":355564,"corporation":false,"usgs":false,"family":"Hunt","given":"Noah","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":950521,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":950522,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schnell, Lena","contributorId":362454,"corporation":false,"usgs":false,"family":"Schnell","given":"Lena","affiliations":[{"id":86531,"text":"Center for the Environmental Management of Military Lands, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":950523,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":950524,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272023,"text":"70272023 - 2025 - Unveiling coseismic deformation from differenced legacy aerial photography and modern lidar topography: The 1983 M6.9 Borah Peak earthquake, Idaho, USA","interactions":[],"lastModifiedDate":"2025-11-13T16:55:22.485744","indexId":"70272023","displayToPublicDate":"2025-09-25T10:48:59","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":"Unveiling coseismic deformation from differenced legacy aerial photography and modern lidar topography: The 1983 M6.9 Borah Peak earthquake, Idaho, USA","docAbstract":"The 1983 M6.9 Borah Peak, Idaho, earthquake is one of the largest historical normal fault earthquakes in the western United States. We quantified meter-scale vertical change along the 35 km-long rupture using topographic differencing of 1966 aerial imagery and 2019 lidar-derived data. The initial differencing results are largely obscured by horizontal and vertical georeferencing errors and flight-line stripes. Our error corrections are designed to be insensitive to the coseismic deformation and reduced error by 50%. We calculated vertical separation and resolved a maximum of 2.02 ± 0.46 m at Doublespring Pass. Our vertical separation measurements are generally consistent with those from prior studies using field data and post-earthquake topographic data. However, the differencing measurements are a few decimeters lower than these prior measurements, indicating that differencing can isolate historical from prehistoric earthquake deformation. Our study demonstrates that revisiting historical earthquakes can provide new insights into the magnitude and patterns of coseismic deformation.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL115882","usgsCitation":"Scott, C.P., Reitman, N.G., and Bello, S., 2025, Unveiling coseismic deformation from differenced legacy aerial photography and modern lidar topography: The 1983 M6.9 Borah Peak earthquake, Idaho, USA: Geophysical Research Letters, v. 52, no. 18, e2025GL115882, 12 p., https://doi.org/10.1029/2025GL115882.","productDescription":"e2025GL115882, 12 p.","ipdsId":"IP-177417","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":496426,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl115882","text":"Publisher Index Page"},{"id":496410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Borah Peak","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.1667,\n 44.25\n ],\n [\n -114.1667,\n 44\n ],\n [\n -113.667,\n 44\n ],\n [\n -113.667,\n 44.25\n ],\n [\n -114.1667,\n 44.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"18","noUsgsAuthors":false,"publicationDate":"2025-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Scott, Chelsea P 0000-0002-3884-4693","orcid":"https://orcid.org/0000-0002-3884-4693","contributorId":248847,"corporation":false,"usgs":false,"family":"Scott","given":"Chelsea","email":"","middleInitial":"P","affiliations":[{"id":6607,"text":"Arizona State University","active":true,"usgs":false}],"preferred":false,"id":949752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reitman, Nadine G. 0000-0002-6730-2682 nreitman@usgs.gov","orcid":"https://orcid.org/0000-0002-6730-2682","contributorId":5816,"corporation":false,"usgs":true,"family":"Reitman","given":"Nadine","email":"nreitman@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":949753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bello, Simone","contributorId":360174,"corporation":false,"usgs":false,"family":"Bello","given":"Simone","affiliations":[{"id":85980,"text":"3Department of Sciences, University G. d’Annunzio Chieti-Pescara, 66100, Chieti, Italy","active":true,"usgs":false}],"preferred":false,"id":949754,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271972,"text":"70271972 - 2025 - Gas emissions from the Sulphur Bank Mercury Mine hydrothermal system, Clear Lake volcanic field, California","interactions":[],"lastModifiedDate":"2025-09-29T15:02:51.73324","indexId":"70271972","displayToPublicDate":"2025-09-25T09:57:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Gas emissions from the Sulphur Bank Mercury Mine hydrothermal system, Clear Lake volcanic field, California","docAbstract":"The Sulphur Bank Mercury Mine (SBMM) hydrothermal system offers insights into active degassing processes in the Clear Lake volcanic field (CLVF), a high-threat region based on its record of Holocene eruptions and proximity to populated areas. Here we present chemical and isotopic analyses of gas samples collected between 2015 and 2023, along with the first comprehensive CO2 flux survey of the SBMM area conducted in 2023. Sampled gases are CO2- and CH4-rich (≥84 and 6 mol% in dry gas, respectively) with high mantle-derived helium contributions (3He/4He = 6.54–7.86 RC/RA). Carbon isotopic compositions of CO2 (δ13C = −10.0 to −9.5 ‰) and CH4 (δ13C = −35.8 ‰) indicate mixed sources, with significant contributions from metamorphism of organic-rich Franciscan Complex rocks hosting the hydrothermal system. Modeling of gas compositions shows that scrubbing by interaction with air-saturated groundwater strongly influences observed compositional variability. From our CO₂ flux measurements, we estimate the deeply derived CO2 emission rate from the SBMM hydrothermal area (0.2 km2) at 240 t d−1, comparable to many quiescently degassing volcanoes worldwide. We also provide a first-order estimate of CH4 emissions at approximately 0.5 t d−1. Our findings establish crucial baseline data for future volcanic monitoring efforts, enhancing detection capabilities for potential changes in this active hydrothermal system. This work contributes to the broader understanding of volatile contributions from volcanic and metamorphic sources to the global carbon budget, while highlighting the strong influence of bedrock geology on gas compositions in the CLVF.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2025.108453","usgsCitation":"Lewicki, J.L., Peek, S., Clor, L., and Hunt, A.G., 2025, Gas emissions from the Sulphur Bank Mercury Mine hydrothermal system, Clear Lake volcanic field, California: Journal of Volcanology and Geothermal Research, v. 468, 108453, 11 p., https://doi.org/10.1016/j.jvolgeores.2025.108453.","productDescription":"108453, 11 p.","ipdsId":"IP-177603","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496226,"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 -122.93378541824276,\n 39.13626270834021\n ],\n [\n -122.93378541824276,\n 38.65\n ],\n [\n -122.25,\n 38.65\n ],\n [\n -122.25,\n 39.13626270834021\n ],\n [\n -122.93378541824276,\n 39.13626270834021\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"468","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":949539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peek, Sara 0000-0002-9770-6557","orcid":"https://orcid.org/0000-0002-9770-6557","contributorId":209971,"corporation":false,"usgs":true,"family":"Peek","given":"Sara","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":949540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clor, Laura E. 0000-0003-2633-5100","orcid":"https://orcid.org/0000-0003-2633-5100","contributorId":209969,"corporation":false,"usgs":true,"family":"Clor","given":"Laura E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":949541,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":174135,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949542,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272174,"text":"70272174 - 2025 - Future forest conditions under alternative management and hydrological scenarios in the Upper Mississippi River floodplain","interactions":[],"lastModifiedDate":"2025-11-18T15:48:07.770771","indexId":"70272174","displayToPublicDate":"2025-09-25T09:44:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Future forest conditions under alternative management and hydrological scenarios in the Upper Mississippi River floodplain","docAbstract":"Floodplain forests are being transformed by multiple pressures, prompting widespread management and restoration efforts. It is uncertain how disturbances, including hydrologic change, and management actions will interact to influence the ecology of these threatened forests.
This study examined the effects of alternative management and hydrologic regimes on forest succession at an Upper Mississippi River floodplain site with a restoration project in planning.
We used the spatially explicit forest landscape model, LANDIS-II, to simulate forest succession for 100 years under four hydrogeomorphic management scenarios, three forest management scenarios, and two scenarios of future hydrologic conditions. We evaluated changes in forest biomass and composition over time and assessed the relative importance of management actions and hydrologic change on succession.
Forest aboveground biomass decreased in all management-hydrology scenarios, especially in the wetter hydrological scenario. Intensified hydrogeomorphic and forest management scenarios reduced the magnitude and extent of biomass declines; however, they were unable to prevent overall declines in biomass or cause large shifts in tree species composition. Silver maple (Acer saccharinum) was projected to decrease in biomass, while increases in biomass were projected for several late-successional species including swamp white oak (Quercus bicolor). Among the factors influencing variation in biomass, forest management had the largest influence in the first 50 years of our simulations, but hydrological regime became the most important factor by the end of the century.
Our simulations indicate that management actions could play an important role in the conservation of floodplain forests, but their effectiveness will likely be limited if recent upward trends in flooding conditions in this system continue in the future. Thus, our results highlight both the potential benefits and limitations of management actions in the face of hydrologic change.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-025-02144-7","usgsCitation":"Trumper, M., De Jager, N.R., Van Appledorn, M., and Meier, A.R., 2025, Future forest conditions under alternative management and hydrological scenarios in the Upper Mississippi River floodplain: Landscape Ecology, v. 40, 186, 21 p., https://doi.org/10.1007/s10980-025-02144-7.","productDescription":"186, 21 p.","ipdsId":"IP-173189","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496735,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-025-02144-7","text":"Publisher Index Page"},{"id":496589,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesota, Wisconsin","otherGeospatial":"Reno Bottoms study area, Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.39940329445804,\n 43.68624998546463\n ],\n [\n -91.39940329445804,\n 43.44291861394157\n ],\n [\n -91.13016274447915,\n 43.44291861394157\n ],\n [\n -91.13016274447915,\n 43.68624998546463\n ],\n [\n -91.39940329445804,\n 43.68624998546463\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","noUsgsAuthors":false,"publicationDate":"2025-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Trumper, Matthew Lewis 0000-0002-9881-7742","orcid":"https://orcid.org/0000-0002-9881-7742","contributorId":357508,"corporation":false,"usgs":true,"family":"Trumper","given":"Matthew Lewis","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":950313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":950314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":950315,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meier, Andrew R.","contributorId":362320,"corporation":false,"usgs":false,"family":"Meier","given":"Andrew","middleInitial":"R.","affiliations":[{"id":16919,"text":"U.S. Army Corps of Engineers, St. Paul District","active":true,"usgs":false}],"preferred":false,"id":950316,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273314,"text":"70273314 - 2025 - Examining the compositional selectivity of hydrocarbon oxidation products using liquid–liquid extraction and solid-phase extraction techniques","interactions":[],"lastModifiedDate":"2026-01-06T15:11:50.945354","indexId":"70273314","displayToPublicDate":"2025-09-25T09:09:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Examining the compositional selectivity of hydrocarbon oxidation products using liquid–liquid extraction and solid-phase extraction techniques","docAbstract":"The effect of extraction methods on detecting hydrocarbon oxidation products (HOPs) in groundwater remains unclear. HOPs are polar, water-soluble byproducts of petroleum biodegradation. Our previous work showed that liquid–liquid extraction (LLE), a method commonly used in regulatory monitoring, has a significantly lower extraction efficiency for HOPs compared to solid-phase extraction (SPE). In this study, we evaluate the analytical limitations and compositional selectivity of LLE and SPE using groundwater samples from the Bemidji, MN, crude oil spill site. Optical properties were characterized using excitation–emission matrix spectroscopy (EEMs), and a three-component PARAFAC model was validated, showing consistent trends across both extracts and whole water samples. Ultrahigh-resolution mass spectrometry (UHR-MS) revealed that LLE selectively recovered aliphatic-like compounds but underrepresented more polar oxygenated HOPs. In contrast, SPE methods were more effective at isolating highly oxidized compound classes. These differences were consistent across a gradient of contamination. Overall, the LLE was less precise and less representative of polar HOPs, introducing bias in the characterization of HOPs. This study is the first to quantitatively demonstrate the compositional selectivity and analytical bias of LLE versus SPE for HOPs using combined EEM-PARAFAC and UHR-MS techniques, with implications for long-term monitoring and site assessment protocols.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5c07016","usgsCitation":"Zito, P., Ghannam, R., Harsha, M.L., Bekins, B., and Podgorski, D.C., 2025, Examining the compositional selectivity of hydrocarbon oxidation products using liquid–liquid extraction and solid-phase extraction techniques: Environmental Science and Technology, v. 59, p. 21324-21331, https://doi.org/10.1021/acs.est.5c07016.","productDescription":"8 p.","startPage":"21324","endPage":"21331","ipdsId":"IP-182330","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":498348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","noUsgsAuthors":false,"publicationDate":"2025-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Zito, Phoebe","contributorId":206101,"corporation":false,"usgs":false,"family":"Zito","given":"Phoebe","email":"","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":953299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ghannam, Rana","contributorId":220750,"corporation":false,"usgs":false,"family":"Ghannam","given":"Rana","email":"","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":953300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harsha, Maxwell L.","contributorId":364842,"corporation":false,"usgs":false,"family":"Harsha","given":"Maxwell","middleInitial":"L.","affiliations":[{"id":37245,"text":"University of New Orleans","active":true,"usgs":false}],"preferred":false,"id":953301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bekins, Barbara 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":139407,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":953302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Podgorski, David C.","contributorId":178153,"corporation":false,"usgs":false,"family":"Podgorski","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":953303,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70272041,"text":"70272041 - 2025 - Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration","interactions":[],"lastModifiedDate":"2025-11-14T15:42:24.888398","indexId":"70272041","displayToPublicDate":"2025-09-25T08:36:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration","docAbstract":"Beavers (Castor canadensis) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model-data integration workflow to address uncertainty in groundwater response to beaver-induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning-based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down-valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down-valley underflow, from 2% during dry pond periods to 20% during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down-valley underflow, minimizes the effect of beaver-induced inundation on water quality. We emphasize the need for field-scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response.
","language":"English","publisher":"Wiley","doi":"10.1029/2024WR039192","usgsCitation":"Wang, L., Babey, T., Perzan, Z., Pierce, S., Briggs, M., Boye, K., and Maher, K., 2025, Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration: Water Resources Research, v. 61, no. 9, e2024WR039192, 28 p., https://doi.org/10.1029/2024WR039192.","productDescription":"e2024WR039192, 28 p.","ipdsId":"IP-175143","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":496711,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr039192","text":"Publisher Index Page"},{"id":496487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Crested Butte","otherGeospatial":"Oh‐Be‐Joyful Creek‐Slate River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -107.04714288137164,\n 38.91446258506133\n ],\n [\n -107.04714288137164,\n 38.87739197906146\n ],\n [\n -106.97879177179699,\n 38.87739197906146\n ],\n [\n -106.97879177179699,\n 38.91446258506133\n ],\n [\n -107.04714288137164,\n 38.91446258506133\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"61","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Lijing","contributorId":258127,"corporation":false,"usgs":false,"family":"Wang","given":"Lijing","email":"","affiliations":[],"preferred":false,"id":949830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Babey, Tristan 0000-0002-6897-3162","orcid":"https://orcid.org/0000-0002-6897-3162","contributorId":215172,"corporation":false,"usgs":false,"family":"Babey","given":"Tristan","email":"","affiliations":[{"id":39190,"text":"Université de Rennes","active":true,"usgs":false}],"preferred":false,"id":949831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perzan, Zach","contributorId":362023,"corporation":false,"usgs":false,"family":"Perzan","given":"Zach","affiliations":[{"id":40182,"text":"University of Nevada Las Vegas","active":true,"usgs":false}],"preferred":false,"id":949832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pierce, Samuel","contributorId":245448,"corporation":false,"usgs":false,"family":"Pierce","given":"Samuel","email":"","affiliations":[{"id":36408,"text":"SLAC National Accelerator Laboratory","active":true,"usgs":false}],"preferred":false,"id":949833,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222756,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":949834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boye, Kristin","contributorId":219255,"corporation":false,"usgs":false,"family":"Boye","given":"Kristin","email":"","affiliations":[{"id":39977,"text":"Stanford Synchrotron Radiation Lightsource (SSRL)","active":true,"usgs":false}],"preferred":false,"id":949835,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Maher, Kate","contributorId":245461,"corporation":false,"usgs":false,"family":"Maher","given":"Kate","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":949836,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272177,"text":"70272177 - 2025 - Quantifying the relative importance of survival threats to a long-lived reptile using expert elicitation","interactions":[],"lastModifiedDate":"2025-11-18T15:36:19.719392","indexId":"70272177","displayToPublicDate":"2025-09-25T08:31:03","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the relative importance of survival threats to a long-lived reptile using expert elicitation","docAbstract":"Long-term survival of a conservation-reliant species requires understanding the impact of threats on population growth rate and the management actions that can help mitigate these threats. We used a threat assessment with expert-elicited estimates to determine the relative effect of each stage-specific threat on the population growth rate of the wood turtle Glyptemys insculpta. In addition, we offered potential management actions that could mitigate these threats and examined the relative cost and benefit of each. The experts responded that predators had the largest effect on hatchling and juvenile survival and that road mortality had the largest effect on adult survival. The population growth rate of the simulated turtle population increased the most when predators were removed from the system, though the population trajectory remained negative. Finally, we found that predator control had the lowest cost:benefit ratio of the proposed management actions. The process used in this analysis of expert elicitation combined with modeling that accounts for uncertainty proved to be a useful technique that is less expensive and labor intensive than empirical studies and quicker to implement, although it relies on sufficient empirical studies to inform expert responses. This process could be replicated for other species to inform species status assessments.
","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01440","usgsCitation":"Moore, J.F., Waddle, J., Johnson, F., Martin, J., Campbell Grant, E.H., Fleming, J., Akre, T.S., Brown, D.J., Lee, Y.M., Drescher-Lehman, J., Kleopfer, J., Meck, J.R., Oxenrider, K.J., Tamplin, J., Tur, A., and Willey, L.L., 2025, Quantifying the relative importance of survival threats to a long-lived reptile using expert elicitation: Endangered Species Research, v. 58, p. 147-158, https://doi.org/10.3354/esr01440.","productDescription":"12 p.","startPage":"147","endPage":"158","ipdsId":"IP-175948","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":496733,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01440","text":"Publisher Index Page"},{"id":496586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.91069443033376,\n 51.71991684948924\n ],\n [\n -87.46840925695676,\n 30.654184225800563\n ],\n [\n -80.05412909012534,\n 24.273039753316198\n ],\n [\n -60.11143954864117,\n 49.272877271756016\n ],\n [\n -73.91069443033376,\n 51.71991684948924\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"58","noUsgsAuthors":false,"publicationDate":"2025-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Jennifer F.","contributorId":362323,"corporation":false,"usgs":false,"family":"Moore","given":"Jennifer","middleInitial":"F.","affiliations":[{"id":86505,"text":"Moore Ecological Analysis and Management","active":true,"usgs":false}],"preferred":false,"id":950317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":215911,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":950318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Fred","contributorId":295463,"corporation":false,"usgs":false,"family":"Johnson","given":"Fred","affiliations":[{"id":6963,"text":"Department of Bioscience, Aarhus University","active":true,"usgs":false}],"preferred":false,"id":950319,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":213876,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":950320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":950321,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fleming, Jillian E. 0000-0003-2570-914X","orcid":"https://orcid.org/0000-0003-2570-914X","contributorId":352270,"corporation":false,"usgs":false,"family":"Fleming","given":"Jillian E.","affiliations":[{"id":84147,"text":"Former USGS employee, USGS Eastern Ecological Science Center","active":true,"usgs":false}],"preferred":false,"id":950322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Akre, Thomas S.","contributorId":362324,"corporation":false,"usgs":false,"family":"Akre","given":"Thomas","middleInitial":"S.","affiliations":[{"id":86506,"text":"Smithsonian National Zoo and Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":950323,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brown, Donald J.","contributorId":362325,"corporation":false,"usgs":false,"family":"Brown","given":"Donald","middleInitial":"J.","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":950324,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lee, Yu Man","contributorId":362326,"corporation":false,"usgs":false,"family":"Lee","given":"Yu","middleInitial":"Man","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":950325,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Drescher-Lehman, Jonathon","contributorId":362327,"corporation":false,"usgs":false,"family":"Drescher-Lehman","given":"Jonathon","affiliations":[{"id":86506,"text":"Smithsonian National Zoo and Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":950326,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kleopfer, John","contributorId":362328,"corporation":false,"usgs":false,"family":"Kleopfer","given":"John","affiliations":[{"id":56188,"text":"Virginia Department of Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":950327,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Meck, Jessica R.","contributorId":272551,"corporation":false,"usgs":false,"family":"Meck","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":37784,"text":"Smithsonian Conservation Biology Institute","active":true,"usgs":false}],"preferred":false,"id":950328,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Oxenrider, Kevin J.","contributorId":244034,"corporation":false,"usgs":false,"family":"Oxenrider","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":40299,"text":"West Virginia Division of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":950329,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Tamplin, Jeff","contributorId":362329,"corporation":false,"usgs":false,"family":"Tamplin","given":"Jeff","affiliations":[{"id":34268,"text":"University of Northern Iowa","active":true,"usgs":false}],"preferred":false,"id":950330,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tur, Anthony","contributorId":348610,"corporation":false,"usgs":false,"family":"Tur","given":"Anthony","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":950331,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Willey, Lisabeth L.","contributorId":272552,"corporation":false,"usgs":false,"family":"Willey","given":"Lisabeth","email":"","middleInitial":"L.","affiliations":[{"id":56384,"text":"Antioch University New England","active":true,"usgs":false}],"preferred":false,"id":950332,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70271940,"text":"70271940 - 2025 - 10Be/9Be and 26Al/10Be support a late Miocene burial age for basal Gray Fossil Site sediments","interactions":[],"lastModifiedDate":"2025-09-25T15:02:09.131409","indexId":"70271940","displayToPublicDate":"2025-09-24T09:46:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22679,"text":"Pan-American Paleontology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"10Be/9Be and 26Al/10Be support a late Miocene burial age for basal Gray Fossil Site sediments","title":"10Be/9Be and 26Al/10Be support a late Miocene burial age for basal Gray Fossil Site sediments","docAbstract":"We provide 2 independent radioisotopic age estimates for cored basal sediments of the Gray Fossil Site using cosmogenic nuclides. The first estimate uses meteoric 10Be/9Be from the bottom of the GFS-1 core, as well as from modern local grasses, to constrain the deposition of basal GFS sinkhole complex sediments to 6.60 ± 0.85 Ma. We corroborated this age estimate using in-situ 10Be and 26Al in quartz sands from the GFS-1 core. This estimate provided a looser constraint than the 10Bemet/9Be approach, yielding a minimum burial age for the basal sediments of 4.43 ± 0.34 Ma. These independent geochronometers provide evidence that the deepest GFS sediments are at least early Pliocene in age, and likely date to the late Miocene.
","language":"English","publisher":"Eagle Hill Institute","usgsCitation":"Odom, W.E., Granger, D.E., and Wallace, S.C., 2025, 10Be/9Be and 26Al/10Be support a late Miocene burial age for basal Gray Fossil Site sediments: Pan-American Paleontology, v. 1, no. 1, 20 p.","productDescription":"20 p.","ipdsId":"IP-162046","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":496082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496066,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.eaglehill.us/papaonline/access-pages/001-Odom-accesspage.shtml","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Tennessee","county":"Washington County","otherGeospatial":"Gray Fossil Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.49790556245541,\n 36.38696818299522\n ],\n [\n -82.49936582790308,\n 36.38696818299522\n ],\n [\n -82.49936582790308,\n 36.385137865922104\n ],\n [\n -82.49790556245541,\n 36.385137865922104\n ],\n [\n -82.49790556245541,\n 36.38696818299522\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"1","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Odom, William Elijah 0000-0001-8577-5056","orcid":"https://orcid.org/0000-0001-8577-5056","contributorId":292616,"corporation":false,"usgs":true,"family":"Odom","given":"William","email":"","middleInitial":"Elijah","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":949452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granger, Darryl E.","contributorId":361787,"corporation":false,"usgs":false,"family":"Granger","given":"Darryl","middleInitial":"E.","affiliations":[{"id":13186,"text":"Purdue University","active":true,"usgs":false}],"preferred":false,"id":949453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, Steven C.","contributorId":361788,"corporation":false,"usgs":false,"family":"Wallace","given":"Steven","middleInitial":"C.","affiliations":[{"id":27535,"text":"East Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":949454,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271947,"text":"70271947 - 2025 - Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts","interactions":[],"lastModifiedDate":"2025-09-25T14:08:33.913615","indexId":"70271947","displayToPublicDate":"2025-09-24T08:58:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3823,"text":"Journal of Hydrology: Regional Studies","active":true,"publicationSubtype":{"id":10}},"title":"Linking stream-reach nitrogen loads and groundwater “reachsheds” to inform wastewater-nitrogen management actions, Cape Cod, Massachusetts","docAbstract":"Coast redwood (Sequoia sempervirens) and giant sequoia (Sequoiadendron giganteum) are two iconic paleoendemic species with limited distributions, well known for their spectacular size. Recently, they have been exposed to high-severity crown fires, with starkly contrasting responses.
We used all available published literature and field observations to understand the responses to fire in an evolutionary context.
Coast redwoods, found in California's coastal rainforests, were highly resilient to high-severity fires, with most trees surviving due to their ability to resprout from the base and trunk, though seedling regeneration was largely lacking. In contrast, giant sequoias, native to the Sierra Nevada, do not resprout, leading to significant tree mortality after very high-severity fires; they released seeds only in patches where some trees survived moderately high-severity fires.
These high-severity fires were novel events for giant sequoias, but not for coast redwoods. Fire suppression has disrupted the natural fire regime in the giant sequoia ecosystem by preventing frequent lightning-caused surface fires, resulting in high-severity fires that killed a substantial number of these giants. In coast redwood forests, infrequent but high-severity crown fires were the norm before burning by Native Americans. Frequent, low-severity burning by Native Americans over the past few hundred years was localized and 20th-century fire suppression has returned the natural fire regime to these forests. The recent crown fires do not represent a threat to redwood conservation; however, other management goals may require emulating Native American burning practices and in some cases may be best termed cultural restoration.
","language":"English","publisher":"Botanical Society of America","doi":"10.1002/ajb2.70089","usgsCitation":"Keeley, J., and Pausas, J.G., 2025, Sequoia and Sequoiadendron: Two paleoendemic megatrees with markedly different adaptive responses to recent high-severity fires: American Journal of Botany, v. 112, e70089, https://doi.org/10.1002/ajb2.70089.","productDescription":"e70089","ipdsId":"IP-172307","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":496408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"112","noUsgsAuthors":false,"publicationDate":"2025-09-24","publicationStatus":"PW","contributors":{"authors":[{"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":949788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pausas, Juli G.","contributorId":361994,"corporation":false,"usgs":false,"family":"Pausas","given":"Juli","middleInitial":"G.","affiliations":[{"id":86413,"text":"Centro de Investigaciones sobre Desertificación","active":true,"usgs":false}],"preferred":false,"id":949789,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70272593,"text":"70272593 - 2025 - Longer rorqual whale mothers produce more female offspring","interactions":[],"lastModifiedDate":"2025-11-24T16:18:56.439154","indexId":"70272593","displayToPublicDate":"2025-09-24T07:59:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3173,"text":"Proceedings of the Royal Society B","active":true,"publicationSubtype":{"id":10}},"title":"Longer rorqual whale mothers produce more female offspring","docAbstract":"Multiple hypotheses have arisen that predict how mammals with the ability to adapt fetal sex ratios should invest in male versus female offspring to maximize inclusive fitness, but large wild-population datasets necessary for testing these hypotheses are challenging to collect. We used whaling data (n = 209 254 sexed fetuses from seven rorqual whale species) to test whether mothers with more resources to invest in offspring produce more male or female offspring. We first modelled fetal sex misidentification in the data and estimated that missexing occurred for fetuses under 30–120 cm across five of seven species. Using Bayesian generalized linear mixed models and a size-restricted dataset to account for misidentification, we estimated a 90% posterior probability that longer mothers have more female offspring overall, ranging from 77% for humpback whales to 99% for sei whales. Our results likely reflect both the difficulty of excluding small males from competition in aquatic environments and the exceptionally high costs of gestation and lactation in baleen whales.
We describe the results of long-term population monitoring of the island night lizard Xantusia riversiana on San Nicolas Island, California, following the species' removal from the U.S. Endangered Species list in 2014. Monitoring activities were carried out from October 2014 through November 2023, but we also incorporate data from earlier work dating back to 1993. Because of habitat loss on the western part of the island, the island night lizard is almost entirely confined to the island's eastern half. The species' distribution remains largely the same since studies in the 1990s, though small increases in distribution were noted at the island's west end. Numbers at most long-term monitoring sites appeared to show a slight decrease associated with a multi-year drought, with numbers returning to previous levels by the end of the monitoring period. Models fit to counts of newly recruited lizards suggested a positive association between winter precipitation and abundance; however, we found a simpler model including constant abundance throughout the study to be more parsimonious. Two monitoring sites showed marked decreases in numbers, with one site declining to zero following infestation of the area by non-native Argentine ants Linepithema humile. The island's vegetation and natural communities continue to gradually recover from a century of overgrazing by sheep and the widespread introduction of aggressive non-native plants. Habitat restoration efforts by U.S. Navy natural resources staff on the island may lead to increasing population numbers and genetic connectivity, but persistent threats remain for the island night lizard on San Nicolas Island.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70094","usgsCitation":"Drost, C.A., Kleeman, P.M., Yackulic, C.B., Halstead, B.J., and Fellers, G.M., 2025, Long-term monitoring of island night lizards on San Nicolas Island: Journal of Wildlife Management, v. 89, no. 8, e70094, 17 p., https://doi.org/10.1002/jwmg.70094.","productDescription":"e70094, 17 p.","ipdsId":"IP-177493","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":500637,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14BERMW","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Island Night Lizard monitoring data on San Nicolas Island, CA, 1995-2023"},{"id":500504,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":500607,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70094","text":"Publisher Index Page"}],"country":"United States","state":"California","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.61377432741922,\n 33.29828231397315\n ],\n [\n -119.61377432741922,\n 33.19720340978597\n ],\n [\n -119.38140334562684,\n 33.19720340978597\n ],\n [\n -119.38140334562684,\n 33.29828231397315\n ],\n [\n -119.61377432741922,\n 33.29828231397315\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Drost, Charles A. 0000-0002-4792-7095 charles_drost@usgs.gov","orcid":"https://orcid.org/0000-0002-4792-7095","contributorId":3151,"corporation":false,"usgs":true,"family":"Drost","given":"Charles","email":"charles_drost@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":956546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kleeman, Patrick M. 0000-0001-6567-3239 pkleeman@usgs.gov","orcid":"https://orcid.org/0000-0001-6567-3239","contributorId":3948,"corporation":false,"usgs":true,"family":"Kleeman","given":"Patrick","email":"pkleeman@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":956548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":215986,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian","email":"bhalstead@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":956549,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fellers, Gary M. 0000-0003-4092-0285","orcid":"https://orcid.org/0000-0003-4092-0285","contributorId":366997,"corporation":false,"usgs":false,"family":"Fellers","given":"Gary","middleInitial":"M.","affiliations":[{"id":87525,"text":"[Previously] U.S. Geological Survey, Western Ecological Research Center, Point Reyes Field10Station, Point Reyes Station, CA","active":true,"usgs":false}],"preferred":false,"id":956550,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271715,"text":"sir20255092 - 2025 - Flood-Inundation Maps of the Current and Jacks Fork Rivers including the Ozark National Scenic Riverways, Southeast Missouri, 2023","interactions":[],"lastModifiedDate":"2026-02-03T15:34:29.756536","indexId":"sir20255092","displayToPublicDate":"2025-09-23T12:04:51","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":"2025-5092","displayTitle":"Flood-inundation maps of the Current and Jacks Fork Rivers including the Ozark National Scenic Riverways, southeast Missouri, 2023","title":"Flood-Inundation Maps of the Current and Jacks Fork Rivers including the Ozark National Scenic Riverways, Southeast Missouri, 2023","docAbstract":"Digital flood-inundation maps for a 131.8-mile reach of the Current River and a 44.6-mile reach of the Jacks Fork River, in southeast Missouri, were created by the U.S. Geological Survey (USGS) in cooperation with the Ozark Foothills Regional Planning Commission and the South Central Ozark Council of Governments. The maps also encompass the 134 miles of the Current and Jacks Fork Rivers within the Ozark National Scenic Riverways, which is the first national park area to protect a river system. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Program website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (hereafter referred to as “stages”) at eight reference USGS streamgages—five on the Current River (USGS station numbers 07064440, 07064533, 07066510, 07067000, and 07068000) and three on the Jacks Fork River (USGS station numbers 07065200, 07065495, and 07066000). Near-real-time stages at these streamgages may be obtained from the USGS National Water Information System at https://doi.org/10.5066/F7P55KJN or the National Weather Service National Water Prediction Service at http://water.noaa.gov/, which also forecasts flood hydrographs at four of these sites (USGS station numbers 07067000, 07068000, 07065495, and 07066000).
Flood profiles were computed for seven of the eight map reaches by means of two-dimensional hydraulic models and the remaining reach by a one-dimensional hydraulic model. The models were calibrated by using stage-streamflow relations or streamflow measurements at the USGS streamgages and from high-flow stage measurements from water-level loggers distributed throughout the reaches.
The hydraulic models were used to compute water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datums. The profile stages ranged from the National Weather Service “action stage” or near bankfull, to a stage exceeding the highest recorded water level at each streamgage. The simulated water-surface profiles were then combined with a digital elevation model (derived from light detection and ranging data having a nonvegetated vertical accuracy of a maximum 10-centimeter root mean square error) to delineate the area flooded at each water level and the associated water depths.
The availability of these maps, along with information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel, resource managers, and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255092","collaboration":"South Central Ozark Council of Governments, Ozark Foothills Regional Planning Commission","usgsCitation":"Heimann, D.C., High, J.L., Atkinson, A.A., and Rydlund, P.H., Jr., 2025, Flood-inundation maps of the Current and Jacks Fork Rivers including the Ozark National Scenic Riverways, southeast Missouri, 2023: U.S. Geological Survey Scientific Investigations Report 2025–5092, 29 p., https://doi.org/10.3133/sir20255092.","productDescription":"Report: viii, 29 p.; Data Release; Dataset","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135288","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":497780,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118892.htm"},{"id":495817,"rank":7,"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":495816,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90H2UQY","text":"USGS data release","linkHelpText":"Hydraulic models and geospatial products associated with flood-inundation mapping of the Current and Jacks Fork Rivers including the Ozark National Scenic Riverways, Southeast Missouri, 2022–25"},{"id":495815,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5092/images"},{"id":495813,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255092/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5092 HTML"},{"id":495809,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5092/sir20255092.pdf","text":"Report","size":"17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5092"},{"id":495808,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5092/coverthb.jpg"},{"id":495814,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5092/sir20255092.XML","description":"SIR 2025-5092 XML"}],"country":"United States","state":"Missouri","otherGeospatial":"Current River, Jacks Fork River, Ozark National Scenic Riverways","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.75,\n 37.5\n ],\n [\n -91.75,\n 36.5\n ],\n [\n -90.75,\n 36.5\n ],\n [\n -90.75,\n 37.5\n ],\n [\n -91.75,\n 37.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The U.S. Geological Survey created flood-inundation maps that make up a 131.8-mile reach of the Current River, a 44.6-mile reach of the Jacks Fork River, including 134 miles of the Ozark National Scenic Riverways in southeast Missouri. The flood-inundation maps show estimates of the extent and depth of flooding corresponding to selected water levels at eight reference U.S. Geological Survey streamgages—five on the Current River (U.S. Geological Survey station numbers 07064440, 07064533, 07066510, 07067000, and 07068000) and three on the Jacks Fork River (U.S. Geological Survey station numbers 07065200, 07065495, and 07066000).
","publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Heimann, David C. 0000-0003-0450-2545 dheimann@usgs.gov","orcid":"https://orcid.org/0000-0003-0450-2545","contributorId":3822,"corporation":false,"usgs":true,"family":"Heimann","given":"David","email":"dheimann@usgs.gov","middleInitial":"C.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"High, Jason L. 0009-0009-1031-1439","orcid":"https://orcid.org/0009-0009-1031-1439","contributorId":361676,"corporation":false,"usgs":true,"family":"High","given":"Jason","middleInitial":"L.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Atkinson, Allison A. 0009-0001-7572-0729 aatkinson@usgs.gov","orcid":"https://orcid.org/0009-0001-7572-0729","contributorId":330979,"corporation":false,"usgs":true,"family":"Atkinson","given":"Allison","email":"aatkinson@usgs.gov","middleInitial":"A.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":949170,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271736,"text":"cir1561 - 2025 - ShakeAlert®—Communication, education, outreach and technical engagement strategic vision","interactions":[],"lastModifiedDate":"2026-02-03T15:33:50.766743","indexId":"cir1561","displayToPublicDate":"2025-09-23T12:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1561","displayTitle":"ShakeAlert®—Communication, Education, Outreach and Technical Engagement Strategic Vision","title":"ShakeAlert®—Communication, education, outreach and technical engagement strategic vision","docAbstract":"In 2006, the U.S. Geological Survey (USGS) began directly supporting ShakeAlert® research and in 2012 the ShakeAlert demonstration system began testing (Given and others, 2018). The ShakeAlert earthquake early warning (EEW) system is a partnership between the U.S. Geological Survey (USGS) and the three West Coast States (Washington, Oregon, and California) served by the ShakeAlert System, which is part of the larger Advanced National Seismic System (ANSS). With more than 143 million people exposed to potentially damaging shaking in the United States (Jaiswal and others, 2015), earthquakes are a national hazard. Most of our Nation’s earthquake risk is concentrated in the highly populated areas on the active plate tectonic boundaries on the West Coast of the conterminous United States. ShakeAlert is the first public alert system in the United States to provide rapid mass notification of earthquake detection, potentially offering seconds of warning before strong shaking arrives. A few seconds may not seem like much time, but the information in ShakeAlert Messages can be used to trigger automated actions that can prevent injury or death, reduce immediate damage, and speed recovery from earthquakes.
The information product issued by the ShakeAlert system is called a ShakeAlert Message and is one of the information products and tools of the ANSS. The ShakeAlert System includes the USGS component, plus the pathways by which ShakeAlert-powered products and (or) services are delivered to end users. Alerts can be delivered to cell phones or be used to trigger automated systems to protect equipment, facilities, and infrastructure, such as slowing or stopping a train. ShakeAlert-powered automated actions can include fire house doors that can be opened to prevent jamming, heavy equipment (for example, trains, elevators, and cranes) that can be automatically stopped or parked in safe positions, and pipeline valves that can be closed to prevent surges and spills. A few seconds of warning also may be sufficient for people to take protective actions, such as drop, cover, and hold on or modified protective actions for a broad range of populations. Advance training may increase the benefit of a speedy response to an alert.
Outreach and education about EEW may raise awareness of the overall earthquake threat and how people can best react when they receive an alert or feel shaking. ShakeAlert communication, education, outreach, and technical engagement (CEO&TE) efforts are highly collaborative and essential for the success of the ShakeAlert System. This strategic vision informs how the vast ShakeAlert CEO&TE Community operates and works together. The CEO&TE Community delineates a strategic framework that is intended to set the path for a long-term, sustainable approach to CEO&TE through three focus areas and five priorities.
The enumeration of the five priorities listed below does not suggest priority ranking.
This strategic vision is a tangible outcome of collaboration among many stakeholders beginning in July 2016. Since then, the work of the ShakeAlert CEO&TE Community has grown into an international effort. The USGS has developed, tested, and implemented a broad spectrum of communication, education, and outreach tools and resources—all of which recognize that seconds matter when it comes to safety and mitigating harm from earthquake hazards. The CEO&TE social science research effort has provided invaluable insights into the ShakeAlert System’s human interface. USGS-licensed technical partners develop, test, and implement real-world applications using ShakeAlert Messages.
The success of ShakeAlert CEO&TE efforts is predicated on robust collaboration across numerous agencies, organizations, and groups. As such, this strategic vision outlines a “partnership model” that delineates roles and responsibilities to ensure alignment with focus areas and priorities. The partnership model includes the CEO&TE lead agency (USGS); its principal partners (State agencies and university partners); its implementation partners (for example, technical partners who build systems to deliver ShakeAlert-powered products and (or) services [focus area one]), earthquake education partners who work to increase public preparedness for seismic events (focus area two); and other organizations that work together to enhance the adoption and effectiveness of the ShakeAlert System. These partners collaborate and convene through a variety of working groups and forums, which are also described in this strategic vision and align with focus area three (internal engagement). The CEO&TE Community collaboratively developed its operating principles and a consensus-based, decision-making strategic framework to guide its collective work. Performance metrics are used to continually measure success. Ultimately, the USGS and ShakeAlert CEO&TE Community are advancing the ShakeAlert System that as of the publication of this strategic vision to “provide earthquake early warning for all” serves more than 50 million people.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1561","usgsCitation":"de Groot, R.M., McBride, S.K., Vinci, M.J., Lotto, G.C., Anderson, M.L., Sumy, D.F., and Terbush, B., 2025, ShakeAlert—Communication, education, outreach, and technical engagement strategic vision: U.S. Geological Survey\nCircular 1561, 32 p., https://doi.org/10.3133/cir1561.","productDescription":"vi, 32 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-159575","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":495882,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1561/coverthb.jpg"},{"id":495886,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1561/images"},{"id":495885,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1561/cir1561.XML","linkFileType":{"id":8,"text":"xml"},"description":"CIR 1561 XML"},{"id":495884,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1561/full","linkFileType":{"id":5,"text":"html"},"description":"CIR 1561 HTML"},{"id":495883,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1561/cir1561.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1561 PDF"}],"contact":"Earthquake Science Center-Pasadena Field Office
U.S. Geological Survey
525 South Wilson Ave.
Pasadena, CA 91106-3212
Digital flood-inundation maps for a 3.1-mile reach of Río de la Plata in and near Comerío, Puerto Rico, were created by the U.S. Geological Survey (USGS). Water-surface profiles were computed for the stream reach by using a one-dimensional steady-state step-backwater model. The model was calibrated to the current (2025) stage-streamflow relation (rating curve 11.0) for the USGS streamgage 50043800, Río de la Plata at Comerío, Puerto Rico. The resulting hydraulic model was then used to compute 16 water-surface profiles for water levels (flood stages) ranging from 10.00 to 40.00 feet at the streamgage and ranging from “action stage” to above “major flood stage” as reported by the National Weather Service. The 40.00-foot stage was selected because it exceeds the peak stage of 34.86 ft recorded during Hurricane Maria at the USGS streamgage 50043800, Río de Plata at Comerío, Puerto Rico. The simulated water-surface profiles were then used in combination with a digital elevation model derived from light detection and ranging data to map the inundated areas associated with each flood profile.
The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood mitigation strategies and to define flood hazard areas to help protect life and property, to coordinate flood response activities such as evacuations and road closures, and to aid post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255094","usgsCitation":"Ostheimer, C.J., and Torres-Garcia, L.M., 2025, Flood-inundation maps for Río de la Plata in and near Comerío, Puerto Rico, 2025: U.S. Geological Survey Scientific Investigations Report 2025–5094, 15 p., https://doi.org/10.3133/sir20255094.","productDescription":"Report: vii, 15 p.; Data Release","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-176013","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":495789,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13UOGOZ","text":"USGS data release","linkHelpText":"Geospatial data sets and hydraulic model for Río de la Plata in and Near Comerío, Puerto Rico"},{"id":495788,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5094/images/"},{"id":495787,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5094/sir20255094.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2025-5082 XML"},{"id":495786,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255094/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5082 HTML"},{"id":495785,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5094/sir20255094.pdf","text":"Report","size":"6.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5082 PDF"},{"id":495780,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5094/coverthb.jpg"},{"id":497779,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118885.htm"}],"country":"United States","city":"Comerio","otherGeospatial":"Puerto Rico, Rio de la Plata","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -66.19365607546672,\n 18.268637648344637\n ],\n [\n -66.20264706241515,\n 18.27758838215894\n ],\n [\n -66.21903386120783,\n 18.274972061568477\n ],\n [\n -66.229184975504,\n 18.262991563440394\n ],\n [\n -66.22758980040052,\n 18.254728669228726\n ],\n [\n -66.24151132857823,\n 18.254590950995066\n ],\n [\n -66.24484669470401,\n 18.250734796117897\n ],\n [\n -66.26891933717856,\n 18.244950403338635\n ],\n [\n -66.26993444860818,\n 18.217403035734378\n ],\n [\n -66.26239381153299,\n 18.185167128209628\n ],\n [\n -66.25673819071034,\n 18.183238292382484\n ],\n [\n -66.2425266306957,\n 18.193984391766037\n ],\n [\n -66.24528193314764,\n 18.183789390509304\n ],\n [\n -66.22352954536923,\n 18.175247173917384\n ],\n [\n -66.20975303311035,\n 18.174696048809224\n ],\n [\n -66.2051125237173,\n 18.197290750643944\n ],\n [\n -66.18263505634692,\n 18.202112411579463\n ],\n [\n -66.16936609980282,\n 18.216851668012367\n ],\n [\n -66.16943860776185,\n 18.22635645849499\n ],\n [\n -66.17494917440196,\n 18.230488705183646\n ],\n [\n -66.17799450869079,\n 18.246878681547642\n ],\n [\n -66.19365607546672,\n 18.268637648344637\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
6460 Busch Blvd, Suite 100
Columbus, OH 43229-1737
Genetic diversity is an important driver affecting the health of wildlife populations. In cooperatively breeding species, human impacts and breeder turnover can affect genetic diversity in groups. We generally do not have strong inferences about how the genetic composition of a group changes through time as individuals are lost (e.g., die, emigrate) or adopted (e.g., immigrate). I wanted to know how breeder turnover, group size, and harvest affected the fluctuation of unique alleles in groups of gray wolves (Canis lupus) in Idaho, USA, during 2008–2020. Turnover of breeding males was strongly associated with allelic change in groups. Turnover of breeding females also had a strong association with allelic change in groups, but was not the most supported model. Harvest was strongly correlated with breeding female turnover but not breeding male turnover. Outside of breeding female turnover, harvest generally had little effect on allelic change in groups. Groups rarely adopted new individuals unless there was a breeding vacancy. I show that over time groups gain and lose alleles in roughly equal proportions, but there are episodic changes to alleles in groups as a function of breeding male turnover. These findings have implications for how we define and evaluate group persistence and breeder lineages in cooperative breeders. Such definitions have important implications for studying the evolution and maintenance of cooperative breeding. It may be beneficial to define characteristics and vital rates of groups based, at least in part, on their underlying genetics when such information can be obtained.
","language":"English","doi":"10.1038/s41437-025-00788-4","usgsCitation":"Ausband, D.E., 2025, Breeder turnover creates allelic variation in groups of gray wolves: Heredity, v. 134, p. 577-583, https://doi.org/10.1038/s41437-025-00788-4.","productDescription":"7 p.","startPage":"577","endPage":"583","ipdsId":"IP-172832","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500588,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41437-025-00788-4","text":"Publisher Index Page"},{"id":500422,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","volume":"134","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956322,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70271918,"text":"70271918 - 2025 - Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths","interactions":[],"lastModifiedDate":"2025-09-25T13:17:30.283112","indexId":"70271918","displayToPublicDate":"2025-09-23T10:25:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths","docAbstract":"Mauna Loa volcano erupts crystal-poor material at its summit and more crystal-rich material on its rift zones. Some of the more olivine-rich lava flows contain xenoliths with diverse mineralogy, including cumulate harzburgites with high-Mg# orthopyroxenes and high-Fo olivines (both > 84). Previous experimental work and thermodynamic modelling has proposed that high-Mg# orthopyroxenes only crystallize from Mauna Loa melts at high pressures (> 6 kbar, > 20 km), leading to suggestions that there is a region of sub-Moho magma storage at Mauna Loa in addition to the geophysically imaged magma reservoir at 2–5 km depth below the summit. We use melt and fluid inclusion barometry combined with thermodynamic models to further investigate this suggestion. Fluid inclusion data from harzburgites and dunitic xenoliths yield storage depths remarkably similar to those found in non-xenolithic crystals from lavas and tephras, with a clear peak at ~ 2–3 km (below the summit). Depths from melt inclusions in these xenoliths overlap with fluid inclusion pressures, ruling out the possibility of fluid inclusion re-equilibration during a period of stalling in a shallower reservoir. We examine five different thermodynamic models and find that the minimum pressure of olivine-orthopyroxene co-saturation varies by ~ 4 kbar (~ 12 km). These models also fail to predict that orthopyroxene is stable in ~ 15–80% of compositionally relevant experimental charges which grew orthopyroxene. Overall, this shows that phase stability modelling is an unreliable method of determining magma storage depth at Mauna Loa. We suggest that model discrepancies reflect a lack of experimental constraints on orthopyroxene stability at > 1200 ℃ and 0.01–5 kbar. Based on the presence of large oikocrystic orthopyroxenes completely enclosing rounded olivine chadacrysts, we suggest that these harzburgitic xenoliths formed through the reaction of intruding melts with olivine mush piles within the Mauna Loa edifice at ~ 3 km depth below the summit, with no need for a deeper storage reservoir. The predominance of pre-eruptive shallow storage means that there is more chance of detecting reservoir destabilization with geophysical monitoring techniques compared to a scenario where melts are supplied from sub-Moho reservoirs.
","language":"English","publisher":"Springer","doi":"10.1007/s00445-025-01869-2","usgsCitation":"Wieser, P.E., Gleeson, M., Rangel, B., DeVitre, C., Bearden, A.T., Lynn, K.J., Antoshechkina, P., Gaffney, A., and Monteleone, B., 2025, Fluid inclusion constraints on the geometry of the magmatic plumbing system beneath Mauna Loa – Part 2: Xenoliths: Bulletin of Volcanology, v. 87, 86, 24 p., https://doi.org/10.1007/s00445-025-01869-2.","productDescription":"86, 24 p.","ipdsId":"IP-176666","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496156,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-025-01869-2","text":"Publisher Index Page"},{"id":496014,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Mauna Loa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.33750669977726,\n 19.719087637337836\n ],\n [\n -155.9431663120125,\n 19.719087637337836\n ],\n [\n -155.9431663120125,\n 18.997816607636395\n ],\n [\n -155.33750669977726,\n 18.997816607636395\n ],\n [\n -155.33750669977726,\n 19.719087637337836\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Wieser, Penny E. 0000-0002-1070-8323","orcid":"https://orcid.org/0000-0002-1070-8323","contributorId":272601,"corporation":false,"usgs":false,"family":"Wieser","given":"Penny","email":"","middleInitial":"E.","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":949375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleeson, Matthew","contributorId":346331,"corporation":false,"usgs":false,"family":"Gleeson","given":"Matthew","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":949376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rangel, Berenise","contributorId":346222,"corporation":false,"usgs":false,"family":"Rangel","given":"Berenise","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":949377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeVitre, Charlotte","contributorId":346229,"corporation":false,"usgs":false,"family":"DeVitre","given":"Charlotte","email":"","affiliations":[{"id":13243,"text":"University of California Berkeley","active":true,"usgs":false}],"preferred":false,"id":949378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bearden, Alexander T.","contributorId":361751,"corporation":false,"usgs":false,"family":"Bearden","given":"Alexander","middleInitial":"T.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":949379,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":949380,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Antoshechkina, Paula 0000-0002-3358-5186","orcid":"https://orcid.org/0000-0002-3358-5186","contributorId":272605,"corporation":false,"usgs":false,"family":"Antoshechkina","given":"Paula","email":"","affiliations":[{"id":7218,"text":"California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":949381,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gaffney, Amy","contributorId":361752,"corporation":false,"usgs":false,"family":"Gaffney","given":"Amy","affiliations":[{"id":13621,"text":"Lawrence Livermore National Laboratory","active":true,"usgs":false}],"preferred":false,"id":949382,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Monteleone, Brian","contributorId":361754,"corporation":false,"usgs":false,"family":"Monteleone","given":"Brian","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":949383,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70271943,"text":"70271943 - 2025 - A simple predictive model for salt marsh internal deterioration under sea-level rise and sediment deficits: Application to Chesapeake Bay","interactions":[],"lastModifiedDate":"2025-09-25T14:37:46.76289","indexId":"70271943","displayToPublicDate":"2025-09-23T09:32:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"A simple predictive model for salt marsh internal deterioration under sea-level rise and sediment deficits: Application to Chesapeake Bay","docAbstract":"Salt marshes are dynamic biogeomorphic systems reliant on autochthonous and allochthonous input to maintain their three-dimensional configuration. Sea-level rise, subsidence, and sediment deficits can lead to submergence, open-water expansion, and ultimately loss of the vegetated marsh plain and associated ecosystem services. Widely used management-focused models focus on vegetation zonation in response to sea level but neglect sediment transport processes and geomorphic change. Process-based research models attempt to represent complex physical and biogeomorphic interactions but operate on spatiotemporal scales that are not directly transferable to restoration or management. Here we bridge these two paradigms and present a novel geomorphic model (UBMorph) based on the sediment-based lifespan concept that accounts for sea-level rise and open-water expansion to predict changes in salt marsh area in Chesapeake Bay. Model parameters such as surface accretion rate and elevation-to-areal loss fraction are selected using a separate, fully coupled biogeomorphic model (MarshMorpho2D) and the predicted lifespan is then compared with high marsh coverage from a zonation model (SLAMM). Across all of Chesapeake Bay, UBMorph estimates an overall loss of 404 km2 (37%) of vegetated marsh area under a dynamic 3–12 mm/y sea-level rise scenario (between 2010 and 2110). We then demonstrate a management-focused application of UBMorph and SLAMM used in tandem, for developing both a marsh condition and restoration model of the Chesapeake Bay portion of Maryland. The restoration model, which includes hydrologic intervention and sediment placement actions, indicates that ~ 400 km2 of marsh require either no intervention or low effort hydrologic intervention presently, whereas if no action is taken, over 700 km2 will require high effort intervention by 2070. This synthesis of research models with management-focused decision models demonstrates a tangible advance in bridging the gap between process-based research and restoration needs.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-025-01618-w","usgsCitation":"Ganju, N., Ackerman, K., Defne, Z., Mariotti, G., Curson, D., Posnik, Z., Carr, J., and Grand, J., 2025, A simple predictive model for salt marsh internal deterioration under sea-level rise and sediment deficits: Application to Chesapeake Bay: Estuaries and Coasts, v. 48, 178, 19 p., https://doi.org/10.1007/s12237-025-01618-w.","productDescription":"178, 19 p.","ipdsId":"IP-177384","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":496166,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-025-01618-w","text":"Publisher Index Page"},{"id":496080,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.56007683480865,\n 39.662435478342644\n ],\n [\n -77.02265802866081,\n 39.662435478342644\n ],\n [\n -77.02265802866081,\n 36.851268885158845\n ],\n [\n -75.56007683480865,\n 36.851268885158845\n ],\n [\n -75.56007683480865,\n 39.662435478342644\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Kate 0000-0003-3925-721X","orcid":"https://orcid.org/0000-0003-3925-721X","contributorId":293631,"corporation":false,"usgs":true,"family":"Ackerman","given":"Kate","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":949457,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mariotti, Giulio","contributorId":207541,"corporation":false,"usgs":false,"family":"Mariotti","given":"Giulio","email":"","affiliations":[{"id":37557,"text":"Louisiana State University, Baton Rouge LA","active":true,"usgs":false}],"preferred":false,"id":949458,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curson, David","contributorId":361793,"corporation":false,"usgs":false,"family":"Curson","given":"David","affiliations":[{"id":86352,"text":"Audubon Mid-Atlantic","active":true,"usgs":false}],"preferred":false,"id":949459,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Posnik, Zachary","contributorId":361794,"corporation":false,"usgs":false,"family":"Posnik","given":"Zachary","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":949460,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carr, Joel 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":220098,"corporation":false,"usgs":true,"family":"Carr","given":"Joel","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":949461,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Grand, Joanna","contributorId":291964,"corporation":false,"usgs":false,"family":"Grand","given":"Joanna","email":"","affiliations":[{"id":27800,"text":"National Audubon Society","active":true,"usgs":false}],"preferred":false,"id":949462,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271936,"text":"70271936 - 2025 - River-to-lake transitional areas contribute disproportionately to in-lake nutrient loading","interactions":[],"lastModifiedDate":"2025-09-25T14:31:08.098564","indexId":"70271936","displayToPublicDate":"2025-09-23T09:22:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22676,"text":"Ocean-Land-Atmosphere Research","active":true,"publicationSubtype":{"id":10}},"title":"River-to-lake transitional areas contribute disproportionately to in-lake nutrient loading","docAbstract":"River-to-lake transitional areas are biogeochemically active sections of the aquatic continuum that are often understudied compared to their adjoining environments. Internal nutrient loading from river-to-lake transitional areas may be a considerable source of nutrients to lakes and if overlooked disconnect upstream management initiatives from in-lake improvements. To contextualize internal nutrient loading by river-to-lake sediments, we conducted sediment core incubations and nutrient assays at 3 time points over a field season from a major contributing tributary of Lake Erie. Using statistical and spatial interpolation models, we upscaled internal nitrogen and phosphorus loading rates across the highly impaired mouth of the Maumee River, which drains into the western basin of Lake Erie. We found that internal nutrient dynamics in this river-to-lake transitional area were regulated by spatial differences in the physical composition and nutrient and organic matter contents of sediments. The Maumee river-to-lake transitional area was largely a source of phosphorus and ammonium nitrogen and a sink of nitrate nitrogen through high denitrification rates. Yet, we observed substantial temporal variation whereby internal nutrient loading was greatest in late summer coinciding with near-zero denitrification. Sediments at this time could contribute an additional ~17% more soluble reactive phosphorus and ~3% more total kjeldahl nitrogen in the bioavailable ammonium nitrogen fraction relative to the daily external nutrient load. High internal nutrient loading rates compared to more offshore areas in western Lake Erie suggest that this degraded river-to-lake transitional area has a disproportional biogeochemical significance and a high potential to contribute to nearshore water quality issues.
","language":"English","publisher":"AAAS","doi":"10.34133/olar.0109","usgsCitation":"Pearce, N.J., Larson, J.H., Kreiling, R.M., Evans, M.A., Bailey, S., Gierke, K., Bartsch, L., Xenopoulos, M.A., and Frost, P.C., 2025, River-to-lake transitional areas contribute disproportionately to in-lake nutrient loading: Ocean-Land-Atmosphere Research, v. 4, 0109, 14 p., https://doi.org/10.34133/olar.0109.","productDescription":"0109, 14 p.","ipdsId":"IP-150298","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":496165,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.34133/olar.0109","text":"Publisher Index Page"},{"id":496079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","city":"Toledo","otherGeospatial":"Maumee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": 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mammal","docAbstract":"Effective conservation requires an understanding of drivers of a species' distribution as well as long-term changes in their distribution. In recent decades, advances in data collection and analysis have allowed researchers to integrate a wide range of information to model species distributions, particularly by allowing presence-only data and detection-nondetection data to be formally combined in integrated species distribution models (ISDMs). However, these models are rarely used to investigate long-term trends, which are important in evaluating a species' status. Here, we use historical presence-only data of river otters (Lontra canadensis; 366 latrine locations from 1999 to 2007 and 105 locations of road-killed individuals recorded from 1999 to 2020) and 919 detection-nondetection surveys from 230 sites between 2021 and 2023 to understand the current distribution of river otters in Rhode Island, USA, as well as the changes in river otter distribution over the past two decades. We found that river otters were strongly associated with key habitat features such as streams and water, positively associated with urban areas, and tolerant of some contaminants, such as lead. Furthermore, despite uncertainties in historical river otter occurrence, we found clear supporting evidence that river otter intensity of use had declined from 1999 to 2023. This decline occurred despite being protected from harvest and in contrast to range expansions in other parts of the northeastern USA throughout the second half of the 20th century. Our results suggest the utility of this approach to detect declines in species for which historical data are available and a need for better understanding the cause of river otter declines. Where monitoring consists of opportunistically collected data, species conservation could benefit by continuing to collect these data as well as introducing designed surveys, as this would allow better integration of data types, improving trend estimation and reducing the amount of (typically more expensive) designed surveys needed.
","language":"English","publisher":"Zoological Society of London","doi":"10.1111/acv.70036","usgsCitation":"Crockett, J.G., Brown, C.B., Gerber, B., 2025, Integrated species distribution model using historical data shows decline in a common semi-aquatic mammal: Animal Conservation, 15 p., https://doi.org/10.1111/acv.70036.","productDescription":"15 p.","ipdsId":"IP-178855","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500623,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/acv.70036","text":"Publisher Index Page"},{"id":500410,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Blackstone River, Block Island Sound, Narragansett 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Island\",\"nation\":\"USA \"}}]}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-09-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Crockett, John G.","contributorId":366635,"corporation":false,"usgs":false,"family":"Crockett","given":"John","middleInitial":"G.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":956111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Charles B.","contributorId":168888,"corporation":false,"usgs":false,"family":"Brown","given":"Charles","email":"","middleInitial":"B.","affiliations":[{"id":25379,"text":"Dept of Biol Sc, Univ of Tulsa, Tulsa OK","active":true,"usgs":false}],"preferred":false,"id":956112,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerber, Brian Daniel 0000-0001-9285-9784","orcid":"https://orcid.org/0000-0001-9285-9784","contributorId":354265,"corporation":false,"usgs":true,"family":"Gerber","given":"Brian Daniel","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956113,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271679,"text":"sir20255063 - 2025 - Assessment of channel morphology, hydraulics, and bedload transport along the Siletz River, western Oregon","interactions":[],"lastModifiedDate":"2026-02-03T15:31:12.18485","indexId":"sir20255063","displayToPublicDate":"2025-09-22T13:02:49","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":"2025-5063","displayTitle":"Assessment of Channel Morphology, Hydraulics, and Bedload Transport along the Siletz River, Western Oregon","title":"Assessment of channel morphology, hydraulics, and bedload transport along the Siletz River, western Oregon","docAbstract":"Chinook salmon (Oncorhynchus tshawytscha) and Pacific lamprey (Entosphenus tridentatus) are native, anadromous fish species in the Siletz River Basin, western Oregon, that face many threats to their survival in freshwater and the ocean. The Confederated Tribes of Siletz Indians of Oregon seek to mitigate freshwater threats to Chinook salmon and Pacific lamprey, where possible, with habitat conservation and restoration efforts. This study was conducted to assist the Confederated Tribes of Siletz Indians of Oregon in documenting and understanding the hydrogeomorphic processes shaping present-day habitat conditions and assessing future habitat implications for Chinook salmon and Pacific lamprey along the main-stem Siletz River. As such, this study focused on understanding geomorphic processes and patterns of channel change, including lateral and vertical adjustments in channel position and changes in bed-material sediment (sands, gravels, and cobbles that mantle the channel bed), which collectively determine overall patterns of channel morphology and fluvial habitats. Objective One was to evaluate lateral changes in channel position, vertical changes in bed elevation, and longitudinal patterns in bed-material particle size along the Siletz River using detailed channel maps developed from aerial photographs collected from 1939 to 2016, long-term records of stage and discharge collected by the U.S. Geological Survey (USGS) near the City of Siletz, and sediment particle size data. Objective Two was to assess hydraulic conditions using one- and two-dimensional hydraulic models and transport capacity of bed-material sediment using bedload transport models and sediment particle size data for a range of discharge conditions. Objective Three was to identify potential burrowing habitat for lamprey larvae (PBH) along the Siletz River network and provide insights in local factors influencing PBH along the main-stem Siletz River. The overall findings are synthesized to describe habitat implications for Chinook salmon and Pacific lamprey under present-day and future conditions.
Results of Objective One, an evaluation of changes in channel position and bed elevations and longitudinal patterns in bed-material particle size along the Siletz River, include the following
Results of Objective Two, an evaluation of hydraulic and bedload transport conditions along the Siletz River, include the following
Results of Objective Three, an analysis of PBH for lamprey larvae, include the following
Together, these results suggest that most of the Siletz River between Wildcat Creek and the City of Siletz has had only modest vertical and lateral change between the 1930s and 2010s because of the bedrock in and along the main channel and the river’s relatively high transport capacity relative to bed-material sediment supply. However, localized sections of the Siletz River where the active channel widens, particularly at channel bends, exhibited some change in channel planform and the locations and area of gravel bars. In the future, moderate increases in autumn-winter discharge may not result in substantial changes in coarse gravel bars along the Siletz River but may result in selective transport of finer bed-material sediment (gravel, sands, and silts) that provide spawning habitats for Chinook salmon and Pacific lamprey and burrowing habitats for lamprey larvae. Assuming no substantial changes in bed-material sediment supply, increased bedload transport capacity may cause frequent entrainment of lamprey larvae that are burrowed in coarse sand deposits, suspension and downstream transport of salmon eggs incubating in gravels, and reductions in the areas of spawning gravels for Chinook salmon and Pacific lamprey. Exact implications of current and future discharge conditions for these species along the Siletz River depends on many factors, including sediment supply, local hydraulics, and the timing of flood events relative to fish life stages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255063","collaboration":"Prepared in cooperation with the Confederated Tribes of Siletz Indians of Oregon","usgsCitation":"Jones, K.L., Keith, M.K., Harden, T.M., White, J.S., van de Wetering, S., and Dunham, J.B., 2025, Assessment of\nchannel morphology, hydraulics, and bedload transport along the Siletz River, western Oregon: U.S. Geological Survey\nScientific Investigations Report 2025–5063, 95 p., https://doi.org/10.3133/sir20255063.","productDescription":"Report: xii, 95 p.; 5 Data Releases","onlineOnly":"Y","ipdsId":"IP-127308","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":496021,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118884.htm","linkFileType":{"id":5,"text":"html"}},{"id":495760,"rank":10,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5063/sir20255063.XML"},{"id":495758,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1489NN8","text":"USGS data release","description":"USGS data release","linkHelpText":"One- and two-dimensional hydraulic models for the Siletz River, Oregon"},{"id":495757,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1N35MQN","text":"USGS data release","description":"USGS data release","linkHelpText":"Water surface elevation data from the Siletz River, 2017–18"},{"id":495751,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5063/coverthb.jpg"},{"id":495752,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5063/sir20255063.pdf","text":"Report","size":"28.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5063"},{"id":495753,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255063/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5063"},{"id":495754,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AWWRA0","text":"USGS data release","description":"USGS data release","linkHelpText":"Active channel mapping for the Siletz River, Oregon, 1939 to 2016"},{"id":495755,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96ZXPP","text":"USGS data release","description":"USGS data release","linkHelpText":"Surficial and subsurface grain-size data for the Siletz River, Oregon, 2017–18"},{"id":495756,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TIADK3","text":"USGS data release","description":"USGS data release","linkHelpText":"Modeled bedload transport capacity for the Siletz River, Oregon"},{"id":495759,"rank":9,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5063/images"}],"country":"United States","state":"Oregon","otherGeospatial":"Siletz River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.1,\n 45\n ],\n [\n -124.1,\n 44.333\n ],\n [\n -123.5,\n 44.333\n ],\n [\n -123.5,\n 45\n ],\n [\n -124.1,\n 45\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
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The Upper Mississippi River Restoration (UMRR) program, a broad partnership of State and Federal agencies administered by the U.S. Army Corps of Engineers, integrates ecosystem monitoring, research, and modeling to rehabilitate habitat and evaluate ecosystem trends over time in the Upper Mississippi River System. Hydrologic data are integral to the UMRR program because they are used in scientific research, decision-making, and restoration project planning. However, a lack of quantitative hydrologic data representing potential future conditions limits the ability to complete informative research on how future conditions may affect river ecology, achieve management goals, and design restoration projects for 50-year horizons.
The U.S. Geological Survey and the U.S. Army Corps of Engineers led a series of workshops with UMRR partners to (1) prioritize needs for understanding future hydrology, (2) discuss appropriate datasets that could address these needs, and (3) develop a plan for acquiring and distributing a hydrologic dataset of potential future conditions. Agency priorities for understanding future hydrology were broad, spanning ecologic, geomorphic, resource management, and engineering disciplines, and were identified for a range of spatial (project site, navigation pool, reach, system) and temporal (daily, seasonal, annual) scales. The LOcalized Constructed Analogs-Variable Infiltration Capacity-mizuRoute hydrologic data products were identified as a potential source of off-the-shelf data to meet UMRR priority needs but warranted a robust quantitative evaluation. The final meeting in the series scoped a proposal to evaluate the LOcalized Constructed Analogs-Variable Infiltration Capacity-mizuRoute hydrologic data products for use in UMRR applications, including contingencies if the data were determined to be unreliable.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251050","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Van Appledorn, M., and Sawyer, L., 2025, Upper Mississippi River Restoration future hydrology meeting series: U.S. Geological Survey Open-File Report 2025–1050, 93 p., https://doi.org/10.3133/ofr20251050.","productDescription":"vii, 93 p.","numberOfPages":"106","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-144284","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":495840,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1050/coverthb.jpg"},{"id":495844,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251050/full"},{"id":495843,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1050/images/"},{"id":495842,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1050/ofr20251050.XML"},{"id":495841,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1050/ofr20251050.pdf","text":"Report","size":"4.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1050"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.2103238355043,\n 37.043422473537504\n ],\n [\n -87.69596012242188,\n 41.69069025518516\n ],\n [\n -89.11501122546446,\n 44.87351523241463\n ],\n [\n -89.14678376857329,\n 46.12049934311611\n ],\n [\n -92.37672035941334,\n 46.134727618766064\n ],\n [\n -94.31468231391703,\n 47.910742701911886\n ],\n [\n -96.86686171848238,\n 47.08812323847167\n ],\n [\n -94.08172387608387,\n 40.82297944373079\n ],\n [\n -89.40096330837447,\n 37.051916822243555\n ],\n [\n -89.2103238355043,\n 37.043422473537504\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, Wisconsin 54603
A series of workshops was held so participants from several agencies could work together to prioritize needs for understanding future hydrologic scenarios, discuss appropriate datasets that could address these needs, and develop a plan for acquiring and distributing a hydrologic dataset representing potential future conditions. Agency priorities for understanding future hydrology spanned ecologic, geomorphic, resource management, and engineering disciplines and were identified for a range of spatial (project site, navigation pool, reach, system) and temporal (daily, seasonal, annual) scales. Participants described desired characteristics of a hydrologic dataset of potential future conditions that could meet agency priority needs and developed a workflow to evaluate a readily available data product.
","publicationDate":"2025-09-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Van Appledorn, Molly 0000-0002-8029-0014","orcid":"https://orcid.org/0000-0002-8029-0014","contributorId":205785,"corporation":false,"usgs":true,"family":"Van Appledorn","given":"Molly","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":949216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawyer, Lucie","contributorId":345904,"corporation":false,"usgs":false,"family":"Sawyer","given":"Lucie","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":949217,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}