{"pageNumber":"76","pageRowStart":"1875","pageSize":"25","recordCount":184657,"records":[{"id":70269918,"text":"70269918 - 2025 - Satellite imagery can predict bird species occupancy and inform multispecies management in pine savannas","interactions":[],"lastModifiedDate":"2025-08-07T15:09:06.947409","indexId":"70269918","displayToPublicDate":"2025-04-25T07:59:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Satellite imagery can predict bird species occupancy and inform multispecies management in pine savannas","docAbstract":"

Multispecies management can contribute to meeting growing challenges of preserving biodiversity, yet current game and threatened species management often focuses on individual species. Satellite imagery available at high spatial and temporal resolution provides a potential tool to overcome the challenge posed by multispecies management of linking patterns of habitat use among species. We sought to determine whether satellite imagery could be used to describe patterns of species occupancy and inform multispecies management in pine savannas in Georgia, USA. We conducted point-count surveys at 7 sites in 2022 for 3 bird species: Colinus virginianus (Northern Bobwhite), Dryobates borealis (Red-cockaded Woodpecker), and Peucaea aestivalis (Bachman’s Sparrow). We built single-season occupancy models comparing a set of models using covariates collected from field vegetation surveys and another set using covariates extracted from Sentinel-2 satellite imagery. We then used a multi-objective optimization algorithm to identify quasi-optimal management solutions (i.e., sets of covariate values from top satellite imagery metric models). We found that models created using satellite imagery performed well at predicting occupancy of all 3 species as measured by the area under the receiver operating characteristic curve (AUC > 0.8) and had higher AUC scores than field-derived habitat covariate-based models. We found combinations of metrics that could result in high rates of predicted probability of occupancy for all species (within 86% of highest possible occupancy probability), but these combinations did not exist at any of the sites. Our results demonstrate that (1) satellite imagery can allow users to build reliable occupancy models without intensive field-based vegetation surveys; and (2) C. virginianus, D. borealis, and P. aestivalis in pine savanna ecosystems could be simultaneously managed through more frequent burning, changes in canopy cover or by producing suitable heterogeneity of habitats after identifying an appropriate scale of management.

","language":"English","publisher":"American Ornithological Society","doi":"10.1093/ornithapp/duaf029","usgsCitation":"Allred, C.R., Schneider, T.M., and Hunter, E.A., 2025, Satellite imagery can predict bird species occupancy and inform multispecies management in pine savannas: Ornithological Applications, https://doi.org/10.1093/ornithapp/duaf029.","ipdsId":"IP-172250","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":493711,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Allred, Cory R.","contributorId":350504,"corporation":false,"usgs":false,"family":"Allred","given":"Cory","middleInitial":"R.","affiliations":[{"id":34764,"text":"Virginia Tech, Department of Fish and Wildlife Conservation","active":true,"usgs":false}],"preferred":false,"id":944953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schneider, Todd M.","contributorId":359085,"corporation":false,"usgs":false,"family":"Schneider","given":"Todd","middleInitial":"M.","affiliations":[{"id":36378,"text":"Georgia Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":944954,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Elizabeth Ann 0000-0003-4710-167X","orcid":"https://orcid.org/0000-0003-4710-167X","contributorId":288535,"corporation":false,"usgs":true,"family":"Hunter","given":"Elizabeth","email":"","middleInitial":"Ann","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":944955,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266101,"text":"fs20253008 - 2025 - U.S. Geological Survey 2024 Rocky Mountain Region Science Exchange—Showcasing cutting-edge science to adapt to extreme weather events and stakeholder needs","interactions":[],"lastModifiedDate":"2025-04-29T18:25:49.532193","indexId":"fs20253008","displayToPublicDate":"2025-04-24T18:10:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3008","displayTitle":"U.S. Geological Survey 2024 Rocky Mountain Region Science Exchange—Showcasing Cutting-Edge Science to Adapt to Extreme Weather Events and Stakeholder Needs","title":"U.S. Geological Survey 2024 Rocky Mountain Region Science Exchange—Showcasing cutting-edge science to adapt to extreme weather events and stakeholder needs","docAbstract":"

Introduction

The Rocky Mountains and the Colorado River Basin in the Western United States are complex, interconnected systems that sustain a large variety of species, including tens of millions of humans. These regions face risks from drought, wildfires, invasive plant and animal species, and habitat reduction. Working with many stakeholders, scientists can help to characterize these risks by providing data and analytical tools to inform land and water resource management decisions. 

The U.S. Geological Survey 2024 Rocky Mountain Region (Region 7) Science Exchange Workshop, held in April 2024, focused on cutting-edge science techniques, evaluating complex interconnected risks, and coproducing science with science partners and stakeholders. These science topics and communication strategies can be used for developing data, interpretations, and decision support tools needed to provide science that resource managers and other stakeholders can use to better understand complex, dynamic natural systems and develop management strategies to plan for and adapt to risks that threaten human communities and natural ecosystems.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253008","usgsCitation":"Andrews, W.J., Titus, T.N., Eng, L.E., Zellman, K.L., Anderson, P.J., and Havens, J.C., 2025, U.S. Geological Survey 2024 Rocky Mountain Region Science Exchange—Showcasing cutting-edge science to adapt to extreme weather events and stakeholder needs: U.S. Geological Survey Fact Sheet 2025-3008, 4 p., https://doi.org/10.3133/fs20253008.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-167985","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":64844,"text":"Rocky Mountain Region Director’s Office","active":true,"usgs":true}],"links":[{"id":485159,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253008/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3008"},{"id":484983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3008/coverthb.jpg"},{"id":484985,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3008/fs20253008.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3008"},{"id":485041,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3008/images"},{"id":485042,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3008/fs20253008.xml"}],"contact":"

Director, Rocky Mountain Region
U.S. Geological Survey
Box 25046, MS-911
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2025-04-24","noUsgsAuthors":false,"publicationDate":"2025-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Andrews, William J. 0000-0003-4780-8835 wandrews@usgs.gov","orcid":"https://orcid.org/0000-0003-4780-8835","contributorId":328,"corporation":false,"usgs":true,"family":"Andrews","given":"William","email":"wandrews@usgs.gov","middleInitial":"J.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Titus, Timothy N. 0000-0003-0700-4875 ttitus@usgs.gov","orcid":"https://orcid.org/0000-0003-0700-4875","contributorId":146,"corporation":false,"usgs":true,"family":"Titus","given":"Timothy","email":"ttitus@usgs.gov","middleInitial":"N.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":934585,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eng, Lauren Ellissa 0009-0003-9808-4184","orcid":"https://orcid.org/0009-0003-9808-4184","contributorId":332901,"corporation":false,"usgs":true,"family":"Eng","given":"Lauren Ellissa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zellman, Kristine L. 0000-0002-7088-429X kzellman@usgs.gov","orcid":"https://orcid.org/0000-0002-7088-429X","contributorId":4849,"corporation":false,"usgs":true,"family":"Zellman","given":"Kristine","email":"kzellman@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":934587,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":934588,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Havens, Jeremy C. 0000-0002-8685-2823","orcid":"https://orcid.org/0000-0002-8685-2823","contributorId":292231,"corporation":false,"usgs":true,"family":"Havens","given":"Jeremy","middleInitial":"C.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":934589,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266112,"text":"70266112 - 2025 - Statistical approaches for modeling correlated grade and tonnage distributions and applications for mineral resource assessments","interactions":[],"lastModifiedDate":"2025-04-25T15:35:26.584633","indexId":"70266112","displayToPublicDate":"2025-04-24T10:32:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14424,"text":"Applied Computing and Geosciences","active":true,"publicationSubtype":{"id":10}},"title":"Statistical approaches for modeling correlated grade and tonnage distributions and applications for mineral resource assessments","docAbstract":"
Correlations between grade and tonnage exist in mineral resource data compiled from published reports, but they are not always addressed during quantitative assessment of undiscovered mineral resources. Failure to account for correlated grade and tonnage distributions can result in geologically unrealistic assessment results. Current software tools simulate univariate ore tonnage and multivariate resource grades of undiscovered deposits independently. As a result, analysts are forced to rely on ad-hoc solutions to minimize the correlation issues by: 1) creating subsets of data with restricted criteria; 2) truncating grade and tonnage distributions; and 3) testing model robustness using exploratory data analysis. While these methods represent pragmatic solutions, the statistical solutions presented here provide additional options to address real correlations in grade and tonnage data used for mineral resource assessments. We present a modified version of the MapMark4 package in R that introduces two alternatives for modeling grade and tonnage distributions, consisting of a multivariate solution that accounts for correlations between ore tonnage and metal grades and an empirical solution that utilizes simple random sampling with replacement to reproduce coupled grades and tonnages from the input data. We present simulations for contained ore and metal for three case studies representing tungsten skarn, komatiite-hosted nickel, and sediment-hosted carbonate amagmatic zinc-lead (Mississippi Valley-type) deposits. Employing the methods presented here yields quantitative mineral resource assessment results that more closely reflect the empirical distributions of grades and tonnages observed in nature and expands the applicability of these tools for ongoing critical mineral resource assessments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.acags.2025.100240","usgsCitation":"Rosera, J.M., Lederer, G.W., and Schuenemeyer, J., 2025, Statistical approaches for modeling correlated grade and tonnage distributions and applications for mineral resource assessments: Applied Computing and Geosciences, v. 26, 100240, 13 p., https://doi.org/10.1016/j.acags.2025.100240.","productDescription":"100240, 13 p.","ipdsId":"IP-169818","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":487776,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.acags.2025.100240","text":"Publisher Index Page"},{"id":485062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","noUsgsAuthors":false,"publicationDate":"2025-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosera, Joshua Mark 0000-0003-3807-5000","orcid":"https://orcid.org/0000-0003-3807-5000","contributorId":270284,"corporation":false,"usgs":true,"family":"Rosera","given":"Joshua","email":"","middleInitial":"Mark","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"preferred":true,"id":934621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lederer, Graham W. 0000-0002-9505-9923","orcid":"https://orcid.org/0000-0002-9505-9923","contributorId":202407,"corporation":false,"usgs":true,"family":"Lederer","given":"Graham","email":"","middleInitial":"W.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":934622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schuenemeyer, John","contributorId":149378,"corporation":false,"usgs":false,"family":"Schuenemeyer","given":"John","email":"","affiliations":[],"preferred":false,"id":934623,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265923,"text":"70265923 - 2025 - Wet antecedent soil moisture increases atmospheric river streamflow magnitudes non-linearly","interactions":[],"lastModifiedDate":"2025-06-12T15:41:54.841369","indexId":"70265923","displayToPublicDate":"2025-04-24T10:26:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Wet antecedent soil moisture increases atmospheric river streamflow magnitudes non-linearly","docAbstract":"

Atmospheric rivers (ARs) drive most riverine floods on the United States (U.S.) West Coast. However, estimating flood risk based solely on AR intensity and duration is challenging because precipitation phase, antecedent conditions, and physical watershed characteristics (e.g., slope and soil depth) can influence the magnitude of floods. Here, we analyze how antecedent soil moisture (ASM) conditions contribute to variability in streamflow during AR events and how that changes across climatic regimes and physiography in 122 U.S. West Coast watersheds. We identify a robust non-linear relationship between streamflow and ASM during ARs in 89% of watersheds. The inflection point in this relationship represents a watershed-specific critical ASM threshold, above which event maximum streamflow is, on average, two to four and a half times larger. Wet ASM conditions amplify the hydrologic impacts of more frequent but weaker, lower moisture transport AR events, while dry ASM conditions attenuate the hydrologic impacts that stronger, higher moisture transport AR events could otherwise cause. Our research shows that watersheds prone to ASM-amplified streamflows have higher evaporation ratios, lower cold-season precipitation, lower snow-to-rain ratios, and shallower, clay-rich soils. Higher evaporation and lower precipitation lead to greater ASM variability during the cold season, increasing streamflow during wet periods and buffering streamflow during dry periods. Lower snow fraction and shallower soils limit the antecedent water storage capacity of a watershed, contributing to greater sensitivity of streamflow peaks to ASM variability. Incorporating ASM thresholds into hydrologic models in these regions prone to AR-amplified streamflow could improve forecasts and decrease uncertainty.

","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-24-0078.1","collaboration":"Desert Research Institute, Reno, NV","usgsCitation":"Webb, M., Albano, C., Harpold, A., Wagner, D.M., and Wilson, A.M., 2025, Wet antecedent soil moisture increases atmospheric river streamflow magnitudes non-linearly: Journal of Hydrometeorology, v. 26, no. 6, p. 741-758, https://doi.org/10.1175/JHM-D-24-0078.1.","productDescription":"18 p.","startPage":"741","endPage":"758","ipdsId":"IP-166108","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":485998,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.92121191786663,\n 33.407810452030205\n ],\n [\n -116.523784768193,\n 36.41502072713284\n ],\n [\n -119.64994516515054,\n 39.88994270690637\n ],\n [\n -120.51138519071847,\n 42.20041323206641\n ],\n [\n -119.3720758190301,\n 48.777534854733574\n ],\n [\n -122.9287960859929,\n 48.977595241145025\n ],\n [\n -123.36076938971661,\n 48.210450784064506\n ],\n [\n -125.09530509112804,\n 48.5114622057049\n ],\n [\n -124.0899142321606,\n 45.77238715755897\n ],\n [\n -124.63673786495912,\n 42.844084204189784\n ],\n [\n -124.31096484013645,\n 41.342509106103535\n ],\n [\n -124.81776995325123,\n 40.42865225014583\n ],\n [\n -123.57485679616491,\n 38.65999426544576\n ],\n [\n -122.45718830306802,\n 37.1653556881036\n ],\n [\n -121.77165200602349,\n 35.90307547409293\n ],\n [\n -120.64970139084915,\n 34.560810038256434\n ],\n [\n -117.92121191786663,\n 33.407810452030205\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"26","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Webb, Mariana J. 0000-0003-0331-2635","orcid":"https://orcid.org/0000-0003-0331-2635","contributorId":353576,"corporation":false,"usgs":false,"family":"Webb","given":"Mariana J.","affiliations":[{"id":84438,"text":"Division of Hydrological Sciences, Desert Research Institute, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":933999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Albano, Christine M.","contributorId":17681,"corporation":false,"usgs":true,"family":"Albano","given":"Christine M.","affiliations":[],"preferred":false,"id":934000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harpold, Adrian A. 0000-0002-2566-9574","orcid":"https://orcid.org/0000-0002-2566-9574","contributorId":353577,"corporation":false,"usgs":false,"family":"Harpold","given":"Adrian A.","affiliations":[{"id":84439,"text":"Dept. of Natural Resources and Environmental Science, Univ. of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":934001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagner, Daniel M. 0000-0002-0432-450X dwagner@usgs.gov","orcid":"https://orcid.org/0000-0002-0432-450X","contributorId":4531,"corporation":false,"usgs":true,"family":"Wagner","given":"Daniel","email":"dwagner@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Anna M.","contributorId":211536,"corporation":false,"usgs":false,"family":"Wilson","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":934003,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266282,"text":"70266282 - 2025 - Automated snow cover detection on mountain glaciers usingspaceborne imagery and machine learning","interactions":[],"lastModifiedDate":"2025-05-02T14:54:35.492386","indexId":"70266282","displayToPublicDate":"2025-04-24T09:53:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3554,"text":"The Cryosphere","active":true,"publicationSubtype":{"id":10}},"title":"Automated snow cover detection on mountain glaciers usingspaceborne imagery and machine learning","docAbstract":"

Tracking the extent of seasonal snow on glaciers over time is critical for assessing glacier vulnerability and the response of glacierized watersheds to climate change. Existing snow cover products do not reliably distinguish seasonal snow from glacier ice and firn, preventing their use for glacier snow cover detection. Despite previous efforts to classify glacier surface facies using machine learning on local scales, currently there is no published comparison of machine learning models for classifying glacier snow cover across different satellite image products. We present an automated snow detection workflow for mountain glaciers using supervised machine-learning-based image classifiers and Landsat 8 and 9, Sentinel-2, and PlanetScope satellite imagery. We develop the image classifiers by testing numerous machine learning algorithms with training and validation data from the U.S. Geological Survey Benchmark Glacier Project glaciers. The workflow produces daily to twice monthly time series of several glacier mass balance and snowmelt indicators (snow-covered area, accumulation area ratio, and seasonal snow line) from 2013 to present. Workflow performance is assessed by comparing automatically classified images and snow lines to manual interpretations at each glacier site. The image classifiers exhibit overall accuracies of 92%–98%, K scores of 84%–96%, and F scores of 93%–98% for all image products. The median difference between automatically and manually delineated median snow line altitudes is 31m (IQR of 73to0m)across all image products. The Sentinel-2 classifier (support vector machine) produces the most accurate glacier mass balance and snowmelt indicators and distinguishes snow from ice and f irn the most reliably. Although they are less accurate, the Landsat- and PlanetScope-derived estimates greatly enhance the temporal coverage of observations. The transient accumulation area ratio produces the least noisy time series, making it the most reliable indicator for characterizing seasonal snow trends. The temporally detailed accumulation area ratio time series reveal that the timing of minimum snow cover conditions varies by up to a month between Arctic (63°N) and midlatitude (48°N) sites, underscoring the potential for bias when estimating glacier minimum snow cover conditions from a single late-summer image. Widespread application of our automated snow detection workflow has the potential to improve regional assessments of glacier mass balance, land ice representations within Earth system models, water resources, and the impacts of climate change on snow cover across broad spatial scales.

","language":"English","publisher":"Copernicus Publications","doi":"10.5194/tc-19-1675-2025","usgsCitation":"Aberle, R., Enderlin, E., O'Neel, S., Florentine, C., Sass, L., Dickson, A., Marshall, H., and Flores, A., 2025, Automated snow cover detection on mountain glaciers usingspaceborne imagery and machine learning: The Cryosphere, v. 19, p. 1675-1693, https://doi.org/10.5194/tc-19-1675-2025.","productDescription":"19 p.","startPage":"1675","endPage":"1693","ipdsId":"IP-161789","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":487924,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-19-1675-2025","text":"Publisher Index Page"},{"id":485326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Unite States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.76360091465392,\n 47.06180837633883\n ],\n [\n -121.3176201884703,\n 48.805343460206615\n ],\n [\n -120.0015482436147,\n 50.335300241584264\n ],\n [\n -130.45623413084917,\n 62.431155673423405\n ],\n [\n -144.1767604606605,\n 64.77803371822662\n ],\n [\n -156.74065293077143,\n 62.94965967944643\n ],\n [\n -153.58716512013862,\n 58.34813914012679\n ],\n [\n -151.25294354192766,\n 56.670611414741046\n ],\n [\n -147.2303378681512,\n 59.785680900702204\n ],\n [\n -139.72127967128716,\n 59.315677918279675\n ],\n [\n -134.82069406634898,\n 55.48786621236388\n ],\n [\n -131.59648302534626,\n 51.752911462025\n ],\n [\n -123.76360091465392,\n 47.06180837633883\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2025-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Aberle, Rainey","contributorId":354302,"corporation":false,"usgs":false,"family":"Aberle","given":"Rainey","affiliations":[],"preferred":false,"id":935376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Enderlin, Ellyn","contributorId":187445,"corporation":false,"usgs":false,"family":"Enderlin","given":"Ellyn","email":"","affiliations":[],"preferred":false,"id":935377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Neel, Shad 0000-0002-9185-0144","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":289666,"corporation":false,"usgs":false,"family":"O'Neel","given":"Shad","affiliations":[{"id":62222,"text":"Cold Regions Research Laboratory","active":true,"usgs":false}],"preferred":false,"id":935378,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Florentine, Caitlyn 0000-0002-7028-0963","orcid":"https://orcid.org/0000-0002-7028-0963","contributorId":205964,"corporation":false,"usgs":true,"family":"Florentine","given":"Caitlyn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":935380,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":935381,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dickson, Adam","contributorId":354305,"corporation":false,"usgs":false,"family":"Dickson","given":"Adam","affiliations":[],"preferred":false,"id":935383,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marshall, Hans-Peter","contributorId":330964,"corporation":false,"usgs":false,"family":"Marshall","given":"Hans-Peter","email":"","affiliations":[{"id":33038,"text":"Department of Geosciences, Boise State University","active":true,"usgs":false}],"preferred":false,"id":935379,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Flores, Alejandro","contributorId":221466,"corporation":false,"usgs":false,"family":"Flores","given":"Alejandro","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":935382,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70273766,"text":"70273766 - 2025 - Movement patterns of invasive red swamp crayfish vary with sex and environmental factors","interactions":[],"lastModifiedDate":"2026-01-28T16:36:02.719179","indexId":"70273766","displayToPublicDate":"2025-04-24T09:27:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Movement patterns of invasive red swamp crayfish vary with sex and environmental factors","docAbstract":"

Invasive species disproportionately invade freshwater ecosystems, threatening biodiversity. Defining when, where, and why aquatic invasive species move can help inform management strategies, yet the movement ecology of some of the most pervasive invasive species remains unknown. Red swamp crayfish (Procambarus clarkii; RSC) are the most widespread invasive crayfish and negatively affect ecosystems worldwide. We employed high-dimensional acoustic telemetry to investigate the movement patterns of 24 individual RSC across three months in an invaded water body. We assessed the effects of various extrinsic factors, such as time of day, temperature, precipitation, and proximity to the water’s edge, along with intrinsic factors, such as sex, reproductive form, and size, at different scales, including movement steps, range distribution, and behavioral states. We found that movement patterns across all scales were overwhelmingly driven by sex and reproductive form. Furthermore, RSC showed increased overall activity at night and near the water’s edge. By establishing baseline movement patterns and identifying key contributing factors, these findings provide a foundation for the development of adaptive management strategies for controlling invasive RSC populations.

","language":"English","publisher":"Springer Nature","doi":"10.1038/s41598-025-96379-8","usgsCitation":"Raboin, M.J., Roth, B.M., Sullivan, A., Allert, A.L., Stoeckel, J.A., Nathan, L.R., Quebedeaux, K.B., Sholtis, M.D., Smerud, J.R., Erickson, R.A., and Cupp, A.R., 2025, Movement patterns of invasive red swamp crayfish vary with sex and environmental factors: Scientific Reports, v. 15, 14312, 12 p., https://doi.org/10.1038/s41598-025-96379-8.","productDescription":"14312, 12 p.","ipdsId":"IP-172876","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":499329,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-96379-8","text":"Publisher Index Page"},{"id":499178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","city":"Novi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.54165103908441,\n 42.52197691173481\n ],\n [\n -83.54165103908441,\n 42.44570736959304\n ],\n [\n -83.43173535865259,\n 42.44570736959304\n ],\n [\n -83.43173535865259,\n 42.52197691173481\n ],\n [\n -83.54165103908441,\n 42.52197691173481\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Raboin, Maggie Jo 0000-0002-1475-7253","orcid":"https://orcid.org/0000-0002-1475-7253","contributorId":317839,"corporation":false,"usgs":true,"family":"Raboin","given":"Maggie","email":"","middleInitial":"Jo","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":954679,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roth, Brian 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B.","contributorId":365734,"corporation":false,"usgs":false,"family":"Quebedeaux","given":"Kathleen","middleInitial":"B.","affiliations":[{"id":50471,"text":"Michigan Department of Natural Resources, Lansing, MI","active":true,"usgs":false}],"preferred":false,"id":954685,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sholtis, Matthew D. 0000-0003-1904-8250","orcid":"https://orcid.org/0000-0003-1904-8250","contributorId":317840,"corporation":false,"usgs":true,"family":"Sholtis","given":"Matthew","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":954686,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smerud, Justin R. 0000-0003-4385-7437 jrsmerud@usgs.gov","orcid":"https://orcid.org/0000-0003-4385-7437","contributorId":5031,"corporation":false,"usgs":true,"family":"Smerud","given":"Justin","email":"jrsmerud@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":954687,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":954688,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":954689,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70266821,"text":"70266821 - 2025 - Linking age and social status of cooperative breeders to vulnerability throughout the harvest season","interactions":[],"lastModifiedDate":"2025-06-23T15:22:37.563269","indexId":"70266821","displayToPublicDate":"2025-04-24T09:21:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Linking age and social status of cooperative breeders to vulnerability throughout the harvest season","docAbstract":"

Individual behaviors are influenced by environmental, genetic, and demographic factors. Some animals choose to live in groups and cooperatively breed, and their behaviors can change depending on dynamic factors such as group size and composition that affect group persistence. In Idaho, USA, gray wolves (Canis lupus) are harvested annually, providing an opportunity to investigate the effects of harvest and seasonal behaviors on a population of cooperative breeders. These annual hunting and trapping seasons overlap with the dispersal and breeding periods for wolves and we do not know how harvest affects the vulnerability of different sex and age classes during these important biological periods. We applied 9 years (2009–2018) of genetic, age, and harvest data from harvested wolves to investigate how behaviors (dispersal and breeding) and biological drivers might influence the vulnerability of wolves to harvest. We created pedigrees from genotypes of non-invasively collected scats to estimate the expected proportion of the wolf population composed of 3 different age classes (pup, yearling, and sexually mature or ≥2 years old) and compared them to the observed number of each age class harvested during biologically significant periods (i.e., dispersal and breeding). We found that pups were more vulnerable to harvest in December when wolf harvest transitioned largely to trapping (accounts for 66% of harvest), and found evidence that adults were more vulnerable to harvest during their breeding season in January and February. In contrast, we found no difference in the expected versus observed number of wolves ≥2 years old in the harvest during peak dispersal season (December), or in the expected versus observed number of yearlings in the harvest during September and October when pups are mobile and groups of wolves abandon the use of pup-rearing sites. Some age classes were disproportionally harvested during certain periods for specific years, but this was not consistent across all years, suggesting there is more to learn about the vulnerability of different age classes to harvest. We found harvest can disproportionally affect some demographic classes of individuals depending on year, biological period, and harvest type. With wolves continuing to recolonize historical ranges, our approach can benefit managers and future studies with the goal of identifying how interannual harvest affects groups of wolves.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70024","usgsCitation":"Rebholz, P., Bassing, S., Waits, L., and Ausband, D.E., 2025, Linking age and social status of cooperative breeders to vulnerability throughout the harvest season: Journal of Wildlife Management, v. 89, no. 5, e70024, 14 p., https://doi.org/10.1002/jwmg.70024.","productDescription":"e70024, 14 p.","ipdsId":"IP-158746","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485834,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Characteristics of volcanic ash reveal changes in fragmentation and eruption dynamics at Poás volcano, Costa Rica, 2016–2019","docAbstract":"Determining whether fresh magma has reached the surface during a volcanic eruption can provide important information for forecasts of future activity, especially in the early stages of an eruption. However, identifying fresh, juvenile pyroclasts in tephra fall deposits can be challenging and inconclusive. We studied the products of explosions at Poás volcano, Costa Rica, in 2016–2019, a period during which the volcano transitioned from a pressurized, hydrothermally sealed state to an open conduit with increased degassing to the atmosphere. The activity consisted of semi-continuous explosions producing <500-m-high plumes, with the exception of explosions on April 14 and 22, 2017, that produced 4-km-high plumes. We analyzed the grain size distribution, componentry, and particle density of the products of twenty explosions, and collected groundmass glass composition on juvenile particles for three of them. Our work demonstrates varying degrees of magma involvement with the hydrothermal system through time, with juvenile material representing a wide range of abundance (~10–70 vol.%) in deposits of individual explosions. Before early April 2017, we infer that small phreatomagmatic explosions were triggered by contact between magmatic fluids and/or magma and the hydrothermal system, based on the presence of abundant hydrothermal fragments and minor juvenile magma. Concurrent with decreasing hydrothermal component in the deposits, explosions in April–May 2017 eroded the walls of the shallow plumbing system, evidenced by an increase in wall-rock lithics in the deposits. These changes coincided with drying of the crater lake, leading to several magmatic explosions in April-September 2017, whose juvenile-rich deposits are consistent with primary fragmentation of fresh magma in the conduit. The eruptive activity changed after this magmatic phase, and in 2019, small explosions mostly recycled the heterogeneous deposits of previous events, producing fine material with high proportions of recycled particles. All explosions from 2016–2019 remobilized already-emplaced magma from the 1953–1955 eruptive period, although distinct glass compositions between explosions suggest difference in crystallization or they tapped different portions of this magma body. Our work sheds light on the eruption dynamics and shallow plumbing system of this persistently active volcano and provides a case study for understanding the variable efficiency of phreatomagmatic fragmentation.","language":"English","publisher":"Springer Nature","doi":"10.1007/s00445-025-01820-5","usgsCitation":"Cascante, M., Giachetti, T., Wright, H.M., Van Eaton, A.R., and Avard, G., 2025, Characteristics of volcanic ash reveal changes in fragmentation and eruption dynamics at Poás volcano, Costa Rica, 2016–2019: Bulletin of Volcanology, v. 87, 36, 24 p., https://doi.org/10.1007/s00445-025-01820-5.","productDescription":"36, 24 p.","ipdsId":"IP-164818","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488131,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-025-01820-5","text":"Publisher Index Page"},{"id":485455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Costa Rica","otherGeospatial":"Poás volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.27139914148874,\n 10.25040774483874\n ],\n [\n -84.27139914148874,\n 10.196657085474186\n ],\n [\n -84.19880426467607,\n 10.196657085474186\n ],\n [\n -84.19880426467607,\n 10.25040774483874\n ],\n [\n -84.27139914148874,\n 10.25040774483874\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-04-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Cascante, Monserrat","contributorId":354536,"corporation":false,"usgs":false,"family":"Cascante","given":"Monserrat","affiliations":[{"id":84637,"text":"University of Oregon, OVSICORI-UNA","active":true,"usgs":false}],"preferred":false,"id":935823,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giachetti, Thomas 0000-0003-1360-6768","orcid":"https://orcid.org/0000-0003-1360-6768","contributorId":287591,"corporation":false,"usgs":false,"family":"Giachetti","given":"Thomas","email":"","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":935824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Heather M. 0000-0001-9013-507X hwright@usgs.gov","orcid":"https://orcid.org/0000-0001-9013-507X","contributorId":3949,"corporation":false,"usgs":true,"family":"Wright","given":"Heather","email":"hwright@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":935825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":935826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Avard, Geoffroy","contributorId":173679,"corporation":false,"usgs":false,"family":"Avard","given":"Geoffroy","email":"","affiliations":[{"id":27271,"text":"Observatorio Volcanológico y Sismológico de Costa Rica, Universidad Nacional, Heredia, Costa Rica","active":true,"usgs":false}],"preferred":false,"id":935827,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268481,"text":"70268481 - 2025 - A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities","interactions":[],"lastModifiedDate":"2025-06-27T15:13:12.47879","indexId":"70268481","displayToPublicDate":"2025-04-24T08:09:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities","docAbstract":"

As wildfires increasingly affect water-supply watersheds, the demand for models to predict water-quality responses is increasing. This work reviews and synthesizes existing post-wildfire applications of water-quality models in the context of geographic and ecohydrological distribution, hydrologic and water-quality response process representation, model parameterization, model and input data scales, model calibration data availability, as well as calibration and performance evaluation approaches. Emphasis is placed on models that simulate water-quality output, rather than sediment and erosional response as the primary focus. Here, identified gaps and opportunities to advance the post-wildfire application of water-quality models include: 1. applying models in under-represented geographic and ecohydrologic regions, 2. simulating multiple streamflow generation mechanisms, including groundwater, with an emphasis on shifting dominant flow pathways as the landscape recovers following wildfire, 3. adding studies that include the simulation of metals, 4. incorporating more biogeochemical and in-stream processes to model applications, 5. applying finer spatial and temporal resolution of precipitation data input as well as finer spatial resolution hydrologic response units, 6. implementing fully distributed grid or element models or finer resolution response units to capture burn severity heterogeneity, 7. collecting enhanced water-quality data for model calibration and validation, 8. conducting model-intercomparison studies, and 9. developing model parameter value guidance in post-wildfire applications. These identified gaps and opportunities may assist users in deciding on key processes and approaches to consider in modeling post-wildfire water-quality conditions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.179435","usgsCitation":"Shephard, Z.M., Partridge, T.F., Murphy, S.F., Walvoord, M.A., and Ebel, B., 2025, A review of post-wildfire adaptations of surface-water-quality models: Synthesis, gaps, and opportunities: Science of the Total Environment, v. 979, 179435, 15 p., https://doi.org/10.1016/j.scitotenv.2025.179435.","productDescription":"179435, 15 p.","ipdsId":"IP-165381","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":491530,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"979","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Shephard, Zachary M. 0000-0003-2994-3355","orcid":"https://orcid.org/0000-0003-2994-3355","contributorId":222581,"corporation":false,"usgs":true,"family":"Shephard","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941495,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Partridge, Trevor Fuess 0000-0003-1589-4783","orcid":"https://orcid.org/0000-0003-1589-4783","contributorId":302668,"corporation":false,"usgs":true,"family":"Partridge","given":"Trevor","email":"","middleInitial":"Fuess","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":941496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":941497,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walvoord, Michelle A. 0000-0003-4269-8366","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":211843,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":941498,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebel, Brian A. 0000-0002-5413-3963","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":211845,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":941499,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266130,"text":"70266130 - 2025 - HarvestStat Africa – Harmonized subnational crop statistics for sub-Saharan Africa","interactions":[],"lastModifiedDate":"2025-04-30T14:55:18.955047","indexId":"70266130","displayToPublicDate":"2025-04-24T07:42:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12552,"text":"Scientific Data - Nature","active":true,"publicationSubtype":{"id":10}},"title":"HarvestStat Africa – Harmonized subnational crop statistics for sub-Saharan Africa","docAbstract":"Sub-Saharan Africa (SSA) faces severe agricultural data scarcity amidst high food insecurity and a large agricultural yield gap, making crop production data crucial for understanding and enhancing food systems. To address this gap, HarvestStat Africa presents the largest compilation of open-access subnational crop statistics and time-series across SSA. Based on agricultural statistics collated by USAID’s Famine Early Warning Systems Network, the subnational crop statistics are standardized and calibrated across changing administrative units to produce consistent and continuous time-series. The dataset includes 546,605 records, primarily spanning from 1980 to 2022, detailing crop production, harvested areas, and yields for 33 countries and 90 crop types, including key cereals in SSA such as wheat, maize, rice, sorghum, barley, millet, and fonio. This new dataset enhances our understanding of how climate variability and change influence agricultural production, supports subnational food system analysis, and aids in operational yield forecasting. As an open-source resource, it sets an important precedent for sharing subnational crop statistics to inform decision-making and modeling efforts.","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-025-05001-z","usgsCitation":"Lee, D., Anderson, W., Chen, X., Davenport, F., Shukla, S., Sahajpal, R., Budde, M., Rowland, J., Verdin, J., You, L., Ahouangbenon, M., Frankel Davis, K., Kebede, E., Ehrmann, S., Justice, C., and Meyer, C., 2025, HarvestStat Africa – Harmonized subnational crop statistics for sub-Saharan Africa: Scientific Data - Nature, v. 12, 690, 13 p., https://doi.org/10.1038/s41597-025-05001-z.","productDescription":"690, 13 p.","ipdsId":"IP-171185","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":487839,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-025-05001-z","text":"Publisher Index 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0000-0001-5438-903X","orcid":"https://orcid.org/0000-0001-5438-903X","contributorId":292417,"corporation":false,"usgs":false,"family":"Lee","given":"Donghoon","email":"","affiliations":[{"id":62899,"text":"Climate Hazards Center, University of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":934708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Weston","contributorId":353902,"corporation":false,"usgs":false,"family":"Anderson","given":"Weston","affiliations":[{"id":84523,"text":"NASA Goddard Space Flight Center, Greenbelt, Maryland, USA","active":true,"usgs":false}],"preferred":false,"id":934709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Xuan","contributorId":204821,"corporation":false,"usgs":false,"family":"Chen","given":"Xuan","email":"","affiliations":[{"id":36987,"text":"Louisiana State University, College of Coast and 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Carsten","contributorId":193124,"corporation":false,"usgs":false,"family":"Meyer","given":"Carsten","email":"","affiliations":[],"preferred":false,"id":934723,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70266022,"text":"ofr20211030T - 2025 - System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor","interactions":[{"subject":{"id":70266022,"text":"ofr20211030T - 2025 - System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor","indexId":"ofr20211030T","publicationYear":"2025","noYear":false,"chapter":"T","displayTitle":"System Characterization Report on Resourcesat-2A Linear Imaging Self Scanning-3 Sensor","title":"System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2025-04-24T14:11:03.291909","indexId":"ofr20211030T","displayToPublicDate":"2025-04-23T12:23:04","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1030","chapter":"T","displayTitle":"System Characterization Report on Resourcesat-2A Linear Imaging Self Scanning-3 Sensor","title":"System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor","docAbstract":"

Executive Summary 

This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-3 sensor and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence since 2021. These reports present and detail the methodology and procedures for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.

Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 for continuity of data and improved temporal resolution. The Resourcesat-2 platform (which includes Resourcesat-2A) is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the Linear Imaging Self Scanning-3 and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/.

The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances.

To summarize the results, we have determined that this sensor provides an interior geometric performance with mean offsets in the range of 1.75 meters (m; 0.06 pixel) to 6.83 m (0.23 pixel) in easting and −1.83 m (−0.06 pixel) to 1.81 m (0.06 pixel) in northing in band-to-band registration and a root mean square error in the range of 3.81 m (0.13 pixel) to 8.19 m (0.27 pixel) in easting and 2.21 m (0.09 pixel) to 4.72 m (0.16 pixel) in northing.

We have measured an exterior geometric error offset in the range of −21.29 to 6.88 m in easting and −7.35 to −2.63 m in northing, and the root mean square error is in the range of 7.19 to 21.43 m in easting and 3.64 to 8.19 m in northing in comparison to the Landsat 8 Operational Land Imager.

The measured radiometric performance was in the range of −0.002 to 0.031 in offset and 0.701 to 0.940 in slope, and the spatial performance was in the range of 1.204 to 1.265 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.251 to 0.277.

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Director, Earth Resources Observation and Science Center
U.S. Geological Survey
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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-04-23","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Park, Seonkyung 0000-0003-3203-1998","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":223182,"corporation":false,"usgs":true,"family":"Park","given":"Seonkyung","email":"","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":934353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shrestha, Mahesh 0000-0002-8368-6399 mshrestha@contractor.usgs.gov","orcid":"https://orcid.org/0000-0002-8368-6399","contributorId":259303,"corporation":false,"usgs":false,"family":"Shrestha","given":"Mahesh","email":"mshrestha@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":934354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":934355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sampath, Aparajithan 0000-0002-6922-4913 asampath@usgs.gov","orcid":"https://orcid.org/0000-0002-6922-4913","contributorId":3622,"corporation":false,"usgs":true,"family":"Sampath","given":"Aparajithan","email":"asampath@usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":934356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clauson, Jeffrey 0000-0003-3406-4988","orcid":"https://orcid.org/0000-0003-3406-4988","contributorId":352867,"corporation":false,"usgs":false,"family":"Clauson","given":"Jeffrey","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":934357,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70274641,"text":"70274641 - 2025 - Pluvial and potential compound flooding in a coupled coastal modeling framework: New York City during post-tropical Cyclone Ida (2021)","interactions":[],"lastModifiedDate":"2026-04-02T16:06:57.228299","indexId":"70274641","displayToPublicDate":"2025-04-23T11:03:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Pluvial and potential compound flooding in a coupled coastal modeling framework: New York City during post-tropical Cyclone Ida (2021)","docAbstract":"

Many coastal urban areas are prone to extreme pluvial flooding due to limitations in stormwater system capacity, with the additional potential for flooding compounded by storm surge, tides, and waves. Understanding and simulating these processes can improve prediction and flood risk management. Here, we adapt the Coupled Ocean–Atmosphere–Wave–Sediment Transport modeling framework (COAWST) to simulate pluvial flooding from post-tropical Cyclone Ida (2021) in the Jamaica Bay watershed of New York City (NYC). We modify the model to capture the volumetric effects of rainfall and parameterize soil infiltration and a stormwater conveyance system as the drainage rate. We generate a spatially continuous flood map of Ida with a root-mean-square error (RMSE) of 20 cm when compared to high-water marks, useful for understanding Ida's impacts and subsequent mitigation planning. Results show that over 23 km2 and 4621 buildings were flooded deeper than 0.3 m during Ida. Sensitivity analyses are used to study the broader risk from events like Ida (pluvial flooding) as well as potential compound (pluvial–coastal) flooding. Spatial shifting of the storm track within a typical 12 h forecast uncertainty reveals a worst-case scenario that increases this flooded area to 62 km2 (5907 buildings). Shifting Ida's rainfall to coincide with high tide increases this flooded area by 1 km2, a relatively small change due to the lack of significant storm surge. The application of COAWST to this storm event addresses a broader goal of developing the capability to model compound pluvial–coastal flooding by simultaneously representing coastal storm processes such as rain, tide, waves, erosion, and atmosphere–wave–ocean interactions. The sensitivity analysis results underscore the need for detailed flood risk assessments, showing that Ida, already NYC's worst rain event, could have been even more devastating with slight shifts in the storm track.

","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-29-2043-2025","usgsCitation":"Kasaei, S., Orton, P.M., Ralston, D.K., and Warner, J., 2025, Pluvial and potential compound flooding in a coupled coastal modeling framework: New York City during post-tropical Cyclone Ida (2021): Hydrology and Earth System Sciences, v. 29, no. 8, p. 2043-2058, https://doi.org/10.5194/hess-29-2043-2025.","productDescription":"16 p.","startPage":"2043","endPage":"2058","ipdsId":"IP-168323","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":502086,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-29-2043-2025","text":"Publisher Index Page"},{"id":502009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","city":"New York City","otherGeospatial":"Jamaica Bay watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.01902277171598,\n 40.81541595710692\n ],\n [\n -74.01902277171598,\n 40.5619948325492\n ],\n [\n -73.61280152477734,\n 40.5619948325492\n ],\n [\n -73.61280152477734,\n 40.81541595710692\n ],\n [\n -74.01902277171598,\n 40.81541595710692\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kasaei, Shima","contributorId":369142,"corporation":false,"usgs":false,"family":"Kasaei","given":"Shima","affiliations":[{"id":28243,"text":"Stevens Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":958528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orton, Phillip M.","contributorId":369143,"corporation":false,"usgs":false,"family":"Orton","given":"Phillip","middleInitial":"M.","affiliations":[{"id":28243,"text":"Stevens Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":958529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralston, David K.","contributorId":369144,"corporation":false,"usgs":false,"family":"Ralston","given":"David","middleInitial":"K.","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":958530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":958531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266105,"text":"70266105 - 2025 - The relationship between body condition, body composition, and growth in amphibians","interactions":[],"lastModifiedDate":"2025-04-25T15:39:07.679497","indexId":"70266105","displayToPublicDate":"2025-04-23T10:36:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The relationship between body condition, body composition, and growth in amphibians","docAbstract":"

Body condition of animals is often assumed to reflect advantages in survival or reproduction, but body condition indices may not reflect body composition, or condition may be unrelated to fitness-associated traits. The relationship between body condition indices and composition has rarely been quantified in amphibians, and body condition has not previously been related to growth in adult amphibians. We used laboratory (quantitative magnetic resonance) and field methods to evaluate the relationship between body composition and the four common body condition indices for wildlife studies (body mass index, Fulton’s index, scaled mass index, and residual index) in two frog and one salamander species in Montana, USA. We then assessed the relationship between body condition and summertime somatic growth during a 3-yr mark-recapture study of one of our study species (Columbia spotted frogs, Rana luteiventris). Correlation of body condition indices with fat and lean mass differed across species, sexes, and whether components were represented as percentages or were scaled based on size. Scaled mass index, residual index, and Fulton’s index were most often well correlated (r > 0.6) with scaled body components, but Fulton’s index was strongly correlated with body length. Scaled mass and residual indices predicted scaled fat relatively well and were uncorrelated with body length. Heavier condition predicted higher growth rates of Columbia spotted frogs, regardless of the index used. Frogs of heavy body condition (90th percentile residual index) grew 0.04 and 0.05 mm/day greater than frogs of light condition (10th percentile) for average length males and females, respectively. Frogs of short body length (10th percentile) grew 0.11 and 0.19 mm/day more than long (90th percentile) males and females, respectively. By examining the relationship between body condition indices and body composition and revealing a link between condition and future growth, our results provide an empirical basis for choosing the most appropriate condition index, as well as a potential link to fitness-related traits.

","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0320954","usgsCitation":"Hinderer, R., Hossack, B.R., and Eby, L., 2025, The relationship between body condition, body composition, and growth in amphibians: PLoS ONE, v. 20, no. 4, e0320954, 15 p., https://doi.org/10.1371/journal.pone.0320954.","productDescription":"e0320954, 15 p.","ipdsId":"IP-170065","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":487777,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0320954","text":"Publisher Index Page"},{"id":485063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Hinderer, Ross K.","contributorId":353872,"corporation":false,"usgs":false,"family":"Hinderer","given":"Ross K.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":934603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":934604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eby, Lisa A.","contributorId":353873,"corporation":false,"usgs":false,"family":"Eby","given":"Lisa A.","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":934605,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266082,"text":"70266082 - 2025 - Additional common milkweed would help Canada meet its share of the trinational eastern migratory monarch butterfly recovery target","interactions":[],"lastModifiedDate":"2025-04-24T14:58:37.413649","indexId":"70266082","displayToPublicDate":"2025-04-23T09:52:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16690,"text":"Facets","active":true,"publicationSubtype":{"id":10}},"title":"Additional common milkweed would help Canada meet its share of the trinational eastern migratory monarch butterfly recovery target","docAbstract":"

The eastern migratory monarch butterfly (Danaus plexippus) population has declined by ∼84% between 1993 and 2024. Population recovery in the Midwestern United States is limited by the availability of the monarch's main host plant for egg laying—common milkweed (Asclepias syriaca). The extent to which common milkweed availability is limiting in other breeding regions is unknown. Our objective was to determine whether Canada has enough common milkweed to support its share of the trinational eastern migratory monarch population recovery target, given ∼29 stems of common milkweed are needed to contribute one adult monarch into the fall migratory population. To meet this objective, we estimated the number of common milkweed stems in Canada using published common milkweed availability estimates by land cover type. We also estimated the size of the Canadian monarch population if the recovery target was achieved using published estimates of wintering monarch density in Mexico, fall migration survival rates, and the relative proportion of monarchs entering fall migration from Canada. We estimate that Canada currently has 484 million common milkweed stems (range: 111 million–1 billion stems) and increasing this amount by 1.61 times (i.e., by ∼295 million stems), or equivalently, by 61%, would support the recovery target.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/facets-2024-0063","usgsCitation":"Mitchell, G.W., Kirby, P., Duffe, J., Fahrig, L., Girard, J., Johnston, M., Larrivee, M., Martin, A., Momeni-Dehaghi, I., Pasher, J., Rezek, E., Shapiro, E., Thogmartin, W.E., and Pouliot, D., 2025, Additional common milkweed would help Canada meet its share of the trinational eastern migratory monarch butterfly recovery target: Facets, v. 10, 14 p., https://doi.org/10.1139/facets-2024-0063.","productDescription":"14 p.","ipdsId":"IP-163947","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":487900,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/facets-2024-0063","text":"Publisher Index Page"},{"id":484979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Mitchell, Greg W.","contributorId":317902,"corporation":false,"usgs":false,"family":"Mitchell","given":"Greg","email":"","middleInitial":"W.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":934532,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirby, Patrick","contributorId":353821,"corporation":false,"usgs":false,"family":"Kirby","given":"Patrick","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":934533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duffe, Jason","contributorId":353824,"corporation":false,"usgs":false,"family":"Duffe","given":"Jason","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":934534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fahrig, Lenore","contributorId":340627,"corporation":false,"usgs":false,"family":"Fahrig","given":"Lenore","email":"","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":934535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Girard, Judith","contributorId":353827,"corporation":false,"usgs":false,"family":"Girard","given":"Judith","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":934536,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnston, Mark K.","contributorId":353830,"corporation":false,"usgs":false,"family":"Johnston","given":"Mark K.","affiliations":[{"id":84513,"text":"Field Museum of Natural History, Chicago","active":true,"usgs":false}],"preferred":false,"id":934537,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Larrivee, Maxim","contributorId":353831,"corporation":false,"usgs":false,"family":"Larrivee","given":"Maxim","affiliations":[{"id":84516,"text":"Insectarium de Montréal","active":true,"usgs":false}],"preferred":false,"id":934538,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martin, Amanda E.","contributorId":353832,"corporation":false,"usgs":false,"family":"Martin","given":"Amanda E.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":934539,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Momeni-Dehaghi, Iman","contributorId":353833,"corporation":false,"usgs":false,"family":"Momeni-Dehaghi","given":"Iman","affiliations":[{"id":84517,"text":"Carlton University","active":true,"usgs":false}],"preferred":false,"id":934540,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pasher, Jon","contributorId":353834,"corporation":false,"usgs":false,"family":"Pasher","given":"Jon","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":934541,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rezek, Elizabeth","contributorId":353835,"corporation":false,"usgs":false,"family":"Rezek","given":"Elizabeth","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":934542,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Shapiro, Elisabeth","contributorId":353836,"corporation":false,"usgs":false,"family":"Shapiro","given":"Elisabeth","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":934543,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":934544,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pouliot, Darren","contributorId":330656,"corporation":false,"usgs":false,"family":"Pouliot","given":"Darren","email":"","affiliations":[{"id":78952,"text":"CCRS, Canada","active":true,"usgs":false}],"preferred":false,"id":934545,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70266396,"text":"70266396 - 2025 - Fisheries dependent and independent data inform a capture technique for an emerging invasive fish species in the mainstem Mississippi River; Black Carp Mylopharyngodon piceus","interactions":[],"lastModifiedDate":"2025-05-06T14:11:54.318665","indexId":"70266396","displayToPublicDate":"2025-04-23T09:02:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Fisheries dependent and independent data inform a capture technique for an emerging invasive fish species in the mainstem Mississippi River; Black Carp Mylopharyngodon piceus","title":"Fisheries dependent and independent data inform a capture technique for an emerging invasive fish species in the mainstem Mississippi River; Black Carp Mylopharyngodon piceus","docAbstract":"

Black Carp Mylopharyngodon piceus were imported into the United States in the 1970s and 1980s for use in aquaculture; escape occurred and reported wild captures increased. Lacking species-specific capture methods, we assessed fisheries dependent incidental Black Carp catches for a common method, hoop nets, by kernel density analysis to identify an area of increased reporting and compare frequency of reports for water temperature, river stage, and capture date to identify seasonality. We then used fisheries independent effort to identify co-occurrence of species via non-metric multi-dimensional scaling and fit Black Carp catch and environmental covariates by generalized linear models to assess site-specific environmental covariates facilitating capture. The best approximating distribution was refitted for predictions and inference. The greatest density of fisheries dependent hoop net captures (39 %) was near the confluence of the Missouri and Mississippi rivers, primarily from July-September. Captures were characterized by median water temperature 26.7°C, river stage 5.02 m, and 223 day-of-year (DOY; mid-August). Ordination of fisheries independent catch identified similarity in environmental covariates of Smallmouth Buffalo Ictiobus bubalus and Black Carp. The probability of capturing ≥ 1 Black Carp increased with DOY, decreased with increasing current velocity, and increased with depth. Most captures occurred in outside bends (87 %) or side channels (12 %). Probability of Black Carp capture was low but increased in summer and early fall when stage is lower, facilitating reduced current velocity and access to deeper areas. Results may be validated beyond this river segment to test if site-specific hydrology or habitat characteristics facilitated increased commercial and biologist capture and for replication.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2025.107368","usgsCitation":"Kroboth, P., Colvin, M.E., and Broaddus, C., 2025, Fisheries dependent and independent data inform a capture technique for an emerging invasive fish species in the mainstem Mississippi River; Black Carp Mylopharyngodon piceus: Fisheries Research, v. 285, 107368, 12 p., https://doi.org/10.1016/j.fishres.2025.107368.","productDescription":"107368, 12 p.","ipdsId":"IP-167531","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":487576,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2025.107368","text":"Publisher Index Page"},{"id":485444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Missouri","otherGeospatial":"MIssissippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.22145042868262,\n 38.90746978465282\n ],\n [\n -90.22145042868262,\n 38.666188258783194\n ],\n [\n -90.1030809646113,\n 38.666188258783194\n ],\n [\n -90.1030809646113,\n 38.90746978465282\n ],\n [\n -90.22145042868262,\n 38.90746978465282\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"285","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroboth, Patrick 0000-0002-9447-4818","orcid":"https://orcid.org/0000-0002-9447-4818","contributorId":216578,"corporation":false,"usgs":true,"family":"Kroboth","given":"Patrick","email":"","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":935820,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":935821,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Broaddus, Courtney 0000-0003-3851-3584","orcid":"https://orcid.org/0000-0003-3851-3584","contributorId":354595,"corporation":false,"usgs":true,"family":"Broaddus","given":"Courtney","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":935822,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266309,"text":"70266309 - 2025 - Comparison of lapilli otoliths and pectoral fin rays for estimating age of Northern Pikeminnows","interactions":[],"lastModifiedDate":"2025-05-05T15:32:14.722693","indexId":"70266309","displayToPublicDate":"2025-04-23T08:25:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2900,"text":"Northwest Science","onlineIssn":"2161-9859","printIssn":"0029-344X","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of lapilli otoliths and pectoral fin rays for estimating age of Northern Pikeminnows","docAbstract":"

The Northern Pikeminnow Ptychocheilus oregonensis is a piscivorous cyprinid native to western North America. Information on the best structure for estimating the age of Northern Pikeminnows is a key knowledge gap that may limit inquiries on management efforts. Thus, the objective of this study was to evaluate between-reader precision and concordance between age estimates for lapilli otoliths and pectoral fin rays from Northern Pikeminnows. Age estimates from lapilli otoliths were compared to those from pectoral fin rays of 150 Northern Pikeminnows captured from Lake Cascade, Idaho, in April–May 2022. Exact percent agreement of estimated ages between the readers was higher for fin rays (75.3%) than otoliths (50.0%), with a mean coefficient of variation of 3.5 and 8.7, respectively. Readers also assigned a confidence rating (0–3; higher value reflects higher confidence in age estimate) to each structure. Confidence ratings were higher for fin ray age estimates (mean ± SD; 1.6 ± 0.6) than otolith estimates (1.1 ± 0.7) between readers. A consensus age was estimated for each structure and fish. Agreement between consensus age estimates for otoliths and fin rays was 26.7% with a coefficient of variation of 14.0. Our findings suggest that fin rays were easier to collect, process, and read than otoliths, and resulted in more precise age estimates than otoliths. Results from our study provide guidance on the best structures for estimating the age of Northern Pikeminnows that can be used to inform management efforts.

","language":"English","publisher":"BioOne","doi":"10.3955/046.098.0106","usgsCitation":"Wilson, C., Marciniak, B., Thomas, M., Messner, J., Corsi, M., and Quist, M.C., 2025, Comparison of lapilli otoliths and pectoral fin rays for estimating age of Northern Pikeminnows: Northwest Science, v. 98, no. 1, p. 79-85, https://doi.org/10.3955/046.098.0106.","productDescription":"7 p.","startPage":"79","endPage":"85","ipdsId":"IP-166941","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Lake Cascade","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.15719052395744,\n 44.765077659324646\n ],\n [\n -116.15719052395744,\n 44.472061689535565\n ],\n [\n -116.02527503288141,\n 44.472061689535565\n ],\n [\n -116.02527503288141,\n 44.765077659324646\n ],\n [\n -116.15719052395744,\n 44.765077659324646\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"98","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wilson, Caleb M.","contributorId":354458,"corporation":false,"usgs":false,"family":"Wilson","given":"Caleb M.","affiliations":[],"preferred":false,"id":935724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marciniak, Bryce","contributorId":354376,"corporation":false,"usgs":false,"family":"Marciniak","given":"Bryce","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935524,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Mike","contributorId":354377,"corporation":false,"usgs":false,"family":"Thomas","given":"Mike","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":935525,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Messner, Jordan","contributorId":354378,"corporation":false,"usgs":false,"family":"Messner","given":"Jordan","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":935526,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corsi, Matthew P.","contributorId":171811,"corporation":false,"usgs":false,"family":"Corsi","given":"Matthew P.","affiliations":[],"preferred":false,"id":935527,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":207142,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935528,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266066,"text":"70266066 - 2025 - Integrating climate change, biological invasions, and infectious wildlife diseases","interactions":[],"lastModifiedDate":"2025-08-04T15:37:15.564366","indexId":"70266066","displayToPublicDate":"2025-04-23T08:00:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Integrating climate change, biological invasions, and infectious wildlife diseases","docAbstract":"Climate change is likely to affect infectious diseases that are facilitated by biological invasions, with repercussions for wildlife conservation and zoonotic risks. Current invasion management and policy are underprepared for the future risks associated with such invasion-related wildlife diseases. By considering evidence from bioclimatology, invasion biology, and disease research, we illustrate how climate change is anticipated to affect disease agents (parasites and pathogens), hosts, and vectors across the different stages of invasions. We highlight the opportunity to integrate these disciplines to identify the effects of climate change on invasion related wildlife diseases. In addition, shifting to a proactive stance in implementing management and policy, such as by incorporating climate-change effects either into preventative and mitigation measures for biosecurity or with rapid response protocols to limit disease spread and impacts, could help to combat future ecological, economic, and human health risks stemming from invasion-related wildlife diseases.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/fee.2849","usgsCitation":"Thieltges, D., Conn, D., Cuthbert, R., Dunn, A., Jolma, R., Hopkins, M., Sarabeev, V., Smolders, S., Stepien, C.A., Wegner, K., and Kocovsky, P.M., 2025, Integrating climate change, biological invasions, and infectious wildlife diseases: Frontiers in Ecology and the Environment, v. 23, no. 6, e2849, 8 p., https://doi.org/10.1002/fee.2849.","productDescription":"e2849, 8 p.","ipdsId":"IP-160601","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":484980,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":487901,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.2849","text":"Publisher Index Page"}],"volume":"23","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Thieltges, David W.","contributorId":353810,"corporation":false,"usgs":false,"family":"Thieltges","given":"David W.","affiliations":[{"id":84503,"text":"NIOZ Royal Netherlands Institute for Sea Research and Groningen Institute for Evolutionary Life-Sciences, GELIFES, University of Groningen","active":true,"usgs":false}],"preferred":false,"id":934494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, David B.","contributorId":353811,"corporation":false,"usgs":false,"family":"Conn","given":"David B.","affiliations":[{"id":84506,"text":"Berry College","active":true,"usgs":false}],"preferred":false,"id":934495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cuthbert, Ross N.","contributorId":353812,"corporation":false,"usgs":false,"family":"Cuthbert","given":"Ross N.","affiliations":[{"id":84507,"text":"Institute for Global Food Security, School of Biological Sciences, Queen’s University Belfast","active":true,"usgs":false}],"preferred":false,"id":934496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Alison M.","contributorId":353813,"corporation":false,"usgs":false,"family":"Dunn","given":"Alison M.","affiliations":[{"id":84508,"text":"Faculty of Biological Sciences, University of Leeds","active":true,"usgs":false}],"preferred":false,"id":934497,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jolma, Rosa","contributorId":353814,"corporation":false,"usgs":false,"family":"Jolma","given":"Rosa","affiliations":[{"id":84509,"text":"Department of Coastal Systems, NIOZ Royal Netherlands Institute for Sea Research and Department of Population Health Sciences, Veterinary Medicine, Utrecht University","active":true,"usgs":false}],"preferred":false,"id":934498,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hopkins, M. Camille 0000-0003-1465-6038","orcid":"https://orcid.org/0000-0003-1465-6038","contributorId":219531,"corporation":false,"usgs":true,"family":"Hopkins","given":"M. Camille","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":934499,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sarabeev, Volodimir","contributorId":353815,"corporation":false,"usgs":false,"family":"Sarabeev","given":"Volodimir","affiliations":[{"id":84510,"text":"Department of Biology, Zaporizhzhia National University and Institute of Parasitology, Slovak Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":934500,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Smolders, Sander","contributorId":353816,"corporation":false,"usgs":false,"family":"Smolders","given":"Sander","affiliations":[{"id":84511,"text":"Institute of Parasitology, Slovak Academy of Sciences, Hlinkova","active":true,"usgs":false}],"preferred":false,"id":934501,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stepien, Carol A.","contributorId":329430,"corporation":false,"usgs":false,"family":"Stepien","given":"Carol","email":"","middleInitial":"A.","affiliations":[{"id":27877,"text":"National Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":934502,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wegner, K. Mathias","contributorId":353817,"corporation":false,"usgs":false,"family":"Wegner","given":"K. Mathias","affiliations":[{"id":84512,"text":"Alfred Wegener Institute - Helmholtz Centre for Polar and Marine Research","active":true,"usgs":false}],"preferred":false,"id":934503,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":934504,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70265982,"text":"sir20255029 - 2025 - Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington","interactions":[{"subject":{"id":70257569,"text":"70257569 - 2024 - Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington","indexId":"70257569","publicationYear":"2024","noYear":false,"title":"Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington"},"predicate":"SUPERSEDED_BY","object":{"id":70265982,"text":"sir20255029 - 2025 - Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington","indexId":"sir20255029","publicationYear":"2025","noYear":false,"title":"Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington"},"id":1}],"lastModifiedDate":"2025-08-07T21:05:21.759632","indexId":"sir20255029","displayToPublicDate":"2025-04-23T07:58:02","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":"2025-5029","displayTitle":"Spatial Stream Network Modeling of Water Temperature within the White River Basin, Mount Rainier National Park, Washington","title":"Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington","docAbstract":"

Water temperature is a primary control on the occurrence and distribution of fish and other ectothermic aquatic species. In the Pacific Northwest, cold-water species such as Pacific salmon (Oncorhynchus spp.) and bull trout (Salvelinus confluentus) have specific temperature requirements during different life stages that must be met to ensure the viability of their populations. Rivers draining Mount Rainier in western Washington, including the White River along its northern flank, support a number of cold-water fish populations, but the spatial distribution of water temperatures, particularly during late-summer baseflow during August and September, and the climatic, hydrologic, and physical processes regulating it are not well constrained. Spatial stream network (SSN) models, which are generalized linear models that incorporate streamwise spatial autocovariance structures, were fit to mean and 7-day average daily maximum water temperature for August and September for the White River Basin. The SSN models were calibrated using water temperature measurements collected in 2010 through 2020. The extent of the models included the White River and its tributaries upstream from its confluence with Silver Creek in Mount Rainier National Park, Washington. SSN models incorporated covariates hypothesized to represent the climatic, hydrologic, and physical processes that influence water temperature. SSN models were fit to the measured data and compared to generalized linear models that lacked spatial autocovariance structures. Statistically significant covariates within the best-fit models included the proportion of ice cover and forest cover within the basin, mean August air temperature, the proportion of consolidated geologic units, and snow-water equivalent. Statistical models that included spatial autocovariance structures had better predictive performance than those that did not. Additionally, models of mean August and September water temperature had better predictive performance than those of 7-day average daily maximum temperature in August and September. Predictions of the spatial distribution of water temperature were similar between August and September with a general warming in the downstream part of the mainstem White River compared to cooler water temperatures in the high-elevation headwater streams. The proportion of ice cover emerged as an inversely related significant covariate to both mean August and September water temperature because streams that receive glacial meltwater are colder than non-glaciated streams. Water temperatures of the upper White River increased downstream and are attributed to warming of water temperature from accumulated solar radiation and inflow of non-glaciated tributaries. Estimated water temperatures for the upper White River model are 3–4 degrees Celsius (°C) warmer for tributaries, but 1–2 °C cooler for the mainstem compared to the regional-scale model. Differences between the upper White River SSN model and the regional-scale NorWeST model are attributed to the fact that the upper White River SSN included water temperature observations specific to the upper White River, whereas water temperature observations from lower elevation streams and downstream from the Mount Rainer National Park boundary were used in the regional scale model.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255029","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Gendaszek, A.S., Leach, A.C., and Jaeger, K.L., 2025, Spatial stream network modeling of water temperature within the White River Basin, Mount Rainier National Park, Washington (ver. 1.1, May 2025): U.S. Geological Survey\nScientific Investigations Report 2025–5029, 17 p., https://doi.org/10.3133/sir20255029. [Supersedes preprint https://doi.org/10.31223/X5712P.]","productDescription":"Report: vi, 17 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-168299","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":484931,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/6542802dd34ee4b6e05bd2cb","text":"USGS data release","description":"USGS data release","linkHelpText":"Stream Temperature Models of White River Watershed, Mount Rainier National Park, Washington"},{"id":484872,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5029/sir20255029.XML"},{"id":484871,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5029/images"},{"id":484870,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255029/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5029"},{"id":484869,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5029/sir20255029.pdf","text":"Report","size":"4.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5029"},{"id":484868,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5029/coverthb2.jpg"},{"id":486241,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2025/5029/versionHistory.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":493767,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118576.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier National Park, upper White River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.75,\n 47\n ],\n [\n -121.75,\n 46.8333\n ],\n [\n -121.5,\n 46.8333\n ],\n [\n -121.5,\n 47\n ],\n [\n -121.75,\n 47\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: April 23.2025; Version 1.1: May 20, 2025","contact":"

Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402

","tableOfContents":"","publishedDate":"2025-04-23","revisedDate":"2025-05-20","noUsgsAuthors":false,"publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Gendaszek, Andrew S. 0000-0002-2373-8986 agendasz@usgs.gov","orcid":"https://orcid.org/0000-0002-2373-8986","contributorId":3509,"corporation":false,"usgs":true,"family":"Gendaszek","given":"Andrew","email":"agendasz@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leach, Anya C. 0000-0001-7828-8858","orcid":"https://orcid.org/0000-0001-7828-8858","contributorId":344667,"corporation":false,"usgs":false,"family":"Leach","given":"Anya C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":934242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaeger, Kristin L. 0000-0002-1209-8506 kjaeger@usgs.gov","orcid":"https://orcid.org/0000-0002-1209-8506","contributorId":199335,"corporation":false,"usgs":true,"family":"Jaeger","given":"Kristin","email":"kjaeger@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":934243,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266185,"text":"70266185 - 2025 - In situ Re-Os geochronology of Re-rich Palaeogene molybdenite by LA-ICP-MS/MS","interactions":[],"lastModifiedDate":"2025-05-12T15:48:34.625109","indexId":"70266185","displayToPublicDate":"2025-04-23T07:53:37","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21215,"text":"Journal of Analytical Atomic Spectrometry (JAAS)","active":true,"publicationSubtype":{"id":10}},"title":"In situ Re-Os geochronology of Re-rich Palaeogene molybdenite by LA-ICP-MS/MS","docAbstract":"

In situ Re–Os geochronology by LA-ICP-MS/MS was previously demonstrated by reacting Os with CH4 or N2O reaction gasses. However, for both reactions, a minor proportion of the Re parent isotope also reacts, potentially leading to significant isobaric interferences of 187Re on 187Os, especially for young samples with little radiogenic in-growth. Here we present an interlaboratory comparison and compare three reaction gas mixtures (CH4 + H2 + He, N2O and N2O + He) with the aim to robustly date Palaeogene (66–23 Ma) molybdenite from the Bingham Canyon and Henderson deposits. CH4 mixed with H2 gas gives the highest sensitivity, while N2O and He gas buffer Re reaction. On balance, the analytical method involving N2O + He reaction gas is most suitable for dating Palaeogene molybdenite, resulting in age precision of 2.6% for Bingham and 5.8% for Henderson. For older, >1 Ga molybdenite, CH4 + H2 + He may give comparatively better age precision.

","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/d5ja00030k","usgsCitation":"Glorie, S., Thompson, J.M., Gilbert, S., and Souders, A., 2025, In situ Re-Os geochronology of Re-rich Palaeogene molybdenite by LA-ICP-MS/MS: Journal of Analytical Atomic Spectrometry (JAAS), v. 40, https://doi.org/10.1039/d5ja00030k.","productDescription":"9 p.","startPage":"1402","ipdsId":"IP-177226","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488475,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1039/d5ja00030k","text":"Publisher Index Page"},{"id":485135,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.9841816212424,\n 41.972113414060146\n ],\n [\n -113.9841816212424,\n 39.36516405224748\n ],\n [\n -101.93106736461608,\n 39.36516405224748\n ],\n [\n -102.12154139795634,\n 41.02494001982191\n ],\n [\n -111.15642398488703,\n 41.04965240752148\n ],\n [\n -111.00013686012169,\n 42.00902777965396\n ],\n [\n -113.9841816212424,\n 41.972113414060146\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","edition":"1392","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glorie, Stijm 0000-0002-3107-9028","orcid":"https://orcid.org/0000-0002-3107-9028","contributorId":353959,"corporation":false,"usgs":false,"family":"Glorie","given":"Stijm","affiliations":[{"id":36897,"text":"University of Adelaide","active":true,"usgs":false}],"preferred":false,"id":934831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thompson, Jay M. 0000-0003-3322-0870","orcid":"https://orcid.org/0000-0003-3322-0870","contributorId":329664,"corporation":false,"usgs":true,"family":"Thompson","given":"Jay","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":934832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilbert, Sarah E. 0000-0003-3259-7983","orcid":"https://orcid.org/0000-0003-3259-7983","contributorId":353960,"corporation":false,"usgs":false,"family":"Gilbert","given":"Sarah E.","affiliations":[{"id":36897,"text":"University of Adelaide","active":true,"usgs":false}],"preferred":false,"id":934833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Souders, Amanda 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":296423,"corporation":false,"usgs":true,"family":"Souders","given":"Amanda","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":934834,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70266192,"text":"70266192 - 2025 - National population exposure and evacuation potential in the United States to earthquake-generated tsunami threats","interactions":[],"lastModifiedDate":"2025-07-31T13:40:24.615057","indexId":"70266192","displayToPublicDate":"2025-04-22T10:44:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"National population exposure and evacuation potential in the United States to earthquake-generated tsunami threats","docAbstract":"

Previous efforts to characterize tsunami threats to people have focused primarily on individual scenarios in specific areas but have not recognized multiple scenarios across an entire country. This study addresses this gap by quantifying population exposure and evacuation potential in the United States to 102 earthquake-related, tsunami-hazard zones, including 92 local scenarios, 8 distant scenarios, and 2 probabilistic products. Geospatial path-distance modeling quantified evacuation potential and the influence of departure delays. We focused on residents to support other national, multi-hazard risk analyses. Millions of residents are in distant-tsunami zones, and hundreds of thousands of residents are in local-tsunami zones. In 41 scenarios, there is at least one resident that may have insufficient time to evacuate before wave arrival. Tens of thousands of residents may have insufficient time to evacuate from local tsunamis that impact the U.S. Pacific Northwest or Puerto Rican coastlines. The largest improvements in evacuation potential may come from reducing departure delays in some areas but may involve vertical-evacuation structures or changing land use in other areas.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2025.105511","usgsCitation":"Wood, N.J., Peters, J., Sheehan, A., and Bausch, D., 2025, National population exposure and evacuation potential in the United States to earthquake-generated tsunami threats: International Journal of Disaster Risk Reduction, v. 123, 105511, 18 p., https://doi.org/10.1016/j.ijdrr.2025.105511.","productDescription":"105511, 18 p.","ipdsId":"IP-176718","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":485209,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","noUsgsAuthors":false,"publicationDate":"2025-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":934864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peters, Jeff 0000-0003-4312-0590 jpeters@usgs.gov","orcid":"https://orcid.org/0000-0003-4312-0590","contributorId":4711,"corporation":false,"usgs":true,"family":"Peters","given":"Jeff","email":"jpeters@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":934865,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sheehan, Anne 0009-0005-0636-6892","orcid":"https://orcid.org/0009-0005-0636-6892","contributorId":358952,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","affiliations":[{"id":30786,"text":"FEMA","active":true,"usgs":false}],"preferred":false,"id":934866,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bausch, Doug","contributorId":195191,"corporation":false,"usgs":false,"family":"Bausch","given":"Doug","email":"","affiliations":[{"id":34169,"text":"Pacific Disaster Center","active":true,"usgs":false}],"preferred":false,"id":934867,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273768,"text":"70273768 - 2025 - Seasonal movements and demographics of the endangered White River Spinedace to inform restoration and translocation","interactions":[],"lastModifiedDate":"2026-01-28T16:54:16.957569","indexId":"70273768","displayToPublicDate":"2025-04-22T09:46:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal movements and demographics of the endangered White River Spinedace to inform restoration and translocation","docAbstract":"

Objective

Translocation is a tool being explored to restart extirpated populations or facilitate new populations of endangered spring-­dependent fish populations. Our objective was to provide information on habitat requirements for endangered White River Spinedace Lepidomeda albivallis during all seasons of the year and the population demographics that are necessary to plan conservation translocations of this species

Methods

We tagged and released White River Spinedace with passive integrated transponders during four twice-a-year events. Fish were subsequently recaptured or detected on six passive antennas placed throughout the Flag Springs Complex, Nevada. We evaluated movement data to understand seasonal habitat use patterns, used a Barker model to estimate monthly survival rates, adjusted counts to account for capture probability and estimate abundance, and applied reverse-time mark–recapture models to estimate recruitment to 70 mm total length.

Results

White River Spinedace were more active but used similar habitats during spawning seasons than during nonspawning seasons. Median life expectancy was about 5 months after tagging, and only 1% of adult White River Spinedace survived 3–4 years posttagging. The estimated population size in the Flag Springs Complex during our sampling period (November 2020 to June 2022) was fewer than a thousand White River Spinedace, and this estimate has been steady or slightly increasing.

Conclusions

Complex spring habitats with water temperatures ranging about 13°C to 21°C that are free from piscivorous fish are appropriate for White River Spinedace. The White River Spinedace population at Flag Springs is small but stable or increasing in size.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/tafafs/vnaf007","usgsCitation":"Burdick, S.M., Harter, J.F., Beckstrand, M., Paul-Wilson, R.K., Hayes, B., Perry, R.W., and Smith, C.D., 2025, Seasonal movements and demographics of the endangered White River Spinedace to inform restoration and translocation: Transactions of the American Fisheries Society, v. 154, no. 3, p. 246-261, https://doi.org/10.1093/tafafs/vnaf007.","productDescription":"16 p.","startPage":"246","endPage":"261","ipdsId":"IP-165644","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":499182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"154","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Burdick, Summer M. 0000-0002-3480-5793 sburdick@usgs.gov","orcid":"https://orcid.org/0000-0002-3480-5793","contributorId":3448,"corporation":false,"usgs":true,"family":"Burdick","given":"Summer","email":"sburdick@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":954695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harter, James F.","contributorId":365736,"corporation":false,"usgs":false,"family":"Harter","given":"James","middleInitial":"F.","affiliations":[{"id":87201,"text":"United States Fish and Wildlife Service, Las Vegas, Nevada","active":true,"usgs":false}],"preferred":false,"id":954696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beckstrand, Mark","contributorId":365737,"corporation":false,"usgs":false,"family":"Beckstrand","given":"Mark","affiliations":[{"id":87202,"text":"Nevada Department of Wildlife, Eli, Nevada","active":true,"usgs":false}],"preferred":false,"id":954697,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paul-Wilson, Rachael Katelyn 0000-0002-8213-1084","orcid":"https://orcid.org/0000-0002-8213-1084","contributorId":298894,"corporation":false,"usgs":true,"family":"Paul-Wilson","given":"Rachael","email":"","middleInitial":"Katelyn","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":954698,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayes, Brian S. 0000-0001-8229-4070","orcid":"https://orcid.org/0000-0001-8229-4070","contributorId":37022,"corporation":false,"usgs":true,"family":"Hayes","given":"Brian S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":954699,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Perry, Russell W. 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":214553,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":954700,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":3111,"corporation":false,"usgs":true,"family":"Smith","given":"Collin","email":"cdsmith@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":954701,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266180,"text":"70266180 - 2025 - Insights from growing Globorotalia truncatulinoides and Globorotalia menardii in the laboratory","interactions":[],"lastModifiedDate":"2025-04-29T14:23:17.274147","indexId":"70266180","displayToPublicDate":"2025-04-22T09:20:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2294,"text":"Journal of Foraminiferal Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Insights from growing Globorotalia truncatulinoides and Globorotalia menardii in the laboratory","title":"Insights from growing Globorotalia truncatulinoides and Globorotalia menardii in the laboratory","docAbstract":"

The vast majority of planktic foraminiferal culture studies have been carried out on spinose species of foraminifera, with relatively few studies on non-spinose species. We conducted a pilot study to test whether live specimens of the non-spinose planktic foraminifera, Globorotalia truncatulinoides and Globorotalia menardii, could be successfully harvested from offshore plankton tow samples in the Gulf of America (Gulf of Mexico) and kept alive in a laboratory at the US Geological Survey St. Petersburg Coastal and Marine Science Center. We collected several G. truncatulinoides specimens (n = 39) from the surface mixed-layer (0–80 meters) via vertical plankton tow in February 2020 during a sediment trap mooring recovery cruise. We collected G. menardii (n = 27) from the upper 200 meters of the water column on follow-up cruises in December 2021 and November 2022. The G. truncatulinoides specimens stayed alive in the laboratory for 8–76 days, and G. menardii for 7–29 days. All non-spinose foraminifera in this study showed a strong preference for eating marine snow aggregates from the plankton tow over Artemia nauplii. Using a combination of morphometric observations and geochemical analysis of the foraminiferal tests, we demonstrate that some specimens of both species grew new chambers while in culture, whereas other individuals added a calcite crust to the final whorl. The G. menardii were cultured in 87Sr-labeled seawater, and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used to verify the presence of laboratory-grown calcite. Our results shed light on the feeding behavior and growth patterns in these two upper-ocean species of non-spinose foraminifera. This study demonstrates the feasibility of conducting laboratory culture experiments with G. truncatulinoides and G. menardii collected via plankton tow in the open ocean.

","language":"English","publisher":"Cushman Foundation for Foraminiferal Research","doi":"10.61551/gsjfr.55.2.131","usgsCitation":"Reynolds, C.E., Fehrenbacher, J.S., Thirumalai, K., Tappa, E., and Richey, J.N., 2025, Insights from growing Globorotalia truncatulinoides and Globorotalia menardii in the laboratory: Journal of Foraminiferal Research, v. 55, no. 2, p. 131-143, https://doi.org/10.61551/gsjfr.55.2.131.","productDescription":"13 p.","startPage":"131","endPage":"143","ipdsId":"IP-167144","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":487832,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.61551/gsjfr.55.2.131","text":"Publisher Index Page"},{"id":485130,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.0986456321281,\n 29.21706725449961\n ],\n [\n -94.0986456321281,\n 23.01990337878115\n ],\n [\n -83.75187197199871,\n 23.01990337878115\n ],\n [\n -83.75187197199871,\n 29.21706725449961\n ],\n [\n -94.0986456321281,\n 29.21706725449961\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"55","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Reynolds, Caitlin E. 0000-0002-1724-3055 creynolds@usgs.gov","orcid":"https://orcid.org/0000-0002-1724-3055","contributorId":4049,"corporation":false,"usgs":true,"family":"Reynolds","given":"Caitlin","email":"creynolds@usgs.gov","middleInitial":"E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":934803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fehrenbacher, Jennifer S.","contributorId":204635,"corporation":false,"usgs":false,"family":"Fehrenbacher","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[{"id":6702,"text":"College of Earth, Ocean and Atmospheric Sciences, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":934804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thirumalai, Kaustubh","contributorId":127444,"corporation":false,"usgs":false,"family":"Thirumalai","given":"Kaustubh","email":"","affiliations":[{"id":6732,"text":"Geological Sciences, University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":934805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tappa, Eric J.","contributorId":353951,"corporation":false,"usgs":false,"family":"Tappa","given":"Eric J.","affiliations":[],"preferred":false,"id":934806,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":174046,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":934807,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270598,"text":"70270598 - 2025 - Growth patterns of invasive Silver Carp in the Mississippi River basin","interactions":[],"lastModifiedDate":"2025-09-22T16:00:44.612147","indexId":"70270598","displayToPublicDate":"2025-04-22T08:38:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"Growth patterns of invasive Silver Carp in the Mississippi River basin","docAbstract":"

Silver Carp (Hypophthalmichthys molitrix) are an invasive fish in the Mississippi River Basin. Their rapid expansion over recent decades coupled with extraordinary growth rates have arguably caught many by surprise. Understanding the atypical growth rates that could be the driving force behind the Silver Carp's explosive expansion may be crucial for development of management strategies. Towards this goal, I synthetized existing data on the growth and maturity patterns of Silver Carp. I compiled 62 estimates of growth representing populations of native Silver Carp in East Asia and invasive Silver Carp in the Mississippi River Basin. A remarkably rapid increase in length at earlier ages, undocumented in their ancestral range, was a defining feature of Silver Carp in the Mississippi River Basin. Some of the fastest growth rates of Silver Carp were recorded in hypereutrophic floodplain lakes and at lower latitudes. Invasive Silver Carp frequently deviated from the growth patterns established by native species as evidenced by abnormally high growth coefficients (K) in relation to asymptotic length (L∞). There is evidence of genetic differentiation between native Silver Carp and those expanding in the Mississippi River Basin possibly resulting from genetic background of introductions, genetic drift, and ecological selection. There is also limited evidence of enemy release, allowing for reallocation of energy from defenses to the rapid growth; though speculative, this is a plausible hypothesis that merits further research. This overview of the growth patterns of invasive Silver Carp underscores the need for novel strategies to mitigate the rapid generation time induced by the atypical growth patterns.

","language":"English","publisher":"Oxford Academic","doi":"10.1093/fshmag/vuaf037","usgsCitation":"Miranda, L.E., 2025, Growth patterns of invasive Silver Carp in the Mississippi River basin: Fisheries, v. 50, no. 9, p. 391-398, https://doi.org/10.1093/fshmag/vuaf037.","productDescription":"8 p.","startPage":"391","endPage":"398","ipdsId":"IP-169732","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":494388,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.64480284612964,\n 43.98127218458305\n ],\n [\n -91.64480284612964,\n 44.2443553877259\n ],\n [\n -91.8346990734972,\n 44.2443553877259\n ],\n [\n -91.8346990734972,\n 43.98127218458305\n ],\n [\n -91.64480284612964,\n 43.98127218458305\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.43082982303389,\n 43.86311653841281\n ],\n [\n -91.43082982303389,\n 30.489493770992354\n ],\n [\n -89.47610816114987,\n 30.489493770992354\n ],\n [\n -89.47610816114987,\n 43.86311653841281\n ],\n [\n -91.43082982303389,\n 43.86311653841281\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":946649,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70270100,"text":"70270100 - 2025 - Discovery of late Holocene-aged Acropora palmata reefs in Dry Tortugas National Park, Florida, USA: The past as a key to the future?","interactions":[],"lastModifiedDate":"2025-08-11T15:39:28.971692","indexId":"70270100","displayToPublicDate":"2025-04-22T08:35:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5781,"text":"The Depositional Record","active":true,"publicationSubtype":{"id":10}},"title":"Discovery of late Holocene-aged Acropora palmata reefs in Dry Tortugas National Park, Florida, USA: The past as a key to the future?","docAbstract":"

Emblematic of global coral-reef ecosystem decline, the coral ecosystem-engineer Acropora palmata is now rare throughout much of the western Atlantic. Understanding when and where this foundation species occurred during the past can provide information about the environmental limits defining its distribution through space and time. In this paper, the present, historical and newly dated geological records of A. palmata are compared to reveal novel insights into the environmental constraints on its occurrence in Dry Tortugas National Park, a subtropical reef system at the south-western terminus of the Florida reef tract. Although past geological investigation found little evidence of the species in the park, a single, moderately sized A. palmata reef existed throughout historical times (1881 Common Era [CE] to present day; ‘historical population’, termed herein). Over the last 140 years, repeated population declines occurred with little to no recovery, culminating in the extirpation of A. palmata from the area during the 2023–2024 CE global coral bleaching event. Reported here for the first time is a significant record of Late Holocene A. palmata populations that existed from ca 4500 to 375 years before present (‘Late Holocene population,’ termed herein) in three broadly distributed areas of the shallow Dry Tortugas platform. This discovery challenges previous assumptions regarding the species' limited contribution to reef development in the area by providing data that extend the known spatial and stratigraphic extent of Holocene populations in this location. It is posited that, although the Late Holocene climate largely suppressed regional reef development, the new records provide evidence for centennial-scale periods of more favourable and stable climate that allowed for short-term expansions of A. palmata populations in the Dry Tortugas. In conclusion, the species' prospects for future success in this and other subtropical location

","language":"English","publisher":"Wiley","doi":"10.1002/dep2.70005","usgsCitation":"Stathakopoulos, A., Toth, L., Modys, P.A., Johnson, S.A., and Kuffner, I.B., 2025, Discovery of late Holocene-aged Acropora palmata reefs in Dry Tortugas National Park, Florida, USA: The past as a key to the future?: The Depositional Record, v. 11, no. 3, p. 808-828, https://doi.org/10.1002/dep2.70005.","productDescription":"21 p.","startPage":"808","endPage":"828","ipdsId":"IP-169190","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":494189,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/dep2.70005","text":"Publisher Index Page"},{"id":493935,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.9661549521622,\n 24.68040740481777\n ],\n [\n -82.9661549521622,\n 24.595463709079198\n ],\n [\n -82.8127098632192,\n 24.595463709079198\n ],\n [\n -82.8127098632192,\n 24.68040740481777\n ],\n [\n -82.9661549521622,\n 24.68040740481777\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-04-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Stathakopoulos, Anastasios 0000-0002-4404-035X astathakopoulos@usgs.gov","orcid":"https://orcid.org/0000-0002-4404-035X","contributorId":147744,"corporation":false,"usgs":true,"family":"Stathakopoulos","given":"Anastasios","email":"astathakopoulos@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":945450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":945451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Modys, Peter Alexander Bacon 0000-0002-2948-5983","orcid":"https://orcid.org/0000-0002-2948-5983","contributorId":336719,"corporation":false,"usgs":true,"family":"Modys","given":"Peter","email":"","middleInitial":"Alexander Bacon","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":945452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Selena Anne-Marie 0000-0003-1015-1788","orcid":"https://orcid.org/0000-0003-1015-1788","contributorId":296373,"corporation":false,"usgs":true,"family":"Johnson","given":"Selena","email":"","middleInitial":"Anne-Marie","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":945453,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":945454,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70273730,"text":"70273730 - 2025 - Editorial: Parasite, host, and microbiome interactions in natural host systems","interactions":[],"lastModifiedDate":"2026-01-26T15:28:25.186533","indexId":"70273730","displayToPublicDate":"2025-04-22T08:24:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"title":"Editorial: Parasite, host, and microbiome interactions in natural host systems","docAbstract":"

No abstract available. 

","language":"English","publisher":"Frontiers Media","doi":"10.3389/fmicb.2025.1589627","usgsCitation":"Couch, C.E., Xavier, R., and Beechler, B.R., 2025, Editorial: Parasite, host, and microbiome interactions in natural host systems: Frontiers in Microbiology, v. 16, 1589627, 2 p., https://doi.org/10.3389/fmicb.2025.1589627.","productDescription":"1589627, 2 p.","ipdsId":"IP-175305","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":499317,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2025.1589627","text":"Publisher Index Page"},{"id":499016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","noUsgsAuthors":false,"plainLanguageSummary":"


","publicationDate":"2025-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Couch, Claire E. 0000-0003-4983-3719","orcid":"https://orcid.org/0000-0003-4983-3719","contributorId":359728,"corporation":false,"usgs":true,"family":"Couch","given":"Claire","middleInitial":"E.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":954458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xavier, Raquel","contributorId":365616,"corporation":false,"usgs":false,"family":"Xavier","given":"Raquel","affiliations":[{"id":87167,"text":"Carlson College of Veterinary Medicine, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":954460,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beechler, Brianna R.","contributorId":365615,"corporation":false,"usgs":false,"family":"Beechler","given":"Brianna","middleInitial":"R.","affiliations":[{"id":87167,"text":"Carlson College of Veterinary Medicine, Oregon State University","active":true,"usgs":false}],"preferred":false,"id":954459,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}