{"pageNumber":"280","pageRowStart":"6975","pageSize":"25","recordCount":184757,"records":[{"id":70243276,"text":"70243276 - 2023 - So goes the snow: Alaska snowpack changes and impacts on pacific salmon in a warming climate","interactions":[],"lastModifiedDate":"2023-05-05T11:38:45.159335","indexId":"70243276","displayToPublicDate":"2023-04-30T06:36:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":691,"text":"Alaska Park Science","printIssn":"1545- 496","active":true,"publicationSubtype":{"id":10}},"title":"So goes the snow: Alaska snowpack changes and impacts on pacific salmon in a warming climate","docAbstract":"In Alaska’s watersheds, climate change is altering the nature and role of the snowpack, defined as snow accumulation that melts in spring. Generally, the amount of precipitation that falls as snow and the length of the snow-cover season both decrease as temperatures exceed 0°C (32°F) more frequently. The impacts of climate change on snowpack vary among watersheds. In southern, coastal parts of Alaska, large decreases in spring snowpack are expected by the mid-21st century, even with more winter precipitation because temperatures warm to above freezing, causing a shift from snow to rain or more melt during the winter. In contrast, modest early spring increases in the snowpack are expected in watersheds where temperatures remain below freezing. In these locations temperatures warm but remain cold enough for the extra winter precipitation to fall as snow, even though the snowpack will begin accumulating later in the fall and melt earlier in the spring as temperatures rise during those warmer seasons. Because potential impacts on hydrological and ecological systems will vary among watersheds, it is difficult to generalize the resulting ecological impacts at broad spatial scales. Here, we explore likely impacts on hydrology in critical anadromous fish habitat in southwest Alaska.","language":"English","publisher":"US National Park Service","usgsCitation":"Littell, J., Reynolds, J.H., Bartz, K.K., McAfee, S., and Hayward, G.D., 2023, So goes the snow: Alaska snowpack changes and impacts on pacific salmon in a warming climate: Alaska Park Science, v. 19, no. 1, p. 62-75.","productDescription":"14 p.","startPage":"62","endPage":"75","ipdsId":"IP-112750","costCenters":[{"id":49028,"text":"Alaska Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":416748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":416743,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.nps.gov/articles/aps-19-1-10.htm"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -167.0502487962713,\n 69.32812262696825\n ],\n [\n -167.0502487962713,\n 63.68078746979131\n ],\n [\n -146.31697991983825,\n 63.68078746979131\n ],\n [\n -146.31697991983825,\n 69.32812262696825\n ],\n [\n -167.0502487962713,\n 69.32812262696825\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":871776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reynolds, Joel H.","contributorId":140498,"corporation":false,"usgs":false,"family":"Reynolds","given":"Joel","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":871777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bartz, Krista K.","contributorId":200705,"corporation":false,"usgs":false,"family":"Bartz","given":"Krista","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":871778,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":871779,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayward, Gregory D.","contributorId":209846,"corporation":false,"usgs":false,"family":"Hayward","given":"Gregory","email":"","middleInitial":"D.","affiliations":[{"id":38010,"text":"US Forest Service, Alaska Region","active":true,"usgs":false}],"preferred":false,"id":871780,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70241229,"text":"sir20235006 - 2023 - Magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 2017—Results","interactions":[],"lastModifiedDate":"2026-03-02T18:01:49.725089","indexId":"sir20235006","displayToPublicDate":"2023-04-28T13:18:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5006","displayTitle":"Magnitude and Frequency of Floods for Rural Streams in Georgia, South Carolina, and North Carolina, 2017—Results","title":"Magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 2017—Results","docAbstract":"

Reliable estimates of the magnitude and frequency of floods are an important part of the framework for hydraulic-structure design and flood-plain management in Georgia, South Carolina, and North Carolina. Annual peak flows measured at U.S. Geological Survey streamgages are used to compute flood‑frequency estimates at those streamgages. However, flood‑frequency estimates also are needed at ungaged stream locations. A process known as regionalization was used to develop regression equations to estimate the magnitude and frequency of floods at ungaged locations.

A multistate approach was used to update estimates of the magnitude and frequency of floods in rural, ungaged basins in Georgia, South Carolina, and North Carolina. Annual peak-flow data through September 2017 were analyzed for 965 streamgages with 10 or more years of data on rural streams in Georgia, South Carolina, North Carolina, and adjacent parts of Alabama, Florida, Tennessee, and Virginia. Flood‑frequency estimates of the 50‑, 20‑, 10‑, 4‑, 2‑, 1‑, 0.5‑, and 0.2‑percent annual exceedance probability streamflows, which correspond to flood-recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively, were computed for the 965 streamgages following national guidelines. As part of the computation of flood‑frequency estimates for the streamgages, an updated value for the regional skew coefficient (0.048) was developed using a Bayesian generalized least squares regression model. The new regional skew has a mean square error or average variance of prediction of 0.092. Additionally, basin characteristics for these stations were computed using a geographical information system.

Exploratory analyses on the 965 streamgages confirmed the five hydrologic regions for Georgia, South Carolina, and North Carolina defined in a previous rural flood‑frequency study. From the 965 streamgages, streamgages with 30 or more years of record were used to complete a peak-flow trend analysis. Of the 965 streamgages, 164 streamgages were found to be redundant and were excluded from the regional regression analyses. Data from the remaining 801 streamgages (292 in Georgia, 75 in South Carolina, 303 in North Carolina, 15 in Alabama, 12 in Florida, 39 in Tennessee, and 65 in Virginia) were used in a regional regression analysis relating basin characteristics to flood‑frequency estimates. This analysis, based on generalized least squares regression, was used to develop a set of predictive equations to estimate the 50‑, 20‑, 10‑, 4‑, 2‑, 1‑, 0.5‑, and 0.2‑percent annual exceedance probability streamflows for rural, ungaged basins in Georgia, South Carolina, and North Carolina. The final set of predictive equations are all functions of drainage area and percentage of the drainage basin within each of the five hydrologic regions. Average errors of prediction for these regression equations range from 35.8 to 44.4 percent.

Flood‑frequency estimates also were computed for 72 regulated (for example, a streamgage where flow is altered by a dam or weir) streamgages in Georgia, South Carolina, and North Carolina with 20 or more years of post-regulation record using data through water year 2019. The water year is the annual period from October 1 through September 30 and is designated by the year in which the period ends. Of the 72 regulated streamgages, 18 had pre-regulated periods of record that also were analyzed as part of this study. Flow adjustments were applied to historic peaks and large floods from the pre-regulated period, if available, for use in the post-regulation frequency analysis. Estimates of large floods provide valuable information in frequency analysis and, thus, were included in the post-regulation frequency analysis.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235006","collaboration":"Prepared in cooperation with the Georgia Department of Transportation (Engineering Division, Office of Bridge Design and Maintenance), South Carolina Department of Transportation (Hydraulic Design Support Office), North Carolina Department of Transportation (Division of Highways, Hydraulics Unit), and the North Carolina Department of Crime Control and Public Safety (Division of Emergency Management, Floodplain Mapping Program)","usgsCitation":"Feaster, T.D., Gotvald, A.J., Musser, J.W., Weaver, J.C., Kolb, K.R., Veilleux, A.G., and Wagner, D.M., 2023, Magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 2017—Results: U.S. Geological Survey Scientific Investigations Report 2023–5006, 75 p., https://doi.org/10.3133/sir20235006.","productDescription":"Report: ix, 75 p.; 2 Data Releases","numberOfPages":"75","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-115205","costCenters":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":414229,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TSBPFS","text":"USGS data release","linkHelpText":"Magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 2017—Data"},{"id":414230,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AQ2AX1","text":"USGS data release","linkHelpText":"Model archive for magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 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Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093

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","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-04-28","noUsgsAuthors":false,"publicationDate":"2023-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Feaster, Toby D. 0000-0002-5626-5011","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":205647,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby","email":"","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weaver, J. Curtis 0000-0001-7068-5445 jcweaver@usgs.gov","orcid":"https://orcid.org/0000-0001-7068-5445","contributorId":2229,"corporation":false,"usgs":true,"family":"Weaver","given":"J.","email":"jcweaver@usgs.gov","middleInitial":"Curtis","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":866595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolb, Katharine 0000-0002-1663-1662 kkolb@usgs.gov","orcid":"https://orcid.org/0000-0002-1663-1662","contributorId":5537,"corporation":false,"usgs":true,"family":"Kolb","given":"Katharine","email":"kkolb@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":866596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Veilleux, Andrea G. 0000-0002-8742-4660 aveilleux@usgs.gov","orcid":"https://orcid.org/0000-0002-8742-4660","contributorId":203278,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":870857,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870858,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70242743,"text":"fs20233011 - 2023 - Magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 2017—Summary","interactions":[],"lastModifiedDate":"2026-02-06T21:55:12.110532","indexId":"fs20233011","displayToPublicDate":"2023-04-28T13:18:00","publicationYear":"2023","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":"2023-3011","displayTitle":"Magnitude and Frequency of Floods for Rural Streams in Georgia, South Carolina, and North Carolina, 2017—Summary","title":"Magnitude and frequency of floods for rural streams in Georgia, South Carolina, and North Carolina, 2017—Summary","docAbstract":"

Reliable flood-frequency estimates are important for hydraulic structure design and floodplain management in Georgia, South Carolina, and North Carolina. Annual peak streamflows (hereafter, referred to as peak flows) measured at 965 U.S. Geological Survey streamgages were used to compute flood-frequency estimates with annual exceedance probabilities (AEPs) of 50, 20, 10, 4, 2, 1, 0.5, and 0.2 percent. These AEPs correspond to flood-recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A subset of these streamgages (801) were used to develop equations to predict the AEP flood flows at ungaged stream locations. This study was completed by the USGS in cooperation with the Georgia, South Carolina, and North Carolina Departments of Transportation and the North Carolina Department of Crime Control and Public Safety, and the results are summarized in this fact sheet. The complete results and the supporting data are presented in the companion scientific investigations report and data release.

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Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive, Suite 500
Norcross, GA 30093

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","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-04-28","noUsgsAuthors":false,"publicationDate":"2023-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Feaster, Toby D. 0000-0002-5626-5011","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":205647,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby","email":"","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weaver, J. Curtis 0000-0001-7068-5445 jcweaver@usgs.gov","orcid":"https://orcid.org/0000-0001-7068-5445","contributorId":2229,"corporation":false,"usgs":true,"family":"Weaver","given":"J.","email":"jcweaver@usgs.gov","middleInitial":"Curtis","affiliations":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":869637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolb, Katharine 0000-0002-1663-1662 kkolb@usgs.gov","orcid":"https://orcid.org/0000-0002-1663-1662","contributorId":5537,"corporation":false,"usgs":true,"family":"Kolb","given":"Katharine","email":"kkolb@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":869638,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70242681,"text":"cir1504 - 2023 - U.S. Geological Survey invasive carp strategic framework, 2023–27","interactions":[],"lastModifiedDate":"2023-04-28T16:51:27.241622","indexId":"cir1504","displayToPublicDate":"2023-04-28T12:38:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1504","displayTitle":"U.S. Geological Survey Invasive Carp Strategic Framework, 2023–27","title":"U.S. Geological Survey invasive carp strategic framework, 2023–27","docAbstract":"

U.S. Geological Survey (USGS) research has supported management of Hypophthalmichthys nobilis (bighead carp), Mylopharyngodon piceus (black carp), Ctenopharyngodon idella (grass carp), and H. molitrix (silver carp), hereafter referred to collectively as invasive carps, for over a decade. This strategic framework identifies thematic research areas to guide funding decisions for USGS invasive carp research during 2023–27. The USGS will use this framework and input from research and management agencies to identify leading-edge research to advance control of these highly damaging invasive species.

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Work"},"url":"https://umesc.usgs.gov/mapping/usgs_science_and_technology_help_managers_battle_invasive_carps_geonarrative.html","text":"USGS Science and Technology Help Managers Battle Invasive Carps"},{"id":415684,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1504/cir1504.XML"},{"id":415683,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1504/images/"},{"id":415680,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1504/coverthb.jpg"},{"id":416509,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1504/cir1504.pdf","text":"Report","size":"27.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Cir 1504"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n 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Associate Director, Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

Biological Threats and Invasive Species Research Program
Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-04-28","noUsgsAuthors":false,"publicationDate":"2023-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":869329,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":869330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calfee, Robin D. 0000-0001-6056-7023 rcalfee@usgs.gov","orcid":"https://orcid.org/0000-0001-6056-7023","contributorId":1841,"corporation":false,"usgs":true,"family":"Calfee","given":"Robin","email":"rcalfee@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":869331,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hlavacek, Enrika 0000-0002-9872-2305","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":297184,"corporation":false,"usgs":false,"family":"Hlavacek","given":"Enrika","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":869332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hortness, Jon 0000-0002-9809-2876 hortness@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-2876","contributorId":3601,"corporation":false,"usgs":true,"family":"Hortness","given":"Jon","email":"hortness@usgs.gov","affiliations":[],"preferred":true,"id":869333,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jackson, P. Ryan 0000-0002-3154-6108 pjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-3154-6108","contributorId":194529,"corporation":false,"usgs":true,"family":"Jackson","given":"P.","email":"pjackson@usgs.gov","middleInitial":"Ryan","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869334,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":202481,"corporation":false,"usgs":true,"family":"Kazyak","given":"David C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":869335,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Knights, Brent C. 0000-0001-8526-8468","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":304124,"corporation":false,"usgs":false,"family":"Knights","given":"Brent","middleInitial":"C.","affiliations":[{"id":65975,"text":"UMESC Retired","active":true,"usgs":false}],"preferred":false,"id":869336,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":869337,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70262374,"text":"70262374 - 2023 - Remote characterization of the 12 January 2020 eruption of Taal Volcano, Philippines, using seismo-acoustic, volcanic lightning, and satellite observations","interactions":[],"lastModifiedDate":"2025-01-16T16:53:12.932796","indexId":"70262374","displayToPublicDate":"2023-04-28T10:47:11","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Remote characterization of the 12 January 2020 eruption of Taal Volcano, Philippines, using seismo-acoustic, volcanic lightning, and satellite observations","docAbstract":"

On 12 January 2020, an eruption began on the shores of the Main Crater Lake (MCL) of Taal Volcano—a caldera system on the southern end of Luzon Island in the Philippines. Taal, one of the most active volcanoes in the Philippines, is located 30 km south of Manila—a major metropolitan area with a population of 13.5 million people. Eruptive activity intensified throughout the day on 12 January, producing prolific volcanic lightning, ashfall, and a sustained plume that reached 16–17 km altitude. The chronology of events was well documented by the Philippine Institute of Volcanology and Seismology and the Tokyo Volcanic Ash Advisory Center. The wealth of data collected during the eruption provides a unique opportunity to investigate how the combination of different remote sensing methods may complement local observations and monitoring. Remote systems tend to provide lower resolution data but are also less likely to be compromised by the eruptive activity, thus providing continuous records of eruptive processes. Here, we present a postevent analysis of the 12 January activity, including data from long‐range lightning, infrasound, and seismic arrays located at distances up to several thousands of kilometers from the volcano. By combining these datasets, we distinguish five phases of activity and infer a major shift in eruption behavior around 12:00 on 12 January (UTC). The remote observations suggest that the most of the water within the MCL (⁠∼42  million m3⁠) was vaporized and incorporated into the volcanic plume within the first 12 hr of the eruption.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120220223","usgsCitation":"Perttu, A., Assink, J.D., Van Eaton, A.R., Caudron, C., Vagasky, C., Krippner, J., McKee, K., De Angelis, S., Perttu, B., Taisne, B., and Lube, G., 2023, Remote characterization of the 12 January 2020 eruption of Taal Volcano, Philippines, using seismo-acoustic, volcanic lightning, and satellite observations: Bulletin of the Seismological Society of America, v. 113, no. 4, p. 1471-1492, https://doi.org/10.1785/0120220223.","productDescription":"22 p.","startPage":"1471","endPage":"1492","ipdsId":"IP-146744","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":467113,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/365748","text":"External 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Introduction 

The U.S. Geological Survey (USGS) serves a principal role in conducting wildlife disease outbreak investigations, surveillance, and ecological research to support management of diseases in free-ranging native wildlife. Approximately 60 percent of emerging human infectious diseases such as COVID-19, are zoonotic, meaning they are transmitted between animals and humans and 70 percent of these diseases originate in wildlife (Jones and others, 2008). The effects of emerging wildlife diseases are global and profound, often resulting in economic and agricultural impacts, declines in wildlife populations, and ecological disturbances.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20233008","programNote":"Ecosystems Mission Area","usgsCitation":"Hopkins, M.C., and Soileau, S.C., 2023, U.S. Geological Survey science to support wildlife disease management: U.S. Geological Survey Fact Sheet 2023–3008, 4 p., https://doi.org/10.3133/fs20233008.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-133721","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":415205,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2023/3008/fs20233008.XML"},{"id":415202,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2023/3008/fs20233008.pdf","text":"Report","size":"3.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2023-3008"},{"id":415201,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2023/3008/coverthb2.jpg"},{"id":415227,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2023/3008/images/"},{"id":415226,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20233008/full"}],"contact":"

Associate Director, Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Mail Stop 300
Reston, VA 20192

Biological Threats and Invasive Species Research Program
Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-04-28","noUsgsAuthors":false,"publicationDate":"2023-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Hopkins, M. 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2023","interactions":[],"lastModifiedDate":"2023-12-16T13:11:35.494236","indexId":"70250588","displayToPublicDate":"2023-04-28T07:11:06","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Hazus Estimated Annualized Earthquake Losses for the United States: FEMA P-366, 2023","docAbstract":"The National Earthquake Hazards Reduction Program (NEHRP) Reauthorization Act of 2018 (Pub.L. 115–307) requires that the Federal Emergency Management Agency (FEMA) “shall support the implementation of a comprehensive earthquake education, outreach, and public awareness program, including development of materials and their wide dissemination to all appropriate audiences and support public access to locality-specific information that may assist the public in preparing for, mitigating against, responding to and recovering from earthquakes and related disasters.” As one effort to satisfy the mission, 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migration dynamics of juvenile salmonids through rivers and estuaries using a hydrodynamically driven enhanced particle tracking model","docAbstract":"

Juvenile salmonids migrate hundreds of kilometers from their natal streams to mature in the ocean. Throughout this migration, they respond to environmental cues such as local water velocities and other stimuli to direct and modulate their movements, often through heavily modified riverine and estuarine habitats. Management strategies in an uncertain future of climate change and altered land use regimes depend heavily on being able to reliably predict their ocean entry timings, route use, and survival rates through rivers and estuaries. We developed a spatially-explicit agent-based model of fish movement in response to hydrodynamic flows that uses movement dynamics gleaned from multi-dimensional tracking datasets of acoustically tagged juveniles moving through an urbanized, branched tidal estuary. We demonstrate how such models can be calibrated, and we apply it to the Sacramento-San Joaquin Delta in Central California. The quality of the out-of-sample validation of the model to predict juvenile salmon survival and route selection indicates that the model is versatile and flexible enough to be used in novel hydroclimatological conditions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2023.110393","usgsCitation":"Sridharan, V.K., Jackson, D., Hein, A.M., Perry, R., Pope, A., Hendrix, N., Danner, E.M., and Lindley, S.T., 2023, Simulating the migration dynamics of juvenile salmonids through rivers and estuaries using a hydrodynamically driven enhanced particle tracking model: Ecological Modeling, v. 482, 110393, 27 p., https://doi.org/10.1016/j.ecolmodel.2023.110393.","productDescription":"110393, 27 p.","ipdsId":"IP-144118","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":443685,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://escholarship.org/uc/item/3298p440","text":"Publisher Index Page"},{"id":418684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay-Delta system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.41195439667275,\n 38.415598404027605\n ],\n [\n -122.41195439667275,\n 37.69791363010357\n ],\n [\n -121.25888467133896,\n 37.69791363010357\n ],\n [\n -121.25888467133896,\n 38.415598404027605\n ],\n [\n -122.41195439667275,\n 38.415598404027605\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"482","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sridharan, Vamsi Krishna","contributorId":315555,"corporation":false,"usgs":false,"family":"Sridharan","given":"Vamsi","email":"","middleInitial":"Krishna","affiliations":[{"id":68351,"text":"Fisheries Collaborative Program, University of California, Santa Cruz; 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Because use of high-resolution hydrologic models is becoming more widespread and estimates are made over large domains, there is a pressing need for systematic evaluation of their performance. Most evaluation efforts to date have focused on smaller basins that have been relatively undisturbed by human activity, but there is also a need to benchmark model performance more comprehensively, including basins impacted by human activities. This study benchmarks the long-term performance of two process-oriented, high-resolution, continental-scale hydrologic models that have been developed to assess water availability and risks in the United States (US): the National Water Model v2.1 application of WRF-Hydro (NWMv2.1) and the National Hydrologic Model v1.0 application of the Precipitation–Runoff Modeling System (NHMv1.0). The evaluation is performed on 5390 streamflow gages from 1983 to 2016 (∼ 33 years) at a daily time step, including both natural and human-impacted catchments, representing one of the most comprehensive evaluations over the contiguous US. Using the Kling–Gupta efficiency as the main evaluation metric, the models are compared against a climatological benchmark that accounts for seasonality. Overall, the model applications show similar performance, with better performance in minimally disturbed basins than in those impacted by human activities. Relative regional differences are also similar: the best performance is found in the Northeast, followed by the Southeast, and generally worse performance is found in the Central and West areas. For both models, about 80 % of the sites exceed the seasonal climatological benchmark. Basins that do not exceed the climatological benchmark are further scrutinized to provide model diagnostics for each application. Using the underperforming subset, both models tend to overestimate streamflow volumes in the West, which could be attributed to not accounting for human activities, such as active management. Both models underestimate flow variability, especially the highest flows; this was more pronounced for NHMv1.0. Low flows tended to be overestimated by NWMv2.1, whereas there were both over and underestimations for NHMv1.0, but they were less severe. Although this study focused on model diagnostics for underperforming sites based on the seasonal climatological benchmark, metrics for all sites for both model applications are openly available online.

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Sandy beaches are important resources providing recreation, tourism, habitat, and coastal protection. They evolve over various time scales due to local winds, waves, storms, and changes in sea level. A common method used to monitor change in sandy beaches is to measure the movement of the shoreline over time. Typically, the rate of change is estimated by fitting a linear regression through a time series of shoreline positions. To best manage the valuable resources within a coastal environment, accurate forecasts of shoreline position are needed. A simple way to estimate future shoreline position is to extrapolate a linear regression into the future, this method is often used to establish management guidelines like construction setback lines. A more recently developed shoreline forecasting technique utilizes the Kalman filter to assimilate shoreline data and modify the linear regression. This paper calculates the uncertainty and accuracy of both the extrapolated linear regression and Kalman filter forecasting methods for 10- and 20-year hindcasts using data collected at five diverse study areas. These data are inherently sparse (8–10 measurements per location, collected over 150 years) and are representative of the observed historical data available for the continental United States for this timeframe. Both methods produced similar results and had regionally averaged forecast accuracies of 5–16 m. We determined that the inaccuracy of the forecasts is largely due to the effects of shorter time scale variability. This variability is roughly proportional to the standard error of the linear regression, which is a useful measure of forecast uncertainty.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocecoaman.2023.106621","usgsCitation":"Farris, A.S., Long, J.W., and Himmelstoss, E.A., 2023, Accuracy of shoreline forecasting using sparse data: Ocean and Coast Management, v. 239, 106621, 11 p., https://doi.org/10.1016/j.ocecoaman.2023.106621.","productDescription":"106621, 11 p.","ipdsId":"IP-149121","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443688,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ocecoaman.2023.106621","text":"Publisher Index Page"},{"id":416543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.0181323609342,\n 42.612604369987906\n ],\n [\n -71.0181323609342,\n 42.45075682456917\n ],\n [\n -70.76006466040619,\n 42.45075682456917\n ],\n [\n -70.76006466040619,\n 42.612604369987906\n ],\n [\n -71.0181323609342,\n 42.612604369987906\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.78751867110105,\n 42.11358574731062\n ],\n [\n -70.78751867110105,\n 41.8932530394155\n ],\n [\n -70.48003375132315,\n 41.8932530394155\n ],\n [\n -70.48003375132315,\n 42.11358574731062\n ],\n [\n -70.78751867110105,\n 42.11358574731062\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.11215000801785,\n 42.036148281625714\n ],\n [\n -70.11215000801785,\n 41.8073620898663\n ],\n [\n -69.84310070321233,\n 41.8073620898663\n ],\n [\n -69.84310070321233,\n 42.036148281625714\n ],\n [\n -70.11215000801785,\n 42.036148281625714\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.59002117122246,\n 31.052924740394133\n ],\n [\n -81.59002117122246,\n 30.69475662400724\n ],\n [\n -81.27704544930633,\n 30.69475662400724\n ],\n [\n -81.27704544930633,\n 31.052924740394133\n ],\n [\n -81.59002117122246,\n 31.052924740394133\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.26851886305553,\n 26.485217152462425\n ],\n [\n -80.26851886305553,\n 26.209674401029375\n ],\n [\n -79.98025175076435,\n 26.209674401029375\n ],\n [\n -79.98025175076435,\n 26.485217152462425\n ],\n [\n -80.26851886305553,\n 26.485217152462425\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"239","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Farris, Amy S. 0000-0002-4668-7261 afarris@usgs.gov","orcid":"https://orcid.org/0000-0002-4668-7261","contributorId":196866,"corporation":false,"usgs":true,"family":"Farris","given":"Amy","email":"afarris@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":871124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Joseph W","contributorId":216005,"corporation":false,"usgs":false,"family":"Long","given":"Joseph","email":"","middleInitial":"W","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":871125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Himmelstoss, Emily A. 0000-0002-1760-5474 ehimmelstoss@usgs.gov","orcid":"https://orcid.org/0000-0002-1760-5474","contributorId":194838,"corporation":false,"usgs":true,"family":"Himmelstoss","given":"Emily","email":"ehimmelstoss@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":871126,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70243181,"text":"70243181 - 2023 - The changing dynamics of highly pathogenic avian influenza H5N1: Next steps for management & science in North America","interactions":[],"lastModifiedDate":"2023-05-03T11:46:44.075926","indexId":"70243181","displayToPublicDate":"2023-04-28T06:45:20","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"The changing dynamics of highly pathogenic avian influenza H5N1: Next steps for management & science in North America","docAbstract":"

Highly pathogenic avian influenza virus (HPAIV) H5N1 was introduced in North America in late 2021 through trans-Atlantic pathways via migratory birds. These introductions have resulted in an unprecedented epizootic, a widespread disease event in animals, heavily affecting poultry, wild birds, and recently mammals. The North American incursions occurred during the largest epidemic season (2021–2022) in Europe where H5N1 may now be endemic (i.e., continuously present). The continuing outbreak includes expansion into Mexico, Central and South America beginning in late 2022. Here, we provide an overview of the Eurasian origin H5N1 introduction to the Americas, including a significant shift in virus dynamics and severe disease in wild birds. Then, to investigate the global changes in confirmed detections in wild birds and poultry across time and geographic regions, we analyzed FAO's EMPRES-i + database. To examine the 2021 introduction and spread in North American wild birds and poultry, we collated publicly available data across USA and Canadian federal sources. Based on our assessment, the unique magnitude of the North American H5N1 spread indicates the need for effective decision framing to prioritize management needs and scientific inquiry, particularly for species at risk and interface areas for wildlife, poultry, and humans. We illustrate the rapidly occurring and likely increasing detrimental effects that this One Health issue has on wildlife, agriculture, and potentially human health, and we offer a reframing of HPAIV disease response towards a decision analytical context to guide scientific prioritization as a potentially valuable change in focus.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2023.110041","usgsCitation":"Harvey, J., Mullinax, J.M., Runge, M.C., and Prosser, D., 2023, The changing dynamics of highly pathogenic avian influenza H5N1: Next steps for management & science in North America: Biological Conservation, v. 282, 110041, 11 p., https://doi.org/10.1016/j.biocon.2023.110041.","productDescription":"110041, 11 p.","ipdsId":"IP-145359","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443690,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2023.110041","text":"Publisher Index Page"},{"id":416650,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"282","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harvey, Johanna","contributorId":304699,"corporation":false,"usgs":false,"family":"Harvey","given":"Johanna","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":871396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":871397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":871398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":871399,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70243337,"text":"70243337 - 2023 - Nitrogen-bedrock interactions regulate multi-element nutrient limitation and sustainability in forests","interactions":[],"lastModifiedDate":"2023-07-11T16:00:18.992243","indexId":"70243337","displayToPublicDate":"2023-04-28T06:40:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Nitrogen-bedrock interactions regulate multi-element nutrient limitation and sustainability in forests","docAbstract":"

Nutrient limitation of tree growth can intensify when nutrients are lost to forest harvest, creating challenges for forest growth and sustainability. Forest harvest accelerates nutrient loss by removing nutrient-containing biomass and by increasing nutrient leaching, shaping patterns of nutrient depletion that cause long-term shifts in nutrient limitation. Nitrogen most frequently limits tree growth, but where nitrogen is abundant, nutrient limitation often shifts to phosphorus and base cations, depending on soil mineralogy. We used the process-based biogeochemical model NutsFor to evaluate how multiple elements can limit long-term forest growth via interactions between soil nitrogen (low vs. high nitrogen) and soil mineralogy (sedimentary vs. basaltic bedrock). Simulations were run for 525 years with 40-year harvest intervals for managed Douglas-fir forests of the Oregon Coast Range. In low nitrogen sites, nutrient limitation switched after several centuries from nitrogen to phosphorus, as cycles of forest growth and harvest depleted soil organic phosphorus pools. In contrast, high nitrogen sites displayed severe base cation depletion and reduced tree growth within only one to two rotations, with sedimentary bedrock sites limited by calcium and basaltic sites by both calcium and potassium. Harvesting stimulated the largest fractional losses of nitrogen and potassium across all simulations, and additionally of calcium in high nitrogen sites. These multi-element simulations of interactions among harvesting, soil nitrogen, and bedrock type provide a set of testable predictions to guide monitoring and changes in management aimed at sustaining long-term forest productivity across a wide range of soil biogeochemical conditions.

","language":"English","publisher":"Springer","doi":"10.1007/s10533-023-01039-6","usgsCitation":"Siah, K.G., Perakis, S.S., Pett-Ridge, J.C., and van der Heijden, G., 2023, Nitrogen-bedrock interactions regulate multi-element nutrient limitation and sustainability in forests: Biogeochemistry, v. 164, p. 389-413, https://doi.org/10.1007/s10533-023-01039-6.","productDescription":"25 p.","startPage":"389","endPage":"413","ipdsId":"IP-147344","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":416848,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"164","noUsgsAuthors":false,"publicationDate":"2023-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Siah, Kaveh G.","contributorId":304967,"corporation":false,"usgs":false,"family":"Siah","given":"Kaveh","email":"","middleInitial":"G.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":872086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perakis, Steven S. 0000-0003-0703-9314 sperakis@usgs.gov","orcid":"https://orcid.org/0000-0003-0703-9314","contributorId":145528,"corporation":false,"usgs":true,"family":"Perakis","given":"Steven","email":"sperakis@usgs.gov","middleInitial":"S.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":872087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pett-Ridge, Julie C.","contributorId":172441,"corporation":false,"usgs":false,"family":"Pett-Ridge","given":"Julie","email":"","middleInitial":"C.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":872088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van der Heijden, Gregory","contributorId":304968,"corporation":false,"usgs":false,"family":"van der Heijden","given":"Gregory","email":"","affiliations":[{"id":66197,"text":"INRA","active":true,"usgs":false}],"preferred":false,"id":872089,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70248739,"text":"70248739 - 2023 - Substantial upper plate faulting above a shallow subduction megathrust earthquake: Mechanics and implications of the surface faulting during the 2016 Kaikoura, New Zealand, earthquake","interactions":[],"lastModifiedDate":"2023-09-19T11:39:45.04709","indexId":"70248739","displayToPublicDate":"2023-04-28T06:37:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Substantial upper plate faulting above a shallow subduction megathrust earthquake: Mechanics and implications of the surface faulting during the 2016 Kaikoura, New Zealand, earthquake","docAbstract":"

The 2016 moment magnitude 7.8 Kaikoura, New Zealand, earthquake occurred at the southern end of the Hikurangi subduction zone where the upper plate above the shallow megathrust is exposed sub-aerially. As a result, the substantial co-seismic deformation in the upper plate above the megathrust rupture was observed geologically and geodetically. We explore the relationship between this surface faulting and the subduction megathrust rupture and find that the greatest upper plate fault slip occurred coincident (in time and location) with the megathrust rupture. Models of Coulomb stress change demonstrate that these surface faults become positively loaded as the upper plate rebounds during the megathrust event, favoring fault slip. In addition, during the megathrust rupture these faults terminate against an uncoupled subduction plate interface. We simulate the effects of decoupling at the base of these faults and find that very large fault slip is an expected consequence of this decoupling, allowing near-complete strain release. In contrast, typical strike-slip faults, pinned at their base, would have lower amounts of fault slip. These two conditions—increased Coulomb stress and basal decoupling—combine to produce the extreme co-seismic upper plate faulting observed above the shallow Kaikoura megathrust earthquake. Similar conditions occur in other global subduction zones, but in most subduction zones the region above the coupled megathrust is underwater and poorly observed. Our analysis of the Kaikoura earthquake indicates a need to reevaluate patterns of strain accumulation and release in these regions, rather than assuming simple models of elastic rebound.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022TC007645","usgsCitation":"Herman, M.W., Furlong, K.P., and Benz, H.M., 2023, Substantial upper plate faulting above a shallow subduction megathrust earthquake: Mechanics and implications of the surface faulting during the 2016 Kaikoura, New Zealand, earthquake: Tectonics, v. 42, no. 5, e2022TC007645, 22 p., https://doi.org/10.1029/2022TC007645.","productDescription":"e2022TC007645, 22 p.","ipdsId":"IP-148754","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":443695,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022tc007645","text":"Publisher Index Page"},{"id":420938,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 173.55247459472434,\n -41.36342774281367\n ],\n [\n 173.55247459472434,\n -42.42606214524861\n ],\n [\n 174.62867300503626,\n -42.42606214524861\n ],\n [\n 174.62867300503626,\n -41.36342774281367\n ],\n [\n 173.55247459472434,\n -41.36342774281367\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Herman, M. W.","contributorId":329824,"corporation":false,"usgs":false,"family":"Herman","given":"M.","email":"","middleInitial":"W.","affiliations":[{"id":36956,"text":"California State University","active":true,"usgs":false}],"preferred":false,"id":883397,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Furlong, K. P.","contributorId":329825,"corporation":false,"usgs":false,"family":"Furlong","given":"K.","email":"","middleInitial":"P.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":883398,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":883399,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70243183,"text":"70243183 - 2023 - Potential effects of habitat change on migratory bird movements and avian influenza transmission in the East Asian-Australasian Flyway","interactions":[],"lastModifiedDate":"2023-05-03T11:36:54.656507","indexId":"70243183","displayToPublicDate":"2023-04-28T06:33:32","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Potential effects of habitat change on migratory bird movements and avian influenza transmission in the East Asian-Australasian Flyway","docAbstract":"
Wild waterbirds, and especially wild waterfowl, are considered to be a reservoir for avian influenza viruses, with transmission likely occurring at the agricultural-wildlife interface. In the past few decades, avian influenza has repeatedly emerged in China along the East Asian-Australasian Flyway (EAAF), where extensive habitat conversion has occurred. Rapid environmental changes in the EAAF, especially distributional changes in rice paddy agriculture, have the potential to affect both the movements of wild migratory birds and the likelihood of spillover at the agricultural-wildlife interface. To begin to understand the potential implications such changes may have on waterfowl and disease transmission risk, we created dynamic Brownian Bridge Movement Models (dBBMM) based on waterfowl telemetry data. We used these dBBMM models to create hypothetical scenarios that would predict likely changes in waterfowl distribution relative to recent changes in rice distribution quantified through remote sensing. Our models examined a range of responses in which increased availability of rice paddies would drive increased use by waterfowl and decreased availability would result in decreased use, predicted from empirical data. Results from our scenarios suggested that in southeast China, relatively small decreases in rice agriculture could lead to dramatic loss of stopover habitat, and in northeast China, increases in rice paddies should provide new areas that can be used by waterfowl. Finally, we explored the implications of how such scenarios of changing waterfowl distribution may affect the potential for avian influenza transmission. Our results provide advance understanding of changing disease transmission threats by incorporating real-world data that predicts differences in habitat utilization by migratory birds over time.
","language":"English","publisher":"MDPI","doi":"10.3390/d15050601","usgsCitation":"Takekawa, J., Prosser, D., Sullivan, J.D., Yin, S., Wang, X., Zhang, G., and Xiao, X., 2023, Potential effects of habitat change on migratory bird movements and avian influenza transmission in the East Asian-Australasian Flyway: Diversity, v. 15, no. 5, 601, 17 p., https://doi.org/10.3390/d15050601.","productDescription":"601, 17 p.","ipdsId":"IP-151017","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443698,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d15050601","text":"Publisher Index Page"},{"id":416648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, North Korea, South Korea, Russia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 110.647426736211,\n 49.63059537353766\n ],\n [\n 110.647426736211,\n 24.72726514910231\n ],\n [\n 138.23321668197326,\n 24.72726514910231\n ],\n [\n 138.23321668197326,\n 49.63059537353766\n ],\n [\n 110.647426736211,\n 49.63059537353766\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Takekawa, John 0000-0003-0217-5907","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":203688,"corporation":false,"usgs":false,"family":"Takekawa","given":"John","affiliations":[{"id":36688,"text":"Suisun Resource Conservation District","active":true,"usgs":false}],"preferred":false,"id":871400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":871401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":871402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yin, Shenglai","contributorId":223544,"corporation":false,"usgs":false,"family":"Yin","given":"Shenglai","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":871403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wang, Xinxin","contributorId":304701,"corporation":false,"usgs":false,"family":"Wang","given":"Xinxin","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":871404,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhang, Geli","contributorId":206235,"corporation":false,"usgs":false,"family":"Zhang","given":"Geli","email":"","affiliations":[],"preferred":false,"id":871405,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Xiao, Xiangming","contributorId":150759,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiangming","affiliations":[{"id":18095,"text":"Center for Spatial Analysis, U of OK, Norman, OK","active":true,"usgs":false}],"preferred":false,"id":871406,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70243020,"text":"sir20235041 - 2023 - Public-supply water use in 2010 and projections of use in 2020 and 2030, Tennessee","interactions":[],"lastModifiedDate":"2026-03-06T21:34:51.78009","indexId":"sir20235041","displayToPublicDate":"2023-04-27T12:28:54","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5041","displayTitle":"Public-Supply Water Use in 2010 and Projections of Use in 2020 and 2030, Tennessee","title":"Public-supply water use in 2010 and projections of use in 2020 and 2030, Tennessee","docAbstract":"

Future water use was projected for public-water systems in Tennessee. Water-use information was compiled for Tennessee for 2010, and projections were made to 2020 and 2030. The water-use models were based on two primary datasets: baseline water-use information for 2010 for Tennessee and projected population in Tennessee.

Population and water withdrawals in Tennessee are expected to increase through 2030. Because population served is projected to increase by about 1 million people during 2010 to 2030, the supply of finished water to meet demand in Tennessee is projected to increase from 921 to 1,137 million gallons per day, or 23 percent. The residential, commercial, and industrial water use, and treatment and nonrevenue water sectors of public supply are about 37, 32, and 30 percent, respectively, of the total water demand in Tennessee during 2010, 2020, and 2030.

In West Tennessee, public-supply water use is 26, 26, and 24 percent of the total water demand in Tennessee during 2010, 2020, and 2030, respectively. From 2010 to 2030, public-supply water use in West Tennessee is projected to increase 13 percent. In Middle Tennessee, public-supply water use is 38, 39, and 41 percent of the total water demand in Tennessee during 2010, 2020, and 2030, respectively. From 2010 to 2030, public-supply water use in Middle Tennessee is projected to increase 33 percent. In East Tennessee, public-supply water use is 36, 36, and 35 percent of the total water demand in Tennessee during 2010, 2020, and 2030, respectively. From 2010 to 2030, public-supply water use in East Tennessee is projected to increase 21 percent.

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\"}}]}","contact":"

Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
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","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-04-27","noUsgsAuthors":false,"publicationDate":"2023-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, John A. 0000-0001-8002-4237 jarobin@usgs.gov","orcid":"https://orcid.org/0000-0001-8002-4237","contributorId":1105,"corporation":false,"usgs":true,"family":"Robinson","given":"John","email":"jarobin@usgs.gov","middleInitial":"A.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":870610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gain, W. Scott wsgain@usgs.gov","contributorId":346,"corporation":false,"usgs":true,"family":"Gain","given":"W.","email":"wsgain@usgs.gov","middleInitial":"Scott","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":870611,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70243060,"text":"ofr20231019 - 2023 - Chemical characterization of San Andreas Fault Observatory at Depth (SAFOD) Phase 3 core","interactions":[],"lastModifiedDate":"2026-02-11T20:53:14.236837","indexId":"ofr20231019","displayToPublicDate":"2023-04-27T12:05:32","publicationYear":"2023","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":"2023-1019","displayTitle":"Chemical Characterization of San Andreas Fault Observatory at Depth (SAFOD) Phase 3 Core","title":"Chemical characterization of San Andreas Fault Observatory at Depth (SAFOD) Phase 3 core","docAbstract":"

We present new X-ray fluorescence compositions of 27 core samples from Phase 3, Hole G of the San Andreas Fault Observatory at Depth, nearly doubling the published dataset for the core. The new analyses consist of major and trace element compositions and the first published data for rare earth elements from Hole G. Whole-rock compositions were obtained to further the analysis of active geochemical processes within the creeping section of the San Andreas Fault in central California. In this report, we plot the new data along with previously published analyses to illustrate some of the compositional features of the Hole G core and to relate them to the core mineralogy.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231019","usgsCitation":"Moore, D.E., and Bradbury, K.K., 2023, Chemical characterization of San Andreas Fault Observatory at Depth (SAFOD) Phase 3 core: U.S. Geological Survey Open-File Report 2023–1019, 15 p., https://doi.org/10.3133/ofr20231019.","productDescription":"iv, 15 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-142575","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":416448,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1019/ofr20231019.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":499770,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114706.htm","linkFileType":{"id":5,"text":"html"}},{"id":416447,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1019/covrthb.jpg"}],"contact":"

Earthquake Science Center
U.S. Geological Survey
350 N. Akron Road
Moffett Field, CA 94035

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-04-27","noUsgsAuthors":false,"publicationDate":"2023-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Diane E. 0000-0002-8641-1075 dmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-8641-1075","contributorId":2704,"corporation":false,"usgs":true,"family":"Moore","given":"Diane","email":"dmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":870859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradbury, Kelly K.","contributorId":304539,"corporation":false,"usgs":false,"family":"Bradbury","given":"Kelly","email":"","middleInitial":"K.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":true,"id":870860,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70243023,"text":"pp1876 - 2023 - Volcanic aquifers of Hawaiʻi—Contributions to assessing groundwater availability on Kauaʻi, Oʻahu, and Maui","interactions":[],"lastModifiedDate":"2026-02-18T22:16:30.66487","indexId":"pp1876","displayToPublicDate":"2023-04-27T09:04:58","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1876","displayTitle":"Volcanic Aquifers of Hawai‘i—Contributions to Assessing Groundwater Availability on Kaua‘i, O‘ahu, and Maui","title":"Volcanic aquifers of Hawaiʻi—Contributions to assessing groundwater availability on Kauaʻi, Oʻahu, and Maui","docAbstract":"

The volcanic aquifers of the Hawaiian Islands supply water to 1.46 million residents, diverse industries, and a large component of the U.S. military in the Pacific. Groundwater also supplies fresh water that supports ecosystems in streams and near the coast. Hawaii’s aquifers are remarkably productive given their small size, but the capacity of the islands to store fresh groundwater is limited because each island is surrounded by seawater, and salt water underlies much of the fresh groundwater. The amount of fresh groundwater available for human use from Hawai‘i’s volcanic aquifers is constrained by the consequences of groundwater withdrawal. Restrictions placed on these consequences can translate to limitations on groundwater availability. Changes in recharge resulting from changes in land cover or climate can alter the effect of withdrawals.

This study uses numerical models of the volcanic aquifers of the islands of Kaua‘i, O‘ahu, and Maui to quantify the consequences of historical and plausible future withdrawals and changes in recharge. The study compares the results of model simulations of multiple scenarios of historical and projected future withdrawal and recharge. Results of the simulations using the groundwater models of the islands of Kaua‘i, O‘ahu, and Maui have implications for other islands in Hawai‘i.

Since the first modern water well was drilled in Hawai‘i in 1879, total groundwater withdrawals on Kaua‘i, O‘ahu, and Maui have risen to nearly 400 million gallons per day. Model simulations indicate that these withdrawals have caused reductions in groundwater discharge to streams and springs, reductions in groundwater discharge to the ocean, changes in subsurface flow between sectors within an island, lowering of groundwater levels, and rise of the interface between fresh water and salt water in the aquifers. Future increases in withdrawals will increase the severity of the consequences. Changes in recharge can alter the effect of withdrawals—increases in recharge can offset the consequences of withdrawals, whereas decreases in recharge can exacerbate the effects of withdrawals.

This study quantifies the consequences of withdrawals for past and plausible future circumstances. The models can be used to test other circumstances. Limits placed on the consequences of withdrawals—such as restrictions to protect stream or coastal ecosystems that rely on groundwater discharge and limitations on water-level decline and rise of the freshwater-saltwater interface to protect the productivity of existing wells—can translate to limits on groundwater availability from Hawai‘i’s volcanic aquifers. Setting acceptable limits to the consequences of groundwater withdrawal is also a critical part of assessing groundwater availability. Once these limits are set, numerical models can be used to quantify the amount of water that can be withdrawn within those limits and thereby inform management decisions that seek to balance the need to limit the consequences of groundwater withdrawals with the need to develop water for human use.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1876","usgsCitation":"Izuka, S.K., and Rotzoll, K., 2023, Volcanic aquifers of Hawai‘i—Contributions to assessing groundwater availability on Kaua‘i, O‘ahu, and Maui (ver. 1.1, June 2023): U.S. Geological Survey Professional Paper 1876, 100 p., https://doi.org/10.3133/pp1876.","productDescription":"Report: ix, 100 p.; 2 Data Releases","numberOfPages":"100","ipdsId":"IP-125998","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":416400,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97CPK5C","text":"MODFLOW–2005 and SWI2 models for assessing groundwater availability scenarios in volcanic aquifers on Kauai, Oahu, and Maui, Hawaii","description":"Rotzoll, K., and Izuka, S.K., 2023, MODFLOW–2005 and SWI2 models for assessing groundwater availability scenarios in volcanic aquifers on Kauai, Oahu, and Maui, Hawaii: U.S. Geological Survey data release, https://doi.org/10.5066/P97CPK5C."},{"id":416401,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L4N2ZI","text":"Mean annual water-budget components for Oahu, Hawaii, for future-climate conditions, CMIP5 RCP8.5 2041–70 scenario rainfall and 2010 land cover","description":"Rotzoll, K., and Johnson, A.G., 2023, Mean annual water-budget components for Oahu, Hawaii, for future-climate conditions, CMIP5 RCP8.5 2041–70 scenario rainfall and 2010 land cover: U.S. Geological Survey data release, https://doi.org/10.5066/P9L4N2ZI."},{"id":416402,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1876/covrthb.jpg"},{"id":500158,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114701.htm","text":"Kauai","linkFileType":{"id":5,"text":"html"}},{"id":416405,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20205126","text":"Scientific Investigations Report 2020-5126","description":"Izuka, S.K., Rotzoll, K., and Nishikawa, T., 2021, Volcanic Aquifers of Hawai‘i—Construction and calibration of numerical models for assessing groundwater availability on Kaua‘i, O‘ahu, and Maui: U.S. Geological Survey Scientific Investigations Report 2020-5126, 63 p., https://doi.org/10.3133/sir20205126.","linkHelpText":"- Volcanic Aquifers of Hawai‘i—Construction and Calibration of Numerical Models for Assessing Groundwater Availability on Kaua‘i, O‘ahu, and Maui"},{"id":416404,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20155164","text":"Scientific Investigations Report 2015-5164","description":"Izuka, S.K., Engott, J.A., Rotzoll, Kolja, Bassiouni, Maoya, Johnson, A.G., Miller, L.D., and Mair, Alan, 2018, Volcanic aquifers of Hawai‘i—Hydrogeology, water budgets, and conceptual models (ver. 2.0, March 2018): U.S. Geological Survey Scientific Investigations Report 2015-5164, 158 p., https://doi.org/10.3133/sir20155164.","linkHelpText":"- Volcanic Aquifers of Hawai‘i—Hydrogeology, Water budgets, and Conceptual Models"},{"id":500159,"rank":11,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114702.htm","text":"Maui","linkFileType":{"id":5,"text":"html"}},{"id":500157,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114700.htm","text":"Oahu","linkFileType":{"id":5,"text":"html"}},{"id":417943,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20233010","text":"Fact Sheet 2023-3010","description":"Izuka, S.K., and Rotzoll, K., 2023, Availability of groundwater from the volcanic aquifers of the Hawaiian Islands: U.S. Geological Survey Fact Sheet 2023-3010, 4 p., https://doi.org/10.3133/fs20233010.","linkHelpText":"- Availability of Groundwater from the Volcanic Aquifers of the Hawaiian 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Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818

","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-04-27","revisedDate":"2023-06-02","noUsgsAuthors":false,"publicationDate":"2023-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Izuka, Scot K. 0000-0002-8758-9414 skizuka@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-9414","contributorId":2645,"corporation":false,"usgs":true,"family":"Izuka","given":"Scot","email":"skizuka@usgs.gov","middleInitial":"K.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotzoll, Kolja 0000-0002-5910-888X kolja@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":3325,"corporation":false,"usgs":true,"family":"Rotzoll","given":"Kolja","email":"kolja@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":870619,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70245410,"text":"70245410 - 2023 - Trends, impacts, and cost of catastrophic and frequent wildfires in the sagebrush biome","interactions":[],"lastModifiedDate":"2023-06-28T15:29:40.122401","indexId":"70245410","displayToPublicDate":"2023-04-27T07:17:53","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Trends, impacts, and cost of catastrophic and frequent wildfires in the sagebrush biome","docAbstract":"

Fire regimes in sagebrush (Artemisia spp.) ecosystems have been greatly altered across the western United States. Broad-scale invasion of non-native annual grasses, climate change, and human activities have accelerated wildfire cycles, increased fire size and severity, and lengthened fire seasons in many sagebrush ecosystems to the point that current wildfire-management practices and postfire restoration efforts cannot keep pace to ameliorate the ecological consequences of sagebrush ecosystem loss. The greatest impact of uncharacteristically frequent fire is the transition from native sagebrush-perennial grass communities to invasive, non-native, annual grasslands that are highly flammable. These community transitions are often permanent, owing to the low probability of reestablishing native perennial plants in non-native annual grass−dominated communities. Moreover, these grasses can form extensive and continuous fine fuel loads that promote more frequent fire and the continued expansion of invasive, non-native annuals. More frequent, larger, and severe wildfires necessitate greater resources for fire-prevention, fire-suppression, and postfire restoration activities, while decreasing critical ecosystem services, economic and recreational opportunities, and cultural traditions. Increased flexibility and better prioritization of management activities based on ecological needs, including commitment to long-term prefire and postfire management, are needed to achieve notable reductions in uncharacteristic wildfire activity and associated negative impacts. Collaboration and partnerships across jurisdictional boundaries, agencies, and disciplines can improve consistency in sagebrush-management approaches and thereby contribute to this effort. Here, we provide a synthesis on sagebrush wildfire trends and the impacts of uncharacteristic fire regimes on sagebrush plant communities, dependent wildlife species, fire-suppression costs, and ecosystem services. We also provide an overview of wildland fire coordination efforts among federal, state, and tribal entities.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2023.03.003","usgsCitation":"Crist, M., Belger, R., Davies, K.W., Davis, D.M., Meldrum, J., Shinneman, D.J., Remington, T., Welty, J.L., and Mayer, K., 2023, Trends, impacts, and cost of catastrophic and frequent wildfires in the sagebrush biome: Rangeland Ecology and Management, v. 89, p. 3-19, https://doi.org/10.1016/j.rama.2023.03.003.","productDescription":"17 p.","startPage":"3","endPage":"19","ipdsId":"IP-135374","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":443700,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2023.03.003","text":"Publisher Index Page"},{"id":418395,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.80334132163102,\n 50.11516069052493\n ],\n [\n -125.80334132163102,\n 34.23519350478195\n ],\n [\n -100.76525585723665,\n 34.23519350478195\n ],\n [\n -100.76525585723665,\n 50.11516069052493\n ],\n [\n -125.80334132163102,\n 50.11516069052493\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Crist, Michele R.","contributorId":178453,"corporation":false,"usgs":false,"family":"Crist","given":"Michele R.","affiliations":[],"preferred":false,"id":876050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belger, Rick","contributorId":311213,"corporation":false,"usgs":false,"family":"Belger","given":"Rick","email":"","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":876051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davies, Kirk W.","contributorId":255108,"corporation":false,"usgs":false,"family":"Davies","given":"Kirk","email":"","middleInitial":"W.","affiliations":[{"id":51433,"text":"Eastern Oregon Agricultural Research Center, USDA Agricultural Research Service, Burns, OR 97720 USA","active":true,"usgs":false}],"preferred":false,"id":876052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Dawn M.","contributorId":254959,"corporation":false,"usgs":false,"family":"Davis","given":"Dawn","email":"","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":876053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":876054,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":876055,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Remington, Thomas E.","contributorId":296730,"corporation":false,"usgs":false,"family":"Remington","given":"Thomas E.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":876056,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Welty, Justin L. 0000-0001-7829-7324 jwelty@usgs.gov","orcid":"https://orcid.org/0000-0001-7829-7324","contributorId":4206,"corporation":false,"usgs":true,"family":"Welty","given":"Justin","email":"jwelty@usgs.gov","middleInitial":"L.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":876057,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mayer, Kenneth E. 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","affiliations":[],"preferred":false,"id":876058,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70242864,"text":"sir20235034 - 2023 - Developing a habitat model to support management of threatened seabeach amaranth (Amaranthus pumilus) at Assateague Island National Seashore, Maryland and Virginia","interactions":[],"lastModifiedDate":"2026-03-06T21:10:26.74788","indexId":"sir20235034","displayToPublicDate":"2023-04-26T14:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5034","displayTitle":"Developing a Habitat Model To Support Management of Threatened Seabeach Amaranth (Amaranthus pumilus) at Assateague Island National Seashore, Maryland and Virginia","title":"Developing a habitat model to support management of threatened seabeach amaranth (Amaranthus pumilus) at Assateague Island National Seashore, Maryland and Virginia","docAbstract":"

Amaranthus pumilus (seabeach amaranth) is a federally threatened plant species that has been the focus of restoration efforts at Assateague Island National Seashore (ASIS). Despite several years with strong population numbers prior to 2010, monitoring efforts have revealed a significant decline in the seabeach amaranth population since that time, the causes of which have been unclear. To examine potential causes for the population decreases, and to help inform management practices for the future, we first evaluated 20 years of plant population data and three seasons of physical landscape characteristics of seabeach amaranth sites spanning the period of decline to assess how these may have contributed to decreases in habitat. Plant population trends, grazing data, and precipitation data indicate the population declines coincided with severe storms and periods of drought. Furthermore, we found that plants tended to occur at sites on portions of ASIS that were lower elevation on narrower regions of the island than sites where plants were not observed. Secondly, using two different data sampling schemes, we developed Bayesian networks to calculate probabilities of habitat and evaluate the importance of different variables, particularly morphologic metrics, included in the Bayesian networks. Model analyses showed that variables capturing the presence of, and proximity to, the seed bank were important for accurate hindcasts, and that specific barrier-island morphologies tended to occur at sites where seabeach amaranth was observed. More specifically, favorable habitat sites tended to be those more likely to experience overwash during high-water events, consistent with the long-held observations that the plants tend to occur in disturbance-prone settings. Model outputs provide spatially explicit maps of relative habitat suitability and helped to identify high-priority areas for amaranth protection. The modeling effort may also assist in determining the management actions most likely to result in the preservation of a long-term sustainable population.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235034","collaboration":"Prepared in cooperation with U.S. National Park Service, Assateague Island National Seashore","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"Gutierrez, B.T., and Lentz, E.E., 2023, Developing a habitat model to support management of threatened seabeach amaranth (Amaranthus pumilus) at Assateague Island National Seashore, Maryland and Virginia: U.S. Geological Survey Scientific Investigations Report 2023–5034, 62 p., https://doi.org/10.3133/sir20235034.","productDescription":"Report: viii, 62 p.; 2 Data Releases","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-138169","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":500902,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114696.htm","linkFileType":{"id":5,"text":"html"}},{"id":416084,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GKXN3H","text":"USGS data release","linkHelpText":"Seabeach amaranth presence-absence and barrier island geomorphology metrics as relates to shorebird habitat for Assateague Island National Seashore—2008, 2010, and 2014"},{"id":416083,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IZMQ1B","text":"USGS data release","linkHelpText":"Assateague Island seabeach amaranth survey data—2001 to 2018"},{"id":416078,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5034/coverthb.jpg"},{"id":416081,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5034/sir20235034.XML"},{"id":416082,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5034/images/"},{"id":416079,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5034/sir20235034.pdf","text":"Report","size":"14.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5034"},{"id":416080,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235034/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5034"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Assateague Island National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.404961539858,\n 37.96286804133118\n ],\n [\n -75.43790635269107,\n 37.87190276298624\n ],\n [\n -75.41868854520543,\n 37.83288321389344\n ],\n [\n -75.3280903099138,\n 37.813365696066924\n ],\n [\n -75.18532945430236,\n 37.95204474129373\n ],\n [\n -75.11943982863623,\n 38.09046248604372\n ],\n [\n -75.07002260938577,\n 38.23940103731053\n ],\n [\n -75.06727720831641,\n 38.334217385797814\n ],\n [\n -75.08649501580261,\n 38.39664223886004\n ],\n [\n -75.15787544360805,\n 38.37297018430121\n ],\n [\n -75.25670988210835,\n 38.245869722482354\n ],\n [\n -75.28690929387204,\n 38.12502605709048\n ],\n [\n -75.37201672702491,\n 37.9780179817395\n ],\n [\n -75.404961539858,\n 37.96286804133118\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road Quissett Campus
Woods Hole, MA 02543-1598

","tableOfContents":"","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2023-04-26","noUsgsAuthors":false,"publicationDate":"2023-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Gutierrez, Benjamin T. 0000-0002-1879-7893 bgutierrez@usgs.gov","orcid":"https://orcid.org/0000-0002-1879-7893","contributorId":2924,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"bgutierrez@usgs.gov","middleInitial":"T.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lentz, Erika E. 0000-0002-0621-8954 elentz@usgs.gov","orcid":"https://orcid.org/0000-0002-0621-8954","contributorId":173964,"corporation":false,"usgs":true,"family":"Lentz","given":"Erika","email":"elentz@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":870047,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70256483,"text":"70256483 - 2023 - Movement and genomic methods reveal mechanisms promoting connectivity in a declining shorebird: The lesser yellowlegs","interactions":[],"lastModifiedDate":"2024-08-07T15:26:01.766255","indexId":"70256483","displayToPublicDate":"2023-04-26T10:12:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"Movement and genomic methods reveal mechanisms promoting connectivity in a declining shorebird: The lesser yellowlegs","docAbstract":"

Integrating tracking technology and molecular approaches provides a comprehensive picture of contemporary and evolutionary mechanisms promoting connectivity. We used mitochondrial DNA and double digest restriction-site associated DNA (ddRAD) sequencing combined with satellite telemetry to investigate the connectivity of geographically disparate breeding populations of a declining boreal shorebird, the lesser yellowlegs (Tringa flavipes). We were able to track 33 individuals on their round-trip migrations to Central and South America and back to the boreal wetlands of North America. Nearly all (93%) adults captured on the breeding grounds returned to within 5 km of the original capture site, with a median dispersal distance of 629 m. While our telemetry data revealed limited breeding dispersal in adults, genetic data uncovered significant interconnectedness across the species’ range. Very little genetic structure was estimated at ddRAD autosomal (ΦST = 0.001), Z-linked (ΦST = 0.001), and mtDNA loci (ΦST = 0.020), and maximum likelihood-based clustering methods placed all individuals in a single cluster regardless of capture location, indicating the species is panmictic. Our data indicate that large-scale juvenile dispersal is the main mechanism maintaining connectivity in this species, resulting in the absence of genomic structure.

","language":"English","publisher":"MDPI","doi":"10.3390/d15050595","usgsCitation":"Christie, K., Wilson, R., Johnson, J., Friis, C., Harwood, C., McDuffie, L.A., Nol, E., and Sonsthagen, S.A., 2023, Movement and genomic methods reveal mechanisms promoting connectivity in a declining shorebird: The lesser yellowlegs: Diversity, v. 15, 595, 16 p., https://doi.org/10.3390/d15050595.","productDescription":"595, 16 p.","ipdsId":"IP-149982","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":443703,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d15050595","text":"Publisher Index Page"},{"id":432340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n 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ssonsthagen@usgs.gov","orcid":"https://orcid.org/0000-0001-6215-5874","contributorId":3711,"corporation":false,"usgs":true,"family":"Sonsthagen","given":"Sarah","email":"ssonsthagen@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":907591,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245603,"text":"70245603 - 2023 - A cross inoculation experiment reveals Ophidiomyces ophiodiicola and Nannizziopsis guarroi can each infect both snakes and lizards","interactions":[],"lastModifiedDate":"2023-06-26T12:27:36.184286","indexId":"70245603","displayToPublicDate":"2023-04-26T07:25:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":850,"text":"Applied and Environmental Microbiology","active":true,"publicationSubtype":{"id":10}},"title":"A cross inoculation experiment reveals Ophidiomyces ophiodiicola and Nannizziopsis guarroi can each infect both snakes and lizards","docAbstract":"
Host range and specificity are key concepts in the study of infectious diseases. However, both concepts remain largely undefined for many influential pathogens, including many fungi within the Onygenales order. This order encompasses reptile-infecting genera (Nannizziopsis, Ophidiomyces, and Paranannizziopsis) formerly classified as the Chrysosporium anamorph of Nannizziopsis vriesii (CANV). The reported hosts of many of these fungi represent a narrow range of phylogenetically related animals, suggesting that many of these disease-causing fungi are host specific, but the true number of species affected by these pathogens is unknown. For example, to date, Nannizziopsis guarroi (the causative agent of yellow fungus disease) and Ophidiomyces ophiodiicola (the causative agent of snake fungal disease) have been documented only in lizards and snakes, respectively. In a 52-day reciprocal-infection experiment, we tested the ability of these two pathogens to infect currently unreported hosts, inoculating central bearded dragons (Pogona vitticeps) with O. ophiodiicola and corn snakes (Pantherophis guttatus) with N. guarroi. We confirmed infection by documenting both clinical signs and histopathological evidence of fungal infection. Our reciprocity experiment resulted in 100% of corn snakes and 60% of bearded dragons developing infections with N. guarroi and O. ophiodiicola, respectively, demonstrating that these fungal pathogens have a broader host range than previously thought and that hosts with cryptic infections may play a role in pathogen translocation and transmission.
","language":"English","publisher":"American Society for Microbiology","doi":"10.1128/aem.02168-22","usgsCitation":"Gentry, S.L., Lorch, J., Lankton, J.S., and Pringle, A., 2023, A cross inoculation experiment reveals Ophidiomyces ophiodiicola and Nannizziopsis guarroi can each infect both snakes and lizards: Applied and Environmental Microbiology, v. 89, no. 5, https://doi.org/10.1128/aem.02168-22.","ipdsId":"IP-150817","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":443704,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10231240","text":"External Repository"},{"id":418458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gentry, Savannah L","contributorId":267882,"corporation":false,"usgs":false,"family":"Gentry","given":"Savannah","email":"","middleInitial":"L","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":876224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lorch, Jeffrey M. 0000-0003-2239-1252","orcid":"https://orcid.org/0000-0003-2239-1252","contributorId":260164,"corporation":false,"usgs":true,"family":"Lorch","given":"Jeffrey M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":876225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lankton, Julia S. 0000-0002-6843-4388 jlankton@usgs.gov","orcid":"https://orcid.org/0000-0002-6843-4388","contributorId":5888,"corporation":false,"usgs":true,"family":"Lankton","given":"Julia","email":"jlankton@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":876226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pringle, Anne","contributorId":267883,"corporation":false,"usgs":false,"family":"Pringle","given":"Anne","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":876227,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70243365,"text":"70243365 - 2023 - Successful hindcast of 7 years of mud morphodynamics influenced by salt pond restoration in south San Francisco Bay","interactions":[],"lastModifiedDate":"2023-05-10T12:07:56.61287","indexId":"70243365","displayToPublicDate":"2023-04-26T07:03:57","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Successful hindcast of 7 years of mud morphodynamics influenced by salt pond restoration in south San Francisco Bay","docAbstract":"

Alviso Slough in South San Francisco Bay has been experiencing restoration of adjacent former salt-production ponds into muted tidal ponds, tidal ponds, and salt marsh. As a result, tidal prism through Alviso Slough has increased and mercury-contaminated sediment has been remobilized. We developed a 2D, high-resolution, process-based model (Delft3D FM-wave) to hindcast observed morpho-dynamic developments and to investigate associated sediment flux in the slough and pond system. Our results contrastingly demonstrate that a successful hindcast of the observed morphodynamic trend is made while reproducing observed intratidal suspended sediment concentrations in Alviso Slough remains a challenge. Our explanation is that the model is able to capture spatial gradients in the tide-residual sediment transports as the result of the large-scale management actions in the system, i.e., the opening of the salt ponds. These tide-residual processes are generally difficult to measure over an entire domain, but are very relevant to model the morphodynamic development. Our model provides a promising tool to trace eroding contaminated sediments to the benefit of restoration project managers and to support planning and design phases of adaptive management measures.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments Proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0103","usgsCitation":"Van der Wegen, M., Reyns, J., Jaffe, B.E., Foxgrover, A.C., Achete, F., Marvin-DiPasquale, M.C., Fregoso, T.A., Nam, J., and Lovering, J., 2023, Successful hindcast of 7 years of mud morphodynamics influenced by salt pond restoration in south San Francisco Bay, in Coastal Sediments Proceedings, p. 1129-1134, https://doi.org/10.1142/9789811275135_0103.","productDescription":"6 p.","startPage":"1129","endPage":"1134","ipdsId":"IP-147951","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"South San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.7132117678304,\n 37.927707430220735\n ],\n [\n -122.7132117678304,\n 37.06078554622208\n ],\n [\n -121.29658481599789,\n 37.06078554622208\n ],\n [\n -121.29658481599789,\n 37.927707430220735\n ],\n [\n -122.7132117678304,\n 37.927707430220735\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Van der Wegen, Mick","contributorId":191095,"corporation":false,"usgs":false,"family":"Van der Wegen","given":"Mick","email":"","affiliations":[],"preferred":false,"id":872171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reyns, Johan","contributorId":224304,"corporation":false,"usgs":false,"family":"Reyns","given":"Johan","email":"","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":872172,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":872173,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foxgrover, Amy C. 0000-0003-0638-5776 afoxgrover@usgs.gov","orcid":"https://orcid.org/0000-0003-0638-5776","contributorId":3261,"corporation":false,"usgs":true,"family":"Foxgrover","given":"Amy","email":"afoxgrover@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872174,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Achete, Fernanda","contributorId":174686,"corporation":false,"usgs":false,"family":"Achete","given":"Fernanda","email":"","affiliations":[{"id":27497,"text":"UNESCO-IHE, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":872175,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":872176,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fregoso, Theresa A. 0000-0001-7802-5812 tfregoso@usgs.gov","orcid":"https://orcid.org/0000-0001-7802-5812","contributorId":2571,"corporation":false,"usgs":true,"family":"Fregoso","given":"Theresa","email":"tfregoso@usgs.gov","middleInitial":"A.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":872177,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nam, Judy 0000-0002-3190-9570","orcid":"https://orcid.org/0000-0002-3190-9570","contributorId":304991,"corporation":false,"usgs":false,"family":"Nam","given":"Judy","email":"","affiliations":[{"id":66200,"text":"Valley Water","active":true,"usgs":false}],"preferred":false,"id":872178,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lovering, Jessica 0000-0002-0705-9633","orcid":"https://orcid.org/0000-0002-0705-9633","contributorId":304992,"corporation":false,"usgs":false,"family":"Lovering","given":"Jessica","affiliations":[{"id":66200,"text":"Valley Water","active":true,"usgs":false}],"preferred":false,"id":872179,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70243161,"text":"70243161 - 2023 - Climate change and pulse migration: Intermittent Chugach Inuit occupation of glacial fiords on the Kenai Coast, Alaska","interactions":[],"lastModifiedDate":"2023-05-02T12:02:04.096155","indexId":"70243161","displayToPublicDate":"2023-04-26T06:59:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":14265,"text":"Frontiers in Environmental Archaeology","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and pulse migration: Intermittent Chugach Inuit occupation of glacial fiords on the Kenai Coast, Alaska","docAbstract":"

For millennia, Inuit peoples of the Arctic and Subarctic have been challenged by the impacts of climate change on the abundance of key subsistence species. Responses to climate-induced declines in animal populations included switching to alternative food sources and/or migrating to regions of greater availability. We examine these dynamics for the Chugach Inuit (Sugpiat) people of southern coastal Alaska by synthesizing a large body of evidence from archeological sites, including radiocarbon dates and archaeofaunal assemblages, and by applying contemporary knowledge of glaciomarine ecosystems, spatial patterns of resource richness, and ocean-climate induced regime shifts in the Gulf of Alaska. We hypothesize that Chugach groups migrated from Cook Inlet and Prince William Sound to the Kenai Peninsula during periods of low sea surface temperatures (SSTs) to harvest harbor seals, which were seasonally aggregated near tidewater glaciers during pupping season, as well as piscivorous seabirds, Pacific cod, and other species that thrive under cool ocean conditions. During warming phases, the Chugach returned to Cook Inlet and Prince William Sound to fish for salmon and other species that abound during higher SSTs. Drivers of this coupled human-natural system of repeated (pulse) migration include the Pacific Decadal Oscillation (PDO), the dominant pattern of sea surface temperatures in the North Pacific that has been shown to generate step-like regime shifts in the marine food web; and coastal glaciers that structure the functioning of fiord ecosystems and support high levels of biological productivity. The culturally-constructed Chugach niche in the glaciomarine habitat of the Gulf of Alaska was based on intergenerationally transmitted ecological knowledge that enabled a resilient, mobile response to climate and resource variation.

","language":"English","publisher":"Frontiers","doi":"10.3389/fearc.2023.1145220","usgsCitation":"Crowell, A., and Arimitsu, M.L., 2023, Climate change and pulse migration: Intermittent Chugach Inuit occupation of glacial fiords on the Kenai Coast, Alaska: Frontiers in Environmental Archaeology, v. 2, 1145220, 27 p., https://doi.org/10.3389/fearc.2023.1145220.","productDescription":"1145220, 27 p.","ipdsId":"IP-148731","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":443708,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fearc.2023.1145220","text":"Publisher Index Page"},{"id":416608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -153.6742409456726,\n 58.647094281081024\n ],\n [\n -145.5039273630105,\n 58.647094281081024\n ],\n [\n -145.5039273630105,\n 61.64055146403999\n ],\n [\n -153.6742409456726,\n 61.64055146403999\n ],\n [\n -153.6742409456726,\n 58.647094281081024\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","noUsgsAuthors":false,"publicationDate":"2023-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Crowell, Aron","contributorId":304674,"corporation":false,"usgs":false,"family":"Crowell","given":"Aron","email":"","affiliations":[{"id":66145,"text":"Arctic Studies Center, Smithsonian","active":true,"usgs":false}],"preferred":false,"id":871312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arimitsu, Mayumi L. 0000-0001-6982-2238 marimitsu@usgs.gov","orcid":"https://orcid.org/0000-0001-6982-2238","contributorId":140501,"corporation":false,"usgs":true,"family":"Arimitsu","given":"Mayumi","email":"marimitsu@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":871313,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70246285,"text":"70246285 - 2023 - Challenges and solutions for automated avian recognition in aerial imagery","interactions":[],"lastModifiedDate":"2023-09-06T16:14:37.067823","indexId":"70246285","displayToPublicDate":"2023-04-26T06:52:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5347,"text":"Remote Sensing in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Challenges and solutions for automated avian recognition in aerial imagery","docAbstract":"

Remote aerial sensing provides a non-invasive, large geographical-scale technology for avian monitoring, but the manual processing of images limits its development and applications. Artificial Intelligence (AI) methods can be used to mitigate this manual image processing requirement. The implementation of AI methods, however, has several challenges: (1) imbalanced (i.e., long-tailed) data distribution, (2) annotation uncertainty in categorization, and (3) dataset discrepancies across different study sites. Here we use aerial imagery data of waterbirds around Cape Cod and Lake Michigan in the United States to examine how these challenges limit avian recognition performance. We review existing solutions and demonstrate as use cases how methods like Label Distribution Aware Marginal Loss with Deferred Re-Weighting, hierarchical classification, and FixMatch address the three challenges. We also present a new approach to tackle the annotation uncertainty challenge using a Soft-fine Pseudo-Label methodology. Finally, we aim with this paper to increase awareness in the ecological remote sensing community of these challenges and bridge the gap between ecological applications and state-of-the-art computer science, thereby opening new doors to future research.

","language":"English","publisher":"Zoological Society of London","doi":"10.1002/rse2.318","usgsCitation":"Miao, Z., Yu, S.X., Landolt, K.L., Koneff, M.D., White, T., Fara, L., Hlavacek, E., Pickens, B.A., Harrison, T.J., and Getz, W., 2023, Challenges and solutions for automated avian recognition in aerial imagery: Remote Sensing in Ecology and Conservation, v. 9, no. 4, p. 439-453, https://doi.org/10.1002/rse2.318.","productDescription":"15 p.","startPage":"439","endPage":"453","ipdsId":"IP-140903","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":443712,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.318","text":"Publisher Index Page"},{"id":435355,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YL80R6","text":"USGS data release","linkHelpText":"Images and annotations to automate the classification of avian species"},{"id":418651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Miao, Zhonqgi","contributorId":315481,"corporation":false,"usgs":false,"family":"Miao","given":"Zhonqgi","email":"","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":876648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Stella X","contributorId":315482,"corporation":false,"usgs":false,"family":"Yu","given":"Stella","email":"","middleInitial":"X","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":876649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landolt, Kyle Lawrence 0000-0002-6738-8586","orcid":"https://orcid.org/0000-0002-6738-8586","contributorId":298782,"corporation":false,"usgs":true,"family":"Landolt","given":"Kyle","email":"","middleInitial":"Lawrence","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":876650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koneff, Mark D.","contributorId":191128,"corporation":false,"usgs":false,"family":"Koneff","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":876651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Timothy","contributorId":236917,"corporation":false,"usgs":false,"family":"White","given":"Timothy","email":"","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":true,"id":876652,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fara, Luke J. 0000-0002-1143-4395","orcid":"https://orcid.org/0000-0002-1143-4395","contributorId":202973,"corporation":false,"usgs":true,"family":"Fara","given":"Luke J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":876653,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hlavacek, Enrika 0000-0002-9872-2305","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":297184,"corporation":false,"usgs":false,"family":"Hlavacek","given":"Enrika","affiliations":[{"id":48800,"text":"Former USGS, UMESC employee","active":true,"usgs":false}],"preferred":false,"id":876654,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pickens, Bradley A.","contributorId":140926,"corporation":false,"usgs":false,"family":"Pickens","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":876655,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":876656,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Getz, Wayne M.","contributorId":287152,"corporation":false,"usgs":false,"family":"Getz","given":"Wayne M.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":876657,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70246660,"text":"70246660 - 2023 - Factors influencing egg thiamine concentrations of Lake Ontario lake trout: 2019–2020","interactions":[],"lastModifiedDate":"2023-07-26T14:47:21.745119","indexId":"70246660","displayToPublicDate":"2023-04-26T06:42:57","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Factors influencing egg thiamine concentrations of Lake Ontario lake trout: 2019–2020","docAbstract":"

In the Great Lakes region, thiamine deficiency is considered a recruitment bottleneck for lake trout Salvelinus namaycush and has been correlated with the consumption of non-native alewife Alosa pseudoharengus. While alewife, the most abundant forage fish in Lake Ontario, are the predominant prey for lake trout, they also consume benthic prey such as round goby Neogobius melanostomus. Because variation in the proportion of alewife in lake trout diets is linked to variation in egg thiamine concentrations, understanding how factors such as region of capture and hatchery-strain of lake trout influence diet, are key to understanding the patterns of variation in egg thiamine concentrations observed in this species. With recent increases in natural recruitment of lake trout being observed in the western region of the lake, understanding if egg thiamine is a potential driver is crucial to the rehabilitation of lake trout. In this study, we evaluated egg thiamine concentrations in lake trout during 2019–2020. We found no significant difference in egg thiamine concentrations among regions. However, a stocked Lake Superior deepwater morphotype (Superior Klondike Wild – SKW) showed significantly higher egg thiamine concentrations compared to the lean morphotype including Seneca (SEN) and Lake Champlain Domestic (LCD) strains. An analysis of fatty acid signatures of each hatchery-strain suggested that the SKW strain consumed a higher proportion of round goby than lean strains. Overall, these results suggest that morphotypic differences in the feeding ecology of lake trout can result in biochemical changes which may influence the effectiveness of restoration efforts.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2023.04.002","usgsCitation":"Heisey, A., Osborne, C., Lantry, B.F., Tillitt, D.E., and Rinchard, J., 2023, Factors influencing egg thiamine concentrations of Lake Ontario lake trout: 2019–2020: Journal of Great Lakes Research, v. 49, no. 4, p. 836-846, https://doi.org/10.1016/j.jglr.2023.04.002.","productDescription":"11 p.","startPage":"836","endPage":"846","ipdsId":"IP-143381","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":418918,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.02742785531385,\n 44.41332381875361\n ],\n [\n -80.02742785531385,\n 43.12875061749628\n ],\n [\n -75.78852391265744,\n 43.12875061749628\n ],\n [\n -75.78852391265744,\n 44.41332381875361\n ],\n [\n -80.02742785531385,\n 44.41332381875361\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"49","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Heisey, Aaron 0000-0001-9897-7546","orcid":"https://orcid.org/0000-0001-9897-7546","contributorId":316602,"corporation":false,"usgs":false,"family":"Heisey","given":"Aaron","affiliations":[{"id":68652,"text":"State Univeristy of New York College at Brockport","active":true,"usgs":false}],"preferred":false,"id":877822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osborne, Christopher 0000-0001-6387-5451","orcid":"https://orcid.org/0000-0001-6387-5451","contributorId":316603,"corporation":false,"usgs":false,"family":"Osborne","given":"Christopher","email":"","affiliations":[{"id":68653,"text":"State Univeristy of New York College University of Buffalo","active":true,"usgs":false}],"preferred":false,"id":877823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":877916,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":877824,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rinchard, Jacques 0000-0002-6247-2551","orcid":"https://orcid.org/0000-0002-6247-2551","contributorId":316604,"corporation":false,"usgs":false,"family":"Rinchard","given":"Jacques","email":"","affiliations":[{"id":68652,"text":"State Univeristy of New York College at Brockport","active":true,"usgs":false}],"preferred":false,"id":877825,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}