{"pageNumber":"78","pageRowStart":"1925","pageSize":"25","recordCount":41031,"records":[{"id":70257578,"text":"70257578 - 2024 - Mitigating risk: Predicting H5N1 avian influenza spread with an empirical model of bird movement","interactions":[],"lastModifiedDate":"2024-08-20T10:52:55.014462","indexId":"70257578","displayToPublicDate":"2024-07-18T12:51:22","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Mitigating risk: Predicting H5N1 avian influenza spread with an empirical model of bird movement","docAbstract":"Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting ~600 bird and mammal species globally and over 83 million birds across North America (Dec 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was effective for wild waterfowl, but predictions lagged HPAIv detections in poultry facilities and among some highly impacted non-migratory species. Our results offer critical advance warning for applied biosecurity management and planning and demonstrate the importance and utility of extensive multi-species tracking to highlight potential high-risk disease spread locations and more effectively manage outbreaks.","language":"English","publisher":"Wiley","doi":"10.1155/2024/5525298","usgsCitation":"McDuie, F., Overton, C.T., Lorenz, A., Matchett, E., Mott, A., Mackell, D.A., Ackerman, J.T., De La Cruz, S.E., Patil, V.P., Prosser, D., Takekawa, J., Orthmeyer, D.L., Pitesky, M.E., Diaz-Munoz, S.L., Riggs, B.M., Gendreau, J., Reed, E.T., Petrie, M.J., Williams, C.K., Buler, J.J., Hardy, M., Ladman, B.S., Legagneux, P., Bety, J., Thomas, P.J., Rodrigue, J., Lefebvre, J., and Casazza, M.L., 2024, Mitigating risk: Predicting H5N1 avian influenza spread with an empirical model of bird movement: Transboundary and Emerging Diseases, 5525298, 15 p.; Data Release, https://doi.org/10.1155/2024/5525298.","productDescription":"5525298, 15 p.; 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Delaware","active":true,"usgs":false}],"preferred":false,"id":910934,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Ladman, Brian S.","contributorId":337102,"corporation":false,"usgs":false,"family":"Ladman","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":910935,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Legagneux, Pierre","contributorId":337103,"corporation":false,"usgs":false,"family":"Legagneux","given":"Pierre","email":"","affiliations":[],"preferred":false,"id":910936,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Bety, Joel","contributorId":203661,"corporation":false,"usgs":false,"family":"Bety","given":"Joel","email":"","affiliations":[{"id":36676,"text":"Université du Québec à Rimouski","active":true,"usgs":false}],"preferred":false,"id":910937,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Thomas, Philippe 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,{"id":70256225,"text":"70256225 - 2024 - Upland Yedoma taliks are an unpredicted source of atmospheric methane","interactions":[],"lastModifiedDate":"2024-07-29T15:11:35.111347","indexId":"70256225","displayToPublicDate":"2024-07-18T10:00:20","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Upland Yedoma taliks are an unpredicted source of atmospheric methane","docAbstract":"<p><span>Landscape drying associated with permafrost thaw is expected to enhance microbial methane oxidation in arctic soils. Here we show that ice-rich, Yedoma permafrost deposits, comprising a disproportionately large fraction of pan-arctic soil carbon, present an alternate trajectory. Field and laboratory observations indicate that talik (perennially thawed soils in permafrost) development in unsaturated Yedoma uplands leads to unexpectedly large methane emissions (35–78 mg m</span><sup>−2</sup><span> d</span><sup>−1</sup><span>&nbsp;summer, 150–180 mg m</span><sup>−2</sup><span> d</span><sup>−1</sup><span>&nbsp;winter). Upland Yedoma talik emissions were nearly three times higher annually than northern-wetland emissions on an areal basis. Approximately 70% emissions occurred in winter, when surface-soil freezing abated methanotrophy, enhancing methane escape from the talik. Remote sensing and numerical modeling indicate the potential for widespread upland talik formation across the pan-arctic Yedoma domain during the 21</span><sup>st</sup><span>&nbsp;and 22</span><sup>nd</sup><span>&nbsp;centuries. Contrary to current climate model predictions, these findings imply a positive and much larger permafrost-methane-climate feedback for upland Yedoma.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41467-024-50346-5","usgsCitation":"Walter Anthony, K., Hasson, N., Edgar, C.W., Sivan, O., Eliani-Russak, E., Bergman, O., Minsley, B.J., James, S.R., Pastick, N.J., Kholodov, A., Zimov, S., Euskirchen, E., Bret-Harte, M.S., Grosse, G., Langer, M., and Nitzbon, J., 2024, Upland Yedoma taliks are an unpredicted source of atmospheric methane: Nature Communications, v. 15, 6056, 17 p., https://doi.org/10.1038/s41467-024-50346-5.","productDescription":"6056, 17 p.","ipdsId":"IP-155147","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":439269,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-024-50346-5","text":"Publisher Index Page"},{"id":431566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","state":"Alaska, Siberia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.9,\n              76.86788949762968\n            ],\n            [\n              -179.9,\n              60\n            ],\n            [\n              -115.26276297805447,\n              60\n            ],\n            [\n              -115.26276297805447,\n              76.86788949762968\n            ],\n            [\n              -179.9,\n              76.86788949762968\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        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Fairbanks","active":true,"usgs":false}],"preferred":false,"id":907143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hasson, Nicholas","contributorId":270233,"corporation":false,"usgs":false,"family":"Hasson","given":"Nicholas","email":"","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":907144,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edgar, Colin W. 0000-0002-7026-8358","orcid":"https://orcid.org/0000-0002-7026-8358","contributorId":260621,"corporation":false,"usgs":false,"family":"Edgar","given":"Colin","email":"","middleInitial":"W.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":907145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sivan, Orit","contributorId":340439,"corporation":false,"usgs":false,"family":"Sivan","given":"Orit","email":"","affiliations":[{"id":81608,"text":"Ben Gurion 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Sergey","contributorId":238033,"corporation":false,"usgs":false,"family":"Zimov","given":"Sergey","email":"","affiliations":[{"id":47689,"text":"Northeast Science Station, Far Eastern Branch of Russian Academy of Science, Chersky, Russia","active":true,"usgs":false}],"preferred":false,"id":907153,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Euskirchen, Eugenie","contributorId":330061,"corporation":false,"usgs":false,"family":"Euskirchen","given":"Eugenie","affiliations":[{"id":78786,"text":"University of Alaska Fairbanks, Fairbanks, AK, USA 99775","active":true,"usgs":false}],"preferred":false,"id":907154,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bret-Harte, Marion S.","contributorId":340443,"corporation":false,"usgs":false,"family":"Bret-Harte","given":"Marion","email":"","middleInitial":"S.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":907155,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":907156,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Langer, Moritz","contributorId":194630,"corporation":false,"usgs":false,"family":"Langer","given":"Moritz","email":"","affiliations":[],"preferred":false,"id":907157,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Nitzbon, Jan","contributorId":340444,"corporation":false,"usgs":false,"family":"Nitzbon","given":"Jan","email":"","affiliations":[{"id":81612,"text":"Alfred Wegener Institute Helmholtz Centre for Polar and Marine 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,{"id":70259514,"text":"70259514 - 2024 - Challenges of implementing a multi-agency monitoring and adaptive management strategy for federally threatened Chinook salmon and steelhead trout during and after dam removal in the Elwha River","interactions":[],"lastModifiedDate":"2024-10-10T14:56:10.219244","indexId":"70259514","displayToPublicDate":"2024-07-18T09:46:05","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Challenges of implementing a multi-agency monitoring and adaptive management strategy for federally threatened Chinook salmon and steelhead trout during and after dam removal in the Elwha River","docAbstract":"<p><span>Adaptive management, a process of planning, implementing, and evaluating management strategies, is often recommended for monitoring ecological systems. However, few examples of successful implementation and retrospective case studies exist. We provide a case study of adaptively managing hatchery-assisted protection and recovery for Chinook salmon (</span><i>Oncorhynchus tshawytscha</i><span>) and winter steelhead trout (</span><i>O. mykiss</i><span>) during and after the removal of two large mainstem dams in the Elwha River, WA. We summarize key aspects of the monitoring and adaptive management plan over the last decade and highlight successes, challenges, and complications during the plan’s implementation. The Elwha Monitoring and Adaptive Management Guidelines included a trigger-based system for moving through four phases of recovery that included preservation, recolonization, local adaptation, and viable natural population, each with differing levels of hatchery production as the management actions. The monitoring component of the plan has been very successful, providing critical data to guide management actions that otherwise may not have occurred and, opportunistically, provided data for other native species in the Elwha River. Implementing adaptive management provided mixed results and was at times hindered by divergent management goals among project partners, the inflexibility of the Endangered Species Act regulatory requirements as implemented for this project, and conflicting information among guidance documents. We learned that some metrics and triggers in the plan were ill-defined or too difficult to measure in the field. In some cases, the performance indicators and/or triggers were successfully modified to incorporate what was learned; however, in other cases, we were unable to revise the values due to differing opinions among partners. The ability to reach consensus on revised triggers appeared to be influenced by the recovery trajectory of the species involved. The implemented adaptive management strategy resulted in substantial collaboration and learning, which resulted in revised management strategies, but was imperfect. Sufficient long-term funding is necessary to implement a well-designed monitoring program and could benefit from including a defined leadership position to shepherd and facilitate a multi-stakeholder adaptive management program. Additionally, incorporating adaptive management into legally binding conditions under the Endangered Species Act is feasible, but requires substantial pre-planning in close coordination with regulatory agencies.</span></p>","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2024.1291265","usgsCitation":"Peters, R.J., Anderson, J.H., Duda, J.J., McHenry, M.L., Pess, G., Brenkman, S.J., Johnson, J.R., Liermann, M.C., Denton, K., Beirne, M.M., Crain, P., and Connor, H.A., 2024, Challenges of implementing a multi-agency monitoring and adaptive management strategy for federally threatened Chinook salmon and steelhead trout during and after dam removal in the Elwha River: Frontiers in Environmental Science, v. 12, 1291265, 17 p., https://doi.org/10.3389/fenvs.2024.1291265.","productDescription":"1291265, 17 p.","ipdsId":"IP-158110","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":466980,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2024.1291265","text":"Publisher Index Page"},{"id":462790,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.49110493450982,\n              48.157497598161655\n            ],\n            [\n              -123.58313451051734,\n              48.15615973501194\n            ],\n            [\n              -123.59113708234375,\n              48.112104690760475\n            ],\n            [\n              -123.61814576225893,\n              47.98564091132425\n            ],\n            [\n              -123.52111457885965,\n              47.8619869781067\n            ],\n            [\n              -123.49724578407385,\n              47.76695819517391\n            ],\n            [\n              -123.56164789896958,\n              47.79088266560885\n            ],\n            [\n              -123.61514479782386,\n              47.76900531751369\n            ],\n            [\n              -123.5451222943402,\n              47.7266261365706\n            ],\n            [\n              -123.43108564580973,\n              47.727303245885054\n            ],\n            [\n              -123.4380878961579,\n              47.88508151537947\n            ],\n            [\n              -123.56112743799368,\n              48.02944171497188\n            ],\n            [\n              -123.49110493450982,\n              48.157497598161655\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2024-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Peters, Roger J.","contributorId":268126,"corporation":false,"usgs":false,"family":"Peters","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":55563,"text":"U.S. Fish and Wildlife Service, Lacey, WA, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":915558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Joseph H.","contributorId":345077,"corporation":false,"usgs":false,"family":"Anderson","given":"Joseph","email":"","middleInitial":"H.","affiliations":[{"id":82482,"text":"Washington State Department of Fish and Wildlife, Olympia, Washington, USA","active":true,"usgs":false}],"preferred":false,"id":915559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Jeffrey J. 0000-0001-7431-8634 jduda@usgs.gov","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":148954,"corporation":false,"usgs":true,"family":"Duda","given":"Jeffrey","email":"jduda@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":915560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McHenry, Michael L.","contributorId":39672,"corporation":false,"usgs":false,"family":"McHenry","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":915561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pess, George ","contributorId":219501,"corporation":false,"usgs":false,"family":"Pess","given":"George ","affiliations":[{"id":37482,"text":"National Oceanographic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":915562,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brenkman, Samuel J.","contributorId":138941,"corporation":false,"usgs":false,"family":"Brenkman","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":12587,"text":"Olympic National Park, Port Angeles, WA","active":true,"usgs":false}],"preferred":false,"id":915563,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Jeffery R.","contributorId":345078,"corporation":false,"usgs":false,"family":"Johnson","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[{"id":82484,"text":"Western Washington Fish and Wildlife Conservation Office, Lacey, Washington, USA","active":true,"usgs":false}],"preferred":false,"id":915564,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liermann, Martin C.","contributorId":139467,"corporation":false,"usgs":false,"family":"Liermann","given":"Martin","email":"","middleInitial":"C.","affiliations":[{"id":6578,"text":"National Marine Fisheries Service, Seattle, WA 98112, USA","active":true,"usgs":false}],"preferred":false,"id":915565,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Denton, Keith","contributorId":345079,"corporation":false,"usgs":false,"family":"Denton","given":"Keith","email":"","affiliations":[{"id":82485,"text":"Denton and Associates, LLC, Sequim, Washington, USA","active":true,"usgs":false}],"preferred":false,"id":915566,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Beirne, Matthew M.","contributorId":194429,"corporation":false,"usgs":false,"family":"Beirne","given":"Matthew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":915567,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Crain, Patrick","contributorId":210017,"corporation":false,"usgs":false,"family":"Crain","given":"Patrick","affiliations":[{"id":38049,"text":"National Park Service, Olympic National Park, 600 East Park Avenue, Port Angeles, WA 98362","active":true,"usgs":false}],"preferred":false,"id":915568,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Connor, Heidi A.","contributorId":268128,"corporation":false,"usgs":false,"family":"Connor","given":"Heidi","email":"","middleInitial":"A.","affiliations":[{"id":55566,"text":"National Park Service, Olympic National Park, Port Angeles, WA, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":915569,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70256591,"text":"70256591 - 2024 - Risk of invasive waterfowl interaction with poultry production: Understanding potential for avian pathogen transmission via species distribution models","interactions":[],"lastModifiedDate":"2024-08-06T12:05:26.727184","indexId":"70256591","displayToPublicDate":"2024-07-18T07:02:10","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Risk of invasive waterfowl interaction with poultry production: Understanding potential for avian pathogen transmission via species distribution models","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Recent outbreaks of highly pathogenic avian influenza have devastated poultry production across the United States, with more than 77 million birds culled in 2022–2024 alone. Wild waterfowl, including various invasive species, host numerous pathogens, including highly pathogenic avian influenza virus (HPAIV), and have been implicated as catalysts of disease outbreaks among native fauna and domestic birds. In major poultry-producing states like Arkansas, USA, where the poultry sector is responsible for significant economic activity (&gt;$4 billion USD in 2022), understanding the risk of invasive waterfowl interactions with domestic poultry is critical. Here, we assessed the risk of invasive waterfowl-poultry interaction in Arkansas by comparing the density of poultry production sites (chicken houses) to areas of high habitat suitability for two invasive waterfowl species, (Egyptian Goose [<i>Alopochen aegyptiaca</i>] and Mute Swan [<i>Cygnus olor</i>]), known to host significant pathogens, including avian influenza viruses. The percentage of urban land cover was the most important habitat characteristic for both invasive waterfowl species. At the 95% confidence interval, chicken house densities in areas highly suitable for both species (Egyptian Goose = 0.91 ± 0.11 chicken houses/km<sup>2</sup>; Mute Swan = 0.61 ± 0.03 chicken houses/km<sup>2</sup>) were three to five times higher than chicken house densities across the state (0.17 ± 0.01 chicken houses/km<sup>2</sup>). We show that northwestern and western Arkansas, both areas of high importance for poultry production, are also at high risk of invasive waterfowl presence. Our results suggest that targeted monitoring efforts for waterfowl-poultry contact in these areas could help mitigate the risk of avian pathogen exposure in Arkansas and similar regions with high poultry production.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.11647","usgsCitation":"Jackson, R.T., Marshall, P.M., Burkhart, C., Schneck, J., Kelly, G., and Roberts, C.P., 2024, Risk of invasive waterfowl interaction with poultry production: Understanding potential for avian pathogen transmission via species distribution models: Biological Invasions, v. 14, no. 7, e11647, 11 p., https://doi.org/10.1002/ece3.11647.","productDescription":"e11647, 11 p.","ipdsId":"IP-151490","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":439271,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.11647","text":"Publisher Index Page"},{"id":432269,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Jackson, Reilly T.","contributorId":341276,"corporation":false,"usgs":false,"family":"Jackson","given":"Reilly","email":"","middleInitial":"T.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":908177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Percival M.","contributorId":341277,"corporation":false,"usgs":false,"family":"Marshall","given":"Percival","email":"","middleInitial":"M.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":908178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burkhart, Chris","contributorId":341278,"corporation":false,"usgs":false,"family":"Burkhart","given":"Chris","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":908179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schneck, Julia","contributorId":341279,"corporation":false,"usgs":false,"family":"Schneck","given":"Julia","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":908180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelly, Grant","contributorId":341280,"corporation":false,"usgs":false,"family":"Kelly","given":"Grant","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":908181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roberts, Caleb Powell 0000-0002-8716-0423","orcid":"https://orcid.org/0000-0002-8716-0423","contributorId":288567,"corporation":false,"usgs":true,"family":"Roberts","given":"Caleb","email":"","middleInitial":"Powell","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908182,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70259616,"text":"70259616 - 2024 - Methods for quantifying interactions between groundwater and surface water","interactions":[],"lastModifiedDate":"2024-10-23T16:31:05.896771","indexId":"70259616","displayToPublicDate":"2024-07-18T06:44:45","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5317,"text":"Annual Review of Environment and Resources","active":true,"publicationSubtype":{"id":10}},"title":"Methods for quantifying interactions between groundwater and surface water","docAbstract":"<div id=\"abstract_content\" class=\"active tab-pane abstract tabbedsection\"><div class=\"articleabstract\"><div><div class=\"description\"><p>Driven by the need for integrated management of groundwater (GW) and surface water (SW), quantification of GW–SW interactions and associated contaminant transport has become increasingly important. This is due to their substantial impact on water quantity and quality. In this review, we provide an overview of the methods developed over the past several decades to investigate GW–SW interactions. These methods include geophysical, hydrometric, and tracer techniques, as well as various modeling approaches. Different methods reveal valuable information on GW–SW interactions at different scales with their respective advantages and limitations. Interpreting data from these techniques can be challenging due to factors like scale effects, heterogeneous hydrogeological conditions, sediment variability, and complex spatiotemporal connections between GW and SW. To facilitate the selection of appropriate methods for specific sites, we discuss the strengths, weaknesses, and challenges of each technique, and we offer perspectives on knowledge gaps in the current science.</p></div></div></div></div>","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-environ-111522-104534","usgsCitation":"Ma, R., Chen, K., Andrews, C.B., Loheide, S.P., Sawyer, A.H., Jiang, X., Briggs, M., Cook, P., Gorelick, S., Prommer, H., Scanlon, B.R., Guo, Z., and Zheng, C., 2024, Methods for quantifying interactions between groundwater and surface water: Annual Review of Environment and Resources, v. 49, p. 623-653, https://doi.org/10.1146/annurev-environ-111522-104534.","productDescription":"31 p.","startPage":"623","endPage":"653","ipdsId":"IP-161314","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":466981,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1146/annurev-environ-111522-104534","text":"Publisher Index Page"},{"id":462931,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ma, Rui","contributorId":345200,"corporation":false,"usgs":false,"family":"Ma","given":"Rui","email":"","affiliations":[{"id":82519,"text":"School of Environmental Studies, China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":915971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Kewei 0000-0002-0444-9724","orcid":"https://orcid.org/0000-0002-0444-9724","contributorId":204253,"corporation":false,"usgs":false,"family":"Chen","given":"Kewei","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":915972,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andrews, Charles B.","contributorId":345201,"corporation":false,"usgs":false,"family":"Andrews","given":"Charles","email":"","middleInitial":"B.","affiliations":[{"id":82520,"text":"S.S. Papadopulos & Associates, Inc","active":true,"usgs":false}],"preferred":false,"id":915973,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loheide, Steven P. II","contributorId":62377,"corporation":false,"usgs":false,"family":"Loheide","given":"Steven","suffix":"II","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":915974,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sawyer, Audrey H","contributorId":272060,"corporation":false,"usgs":false,"family":"Sawyer","given":"Audrey","email":"","middleInitial":"H","affiliations":[{"id":36630,"text":"Ohio State University","active":true,"usgs":false}],"preferred":false,"id":915975,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jiang, Xue","contributorId":345202,"corporation":false,"usgs":false,"family":"Jiang","given":"Xue","email":"","affiliations":[{"id":82519,"text":"School of Environmental Studies, China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":915976,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":222759,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":915977,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cook, Peter G.","contributorId":298729,"corporation":false,"usgs":false,"family":"Cook","given":"Peter G.","affiliations":[{"id":40595,"text":"Flinders University","active":true,"usgs":false}],"preferred":false,"id":915978,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gorelick, Steven M.","contributorId":345203,"corporation":false,"usgs":false,"family":"Gorelick","given":"Steven M.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":915979,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Prommer, Henning","contributorId":298649,"corporation":false,"usgs":false,"family":"Prommer","given":"Henning","email":"","affiliations":[{"id":16662,"text":"University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":915980,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Scanlon, Bridget R. 0000-0002-1234-4199","orcid":"https://orcid.org/0000-0002-1234-4199","contributorId":328586,"corporation":false,"usgs":false,"family":"Scanlon","given":"Bridget","email":"","middleInitial":"R.","affiliations":[{"id":78414,"text":"Bureau of Economic Geology, Jackson School of Geosciences, University of Texas at Austin, J.J. Pickle Research Campus, Bldg. 130, 10100 Burnet Rd., Austin, TX 78758-4445","active":true,"usgs":false}],"preferred":false,"id":915981,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Guo, Zhilin","contributorId":345204,"corporation":false,"usgs":false,"family":"Guo","given":"Zhilin","email":"","affiliations":[{"id":82521,"text":"School of Environmental Science and Engineering, Southern University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":915982,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Zheng, Chunmiao","contributorId":214041,"corporation":false,"usgs":false,"family":"Zheng","given":"Chunmiao","email":"","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":915983,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70261687,"text":"70261687 - 2024 - Quantifying compound and nonlinear effects of hurricane-induced flooding using a dynamically coupled hydrological-ocean model","interactions":[],"lastModifiedDate":"2024-12-18T17:31:19.925788","indexId":"70261687","displayToPublicDate":"2024-07-17T11:21:33","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying compound and nonlinear effects of hurricane-induced flooding using a dynamically coupled hydrological-ocean model","docAbstract":"<p><span>We recently developed a dynamically coupled hydrological-ocean modeling system that provides seamless coverage across the land-ocean continuum during hurricane-induced compound flooding. This study introduced a local inertial equation and a diagonal flow algorithm to the overland routing of the coupled system’s hydrology model (WRF-Hydro). Using Hurricane Florence (2018) as a test case, the performance of the coupled model was significantly improved, evidenced by its enhanced capability of capturing backwater and increased water level simulation accuracy and stability. With four model experiments, we present a framework to detangle, define, and quantify compound and nonlinear effects. The results revealed that the flood peaks in the lower Cape Fear River Basin and the coastal waters were contributed by inland flooding and storm surge, respectively. These two processes had comparable contributions to the flooding in the Cape Fear River Estuary. The compound effect was identified when the flood levels resulting from the combination of land and ocean processes surpassed those caused by an individual process alone. The compound effect during Hurricane Florence exhibited limited impact on flood peaks, primarily due to the time lag between the peaks of the storm surge and the inland flooding. In the period between the two peaks, the compound effect was salient and significantly impacted the magnitude and variation of the flood level. The nonlinear effect, defined as the difference between the compound flood level and the superposition of storm surge and inland flooding water levels, reduced flood levels in the river channels while increasing flood levels on the floodplain.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR036455","usgsCitation":"Bao, D., Xue, Z.G., and Warner, J.C., 2024, Quantifying compound and nonlinear effects of hurricane-induced flooding using a dynamically coupled hydrological-ocean model: Water Resources Research, v. 60, no. 7, e2023WR036455, 21 p., https://doi.org/10.1029/2023WR036455.","productDescription":"e2023WR036455, 21 p.","ipdsId":"IP-162739","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466982,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr036455","text":"Publisher Index Page"},{"id":465288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Bao, Daoyang","contributorId":294534,"corporation":false,"usgs":false,"family":"Bao","given":"Daoyang","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":921432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xue, Z. George","contributorId":347342,"corporation":false,"usgs":false,"family":"Xue","given":"Z.","email":"","middleInitial":"George","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":921433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921434,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70266310,"text":"70266310 - 2024 - Spatio-temporal distribution of adult Pacific lamprey Entosphenus tridentatus relative to habitat fragmentation","interactions":[],"lastModifiedDate":"2025-05-05T15:22:55.579935","indexId":"70266310","displayToPublicDate":"2024-07-17T10:15:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatio-temporal distribution of adult Pacific lamprey <i>Entosphenus tridentatus</i> relative to habitat fragmentation","title":"Spatio-temporal distribution of adult Pacific lamprey Entosphenus tridentatus relative to habitat fragmentation","docAbstract":"<p><span>Pacific lamprey (</span><i>Entosphenus tridentatus</i><span>), a fish species native to the Pacific Northwest (USA), have distinctive cultural and ecological value but determining their spatial and temporal distribution is challenging due to a general lack systematic monitoring. In this study, we used counts of Pacific lamprey redds to model the probability of occurrence and abundance of Pacific lamprey based on environmental covariates including artificial barriers, assuming higher predicted lamprey redds translates to more suitable spawning habitats. Using generalized linear mixed zero-inflated models, results suggest that Pacific lamprey abundance was generally lower in high gradient streams, further from the ocean. Stream reaches with warmer spring water temperatures and greater historical median spring flows supported higher abundances. Lamprey occurrence was primarily influenced by spring water temperatures and distance from the ocean. We further observed that when streams warm beyond 18°C, confidence intervals around the abundance estimates widen and zero-inflation increases, indicating a decrease in occurrence. One objective of the study was to recommend where barrier removal or restoration should be prioritized to increase passage and thus access to upstream habitats. We considered artificial barriers to primarily influence the probability of occurrence through access. The barrier variable in this model had a negative effect on the probability of lamprey occurrence, but it was not a strong predictor in the model. While we are not able to suggest specific locations that would most benefit barrier removal or improvement based on these model results, we can identify the watersheds with a higher probability to support Pacific lamprey and provide potential additional habitats by improving habitat connectivity. Focusing restoration and/ or removal of barriers on watersheds in the Mid-South region of the Oregon Coast (i.e., Alsea, Siuslaw, Coos, Coquille, and Sixes rivers) with higher habitat suitability could prioritize use of limited funds, increase the probability of benefiting Pacific lamprey, and potentially other native lampreys and migratory (e.g., salmon, steelhead;&nbsp;</span><i>Oncorhynchus</i><span>) species. Although this manuscript focuses on the Oregon Coast region, the methods are transferrable to other regions where Pacific lamprey are present.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.4344","usgsCitation":"Anlauf-Dunn, K., Clemens, B.J., Falcy, M.R., and Zambory, C.L., 2024, Spatio-temporal distribution of adult Pacific lamprey Entosphenus tridentatus relative to habitat fragmentation: River Research and Applications, v. 40, no. 10, p. 1940-1953, https://doi.org/10.1002/rra.4344.","productDescription":"15 p.","startPage":"1940","endPage":"1953","ipdsId":"IP-151718","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":485386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.6594960692569,\n              46.176607066943575\n            ],\n            [\n              -124.60365099466847,\n              46.176607066943575\n            ],\n            [\n              -124.60365099466847,\n              42.5032728886724\n            ],\n            [\n              -122.6594960692569,\n              42.5032728886724\n            ],\n            [\n              -122.6594960692569,\n              46.176607066943575\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"40","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Anlauf-Dunn, Kara J.","contributorId":354379,"corporation":false,"usgs":false,"family":"Anlauf-Dunn","given":"Kara J.","affiliations":[{"id":36223,"text":"Oregon Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":935529,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":935530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Falcy, Matthew Richard 0000-0002-3332-2239","orcid":"https://orcid.org/0000-0002-3332-2239","contributorId":288500,"corporation":false,"usgs":true,"family":"Falcy","given":"Matthew","email":"","middleInitial":"Richard","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zambory, Courtney L.","contributorId":264754,"corporation":false,"usgs":false,"family":"Zambory","given":"Courtney","email":"","middleInitial":"L.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":935532,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70261807,"text":"70261807 - 2024 - Spatial and seasonal variability in trophic relationships and carbon sources of two key invertebrate species in Lake Ontario","interactions":[],"lastModifiedDate":"2024-12-26T15:58:47.817683","indexId":"70261807","displayToPublicDate":"2024-07-17T09:45:25","publicationYear":"2024","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":"Spatial and seasonal variability in trophic relationships and carbon sources of two key invertebrate species in Lake Ontario","docAbstract":"<p><span>Mysids (</span><i>Mysis diluviana)</i><span>&nbsp;and dreissenids (</span><span>Dreissena polymorpha</span><span>&nbsp;and mostly&nbsp;</span><i>D. bugensis</i><span>) are important invertebrate taxa in the food webs of the Laurentian Great Lakes but there are uncertainties about the seasonal and spatial variability in their&nbsp;stable isotope&nbsp;signatures. We quantified δ</span><sup>13</sup><span>C and δ</span><sup>15</sup><span>N in 304 mysid and 366 dreissenid samples across five spatial ecoregions, varying site depth, and three seasons (spring, summer, and fall) in Lake Ontario in 2012 and 2013.&nbsp;Particulate organic matter&nbsp;(POM) was also collected across site depth and season from the Deep Hole ecoregion for use as an isotopic baseline. Lipid normalization models for δ</span><sup>13</sup><span>C were generated for both taxa to reduce lipid bias in our statistical analysis. Season was a significant predictor of POM stable isotopes, with δ</span><sup>13</sup><span>C lower in the summer and δ</span><sup>15</sup><span>N decreasing from spring to summer before increasing into fall.&nbsp;Mysid&nbsp;lipid normalized δ</span><sup>13</sup><span>C varied by site depth and ecoregion while δ</span><sup>15</sup><span>N decreased across season and did not vary by site depth or ecoregion. Dreissenid stable isotopes varied significantly across season, depth, and ecoregion, with site depth having positive relationship with δ</span><sup>15</sup><span>N. Mysids and dreissenids were two trophic positions higher than POM based on δ</span><sup>15</sup><span>N; this comparison was restricted to the one region where POM was collected. Isotopic variability suggested selective feeding within POM and differing trophic pathways between mysids and dreissenids. Collecting an appropriate taxon across all observed variables to serve as an isotopic baseline, particularly in spatial and temporal studies, is critical to the correct interpretation of&nbsp;trophic relationships.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2024.102354","usgsCitation":"Uzarski, D., Fisk, A., Heuvel, C., O’Malley, B., Weidel, B., Larocque, S., and Johnson, T., 2024, Spatial and seasonal variability in trophic relationships and carbon sources of two key invertebrate species in Lake Ontario: Journal of Great Lakes Research, v. 50, no. 4, 102354, 11 p., https://doi.org/10.1016/j.jglr.2024.102354.","productDescription":"102354, 11 p.","ipdsId":"IP-152427","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":465462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake 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T.","contributorId":51604,"corporation":false,"usgs":false,"family":"Fisk","given":"Aaron T.","affiliations":[],"preferred":false,"id":921874,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heuvel, Cecilia E.","contributorId":347539,"corporation":false,"usgs":false,"family":"Heuvel","given":"Cecilia E.","affiliations":[],"preferred":false,"id":921942,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Malley, Brian 0000-0001-5035-3080 bomalley@usgs.gov","orcid":"https://orcid.org/0000-0001-5035-3080","contributorId":216560,"corporation":false,"usgs":true,"family":"O’Malley","given":"Brian","email":"bomalley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":921875,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":921876,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Larocque, Sarah M.","contributorId":347506,"corporation":false,"usgs":false,"family":"Larocque","given":"Sarah M.","affiliations":[{"id":48871,"text":"University of Windsor","active":true,"usgs":false}],"preferred":false,"id":921877,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Timothy B.","contributorId":251690,"corporation":false,"usgs":false,"family":"Johnson","given":"Timothy B.","affiliations":[{"id":50374,"text":"Ontario Ministry of Natural Resources and Forests (OMNRF)","active":true,"usgs":false}],"preferred":false,"id":921878,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70269803,"text":"70269803 - 2024 - Geologic constraints on the formation and evolution of Saturn’s mid-sized moons","interactions":[],"lastModifiedDate":"2025-08-04T14:08:13.968272","indexId":"70269803","displayToPublicDate":"2024-07-17T09:03:44","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3454,"text":"Space Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Geologic constraints on the formation and evolution of Saturn’s mid-sized moons","docAbstract":"<p><span>Saturn’s mid-sized icy moons have complex relationships with Saturn’s interior, the rings, and with each other, which can be expressed in their shapes, interiors, and geology. Observations of their physical states can, thus, provide important constraints on the ages and formation mechanism(s) of the moons, which in turn informs our understanding of the formation and evolution of Saturn and its rings. Here, we describe the cratering records of the mid-sized moons and the value and limitations of their use for constraining the histories of the moons. We also discuss observational constraints on the interior structures of the moons and geologically-derived inferences on their thermal budgets through time. Overall, the geologic records of the moons (with the exception of Mimas) include evidence of epochs of high heat flows, short- and long-lived subsurface oceans, extensional tectonics, and considerable cratering. Curiously, Mimas presents no clear evidence of an ocean within its surface geology, but its rotation and orbit indicate a present-day ocean. While the moons need not be primordial to produce the observed levels of interior evolution and geologic activity, there is likely a minimum age associated with their development that has yet to be determined. Uncertainties in the populations impacting the moons makes it challenging to further constrain their formation timeframes using craters, whereas the characteristics of their cores and other geologic inferences of their thermal evolutions may help narrow down their potential histories. Disruptive collisions may have also played an important role in the formation and evolution of Saturn’s mid-sized moons, and even the rings of Saturn, although more sophisticated modeling is needed to determine the collision conditions that produce rings and moons that fit the observational constraints. Overall, the existence and physical characteristics of Saturn’s mid-sized moons provide critical benchmarks for the development of formation theories.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11214-024-01084-z","usgsCitation":"Rhoden, A., Ferguson, S., Bottke, W.F., Castillo-Rogez, J., Martin, E., Bland, M.T., Kirchoff, M., Zannoni, M., Rambaux, N., and Salmon, J., 2024, Geologic constraints on the formation and evolution of Saturn’s mid-sized moons: Space Science Reviews, v. 220, 55, 57 p., https://doi.org/10.1007/s11214-024-01084-z.","productDescription":"55, 57 p.","ipdsId":"IP-163707","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":493791,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11214-024-01084-z","text":"Publisher Index Page"},{"id":493411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Dione, Enceladus, Mimas, Rhea, Saturn, Tethys","volume":"220","noUsgsAuthors":false,"publicationDate":"2024-07-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Rhoden, Alyssa","contributorId":358966,"corporation":false,"usgs":false,"family":"Rhoden","given":"Alyssa","affiliations":[{"id":27081,"text":"Southwest Research Inst.","active":true,"usgs":false}],"preferred":false,"id":944655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferguson, Sierra","contributorId":358968,"corporation":false,"usgs":false,"family":"Ferguson","given":"Sierra","affiliations":[{"id":27081,"text":"Southwest Research Inst.","active":true,"usgs":false}],"preferred":false,"id":944656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bottke, William F.","contributorId":191219,"corporation":false,"usgs":false,"family":"Bottke","given":"William","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":944657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Castillo-Rogez, Julie C.","contributorId":172691,"corporation":false,"usgs":false,"family":"Castillo-Rogez","given":"Julie C.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":944658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Emily","contributorId":358970,"corporation":false,"usgs":false,"family":"Martin","given":"Emily","affiliations":[{"id":85731,"text":"Smithsonian Institute, AIr and Space Museum","active":true,"usgs":false}],"preferred":false,"id":944659,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bland, Michael T. 0000-0001-5543-1519 mbland@usgs.gov","orcid":"https://orcid.org/0000-0001-5543-1519","contributorId":146287,"corporation":false,"usgs":true,"family":"Bland","given":"Michael","email":"mbland@usgs.gov","middleInitial":"T.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":944660,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kirchoff, Michelle R.","contributorId":351638,"corporation":false,"usgs":false,"family":"Kirchoff","given":"Michelle R.","affiliations":[{"id":41659,"text":"SWRI","active":true,"usgs":false}],"preferred":false,"id":944661,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Zannoni, Marco","contributorId":358971,"corporation":false,"usgs":false,"family":"Zannoni","given":"Marco","affiliations":[{"id":36660,"text":"Università di Bologna","active":true,"usgs":false}],"preferred":false,"id":944662,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rambaux, Nicolas","contributorId":358972,"corporation":false,"usgs":false,"family":"Rambaux","given":"Nicolas","affiliations":[{"id":65036,"text":"Observatoire de Paris","active":true,"usgs":false}],"preferred":false,"id":944663,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Salmon, Julien","contributorId":358973,"corporation":false,"usgs":false,"family":"Salmon","given":"Julien","affiliations":[{"id":27081,"text":"Southwest Research Inst.","active":true,"usgs":false}],"preferred":false,"id":944664,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70257651,"text":"70257651 - 2024 - New, dated small impacts on the South Polar Layered Deposits (SPLD), Mars, and implications for shallow subsurface properties","interactions":[],"lastModifiedDate":"2024-08-21T13:54:45.150993","indexId":"70257651","displayToPublicDate":"2024-07-17T08:52:47","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"New, dated small impacts on the South Polar Layered Deposits (SPLD), Mars, and implications for shallow subsurface properties","docAbstract":"<p><span>The&nbsp;Mars Reconnaissance Orbiter&nbsp;(MRO) Context Camera (CTX) imaged two newly formed impact craters on the South Polar Layered Deposits (SPLD) of Mars in 2018 and 2020. These two new craters, the first detected on the SPLD, measure ∼17 m and&nbsp;∼48 m in diameter. Follow-up observations were conducted with the High Resolution Imaging Science Experiment (HiRISE), showing seasonal and interannual changes, and providing stereo coverage for the production of&nbsp;digital terrain models&nbsp;(DTMs). Mars Climate Sounder (MCS) data were obtained over the region of these new impacts, giving surface temperature information for the time interval before and after the impacts were detected. Taken together, the optical and infrared observations of these sites reveal craters largely consistent with the morphologies of other small, dated impact craters on Mars, and crater&nbsp;</span>ejecta<span>&nbsp;patterns that suggest a more dust/regolith-dominated upper few meters of the SPLD in contrast to mid-latitude buried ice and lobate debris aprons (LDAs). This supports previous conclusions that the SPLD may have an upper surface depleted in water ice relative to the North PLDs, possibly the result of a widespread deflation event.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2024.115977","usgsCitation":"Landis, M., Dundas, C., McEwen, A.S., Daubar, I.J., Hayne, P.O., Byrne, S., Sutton, S.S., Rangarajan, V.G., Tornabene, L.L., Britton, A., and Herkenhoff, K., 2024, New, dated small impacts on the South Polar Layered Deposits (SPLD), Mars, and implications for shallow subsurface properties: Icarus, v. 419, 115977, 14 p., https://doi.org/10.1016/j.icarus.2024.115977.","productDescription":"115977, 14 p.","ipdsId":"IP-153796","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":486917,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.icarus.2024.115977","text":"Publisher Index Page"},{"id":432996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Landis, Margaret E.","contributorId":176713,"corporation":false,"usgs":false,"family":"Landis","given":"Margaret E.","affiliations":[{"id":25655,"text":"Lunar and Planetary Laboratory, 1629 E. University Blvd., The University of Arizona, Tucson, AZ 85721, United States","active":true,"usgs":false}],"preferred":false,"id":911218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dundas, Colin M. 0000-0003-2343-7224","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":237028,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":911219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daubar, Ingrid J.","contributorId":204233,"corporation":false,"usgs":false,"family":"Daubar","given":"Ingrid","email":"","middleInitial":"J.","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":911221,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hayne, Paul O.","contributorId":174125,"corporation":false,"usgs":false,"family":"Hayne","given":"Paul","email":"","middleInitial":"O.","affiliations":[{"id":27365,"text":"NASA Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":911222,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrne, Shane","contributorId":53513,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911223,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sutton, Sarah S.","contributorId":203706,"corporation":false,"usgs":false,"family":"Sutton","given":"Sarah","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":911224,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rangarajan, Vidhya Ganesh","contributorId":303377,"corporation":false,"usgs":false,"family":"Rangarajan","given":"Vidhya","email":"","middleInitial":"Ganesh","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911225,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tornabene, Livio L.","contributorId":203691,"corporation":false,"usgs":false,"family":"Tornabene","given":"Livio","email":"","middleInitial":"L.","affiliations":[{"id":13255,"text":"University of Western Ontario","active":true,"usgs":false}],"preferred":false,"id":911226,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Britton, Andrew","contributorId":343481,"corporation":false,"usgs":false,"family":"Britton","given":"Andrew","email":"","affiliations":[{"id":82100,"text":"Jacobs/NASA Johnson Space Center","active":true,"usgs":false}],"preferred":false,"id":911227,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":911228,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70257666,"text":"70257666 - 2024 - Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics","interactions":[],"lastModifiedDate":"2024-08-21T13:34:18.045457","indexId":"70257666","displayToPublicDate":"2024-07-17T08:25:08","publicationYear":"2024","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":"Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics","docAbstract":"<p><span>Invasive dreissenid mussels (</span><i>Dreissena polymorpha</i><span>&nbsp;and&nbsp;</span><i>Dreissena rostriformis bugensis</i><span>) have altered Great&nbsp;Lakes ecosystems&nbsp;through a multitude of effects on benthic habitats, food web structure, and nutrient cycling. This study explores whether spatially continuous geographic data of environmental factors can be utilized to predict&nbsp;</span><i>Dreissena</i><span>&nbsp;spp. spatial distributions on a lake-wide scale. Categorical variables were also assessed for significant relationships with&nbsp;</span><i>Dreissena</i><span>&nbsp;spp. biomass. Point observations from the 2017&nbsp;Lake Huron&nbsp;benthic survey under the Cooperative Science and Monitoring Initiative (CSMI) were utilized for&nbsp;in situ measurements&nbsp;of dreissenid presence and biomass at 119 sites across&nbsp;Lake Huron. Basin, bathymetric zone, and tributary influence were found to have statistically significant relationships to dreissenid biomass. A boosted regression tree (BRT) model (ROC score 0.707) was developed to spatially predict dreissenid presence probability across Lake Huron from six environmental explanatory variables: April, May, and October chlorophyll, June&nbsp;dissolved organic carbon, January bottom temperature, and May bottom temperature. The importance of food availability and bottom temperature illuminated relationships between dreissenid mussels and periods of benthic-pelagic mixing in the spring and fall seasons. Future models could be improved through advancements in survey technology for improved geographic characterization of mussel habitat characteristics and environmental constraints.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2024.102369","usgsCitation":"Morrison, J.M., Esselman, P.C., Riseng, C.M., Elgin, A.K., and Rowe, M.D., 2024, Predicting Lake Huron Dreissena spp. spatial distribution patterns from environmental characteristics: Journal of Great Lakes Research, v. 50, no. 4, 102369, 11 p., https://doi.org/10.1016/j.jglr.2024.102369.","productDescription":"102369, 11 p.","ipdsId":"IP-138355","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":432994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Huron","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      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Center","active":true,"usgs":true}],"preferred":true,"id":911326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riseng, Catherine M.","contributorId":30144,"corporation":false,"usgs":true,"family":"Riseng","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":911327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elgin, Ashley K.","contributorId":216170,"corporation":false,"usgs":false,"family":"Elgin","given":"Ashley","email":"","middleInitial":"K.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":911328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rowe, Mark D.","contributorId":303683,"corporation":false,"usgs":false,"family":"Rowe","given":"Mark","email":"","middleInitial":"D.","affiliations":[{"id":65877,"text":"4NOAA Great Lakes Environmental Research 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,{"id":70263545,"text":"70263545 - 2024 - Slip rate for the Rose Canyon fault through San Diego, California, based on analysis of GPS data: Evidence for a potential Rose Canyon–San Miguel-Vallecitos fault connection?","interactions":[],"lastModifiedDate":"2025-02-13T16:56:38.677011","indexId":"70263545","displayToPublicDate":"2024-07-16T10:52:06","publicationYear":"2024","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":"Slip rate for the Rose Canyon fault through San Diego, California, based on analysis of GPS data: Evidence for a potential Rose Canyon–San Miguel-Vallecitos fault connection?","docAbstract":"<p><span>The Rose Canyon fault is the southern extension of the larger Newport–Inglewood–Rose Canyon fault system, which represents a major structural boundary in the Inner Continental Borderland (ICB) offshore of southern California. Ten to fifteen percent of total plate boundary motion in southern California is thought to be accommodated by the faults of the ICB, but the exact distribution of slip is uncertain. With an onshore segment, the Rose Canyon fault offers an opportunity to measure the slip rate using traditional geodetic methods. In this study, we use Global Positioning System (GPS) surface velocities from a combined campaign and continuous GPS network to constrain elastic models of the Rose Canyon fault. We then compare the observed surface velocities with proposed conceptual models of regional fault connections that facilitate the transfer of slip into the Rose Canyon fault to assess how well the observations are explained by the models. The results of elastic half‐space models suggest that the Rose Canyon fault may be slipping toward the higher end of geologic estimates, with the preferred model indicating a slip rate of 2.4 ± 0.5&nbsp;mm/yr. Although limited in terms of near‐fault benchmarks, we find an improved model fit using an asymmetrical elastic half‐space model and a higher slip rate, suggesting a potential rheological contrast across the Rose Canyon fault, similar to observations from the northern Newport–Inglewood fault segments. Observed GPS surface velocities, background seismicity, and gravity anomalies south of San Diego Bay point toward a more easterly trace for the Rose Canyon fault, suggesting a possible connection with the San Miguel–Vallecitos fault system. Such a connection could increase the potential rupture lengths of future earthquakes and have important consequences for regional seismic hazards.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120230278","usgsCitation":"Singleton, D.M., Maloney, J., Agnew, D., and Rockwell, T., 2024, Slip rate for the Rose Canyon fault through San Diego, California, based on analysis of GPS data: Evidence for a potential Rose Canyon–San Miguel-Vallecitos fault connection?: Bulletin of the Seismological Society of America, v. 114, no. 5, p. 2751-2766, https://doi.org/10.1785/0120230278.","productDescription":"16 p.","startPage":"2751","endPage":"2766","ipdsId":"IP-149537","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -118.03132304321895,\n              32.37326157121886\n            ],\n            [\n              -114.89786575651428,\n              32.75462583665147\n            ],\n            [\n              -114.93333927794629,\n              33.64921849858126\n            ],\n            [\n              -118.29120454417611,\n              35.815309260323346\n            ],\n            [\n              -121.93695511034596,\n              35.53619205111963\n            ],\n            [\n              -121.70925414240213,\n              34.55709712444637\n            ],\n            [\n              -118.03132304321895,\n              32.37326157121886\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"114","issue":"5","noUsgsAuthors":false,"publicationDate":"2024-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Singleton, Drake Moore 0000-0001-5346-0623","orcid":"https://orcid.org/0000-0001-5346-0623","contributorId":261207,"corporation":false,"usgs":true,"family":"Singleton","given":"Drake","email":"","middleInitial":"Moore","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":927318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Jillian","contributorId":304141,"corporation":false,"usgs":false,"family":"Maloney","given":"Jillian","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":927319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Agnew, Duncan 0000-0002-2360-7783","orcid":"https://orcid.org/0000-0002-2360-7783","contributorId":178605,"corporation":false,"usgs":false,"family":"Agnew","given":"Duncan","email":"","affiliations":[],"preferred":false,"id":927320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rockwell, Thomas","contributorId":175454,"corporation":false,"usgs":false,"family":"Rockwell","given":"Thomas","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":927321,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70255882,"text":"fs20243027 - 2024 - The 3D Elevation Program—Supporting Mississippi's economy","interactions":[],"lastModifiedDate":"2024-07-15T16:52:08.385282","indexId":"fs20243027","displayToPublicDate":"2024-07-15T12:34:00","publicationYear":"2024","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":"2024-3027","displayTitle":"The 3D Elevation Program—Supporting Mississippi’s Economy","title":"The 3D Elevation Program—Supporting Mississippi's economy","docAbstract":"<h1>Introduction</h1><p>Mississippi has a dispersed population of nearly three million residents in an area of approximately 48,400 square miles and has a favorable climate for agriculture, with abundant precipitation and minimal extreme temperatures. The topography consists mostly of low hills and lowland plains, with the highest elevation about 800 feet above sea level. An exception is the nearly flat Mississippi Alluvial Plain, or “Delta,” in the northwestern part of the State. Agriculture and forestry are Mississippi’s major industries. With 65 percent of its area forested, the State is one of the country’s top producers of lumber and wood-related products. In addition to agriculture and forest resources management, other important economic activities are infrastructure and construction management, flood risk management, and water supply and quality assessment. High-quality elevation data can help to support these activities. 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 \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/programs/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/programs/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>MS 511<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:3DEP@usgs.gov\" data-mce-href=\"mailto:3DEP@usgs.gov\">3DEP@usgs.gov</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Water Supply and Quality</li><li>Flood Risk Management</li><li>Forest Resources Management</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2024-07-15","noUsgsAuthors":false,"publicationDate":"2024-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Heleine, George 0000-0001-9718-2581 gheleine@usgs.gov","orcid":"https://orcid.org/0000-0001-9718-2581","contributorId":340015,"corporation":false,"usgs":true,"family":"Heleine","given":"George","email":"gheleine@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":905884,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70269006,"text":"70269006 - 2024 - Using integrated step selection to determine effects of predation risk on bison habitat selection and movement","interactions":[],"lastModifiedDate":"2025-07-16T13:13:35.625098","indexId":"70269006","displayToPublicDate":"2024-07-15T09:11:55","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Using integrated step selection to determine effects of predation risk on bison habitat selection and movement","docAbstract":"<p><span>Animal movement is a fundamental mechanism that shapes communities and ecosystems. Ungulates alter the ecosystems they inhabit and understanding their movements and distribution is critical for linking habitat with population dynamics. Predation risk has been shown to strongly influence ungulate movement patterns, such that ungulates may select habitat where predation risk is lower (refugia), adjust movement rates, temporal patterns, or selection of cover variables in areas with greater predation risk. We evaluated potential predation avoidance behavior in a population of plains bison inhabiting the north rim of Grand Canyon National Park (GRCA) and adjacent Kaibab National Forest (KNF). The KNF has year-round hunting managed by Arizona Game and Fish Department, whereas hunting is not allowed in GRCA. Human-maintained water sources on the KNF are particularly important resources for bison wherein they may be exposed to higher predation risk to access these resources. We used 2-h GPS locations for three years from 31 bison (</span><i>n</i><span> = 9 males;&nbsp;</span><i>n</i><span> = 22 females), and integrative step selection analysis to test four hypotheses about the potential for bison to reduce their risk from human predation by avoiding areas of high predation risk; moving faster in areas with high predation risk; entering high-risk areas at night when risk is reduced; and entering high-risk areas in habitats that provide cover (coniferous forest). The highest performing model indicated bison movement was 1.3 times faster per 2-h step interval than in areas with no hunting across all vegetation classes (coniferous forest, shrub, quaking aspen, grass-forb meadow) and across all topography classes (valley, slope, ridge). Bison moved more slowly in grass-forb meadows than all other vegetation types, and in valleys relative to slopes and ridges. Several radio-collared individuals had no GPS locations in KNF for the duration of the study. Bison avoided predation risk using two strategies: moving faster while in the KNF, and fully avoiding high-risk areas by remaining within GRCA. Management that manipulates or reduces timing of hunting seasons may reduce perceived predation risk and encourage bison to distribute into the KNF and across a broader range of available habitat.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4909","usgsCitation":"Salganek, S., Schoenecker, K., and Terwilliger, M., 2024, Using integrated step selection to determine effects of predation risk on bison habitat selection and movement: Ecosphere, v. 15, no. 7, e4909, 16 p., https://doi.org/10.1002/ecs2.4909.","productDescription":"e4909, 16 p.","ipdsId":"IP-148082","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":492488,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4909","text":"Publisher Index Page"},{"id":492199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","county":"Coconino County","otherGeospatial":"Kaibab Plateau","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.68098786953385,\n              36.999074018413296\n            ],\n            [\n              -112.68098786953385,\n              35.85596339767277\n            ],\n            [\n              -111.67893358079623,\n              35.85596339767277\n            ],\n            [\n              -111.67893358079623,\n              36.999074018413296\n            ],\n            [\n              -112.68098786953385,\n              36.999074018413296\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Salganek, Skye","contributorId":357945,"corporation":false,"usgs":false,"family":"Salganek","given":"Skye","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":942896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoenecker, Kathryn A. 0000-0001-9906-911X","orcid":"https://orcid.org/0000-0001-9906-911X","contributorId":202531,"corporation":false,"usgs":true,"family":"Schoenecker","given":"Kathryn A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":942897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terwilliger, Miranda L.N.","contributorId":357947,"corporation":false,"usgs":false,"family":"Terwilliger","given":"Miranda L.N.","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":942898,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70256181,"text":"70256181 - 2024 - Modeling the potential habitat gained by planting sagebrush in burned landscapes","interactions":[],"lastModifiedDate":"2024-08-01T18:09:27.139004","indexId":"70256181","displayToPublicDate":"2024-07-15T07:03:24","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18016,"text":"Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the potential habitat gained by planting sagebrush in burned landscapes","docAbstract":"<p>Many revegetation projects are intended to benefit wildlife species. Yet, there are few a priori evaluations that assess the potential efficiency of restoration actions in recovering wildlife habitats. We developed a spatial vegetation–habitat recovery model to gauge the degree to which field planting strategies could be expected to recover multi-factor habitat conditions for wildlife following wildfires. We simulated a wildfire footprint, multiple sagebrush (<i>Artemisia</i> spp.) planting scenarios, and tracked projected vegetation growth for 15 years post-fire. We used a vegetation transition framework to track and estimate the degree to which revegetation could accelerate habitat restoration for a Greater sage-grouse (<i>Centrocercus</i>) population within the Great Basin, western United States. We assessed the amount of habitat 15 years post-fire to estimate the degree to which revegetation could be expected to accelerate habitat restoration. Our results highlight a potential disconnect between the expansive areas required by wide-ranging wildlife such as sage-grouse and the relatively small areas that planting treatments have created. Habitat restorations and planting strategies that are intended to benefit sage-grouse may only speed up localized habitat restoration. This study provides an example of how linked revegetation–habitat modeling approaches can scope the expected return on restoration investment for habitat improvements and support the strategic use of limited restoration resources.</p>","language":"English","publisher":"MDPI","doi":"10.3390/conservation4030024","usgsCitation":"Heinrichs, J., O’Donnell, M.S., Orning, E.K., Pyke, D.A., Ricca, M.A., Coates, P.S., and Aldridge, C.L., 2024, Modeling the potential habitat gained by planting sagebrush in burned landscapes: Conservation, v. 4, no. 3, p. 364-377, https://doi.org/10.3390/conservation4030024.","productDescription":"14 p.","startPage":"364","endPage":"377","ipdsId":"IP-110620","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":439279,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/conservation4030024","text":"Publisher Index Page"},{"id":434928,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S4WHHV","text":"USGS data release","linkHelpText":"veg_sim: Modeling Greater sage-grouse habitat suitability 15-years post simulated fire event and sagebrush transplanting (2015-2030)"},{"id":431438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.21272893162755,\n              42.005085754708546\n            ],\n            [\n              -117.21272893162755,\n              40.091378407222805\n            ],\n            [\n              -113.98274846287774,\n              40.091378407222805\n            ],\n            [\n              -113.98274846287774,\n              42.005085754708546\n            ],\n            [\n              -117.21272893162755,\n              42.005085754708546\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"4","issue":"3","noUsgsAuthors":false,"publicationDate":"2024-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Heinrichs, Julie A. 0000-0001-7733-5034","orcid":"https://orcid.org/0000-0001-7733-5034","contributorId":240888,"corporation":false,"usgs":false,"family":"Heinrichs","given":"Julie A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":907004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":907005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orning, Elizabeth Kari 0000-0002-1376-729X","orcid":"https://orcid.org/0000-0002-1376-729X","contributorId":315548,"corporation":false,"usgs":true,"family":"Orning","given":"Elizabeth","email":"","middleInitial":"Kari","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":907006,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":907007,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ricca, Mark A. 0000-0003-1576-513X mark_ricca@usgs.gov","orcid":"https://orcid.org/0000-0003-1576-513X","contributorId":139103,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark","email":"mark_ricca@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":907059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":907060,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":907008,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70256026,"text":"70256026 - 2024 - Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall","interactions":[],"lastModifiedDate":"2024-07-16T11:45:30.466723","indexId":"70256026","displayToPublicDate":"2024-07-15T06:38:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2824,"text":"Natural Hazards and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall","docAbstract":"<div id=\"abstract\" class=\"abstract sec\"><div class=\"abstract-content show-no-js\"><p id=\"d1e137\">Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9&nbsp;January&nbsp;2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity,<span>&nbsp;</span><span class=\"inline-formula\"><i>I</i><sub>15</sub></span>, the model generally under-forecasted the inundation area. The observed peak<span>&nbsp;</span><span class=\"inline-formula\"><i>I</i><sub>15</sub></span><span>&nbsp;</span>lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower<span>&nbsp;</span><span class=\"inline-formula\"><i>I</i><sub>15</sub></span><span>&nbsp;</span>than observed. Using these<span>&nbsp;</span><span class=\"inline-formula\"><i>I</i><sub>15</sub></span><span>&nbsp;</span>values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.</p></div></div><div id=\"citation-footer\" class=\"sec\"><br></div>","language":"English","publisher":"Copernicus","doi":"10.5194/nhess-24-2359-2024","usgsCitation":"Prescott, A.B., McGuire, L.A., Jun, K., Barnhart, K.R., and Oakley, N.S., 2024, Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall: Natural Hazards and Earth System Sciences, v. 24, p. 2359-2374, https://doi.org/10.5194/nhess-24-2359-2024.","productDescription":"16 p.","startPage":"2359","endPage":"2374","ipdsId":"IP-152472","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":439280,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-24-2359-2024","text":"Publisher Index Page"},{"id":431114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.75019791480449,\n              34.53021226184279\n            ],\n            [\n              -119.75019791480449,\n              34.35558316444329\n            ],\n            [\n              -119.46803043876221,\n              34.35558316444329\n            ],\n            [\n              -119.46803043876221,\n              34.53021226184279\n            ],\n            [\n              -119.75019791480449,\n              34.53021226184279\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"24","noUsgsAuthors":false,"publicationDate":"2024-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Prescott, A. B.","contributorId":340170,"corporation":false,"usgs":false,"family":"Prescott","given":"A.","email":"","middleInitial":"B.","affiliations":[{"id":81489,"text":"Department of Geosciences, The University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":906433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGuire, L. A.","contributorId":261566,"corporation":false,"usgs":false,"family":"McGuire","given":"L.","email":"","middleInitial":"A.","affiliations":[{"id":52879,"text":"University of Arizona, Department of Geosciences, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":906434,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jun, K.-S.","contributorId":340171,"corporation":false,"usgs":false,"family":"Jun","given":"K.-S.","email":"","affiliations":[{"id":81490,"text":"Department of Computer Science, The University of Arizona, Tucson, AZ","active":true,"usgs":false}],"preferred":false,"id":906435,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":906436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oakley, N. S. 0000-0001-5680-9296","orcid":"https://orcid.org/0000-0001-5680-9296","contributorId":236978,"corporation":false,"usgs":false,"family":"Oakley","given":"N.","email":"","middleInitial":"S.","affiliations":[{"id":47583,"text":"Desert Research Institute and Center for Western Weather and Water Extremes","active":true,"usgs":false}],"preferred":false,"id":906437,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70256058,"text":"70256058 - 2024 - Remote sensing of volcano deformation and surface change","interactions":[],"lastModifiedDate":"2024-07-17T12:07:08.404231","indexId":"70256058","displayToPublicDate":"2024-07-14T07:06:11","publicationYear":"2024","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Remote sensing of volcano deformation and surface change","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Volcanic unrest and eruptions are associated with surface deformation and landscape change that can be detected, characterized, and tracked via remote sensing measurements. Subsurface processes, including magma accumulation, withdrawal, and transport, can cause displacements at the surface that are best tracked at subaerial volcanoes with interferometric synthetic aperture radar (InSAR) and Global Navigation Satellite System (GNSS) measurements, although non-volcanic activity, like hydrothermal and tectonic sources, can complicate interpretations. Surface change is often associated with the emplacement of volcanic deposits, which modify the landscape and can experience post-emplacement deformation or morphological changes over time. Measurement of surface topography at volcanoes via remote means is a particularly important capability, given the control that topography exerts on many volcanic hazards and the potential for topographic change measurements to provide information about eruption rates. A much broader set of tools is available to investigate surface change at volcanoes, including not only InSAR and GNSS, but also synthetic aperture radar amplitude data, visible imagery, and lidar, acquired from airborne, ground-based, and satellite platforms. These data can also be used to identify instability of volcanic flanks and even have potential for use in detecting airborne ash plumes. Although hidden from traditional airborne and space-based remote sensing, deformation and surface change associated with submarine volcanism can be investigated with pressure sensors and bathymetric measurements—the below-water remote sensing analogs of GNSS and InSAR, respectively.</p></div></div>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Remote Sensing for Characterization of Geohazards and Natural Resources","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-031-59306-2_9","usgsCitation":"Poland, M., 2024, Remote sensing of volcano deformation and surface change, chap. <i>of</i> Remote Sensing for Characterization of Geohazards and Natural Resources, p. 173-203, https://doi.org/10.1007/978-3-031-59306-2_9.","productDescription":"31 p.","startPage":"173","endPage":"203","ipdsId":"IP-113436","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":431126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-07-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Poland, Michael 0000-0001-5240-6123","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":49920,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":906552,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70255933,"text":"sir20245059 - 2024 - Groundwater flow model for the Des Moines River alluvial aquifer near Des Moines, Iowa","interactions":[],"lastModifiedDate":"2026-02-03T19:47:34.689565","indexId":"sir20245059","displayToPublicDate":"2024-07-12T12:20:43","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5059","displayTitle":"Groundwater Flow Model for the Des Moines River Alluvial Aquifer near Des Moines, Iowa","title":"Groundwater flow model for the Des Moines River alluvial aquifer near Des Moines, Iowa","docAbstract":"<p>Des Moines Water Works (DMWW) is a regional municipal water utility that provides residential and commercial water resources to about 600,000 customers in Des Moines, Iowa, and surrounding municipalities in central Iowa. DMWW has identified a need for increased water supply and is exploring the potential for expanding groundwater production capabilities in the Des Moines River alluvial aquifer, where it operates two radial collector wells (RCWs). The U.S. Geological Survey, in cooperation with DMWW, completed a study of the Des Moines River alluvial aquifer and interactions of the RCWs with the aquifer; no previously published model has included the existing well locations, which is the focus of this model. A conceptual and numerical groundwater flow model have been developed to characterize the Des Moines River alluvial aquifer under existing conditions, to simulate water levels observed in the RCWs, and to provide publicly accessible hydrologic data and research that advance understanding of the regional hydrologic system and can potentially be used in the future to evaluate groundwater production scenarios. Model performance was assessed by comparing observed and simulated groundwater levels that included water level elevations, water level changes, water level inequality observations, surface water streamflow, and change in surface water volume from upstream to downstream. Water table elevation in the aquifer layers is on average slightly overestimated with average absolute value error less than 1.5 meters at both RCWs and less than 2.5 meters for all observation wells in the alluvial aquifer layers. The model also accurately simulated water tables greater than the RCW design minimum (a water level threshold at which RCW pumping is reduced) in all timesteps for which water level observation data existed. Water table elevation error was higher in other model layers that were not the focus of the study, and the model did not accurately match streamflow targets.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245059","collaboration":"Prepared in cooperation with Des Moines Water Works","usgsCitation":"Bristow, E.L., and Davis, K.W., 2024, Groundwater flow model for the Des Moines River alluvial aquifer near Des Moines, Iowa: U.S. Geological Survey Scientific Investigations Report 2024–5059, 47 p., https://doi.org/10.3133/sir20245059.","productDescription":"Report: ix, 47 p.; 3 Data Releases; 1 Dataset","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154246","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":430905,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5059/sir20245059.pdf","text":"Report","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024–5059"},{"id":430904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5059/coverthb.jpg"},{"id":430906,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5059/sir20245059.XML"},{"id":430907,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5059/images/"},{"id":430908,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245059/full"},{"id":430909,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":430910,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZDDVY","text":"USGS data release","linkHelpText":"MODFLOW 6 groundwater flow model for the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":430911,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B9AVKJ","text":"USGS data release","linkHelpText":"Geophysical data collected in the Des Moines River, Beaver Creek, and the Des Moines River floodplain, Des Moines, Iowa, 2018"},{"id":430912,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F3CKLC","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":499480,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117123.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Iowa","city":"Des Moines","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.75578446475713,\n              41.70743368403336\n            ],\n            [\n              -93.75578446475713,\n              41.53433869670215\n            ],\n            [\n              -93.54349781702975,\n              41.53433869670215\n            ],\n            [\n              -93.54349781702975,\n              41.70743368403336\n            ],\n            [\n              -93.75578446475713,\n              41.70743368403336\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/cm-water\" data-mce-href=\"https://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br>U.S. Geological Survey<br>400 South Clinton Street, Suite 269<br>Iowa City, IA 52240</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Conceptual Model and Hydrogeologic Framework</li><li>Numerical Groundwater Flow Model</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2024-07-12","noUsgsAuthors":false,"publicationDate":"2024-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Bristow, Emilia L. 0000-0002-7939-166X ebristow@usgs.gov","orcid":"https://orcid.org/0000-0002-7939-166X","contributorId":214538,"corporation":false,"usgs":true,"family":"Bristow","given":"Emilia L.","email":"ebristow@usgs.gov","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":906068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Kyle W. 0000-0002-8723-0110","orcid":"https://orcid.org/0000-0002-8723-0110","contributorId":201549,"corporation":false,"usgs":true,"family":"Davis","given":"Kyle W.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":906069,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70257575,"text":"70257575 - 2024 - Epidemiological modeling of SARS-CoV-2 in white-tailed deer (Odocoileus virginianus) reveals conditions for introduction and widespread transmission","interactions":[],"lastModifiedDate":"2024-08-19T11:35:31.903455","indexId":"70257575","displayToPublicDate":"2024-07-12T06:32:50","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5727,"text":"PLOS Computational Biology","active":true,"publicationSubtype":{"id":10}},"title":"Epidemiological modeling of SARS-CoV-2 in white-tailed deer (Odocoileus virginianus) reveals conditions for introduction and widespread transmission","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>Emerging infectious diseases with zoonotic potential often have complex socioecological dynamics and limited ecological data, requiring integration of epidemiological modeling with surveillance. Although our understanding of SARS-CoV-2 has advanced considerably since its detection in late 2019, the factors influencing its introduction and transmission in wildlife hosts, particularly white-tailed deer (<i>Odocoileus virginianus</i>), remain poorly understood. We use a Susceptible-Infected-Recovered-Susceptible epidemiological model to investigate the spillover risk and transmission dynamics of SARS-CoV-2 in wild and captive white-tailed deer populations across various simulated scenarios. We found that captive scenarios pose a higher risk of SARS-CoV-2 introduction from humans into deer herds and subsequent transmission among deer, compared to wild herds. However, even in wild herds, the transmission risk is often substantial enough to sustain infections. Furthermore, we demonstrate that the strength of introduction from humans influences outbreak characteristics only to a certain extent. Transmission among deer was frequently sufficient for widespread outbreaks in deer populations, regardless of the initial level of introduction. We also explore the potential for fence line interactions between captive and wild deer to elevate outbreak metrics in wild herds that have the lowest risk of introduction and sustained transmission. Our results indicate that SARS-CoV-2 could be introduced and maintained in deer herds across a range of circumstances based on testing a range of introduction and transmission risks in various captive and wild scenarios. Our approach and findings will aid One Health strategies that mitigate persistent SARS-CoV-2 outbreaks in white-tailed deer populations and potential spillback to humans.</p></div></div>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pcbi.1012263","usgsCitation":"Rosenblatt, E., Cook, J.D., DiRenzo, G.V., Campbell Grant, E.H., Arce, F., Pepin, K.M., Rudolph, F.J., Runge, M.C., Shriner, S.A., Walsh, D.P., and Mosher, B., 2024, Epidemiological modeling of SARS-CoV-2 in white-tailed deer (Odocoileus virginianus) reveals conditions for introduction and widespread transmission: PLOS Computational Biology, v. 20, no. 7, e1012263, 27 p., https://doi.org/10.1371/journal.pcbi.1012263.","productDescription":"e1012263, 27 p.","ipdsId":"IP-154833","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":439284,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1012263","text":"Publisher Index Page"},{"id":432879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Rosenblatt, Elias","contributorId":276324,"corporation":false,"usgs":false,"family":"Rosenblatt","given":"Elias","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":910898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Jonathan D. 0000-0001-7000-8727","orcid":"https://orcid.org/0000-0001-7000-8727","contributorId":291411,"corporation":false,"usgs":true,"family":"Cook","given":"Jonathan","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":910899,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":910900,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":910901,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Arce, Fernando","contributorId":342247,"corporation":false,"usgs":false,"family":"Arce","given":"Fernando","email":"","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":910902,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pepin, Kimberly M","contributorId":343386,"corporation":false,"usgs":false,"family":"Pepin","given":"Kimberly","email":"","middleInitial":"M","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":910903,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rudolph, F. Javiera","contributorId":342245,"corporation":false,"usgs":false,"family":"Rudolph","given":"F.","email":"","middleInitial":"Javiera","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":910904,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"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":910905,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Shriner, Susan A.","contributorId":168690,"corporation":false,"usgs":false,"family":"Shriner","given":"Susan","email":"","middleInitial":"A.","affiliations":[{"id":13407,"text":"Colorado State Univ.","active":true,"usgs":false}],"preferred":false,"id":910906,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":910907,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Mosher, Brittany A.","contributorId":337881,"corporation":false,"usgs":false,"family":"Mosher","given":"Brittany A.","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":910908,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70264427,"text":"70264427 - 2024 - Pliocene–Pleistocene warm-water incursions and water mass changes on the Ross Sea continental shelf (Antarctica) based on foraminifera from IODP Expedition 374","interactions":[],"lastModifiedDate":"2025-03-14T14:36:34.474979","indexId":"70264427","displayToPublicDate":"2024-07-11T09:27:30","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2391,"text":"Journal of Micropalaeontology","active":true,"publicationSubtype":{"id":10}},"title":"Pliocene–Pleistocene warm-water incursions and water mass changes on the Ross Sea continental shelf (Antarctica) based on foraminifera from IODP Expedition 374","docAbstract":"<p><span>International Ocean Discovery Program (IODP) Expedition 374 sailed to the Ross Sea in 2018 to reconstruct paleoenvironments, track the history of key water masses, and assess model simulations that show warm-water incursions from the Southern Ocean led to the loss of marine-based Antarctic ice sheets during past interglacials. IODP Site U1523 (water depth 828 m) is located at the continental shelf break, northeast of Pennell Bank on the southeastern flank of Iselin Bank, where it lies beneath the Antarctic Slope Current (ASC). This site is sensitive to warm-water incursions from the Ross Sea Gyre and modified Circumpolar Deep Water (mCDW) today and during times of past warming climate. Multiple incursions of subpolar or temperate planktic foraminifera taxa occurred at Site U1523 after 3.8 Ma and prior to&nbsp;</span><span class=\"inline-formula\">∼</span><span> 1.82 Ma. Many of these warm-water taxa incursions likely represent interglacials of the latest Early Pliocene and Early Pleistocene, including Marine Isotope Stage (MIS) Gi7 to Gi3 (</span><span class=\"inline-formula\">∼</span><span> 3.72–3.65 Ma), and Early Pleistocene MIS 91 or 90 (</span><span class=\"inline-formula\">∼</span><span> 2.34–2.32 Ma) and MIS 77–67 (</span><span class=\"inline-formula\">∼</span><span> 2.03–1.83 Ma) and suggest warmer-than-present conditions and less ice cover in the Ross Sea. However, a moderately resolved age model based on four key events prohibits us from precisely correlating with Marine Isotope Stages established by the LR04 Stack; therefore, these correlations are best estimates. Diatom-rich intervals during the latest Pliocene at Site U1523 include evidence of anomalously warm conditions based on the presence of subtropical and temperate planktic foraminiferal species in what likely correlates with interglacial MIS G17 (</span><span class=\"inline-formula\">∼</span><span> 2.95 Ma), and a second interval that likely correlates with MIS KM3 (</span><span class=\"inline-formula\">∼</span><span> 3.16 Ma) of the mid-Piacenzian Warm Period. Collectively, these multiple incursions of warmer-water planktic foraminifera provide evidence for polar amplification during super-interglacials of the Pliocene and Early Pleistocene. Higher abundances of planktic and benthic foraminifera during the Mid- to Late Pleistocene associated with interglacials of the MIS 37–31 interval (</span><span class=\"inline-formula\">∼</span><span> 1.23–1.07 Ma), MIS 25 (</span><span class=\"inline-formula\">∼</span><span> 0.95 Ma), MIS 15 (</span><span class=\"inline-formula\">∼</span><span> 0.60 Ma), and MIS 6–5e transition (</span><span class=\"inline-formula\">∼</span><span> 0.133–0.126 Ma) also indicate a reduced ice shelf and relatively warm conditions, including multiple warmer interglacials during the Mid-Pleistocene Transition (MPT). A decrease in sedimentation rate after&nbsp;</span><span class=\"inline-formula\">∼</span><span> 1.78 Ma is followed by a major change in benthic foraminiferal biofacies marked by a decrease in&nbsp;</span><i>Globocassidulina subglobosa</i><span>&nbsp;and a decrease in mud (</span><span class=\"inline-formula\"><i>&lt;</i></span><span> 63 </span><span class=\"inline-formula\">µ</span><span>m) after&nbsp;</span><span class=\"inline-formula\">∼</span><span> 1.5 Ma. Subsequent dominance of&nbsp;</span><i>Trifarina earlandi</i><span>&nbsp;biofacies beginning during MIS 15 (</span><span class=\"inline-formula\">∼</span><span> 600 ka) indicate progressive strengthening of the Antarctic Slope Current along the shelf edge of the Ross Sea during the mid to Late Pleistocene. A sharp increase in foraminiferal fragmentation after the MPT (</span><span class=\"inline-formula\">∼</span><span> 900 ka) and variable abundances of&nbsp;</span><i>T. earlandi</i><span>&nbsp;indicate higher productivity, a stronger but variable ASC during interglacials, and/or corrosive waters, suggesting changes in water masses entering (mCDW) and exiting (High Salinity Shelf Water or Dense Shelf Water) the Ross Sea since the MPT.</span></p>","language":"English","publisher":"Copernicus Publications","doi":"10.5194/jm-43-211-2024","usgsCitation":"Seidenstein, J.L., Leckie, R., McKay, R., De Santis, L., Harwood, D., and IODP Expedition 374 Scientists, 2024, Pliocene–Pleistocene warm-water incursions and water mass changes on the Ross Sea continental shelf (Antarctica) based on foraminifera from IODP Expedition 374: Journal of Micropalaeontology, v. 43, no. 2, p. 211-238, https://doi.org/10.5194/jm-43-211-2024.","productDescription":"28 p.","startPage":"211","endPage":"238","ipdsId":"IP-154696","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":488299,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/jm-43-211-2024","text":"Publisher Index Page"},{"id":483338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, Ross Ice Shelf","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -179.9,\n              -70\n            ],\n            [\n              -179.9,\n              -78\n            ],\n            [\n              -150,\n              -78\n            ],\n            [\n              -150,\n              -70\n            ],\n            [\n              -179.9,\n              -70\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              170,\n              -70\n            ],\n            [\n              170,\n              -78\n            ],\n            [\n              179.9,\n              -78\n            ],\n            [\n              179.9,\n              -70\n            ],\n            [\n              170,\n              -70\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"43","issue":"2","noUsgsAuthors":false,"publicationDate":"2024-07-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Seidenstein, Julia Lynn 0000-0002-0585-1977","orcid":"https://orcid.org/0000-0002-0585-1977","contributorId":290625,"corporation":false,"usgs":true,"family":"Seidenstein","given":"Julia","email":"","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":930738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leckie, R. Mark","contributorId":352312,"corporation":false,"usgs":false,"family":"Leckie","given":"R. Mark","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":930739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKay, Robert","contributorId":9546,"corporation":false,"usgs":true,"family":"McKay","given":"Robert","affiliations":[],"preferred":false,"id":930752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"De Santis, L.","contributorId":96471,"corporation":false,"usgs":true,"family":"De Santis","given":"L.","email":"","affiliations":[],"preferred":false,"id":930753,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harwood, David","contributorId":352313,"corporation":false,"usgs":false,"family":"Harwood","given":"David","affiliations":[{"id":16610,"text":"University of Nebraska-Lincoln","active":true,"usgs":false}],"preferred":false,"id":930740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"IODP Expedition 374 Scientists","contributorId":352319,"corporation":true,"usgs":false,"organization":"IODP Expedition 374 Scientists","id":930754,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70255943,"text":"70255943 - 2024 - Drought as an emergent driver of ecological transformation in the twenty-first century","interactions":[],"lastModifiedDate":"2024-09-11T16:18:09.909012","indexId":"70255943","displayToPublicDate":"2024-07-10T10:28:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Drought as an emergent driver of ecological transformation in the twenty-first century","docAbstract":"<p><span>Under climate change, ecosystems are experiencing novel drought regimes, often in combination with stressors that reduce resilience and amplify drought’s impacts. Consequently, drought appears increasingly likely to push systems beyond important physiological and ecological thresholds, resulting in substantial changes in ecosystem characteristics persisting long after drought ends (i.e., ecological transformation). In the present article, we clarify how drought can lead to transformation across a wide variety of ecosystems including forests, woodlands, and grasslands. Specifically, we describe how climate change alters drought regimes and how this translates to impacts on plant population growth, either directly or through drought's interactions with factors such as land management, biotic interactions, and other disturbances. We emphasize how interactions among mechanisms can inhibit postdrought recovery and can shift trajectories toward alternate states. Providing a holistic picture of how drought initiates long-term change supports the development of risk assessments, predictive models, and management strategies, enhancing preparedness for a complex and growing challenge.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biae050","usgsCitation":"Moss, W.E., Crausbay, S., Rangwala, I., Wason, J., Trauernicht, C., Stevens-Rumann, C.S., Sala, A., Rottler, C.M., Pederson, G.T., Miller, B.W., Magness, D., Littell, J., Frelich, L., Frazier, A.G., Davis, K., Coop, J., Cartwright, J.M., and Booth, R.K., 2024, Drought as an emergent driver of ecological transformation in the twenty-first century: BioScience, v. 74, no. 8, p. 524-538, https://doi.org/10.1093/biosci/biae050.","productDescription":"15 p.","startPage":"524","endPage":"538","ipdsId":"IP-153234","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":490028,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biae050","text":"Publisher Index Page"},{"id":430975,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Moss, Wynne Emily 0000-0002-2813-1710","orcid":"https://orcid.org/0000-0002-2813-1710","contributorId":338331,"corporation":false,"usgs":true,"family":"Moss","given":"Wynne","email":"","middleInitial":"Emily","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":906093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crausbay, Shelley","contributorId":217758,"corporation":false,"usgs":false,"family":"Crausbay","given":"Shelley","affiliations":[{"id":13470,"text":"Conservation Science Partners","active":true,"usgs":false}],"preferred":false,"id":906094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rangwala, Imtiaz","contributorId":259891,"corporation":false,"usgs":false,"family":"Rangwala","given":"Imtiaz","affiliations":[{"id":52460,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":false}],"preferred":false,"id":906095,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wason, Jay","contributorId":300108,"corporation":false,"usgs":false,"family":"Wason","given":"Jay","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":906096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trauernicht, Clay","contributorId":221125,"corporation":false,"usgs":false,"family":"Trauernicht","given":"Clay","email":"","affiliations":[{"id":40329,"text":"University of Hawai‘i at Mānoa, Department of Natural Resources and Environmental Management","active":true,"usgs":false}],"preferred":false,"id":906097,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stevens-Rumann, Camille S.","contributorId":274486,"corporation":false,"usgs":false,"family":"Stevens-Rumann","given":"Camille","email":"","middleInitial":"S.","affiliations":[{"id":56622,"text":"Forest Restoration Institute, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":906098,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sala, Anna","contributorId":147094,"corporation":false,"usgs":false,"family":"Sala","given":"Anna","email":"","affiliations":[{"id":5103,"text":"The University of Montana, Division of Biological Sciences, Missoula, Montana 59812","active":true,"usgs":false}],"preferred":false,"id":906099,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rottler, Caitlin M.","contributorId":138853,"corporation":false,"usgs":false,"family":"Rottler","given":"Caitlin","email":"","middleInitial":"M.","affiliations":[{"id":12546,"text":"Univ of Wyoming, Department of Botany, 1000 E. University Ave., Laramie, WY 82071; Univ of WY, Program in Ecology, 1000 E. University Ave., Laramie, WY 82071 USA","active":true,"usgs":false}],"preferred":false,"id":906100,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":906101,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":906102,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Magness, Dawn","contributorId":147692,"corporation":false,"usgs":false,"family":"Magness","given":"Dawn","affiliations":[{"id":16903,"text":"U.S. Fish and Wildlife Service, Kenai National Wildlife Refuge, Soldotna, AK, 99669, USA","active":true,"usgs":false}],"preferred":false,"id":906103,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"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":906104,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Frelich, Lee","contributorId":225721,"corporation":false,"usgs":false,"family":"Frelich","given":"Lee","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":906105,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Frazier, Abby G.","contributorId":221112,"corporation":false,"usgs":false,"family":"Frazier","given":"Abby","email":"","middleInitial":"G.","affiliations":[{"id":40321,"text":"USDA Forest Service, Pacific Southwest Research Station","active":true,"usgs":false}],"preferred":false,"id":906106,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Davis, Kimberly R.","contributorId":192195,"corporation":false,"usgs":false,"family":"Davis","given":"Kimberly R.","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":906107,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Coop, Jonathan","contributorId":298238,"corporation":false,"usgs":false,"family":"Coop","given":"Jonathan","affiliations":[{"id":38118,"text":"Western Colorado University","active":true,"usgs":false}],"preferred":false,"id":906108,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":906109,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Booth, Robert K","contributorId":220202,"corporation":false,"usgs":false,"family":"Booth","given":"Robert","email":"","middleInitial":"K","affiliations":[{"id":16160,"text":"Lehigh University","active":true,"usgs":false}],"preferred":false,"id":906110,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70256416,"text":"70256416 - 2024 - A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps","interactions":[],"lastModifiedDate":"2024-08-01T14:20:43.087876","indexId":"70256416","displayToPublicDate":"2024-07-10T09:19:31","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps","docAbstract":"<p><span>Wildfire substantially alters aquatic ecosystems by inducing moderate to catastrophic physical and chemical changes. However, the relations of environmental and watershed variables that drive those effects are complex. We present a Driver-Factor-Stressor-Effect (DFSE) conceptual framework to assess the current state of the science related to post-wildfire water-quality. We reviewed 64 peer-reviewed papers using the DFSE framework to identify drivers, factors, stressors, and effects associated with each study. A total of five drivers were identified and ranked according to their frequency of occurrence in the literature: atmospheric processes&nbsp;&gt;&nbsp;fire characteristics&nbsp;&gt;&nbsp;ecologic processes and characteristics&nbsp;&gt;&nbsp;land surface characteristics&nbsp;&gt;&nbsp;soil characteristics. Commonly reported stressors include increased nutrients, runoff, and sediment transport. Furthermore, although several different factors have been used at least once to explain water-quality effects, relatively few factors outside of precipitation and fire characteristics are frequently studied. We identified several gaps indicating the need for long-term monitoring, multi-factor studies, consideration of organic contaminants, consideration of groundwater, and inclusion of soil characteristics. This assessment expands on other reviews and meta-analyses by exploring causal linkages between influential variables and overall effects in post-wildfire watersheds. Information gathered from our assessment and the framework itself can be used to inform future monitoring plans and as a guide for modeling efforts focused on better understanding specific processes or to mitigate potential risks of post-wildfire water quality.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR036260","usgsCitation":"Elliott, S.M., Hornberger, M.I., Rosenberry, D.O., Frus, R., and Webb, R.M., 2024, A conceptual framework to assess post-wildfire water quality: State of the science and knowledge gaps: Water Resources Research, v. 60, no. 7, e2023WR036260, 20 p.; Data Release, https://doi.org/10.1029/2023WR036260.","productDescription":"e2023WR036260, 20 p.; Data Release","ipdsId":"IP-156361","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":439286,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr036260","text":"Publisher Index Page"},{"id":434931,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97JZOVY","text":"USGS data release","linkHelpText":"Annotated bibliography of 64 papers reviewed and summarized in a conceptual framework to assess post-wildfire water quality"},{"id":432026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":907311,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":907312,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":907313,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frus, Rebecca J. 0000-0002-2435-7202","orcid":"https://orcid.org/0000-0002-2435-7202","contributorId":340187,"corporation":false,"usgs":false,"family":"Frus","given":"Rebecca J.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":907314,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Webb, Richard M. 0000-0001-9531-2207 rmwebb@usgs.gov","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":1570,"corporation":false,"usgs":true,"family":"Webb","given":"Richard","email":"rmwebb@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":907315,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70256047,"text":"70256047 - 2024 - Seasonality of retreat rate of a wave-exposed marsh edge","interactions":[],"lastModifiedDate":"2024-07-16T11:53:48.411487","indexId":"70256047","displayToPublicDate":"2024-07-10T06:53:09","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7357,"text":"JGR Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Seasonality of retreat rate of a wave-exposed marsh edge","docAbstract":"<div class=\"article-section__content en main\"><p>Wave-driven erosion of marsh boundaries is a major cause of marsh loss, but little research has captured the effect of seasonal differences on marsh-edge retreat rates to illuminate temporal patterns of when the majority of this erosion is occurring. Using five surface models captured over a study year of a marsh with a steep escarped boundary in South San Francisco Bay, we find a pronounced seasonal signal, where rapid marsh retreat in the spring and summer is driven by a strong sea breeze but little change is found in the marsh-edge position in the fall and winter. We found accretion in the mudflat transition region close to the marsh boundary in the calmer seasons however, suggesting intertwined morphodynamics of mudflats and the eroding marsh-scarp. We observed large spatial heterogeneity in retreat rates within seasons, but less on longer (annual and decadal) timescales. The relationship between marsh-edge retreat rates and properties of the wave field nearby is explored and contextualized against extant relationships, but our results speak to the difficulty in addressing spatial erosion/accretion variability on short (seasonal) timescales with simple models.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JF007468","usgsCitation":"WinklerPrins, L.T., Lacy, J.R., Stacey, M., Logan, J.B., and Stevens, A.W., 2024, Seasonality of retreat rate of a wave-exposed marsh edge: JGR Earth Surface, v. 129, no. 7, e2023JF007468, https://doi.org/10.1029/2023JF007468.","productDescription":"e2023JF007468","ipdsId":"IP-155496","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":439288,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jf007468","text":"Publisher Index Page"},{"id":431116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"129","issue":"7","noUsgsAuthors":false,"publicationDate":"2024-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"WinklerPrins, Lukas T. 0000-0003-0508-1455","orcid":"https://orcid.org/0000-0003-0508-1455","contributorId":304096,"corporation":false,"usgs":false,"family":"WinklerPrins","given":"Lukas","email":"","middleInitial":"T.","affiliations":[{"id":65968,"text":"UC Berkeley, contracted to USGS PCMSC","active":true,"usgs":false}],"preferred":false,"id":906491,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":906492,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stacey, Mark T.","contributorId":94531,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark T.","affiliations":[{"id":12776,"text":"Department of Civil and Environmental Engineering,  University of California, Berkeley, California, USA","active":true,"usgs":false}],"preferred":false,"id":906493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":906494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stevens, Andrew W. 0000-0003-2334-129X astevens@usgs.gov","orcid":"https://orcid.org/0000-0003-2334-129X","contributorId":139313,"corporation":false,"usgs":true,"family":"Stevens","given":"Andrew","email":"astevens@usgs.gov","middleInitial":"W.","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":906495,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70256002,"text":"70256002 - 2024 - On connecting hydro-social parameters to vegetation greenness differences in an evolving groundwater-dependent ecosystem","interactions":[],"lastModifiedDate":"2024-07-12T11:51:49.080855","indexId":"70256002","displayToPublicDate":"2024-07-10T06:47:49","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"On connecting hydro-social parameters to vegetation greenness differences in an evolving groundwater-dependent ecosystem","docAbstract":"<div class=\"html-p\">Understanding groundwater-dependent ecosystems (i.e., areas with a relatively shallow water table that plays a major role in supporting vegetation health) is key to sustaining water resources in the western United States. Groundwater-dependent ecosystems (GDEs) in Colorado have non-pristine temporal and spatial patterns, compared to agro-ecosystems, which make it difficult to quantify how these ecosystems are impacted by changes in water availability. The goal of this study is to examine how key hydrosocial parameters perturb GDE water use in time and in space. The temporal approach tests for the additive impacts of precipitation, surface water discharge, surface water mass balance as a surrogate for surface–groundwater exchange, and groundwater depth on the monthly Landsat normalized difference vegetation index (NDVI). The spatial approach tests for the additive impacts of river confluences, canal augmentation, development, perennial tributary confluences, and farmland modification on temporally integrated NDVI. Model results show a temporal trend (monthly, 1984–2019) is identifiable along segments of the Arkansas River at resolutions finer than 10 km. The temporal impacts of river discharge correlate with riparian water use sooner in time compared to precipitation, but this result is spatially variable and dependent on the covariates tested. Spatially, areal segments of the Arkansas River that have confluences with perennial streams have increased cumulative vegetation density. Quantifying temporal and spatial dependencies between the sources and effects of GDEs could aid in preventing the loss of a vulnerable ecosystem to increased water demand, changing climate, and evolving irrigation methodologies.</div>","language":"English","publisher":"MDPI","doi":"10.3390/rs16142536","usgsCitation":"Lurtz, M.R., Morrison, R.R., and Nagler, P.L., 2024, On connecting hydro-social parameters to vegetation greenness differences in an evolving groundwater-dependent ecosystem: Remote Sensing, v. 16, no. 14, 2536, 20 p., https://doi.org/10.3390/rs16142536.","productDescription":"2536, 20 p.","ipdsId":"IP-165588","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":439289,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs16142536","text":"Publisher Index Page"},{"id":430998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -102.05312742592827,\n              37.89105892695899\n            ],\n            [\n              -102.05312742592827,\n              38.25691608432268\n            ],\n            [\n              -103.13634969634639,\n              38.25691608432268\n            ],\n            [\n              -103.13634969634639,\n              37.89105892695899\n            ],\n            [\n              -102.05312742592827,\n              37.89105892695899\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","issue":"14","noUsgsAuthors":false,"publicationDate":"2024-07-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Lurtz, Matthew R.","contributorId":300337,"corporation":false,"usgs":false,"family":"Lurtz","given":"Matthew","email":"","middleInitial":"R.","affiliations":[{"id":65088,"text":"Civil and Environmental Engineering, Colorado State University, Fort Collins, CO, 80523 USA","active":true,"usgs":false}],"preferred":false,"id":906322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrison, Ryan R.","contributorId":198245,"corporation":false,"usgs":false,"family":"Morrison","given":"Ryan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":906323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":906324,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70258330,"text":"70258330 - 2024 - Next generation public supply water withdrawal estimation for the conterminous United States using machine learning and operational frameworks","interactions":[],"lastModifiedDate":"2024-09-11T14:29:26.678447","indexId":"70258330","displayToPublicDate":"2024-07-09T09:25:27","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Next generation public supply water withdrawal estimation for the conterminous United States using machine learning and operational frameworks","docAbstract":"<p><span>Estimation of human water withdrawals is more important now than ever due to uncertain water supplies, population growth, and climate change. Fourteen percent of the total water withdrawal in the United States is used for public supply, typically including deliveries to domestic, commercial, and occasionally including industrial, irrigation, and thermoelectric water withdrawal. Stewards of water resources in the USA require estimates of water withdrawals to manage and plan for future demands and sustainable water supplies. This study compiled the most comprehensive conterminous United States water withdrawal data set to date and developed a machine learning framework for estimating public supply withdrawals and associated uncertainty for the period 2000–2020. The modeling approach provides service area resolution estimates to allow for annual and monthly water withdrawal estimation while incorporating a complex array of driving factors that include hydroclimatic, demographic, socioeconomic, geographic, and land use factors. Model results reveal highly variable and lognormally distributed per-capita water withdrawal, spanning from 30 to 650 gallons per capita per day (GPCD), across community, regional, and national scales, with pronounced seasonal variations. Analysis of estimated withdrawal trends indicates that the national annual average withdrawal experienced a decline at a rate of 0.58 GPCD/year during the period from 2000 to 2020. Model interpretation reveals a complex interplay between public supply withdrawal and key predictors, including population size, warm-season precipitation, counts of large buildings and houses, and areas of urban and commercial land use. The developed models can forecast future public supply driven by various climate, demographic, and socioeconomic scenarios.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023WR036632","usgsCitation":"Alzraiee, A.H., Niswonger, R.G., Luukkonen, C., Larsen, J., Martin, D., Herbert, D.M., Buchwald, C.A., Dieter, C., Miller, L.D., Stewart, J.S., Houston, N., Paulinski, S., and Kristen Valseth, 2024, Next generation public supply water withdrawal estimation for the conterminous United States using machine learning and operational frameworks: Water Resources Research, v. 60, no. 7, e2023WR036632, 25 p., https://doi.org/10.1029/2023WR036632.","productDescription":"e2023WR036632, 25 p.","ipdsId":"IP-154316","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia  Water Science Center","active":true,"usgs":true},{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":439290,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023wr036632","text":"Publisher Index Page"},{"id":433692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous 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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