{"pageNumber":"24","pageRowStart":"575","pageSize":"25","recordCount":11004,"records":[{"id":70250754,"text":"70250754 - 2023 - Microfossils and biostratigraphy of the Upper Cretaceous Coon Creek Formation Lagerstätte, Mississippi Embayment, USA","interactions":[],"lastModifiedDate":"2024-01-03T12:53:39.320366","indexId":"70250754","displayToPublicDate":"2023-12-22T06:49:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1791,"text":"Geological Society, London, Special Publications","active":true,"publicationSubtype":{"id":10}},"title":"Microfossils and biostratigraphy of the Upper Cretaceous Coon Creek Formation Lagerstätte, Mississippi Embayment, USA","docAbstract":"<div id=\"abstracts\" data-extent=\"frontmatter\"><div class=\"core-container\"><div>The Upper Cretaceous Coon Creek Formation type-locality in McNairy County, Tennessee, is an exceptional marine invertebrate Lagerstätte that was deposited in a nearshore reentrant into the ancestral continent of Appalachia. Extensive taxonomic analysis of the macrofauna has been done for over 100 years. However, documentation of the microfossil component at the type-locality has largely been ignored. This paper provides analysis of calcareous microfossils (benthic and planktonic foraminifera, calcareous nannofossils and ostracods) and palynomorphs (pollen, spores, algal remains and dinoflagellates) for detailed age control and information regarding environment of deposition. The Coon Creek type-locality is late Campanian (76.8–76.0 Ma) in age and was deposited in 35–60 m water depths. Calcareous nannofossil assemblages suggest that there was an influence of colder water through time, possibly by a connection to the northern Western Interior Seaway. The complex interplay between currents of the Gulf of Mexico and the Western Interior Seaway, upwelling and runoff influenced the palaeoenvironment. Increased influx of freshwater palynomorphs near the top of the section suggests placement proximal to the palaeoshoreline and that weathering increased through time. Changes in the dinoflagellate assemblage may be linked to a mosasaur mass mortality event and the presence of a harmful algal bloom.</div></div></div>","language":"English","publisher":"Geological Society, London","doi":"10.1144/SP545-2023-137","usgsCitation":"Self-Trail, J., Gardner, K.F., O’Keefe, J.M., Mason, P.H., Puckett, M., Gibson, M.A., and McCarty, M., 2023, Microfossils and biostratigraphy of the Upper Cretaceous Coon Creek Formation Lagerstätte, Mississippi Embayment, USA: Geological Society, London, Special Publications, v. 545, 22 p., https://doi.org/10.1144/SP545-2023-137.","productDescription":"22 p.","ipdsId":"IP-155094","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":424063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee","county":"McNairy County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.3641,35.3852],[-88.3638,35.3738],[-88.3642,35.3675],[-88.3653,35.3148],[-88.3755,35.3141],[-88.3763,35.3041],[-88.3776,35.2909],[-88.3686,35.2906],[-88.3722,35.1734],[-88.3798,34.9982],[-88.4123,34.9983],[-88.5458,34.9979],[-88.6689,34.9975],[-88.7867,34.9972],[-88.7849,35.133],[-88.7846,35.2475],[-88.7192,35.2477],[-88.7162,35.2582],[-88.7072,35.2579],[-88.7081,35.2637],[-88.6908,35.3056],[-88.6393,35.3038],[-88.6396,35.3138],[-88.6399,35.3184],[-88.6608,35.3204],[-88.6674,35.3405],[-88.6197,35.3675],[-88.5773,35.3812],[-88.5267,35.3863],[-88.3724,35.38],[-88.3726,35.385],[-88.3641,35.3852]]]},\"properties\":{\"name\":\"McNairy\",\"state\":\"TN\"}}]}","volume":"545","noUsgsAuthors":false,"publicationDate":"2023-12-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":891272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, Kristina Frank 0000-0001-9872-9294","orcid":"https://orcid.org/0000-0001-9872-9294","contributorId":297849,"corporation":false,"usgs":true,"family":"Gardner","given":"Kristina","email":"","middleInitial":"Frank","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":891273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Keefe, Jennifer M K","contributorId":200148,"corporation":false,"usgs":false,"family":"O’Keefe","given":"Jennifer","email":"","middleInitial":"M K","affiliations":[],"preferred":false,"id":891274,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mason, Patricia H.","contributorId":332897,"corporation":false,"usgs":false,"family":"Mason","given":"Patricia","email":"","middleInitial":"H.","affiliations":[{"id":24668,"text":"University of North Carolina, Wilmington","active":true,"usgs":false}],"preferred":false,"id":891275,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Puckett, Mark","contributorId":317218,"corporation":false,"usgs":false,"family":"Puckett","given":"Mark","email":"","affiliations":[],"preferred":false,"id":891276,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gibson, Michael A.","contributorId":332898,"corporation":false,"usgs":false,"family":"Gibson","given":"Michael","email":"","middleInitial":"A.","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":891277,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCarty, Maeve","contributorId":317219,"corporation":false,"usgs":false,"family":"McCarty","given":"Maeve","email":"","affiliations":[],"preferred":false,"id":891278,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70250607,"text":"ofr20231076 - 2023 - Preliminary geologic map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California","interactions":[],"lastModifiedDate":"2026-02-11T21:44:26.272299","indexId":"ofr20231076","displayToPublicDate":"2023-12-19T13:22:44","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1076","displayTitle":"Preliminary Geologic Map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California","title":"Preliminary geologic map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California","docAbstract":"<p>This investigation delineates the geologic framework of an area of 75 square kilometers (km<sup>2</sup>) located west of the Salton Sea in southern California (fig. 1, on sheet 1). The study area encompasses the south flank of the Santa Rosa Mountains and the eastern part of the Borrego Badlands (sheet 1). In this study area, regionally important stratigraphic and structural elements collectively inform the late Cenozoic geologic evolution of the Anza-Borrego sector of the Salton Trough province. Critical stratigraphic and structural elements in the map area include the following:</p><div id=\":1yq\" class=\"Ar Au Ao\"><div id=\":1ym\" class=\"Am aiL Al editable LW-avf tS-tW tS-tY\" aria-label=\"Message Body\" aria-multiline=\"true\" aria-owns=\":212\" aria-controls=\":212\" aria-expanded=\"false\"><ol><li>The well exposed sequence of late Cenozoic, nonmarine sedimentary rocks that filled the Anza-Borrego subbasin (fig. 1) of the Salton Trough;</li><li>A tectonic boundary that—in the southern Santa Rosa Mountains—separates the sedimentary strata from underlying crystalline rocks of Peninsular Ranges type. This tectonic boundary, named the West Salton Detachment Fault System by Axen and Fletcher (1998), is projected to underlie all late Cenozoic sedimentary strata in the Anza-Borrego subbasin of the Salton Trough;</li><li>A variety of transpressional, transtensional, and strike-slip structures that have deformed the late Cenozoic sedimentary strata and collectively guided syntectonic and posttectonic depositional events within the Anza-Borrego subbasin of the Salton Trough; and</li><li>The southeasternmost surface expression of the Clark Fault, a major strand of the dextral San Jacinto Fault Zone.</li></ol></div></div><p>Geologic mapping and analysis for this investigation focused on clarifying geologic relations among these four stratigraphic and structural aspects in the map area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231076","usgsCitation":"Pettinga, J.R., Dudash, S.L., and Cossette, P.M., 2023, Preliminary Geologic Map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California: U.S. Geological Survey Open-File Report 2023–1076, scale 1:12,000, https://doi.org/10.3133/ofr20231076.","productDescription":"2 Plates: 70.66 x 31.92 inches and 51.22 x 32.64 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-100617","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":423753,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2023/1076/ofr20231076_sheet1.pdf","text":"Sheet 1","size":"13 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":423752,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1076/covrthb.jpg"},{"id":499789,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115708.htm","linkFileType":{"id":5,"text":"html"}},{"id":423768,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L8YSQX","text":"USGS Data Release","linkHelpText":"Digital Database for the Preliminary Geologic Map of the Southern Santa Rosa Mountains and Borrego Badlands, San Diego County, Southern California"},{"id":423754,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2023/1076/ofr20231076_sheet2.pdf","text":"Sheet 2","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Borrego Badlands, southern Santa Rosa Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -116.208333,\n              33.316667\n            ],\n            [\n              -116.208333,\n              33.25\n            ],\n            [\n              -116.083333,\n              33.25\n            ],\n            [\n              -116.083333,\n              33.316667\n            ],\n            [\n              -116.208333,\n              33.316667\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fusgs.gov%2F&amp;data=05%7C01%7Cjtran%40usgs.gov%7C2acc9ccfe04c490508e208db57150e3b%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C638199520171483214%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&amp;sdata=M5pIPYGVMGFOGVgSlKnAjJ%2FMw0n5BBDivZ0f4E1wjFs%3D&amp;reserved=0\" data-mce-href=\"https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fusgs.gov%2F&amp;data=05%7C01%7Cjtran%40usgs.gov%7C2acc9ccfe04c490508e208db57150e3b%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C638199520171483214%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&amp;sdata=M5pIPYGVMGFOGVgSlKnAjJ%2FMw0n5BBDivZ0f4E1wjFs%3D&amp;reserved=0\">U.S. Geological Survey</a><br>Building 19, 350 N. Akron Rd.<br>P.O. Box 158<br>Moffett Field, CA 94035</p>","tableOfContents":"<ul><li>Introduction</li><li>Geologic Setting</li><li>Stratigraphic Framework Adopted for this Report</li><li>Structural Geology</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-12-19","noUsgsAuthors":false,"publicationDate":"2023-12-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Pettinga, Jarg R. 0000-0002-5299-3265","orcid":"https://orcid.org/0000-0002-5299-3265","contributorId":329743,"corporation":false,"usgs":false,"family":"Pettinga","given":"Jarg","email":"","middleInitial":"R.","affiliations":[{"id":78707,"text":"University of Canterbury Christchurch, New Zealand","active":true,"usgs":false}],"preferred":true,"id":890545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dudash, Stephanie L. 0000-0001-8728-5915 sdudash@usgs.gov","orcid":"https://orcid.org/0000-0001-8728-5915","contributorId":5911,"corporation":false,"usgs":true,"family":"Dudash","given":"Stephanie","email":"sdudash@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890546,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cossette, Pamela M. 0000-0002-9608-6595 pcossette@usgs.gov","orcid":"https://orcid.org/0000-0002-9608-6595","contributorId":1458,"corporation":false,"usgs":true,"family":"Cossette","given":"Pamela","email":"pcossette@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":890547,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250474,"text":"sir20235121 - 2023 - Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia","interactions":[],"lastModifiedDate":"2026-03-13T15:40:20.136121","indexId":"sir20235121","displayToPublicDate":"2023-12-14T07:40:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5121","displayTitle":"Hydrogeology, Karst, and Groundwater Availability of Monroe County, West Virginia","title":"Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia","docAbstract":"<p>Monroe County is in southeastern West Virginia, encompassing an area of 474 square miles. The area consists of karst and siliciclastic aquifers of Ordovician, Silurian, Devonian, and Mississippian age and is in parts of two physiographic provinces: the Valley and Ridge Province to the east of Peters Mountain, and the Appalachian Plateau Province to the west of Peters Mountain. This study was developed in response to inquiries from the Monroe County Commission requesting assessment of the water resources of the county to better understand the quantity of the county’s groundwater resources, for both current [2023] and future demand, and to provide information to support protection and management of the county’s valuable groundwater resources.</p><p>Various products were developed for this study that provide knowledge with respect to water availability and contamination susceptibility of the karst aquifers within the county. U.S. Geological Survey (USGS) geologists conducted extensive geologic mapping in support of the project, producing (1) a countywide bedrock geologic map, (2) a countywide hydrogeologic map, and (3) a light detection and ranging (lidar)-derived countywide digital elevation model and associated sinkhole map. A significant part of this work was to map in detail the Greenbrier Group at the formation level, which prior to this study had only partially been completed. The report also includes (4) a description of the lithologic units identified as part of the geologic mapping process.</p><p>U.S. Geological Survey hydrologists completed several additional products for the hydrology part of the effort, including development of (1) a countywide potentiometric surface (water-table) map, (2) a countywide base-flow stream assessment, (3) countywide water-budget estimates, (4) well log surveys for 15 wells to better understand subsurface controls on groundwater flow within the study area, (5) two groundwater tracer tests to better refine the groundwater divide from the northern and southern parts of the karst aquifer in Monroe County; and finally, based on all available data collected for the study including the potentiometric surface map, geologic map, current [2023] and legacy fluorometric groundwater tracer tests, and base-flow stream assessments, (6) groundwater-basin delineations were reassessed for principal groundwater basins within the Greenbrier aquifer.</p><p>In Monroe County, four principal hydrogeologic settings produce large yields of water for residential, agricultural, and other uses. The most relied upon water-bearing zone with respect to current [2023] public water supply is from springs along Peters Mountain. These springs are derived from intervals of fractured sandstone and resultant alluvial deposits. Groundwater flows downslope through these permeable alluvial deposits and discharges at the contact with less permeable strata, such as the Reedsville Shale. The second most relied upon water-bearing zone in Monroe County is within the karstic Greenbrier Group aquifer, in which the basal Hillsdale Limestone overlies the less permeable Maccrady Shale. This geologic contact between the Hillsdale Limestone and Maccrady Shale is not only targeted as a source of water for agricultural supply but also is targeted as a source of water for residential supply. The third most relied upon water-bearing zone is composed of shallow perched aquifers within the Greenbrier Group. The discontinuous nature of these perched aquifers makes mapping their extent impossible, but they are related to permeable geologic strata, such as karstified limestones with solutionally enhanced permeability that overlies less permeable shale or chert bedrock. During geologic mapping of the county, several of these perched aquifers were documented in the Pickaway, Union, and Alderson Limestones. A fourth zone consists of springs from Ordovician carbonates at the base of Peters Mountain, which are influenced by sinking streams as well as upwelling along faults. In terms of water quantity, the most sustainable springs are those having deeper-sourced flows.</p><p>Public supplies are a principal source of water used for residential and commercial supply in the region, accounting for 0.49 million gallons per day (Mgal/d) of fresh-water withdrawals (0.14 Mgal/d of groundwater and 0.35 Mgal/d of surface water) for residential and commercial use and serving 6,645 individuals (49.2 percent of the population). An estimated 6,861 people, (50.8 percent of the population) primarily rely on private wells or other unregulated sources, such as springs, and withdraw 0.55 Mgal/d of groundwater for their residential use. Public water supply in the region is primarily (71.4 percent) derived from springs and augmented by stream withdrawals (backup sources mainly during low-flow periods), with the remaining portion (28.6 percent) derived from groundwater withdrawals from wells. For rural residents, however, 100 percent of their withdrawals are derived from groundwater (wells or springs).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235121","isbn":"978-1-4113-4541-6","collaboration":"Prepared in cooperation with the West Virginia Department of Environmental Protection, the West Virginia Department of Health & Human Resources, and the Monroe County Commission","usgsCitation":"Kozar, M.D., Doctor, D.H., Jones, W.K., Chien, N., Cox, C.E., Orndorff, R.C., Weary, D.J., Weaver, M.R., McAdoo, M.A., and Parker, M., 2023, Hydrogeology, karst, and groundwater availability of Monroe County, West Virginia: U.S. Geological Survey Scientific Investigations Report 2023–5121, 82 p., https://doi.org/10.3133/sir20235121.","productDescription":"Report: xii, 81 p.; 4 Appendixes, 5 Data Releases","numberOfPages":"81","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-153904","costCenters":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":423493,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O85K6T","text":"USGS data release","linkHelpText":"Lidar-derived closed depression vector data and density raster in karst areas of Monroe County, West Virginia"},{"id":423494,"rank":12,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TKR3XJ","text":"USGS data release","linkHelpText":"Lidar-derived imagery and digital elevation model of Monroe County, West Virginia at 3-meter resolution"},{"id":423487,"rank":5,"type":{"id":34,"text":"Image 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release","linkHelpText":"Density raster of caves in Monroe County, West Virginia"},{"id":426143,"rank":15,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig04_plate.pdf","text":"Plate of Figure 4","size":"19.7 MB","linkHelpText":"- Hydrogeologic Map of Monroe County, West Virginia"},{"id":426144,"rank":16,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig05_plate.pdf","text":"Plate of Figure 5","size":"10.7 MB","linkHelpText":"- Geologic Map of Monroe County, West Virginia"},{"id":423485,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235121/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5121"},{"id":426145,"rank":17,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_fig25_plate.pdf","text":"Plate of Figure 25","size":"1.98 MB","linkHelpText":"- Potentiometric-Surface Map of Monroe County, West Virginia"},{"id":423488,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix1.csv","text":"Appendix 1","size":"15.6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Well Depth, Casing, Yield, Water Level, and Specific Capacity Data From County Health Department Well Completion Reports"},{"id":423489,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix2.csv","text":"Appendix 2","size":"17.3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Base-flow Data for 83 Sites Measured in September 2019 in Monroe County, West Virginia"},{"id":501160,"rank":18,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115685.htm","linkFileType":{"id":5,"text":"html"}},{"id":423496,"rank":14,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TFAN5X","text":"USGS data release","linkHelpText":"Interpolated groundwater levels and altitudes for Monroe County, West Virginia, 2017–2019"},{"id":423495,"rank":13,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KF9FD2","text":"USGS data release","linkHelpText":"Fluorescein and Rhodamine WT concentration and recovery data for select samples collected in Monroe County, West Virginia, in August and September 2019"},{"id":423491,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5121/sir20235121_appendix4.zip","text":"Appendix 4","size":"14.9 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Results of Annual Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia"}],"country":"United States","state":"West Virginia","county":"Monroe 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<a href=\"https://www.usgs.gov/centers/va-wv-water\" data-mce-href=\"https://www.usgs.gov/centers/va-wv-water\">Virginia and West Virginia Water Science Center</a><br>U.S. Geological Survey<br>1730 East Parham Road<br>Richmond, Virginia 23228</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"https://pubs.er.usgs.gov/contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hydrogeology</li><li>Karst Features</li><li>Groundwater Availability</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Well Depth, Casing, Yield, Water Level, and Specific Capacity Data From County Health Department Well Completion Reports</li><li>Appendix 2. Base-flow Data for 83 Sites Measured in September 2019 in Monroe County, West Virginia</li><li>Appendix 3. Results of Monthly Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia</li><li>Appendix 4. Results of Annual Hydrograph Analyses for Four Major Watersheds in Monroe County and for the Greenbrier River at Alderson, West Virginia</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-12-14","noUsgsAuthors":false,"publicationDate":"2023-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Kozar, Mark D. 0000-0001-7755-7657 mdkozar@usgs.gov","orcid":"https://orcid.org/0000-0001-7755-7657","contributorId":1963,"corporation":false,"usgs":true,"family":"Kozar","given":"Mark","email":"mdkozar@usgs.gov","middleInitial":"D.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":890052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":890053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, William K. 0009-0000-9851-3514","orcid":"https://orcid.org/0009-0000-9851-3514","contributorId":332334,"corporation":false,"usgs":false,"family":"Jones","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":79454,"text":"Environmental Data LLC, Warm Springs, VA","active":true,"usgs":false}],"preferred":false,"id":890054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chien, Nathan 0009-0001-2274-9085","orcid":"https://orcid.org/0009-0001-2274-9085","contributorId":332335,"corporation":false,"usgs":false,"family":"Chien","given":"Nathan","email":"","affiliations":[{"id":79455,"text":"Previous employee USGS VA-WV WSC","active":true,"usgs":false}],"preferred":false,"id":890055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cox, Cheyenne E. 0000-0002-5213-7880","orcid":"https://orcid.org/0000-0002-5213-7880","contributorId":332336,"corporation":false,"usgs":false,"family":"Cox","given":"Cheyenne","email":"","middleInitial":"E.","affiliations":[{"id":79456,"text":"former USGS Employee (Florence Bascom)","active":true,"usgs":false}],"preferred":false,"id":890056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":890057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weary, David J. 0000-0002-6115-6397 dweary@usgs.gov","orcid":"https://orcid.org/0000-0002-6115-6397","contributorId":545,"corporation":false,"usgs":true,"family":"Weary","given":"David","email":"dweary@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science 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,{"id":70251283,"text":"70251283 - 2023 - Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon","interactions":[],"lastModifiedDate":"2024-02-02T12:42:56.771463","indexId":"70251283","displayToPublicDate":"2023-12-14T06:37:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17146,"text":"Frontiers Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon","docAbstract":"<div class=\"JournalAbstract\"><p><strong>Introduction:</strong><span>&nbsp;</span>Forecasting range shifts in response to climate change requires accurate species distribution models (SDMs), particularly at the margins of species' ranges. However, most studies producing SDMs rely on sparse species occurrence datasets from herbarium records and public databases, along with random pseudoabsences. While environmental covariates used to fit SDMS are increasingly precise due to satellite data, the availability of species occurrence records is still a large source of bias in model predictions. We developed distribution models for hybridizing sister species of western and eastern Joshua trees (<i>Yucca brevifolia</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Y. jaegeriana</i>, respectively), iconic Mojave Desert species that are threatened by climate change and habitat loss.</p><p><strong>Methods:</strong><span>&nbsp;</span>We conducted an intensive visual grid search of online satellite imagery for 672,043 0.25 km<sup>2</sup><span>&nbsp;</span>grid cells to identify the two species' presences and absences on the landscape with exceptional resolution, and field validated 29,050 cells in 15,001 km of driving. We used the resulting presence/absence data to train SDMs for each Joshua tree species, revealing the contemporary environmental gradients (during the past 40 years) with greatest influence on the current distribution of adult trees.</p><p><strong>Results:</strong><span>&nbsp;</span>While the environments occupied by<span>&nbsp;</span><i>Y. brevifolia</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Y. jaegeriana</i><span>&nbsp;</span>were similar in total aridity, they differed with respect to seasonal precipitation and temperature ranges, suggesting the two species may have differing responses to climate change. Moreover, the species showed differing potential to occupy each other's geographic ranges: modeled potential habitat for<span>&nbsp;</span><i>Y. jaegeriana</i><span>&nbsp;</span>extends throughout the range of<span>&nbsp;</span><i>Y. brevifolia</i>, while potential habitat for<span>&nbsp;</span><i>Y. brevifolia</i><span>&nbsp;</span>is not well represented within the range of<span>&nbsp;</span><i>Y. jaegeriana</i>.</p><p><strong>Discussion:</strong><span>&nbsp;</span>By reproducing the current range of the Joshua trees with high fidelity, our dataset can serve as a baseline for future research, monitoring, and management of this species, including an increased understanding of dynamics at the trailing and leading margins of the species' ranges and potential for climate refugia.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.1266892","usgsCitation":"Esque, T., Shryock, D., Berr, G.A., Chen, F., DeFalco, L., Lewicki, S.M., Cunningham, B.L., Gaylord, E.J., Poage, C.S., Gantz, G.E., Van Gaalen, R.A., Gottsacker, B.O., Mcdonald, A.M., Yoder, J., Smith, C., and Nussear, K., 2023, Unprecedented distribution data for Joshua trees (Yucca brevifolia and Y. jaegeriana) reveal contemporary climate associations of a Mojave Desert icon: Frontiers Ecology and Evolution, v. 11, 1266892, 20 p., https://doi.org/10.3389/fevo.2023.1266892.","productDescription":"1266892, 20 p.","ipdsId":"IP-159615","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441412,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.1266892","text":"Publisher Index Page"},{"id":425278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      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0009-0000-9484-8878","orcid":"https://orcid.org/0009-0000-9484-8878","contributorId":333765,"corporation":false,"usgs":true,"family":"Mcdonald","given":"Amanda","email":"","middleInitial":"Marie","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":893860,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Yoder, J.B.","contributorId":333766,"corporation":false,"usgs":false,"family":"Yoder","given":"J.B.","affiliations":[{"id":7080,"text":"California State University, Northridge","active":true,"usgs":false}],"preferred":false,"id":893862,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Smith, C.I.","contributorId":333767,"corporation":false,"usgs":false,"family":"Smith","given":"C.I.","affiliations":[{"id":7268,"text":"Willamette University","active":true,"usgs":false}],"preferred":false,"id":893863,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Nussear, K.E. 0000-0002-3849-8911","orcid":"https://orcid.org/0000-0002-3849-8911","contributorId":333768,"corporation":false,"usgs":false,"family":"Nussear","given":"K.E.","email":"","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":893864,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70256559,"text":"70256559 - 2023 - Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations","interactions":[],"lastModifiedDate":"2024-08-16T11:38:31.421824","indexId":"70256559","displayToPublicDate":"2023-12-14T06:17:46","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>The use of species distribution models has proliferated, providing insights for sustainable management of migratory species in a globally changing environment. However, many of these models are based on statistical relationships developed from historical conditions that may not perform well under changing or even analogous conditions caused by climate change. In this paper, we used a mechanistic species distribution model called GR3D (Global Repositioning Dynamics for Diadromous Fish Distribution) to examine the integrated dynamics of American shad (<i>Alosa sapidissima</i>) populations across their native range along the Eastern U.S. coast, where the species demonstrates latitudinal variations in life histories and reproductive strategies. The initial design of the model was adapted to incorporate region-specific parameterization to fit the species ecology. Then, a sensitivity analysis was performed to test the influences of uncertain processes regarding American shad distribution at sea, straying and reproduction on key characteristics of the species distribution. The sensitivity analysis showed the influence of the Allee effect (i.e., “depensatory” process) and the homing rate (i.e., fidelity to the breeding sites) on the probability of presence and abundances among catchments and metapopulations estimated by the model. Contrary to the homing rate, the distance of straying did not change the estimated number of metapopulations or abundances. Homing strength, however, was quite influential. The integration of complex migration patterns during the marine phase (i.e., wintering and summering offshore areas) provided more likely estimates of the species' overall distribution. Overall, our study illustrated the utility of incorporating factors governing the large-scale distribution of migratory species to improve local management.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4712","usgsCitation":"Poulet, C., Lassalle, G., Jordaan, A., Limburg, K., Nack, C.C., Nye, J.A., O’Malley, A., O’Malley-Barber, B., Stich, D.S., Waldman, J., Zydlewski, J.D., and Lambert, P., 2023, Effect of straying, reproductive strategies, and ocean distribution on the structure of American shad populations: Ecosphere, v. 14, no. 12, e4712, 21 p., https://doi.org/10.1002/ecs2.4712.","productDescription":"e4712, 21 p.","ipdsId":"IP-147500","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":441419,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4712","text":"Publisher Index Page"},{"id":432849,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.25384275260296,\n              23.589986588351152\n            ],\n            [\n              -59.41399900260346,\n              23.589986588351152\n            ],\n            [\n              -59.41399900260346,\n              51.4169004286193\n            ],\n            [\n              -85.25384275260296,\n              51.4169004286193\n            ],\n            [\n              -85.25384275260296,\n              23.589986588351152\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  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Amherst","active":true,"usgs":false}],"preferred":false,"id":907980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Limburg, Karin E.","contributorId":341130,"corporation":false,"usgs":false,"family":"Limburg","given":"Karin E.","affiliations":[{"id":12623,"text":"State University of New York College of Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":907981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nack, Christopher C.","contributorId":341131,"corporation":false,"usgs":false,"family":"Nack","given":"Christopher","email":"","middleInitial":"C.","affiliations":[{"id":62153,"text":"Ramboll","active":true,"usgs":false}],"preferred":false,"id":907982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nye, Janet A.","contributorId":341132,"corporation":false,"usgs":false,"family":"Nye","given":"Janet","email":"","middleInitial":"A.","affiliations":[{"id":55603,"text":"University of North Carolina Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":907983,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Malley, Andrew","contributorId":341133,"corporation":false,"usgs":false,"family":"O’Malley","given":"Andrew","affiliations":[{"id":81706,"text":"Gomez and Sullivan Engineers","active":true,"usgs":false}],"preferred":false,"id":907984,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"O’Malley-Barber, Betsy","contributorId":341134,"corporation":false,"usgs":false,"family":"O’Malley-Barber","given":"Betsy","email":"","affiliations":[{"id":81706,"text":"Gomez and Sullivan Engineers","active":true,"usgs":false}],"preferred":false,"id":907985,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stich, Dan S.","contributorId":341135,"corporation":false,"usgs":false,"family":"Stich","given":"Dan","email":"","middleInitial":"S.","affiliations":[{"id":81707,"text":"State University of New York Oneonta","active":true,"usgs":false}],"preferred":false,"id":907986,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Waldman, John R.","contributorId":341136,"corporation":false,"usgs":false,"family":"Waldman","given":"John R.","affiliations":[{"id":32856,"text":"Queens College","active":true,"usgs":false}],"preferred":false,"id":907987,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":907988,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lambert, Patrick","contributorId":341137,"corporation":false,"usgs":false,"family":"Lambert","given":"Patrick","affiliations":[{"id":81705,"text":"INRAe","active":true,"usgs":false}],"preferred":false,"id":907989,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70266207,"text":"70266207 - 2023 - Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model","interactions":[],"lastModifiedDate":"2025-04-30T15:45:29.630755","indexId":"70266207","displayToPublicDate":"2023-12-14T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model","docAbstract":"Understanding spatio-temporal variability in demography and the influence of environmental conditions offers insight into the factors underlying population dynamics. This is particularly true for species with divergent demographic patterns across large geographic areas. The contrasting abundance trends observed across the range of Steller sea lions (Eumetopias jubatus) have been studied extensively, with research suggesting that the primary drivers of localized population dynamics vary over time and space. We developed a Bayesian integrated population model for the endangered western distinct population segment of Steller sea lions that combines mark-recapture and count data from 2000-2021 to estimate demographic rates, abundance trends, and the effects of environmental variability on population growth. Our results highlight subregional demographic differences, including reduced pup survival in the central Aleutian Islands and reduced yearling survival west of Samalga Pass. Range-wide abundance increased by 1.7% yr-1 (95% credible interval: 0.14; 3.4%) over the study period, with a positive annual growth rate of 3.0% (1.1; 5.1%) yr-1 east of Samalga Pass, a negative growth rate of -2.1% (-4.6; 0.5%) yr-1 west of Samalga Pass, and an overall low probability of local extirpation (<2%) in 100 years even in subregions experiencing continued decline. The effect of environmental variability on population growth varied depending on subpopulation size and vital rates and was strongest in the area of greatest decline. Our model improves upon existing approaches for estimating abundance, accounts for environmental variability within the viability analysis, and can facilitate evaluating the efficacy of conservation actions and progress toward recovery goals.","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01282","usgsCitation":"Warlick, A., Johnson, D., Sweeney, K., Gelatt, T., and Converse, S.J., 2023, Examining the effect of environmental variability on the viability of endangered Steller sea lions using an integrated population model: Endangered Species Research, v. 52, p. 343-361, https://doi.org/10.3354/esr01282.","productDescription":"19 p.","startPage":"343","endPage":"361","ipdsId":"IP-151798","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487889,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01282","text":"Publisher Index Page"},{"id":485208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -192.3038114894406,\n              57.51067207764723\n            ],\n            [\n              -192.3038114894406,\n              51.43442138881829\n            ],\n            [\n              -154.88087376804862,\n              51.43442138881829\n            ],\n            [\n              -154.88087376804862,\n              57.51067207764723\n            ],\n            [\n              -192.3038114894406,\n              57.51067207764723\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Warlick, Amanda J.","contributorId":353988,"corporation":false,"usgs":false,"family":"Warlick","given":"Amanda J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":934927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":353989,"corporation":false,"usgs":false,"family":"Johnson","given":"Devin S.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934928,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweeney, Katie L.","contributorId":353990,"corporation":false,"usgs":false,"family":"Sweeney","given":"Katie L.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934929,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gelatt, Tom S.","contributorId":353991,"corporation":false,"usgs":false,"family":"Gelatt","given":"Tom S.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":934930,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":934931,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70250622,"text":"70250622 - 2023 - Decline in small mammal species richness in coastal-central California, 1997–2013","interactions":[],"lastModifiedDate":"2023-12-20T12:54:43.939749","indexId":"70250622","displayToPublicDate":"2023-12-10T06:49:05","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Decline in small mammal species richness in coastal-central California, 1997–2013","docAbstract":"<p>The richness and composition of a small mammal community inhabiting semiarid California oak woodland may be changing in response to climate change, but we know little about the causes or consequence of these changes. We applied a capture-mark-recapture model to 17 years (1997–2013) of live trapping data to estimate species-specific abundances. The big-eared woodrat was the most frequently captured species in the area, contributing 58% of total captures. All small mammal populations exhibited seasonal fluctuations, whereas those of the California mouse, brush mouse, and pinyon mouse declined during the study period. We also applied a multispecies dynamic occupancy model to our small mammal detection history data to estimate species richness, occupancy ( ), detection (p), local extinction ( ), and colonization ( ) probabilities, and to discern factors affecting these parameters. We found that decreased from 0.369 ± 0.088 in 1997 to 0.248 ± 0.054 in 2013; was lower during the dry season (May–September) than the wet season (October–April) and was positively influenced by total seasonal rainfall (slope parameter,  = 0.859 ± 0.371; 95% CI = 0.132–1.587). Mean mammalian species richness decreased from 11.943 ± 0.461 in 1997 to 7.185 ± 0.425 in 2013. With highly variable climatic patterns expected in the future, especially increased frequency and intensity of droughts, it is important to monitor small mammal communities inhabiting threatened California oak woodlands.</p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10611","usgsCitation":"Ghimirey, Y.P., Tietje, W.D., Polyakov, A.Y., Hines, J.E., and Oli, M.K., 2023, Decline in small mammal species richness in coastal-central California, 1997–2013: Ecology and Evolution, v. 13, no. 12, e10611, 11 p., https://doi.org/10.1002/ece3.10611.","productDescription":"e10611, 11 p.","ipdsId":"IP-157415","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441442,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10611","text":"Publisher Index Page"},{"id":423789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Camp Roberts","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.94253263683494,\n              35.90849811107087\n            ],\n            [\n              -120.94253263683494,\n              35.64500150778204\n            ],\n            [\n              -120.60126981945214,\n              35.64500150778204\n            ],\n            [\n              -120.60126981945214,\n              35.90849811107087\n            ],\n            [\n              -120.94253263683494,\n              35.90849811107087\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"12","noUsgsAuthors":false,"publicationDate":"2023-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Ghimirey, Yadav P.","contributorId":332600,"corporation":false,"usgs":false,"family":"Ghimirey","given":"Yadav","email":"","middleInitial":"P.","affiliations":[{"id":79505,"text":"Univ. of FL","active":true,"usgs":false}],"preferred":false,"id":890598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tietje, William D.","contributorId":332601,"corporation":false,"usgs":false,"family":"Tietje","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":79506,"text":"Friends of Nature, Nepal","active":true,"usgs":false}],"preferred":false,"id":890599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Polyakov, Anne Y.","contributorId":332602,"corporation":false,"usgs":false,"family":"Polyakov","given":"Anne","email":"","middleInitial":"Y.","affiliations":[{"id":79507,"text":"Univ. of CA","active":true,"usgs":false}],"preferred":false,"id":890600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":890601,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oli, Madan K. 0000-0001-6944-0061","orcid":"https://orcid.org/0000-0001-6944-0061","contributorId":201302,"corporation":false,"usgs":false,"family":"Oli","given":"Madan","email":"","middleInitial":"K.","affiliations":[{"id":13453,"text":"University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":890602,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70271334,"text":"70271334 - 2023 - FishPass sortable attribute database: Phenological, morphological, physiological, and behavioural characteristics related to passage and movement of Laurentian Great Lakes fishes","interactions":[],"lastModifiedDate":"2025-09-08T15:55:48.348064","indexId":"70271334","displayToPublicDate":"2023-12-09T10:11:30","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"FishPass sortable attribute database: Phenological, morphological, physiological, and behavioural characteristics related to passage and movement of Laurentian Great Lakes fishes","docAbstract":"<p><span>In-stream barriers pose threats to fishes, including habitat loss, constraints on migration, and reduced connectivity between populations. Despite many negative consequences, barriers can serve to protect native species by limiting the spread of&nbsp;invasive species. For example, in the Laurentian Great Lakes, physical barriers have long been used to control invasive&nbsp;sea lamprey&nbsp;(</span><i>Petromyzon marinus</i><span>) populations by limiting access to potential upstream spawning and rearing habitat. Selective fish passage systems could solve this management trade-off, termed the “connectivity conundrum”, but must efficiently pass multiple native or desirable species while blocking invasive species. Designing such fish passage systems requires an understanding of the attribute dimensions of the fish community, specifically, the&nbsp;phenology, morphology, physiology, and behaviour of each species. Here, we describe the first comprehensive collection of sortable attributes associated with fish passage. The integrated database consists of 21 biological attributes that influence the movement and passage of 220 species in the Great Lakes, including native species, established non-native species, and unestablished but potentially invasive fishes. Data coverage varies with species, taxonomic orders, and attribute dimensions. Behavioural attributes were typically underrepresented in the literature, and the ecology of potential invaders was not well understood. The synthesis described herein is a critical step towards a holistic approach to fish passage design and may help to inform management actions related to population connectivity. The database is openly accessible online and is expected to be updated periodically.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2023.08.006","usgsCitation":"Benoit, D.M., Zielinski, D.P., Swanson, R.G., McLaughlin, R.L., Castro-Santos, T., Goodwin, R., Pratt, T.C., and Muir, A.M., 2023, FishPass sortable attribute database: Phenological, morphological, physiological, and behavioural characteristics related to passage and movement of Laurentian Great Lakes fishes: Journal of Great Lakes Research, v. 49, no. 6, 102229, 10 p., https://doi.org/10.1016/j.jglr.2023.08.006.","productDescription":"102229, 10 p.","ipdsId":"IP-152464","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":495384,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2023.08.006","text":"Publisher Index 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,{"id":70250280,"text":"sim3496 - 2023 - Surficial geologic map of the Owlshead Mountains 30' x 60' quadrangle, Inyo and San Bernardino Counties, California","interactions":[],"lastModifiedDate":"2026-02-19T17:36:45.966647","indexId":"sim3496","displayToPublicDate":"2023-12-05T10:20:40","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3496","displayTitle":"Surficial Geologic Map of the Owlshead Mountains 30' x 60' Quadrangle, Inyo and San Bernardino Counties, California","title":"Surficial geologic map of the Owlshead Mountains 30' x 60' quadrangle, Inyo and San Bernardino Counties, California","docAbstract":"<p>The surficial geologic map of the Owlshead Mountains 30' x 60' quadrangle depicts the distribution and characteristics of surficial-deposit materials and neotectonic deformation for an area of approximately 5,000 square kilometers (km<sup>2</sup>) located in the western Basin and Range Province of eastern California. The map represents a new compilation of the surficial geology that encompasses deposits within the late Pliocene to Quaternary. The map is based primarily on new mapping conducted between 2001 and 2009. Map compilation was supported by field observations distributed across the map area, combined with reference to several published and unpublished mapping sources that mostly emphasized neotectonic deformation. The surficial-deposit units included in the map follow a classification scheme that systematically denotes depositional process, relative age, and any secondary sedimentologic or morphologic characteristics. Identification, correlation, and age estimation of map units are based primarily on the relative degree of development of certain time-dependent characteristics such as surface morphology, including local dissection and surface preservation, surface clast modification, and degree of soil development; these characteristics are implicitly incorporated into unit designations. The map represents a detailed and regionally uniform synthesis of the late Neogene geology for this large area that provides a framework applicable to many interpretative studies, such as regional patterns of deposition and dissection; surface drainage development and evolution; and the distribution, style, and timing of neotectonic deformation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3496","usgsCitation":"Menges, C.M., and Cossette, P.M., 2023, Surficial geologic map of the Owlshead Mountains 30' x 60' quadrangle, Inyo and San Bernardino Counties, California: U.S. Geological Survey Scientific Investigations Map 3496, pamphlet 46 p., 2 sheets, 1:62,500, https://doi.org/10.3133/sim3496.","productDescription":"Report: iv, 46 p.; 2 Sheet: 59.92 × 42.54 inches and 50.57 × 30.83 inches; Database; Data Release","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107100","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":500199,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115656.htm","linkFileType":{"id":5,"text":"html"}},{"id":423113,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3496/sim3496_database.zip","text":"Database","size":"140 MB","linkFileType":{"id":6,"text":"zip"}},{"id":423112,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3496/sim3496_sheet2.pdf","text":"Sheet 2","size":"1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":423109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3496/covrthb_.jpg"},{"id":423110,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3496/sim3496_pamphlet.pdf","text":"Pamphlet","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":423111,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3496/sim3496_sheet1.pdf","text":"Sheet 1","size":"26 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.00,\n              36.00\n            ],\n            [\n              -117.00,\n              35.30\n            ],\n            [\n              -116.00,\n              35.30\n            ],\n            [\n              -116.00,\n              36.00\n            ],\n            [\n              -117.00,\n              36.00\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fusgs.gov%2F&amp;data=05%7C01%7Cjtran%40usgs.gov%7C2acc9ccfe04c490508e208db57150e3b%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C638199520171483214%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&amp;sdata=M5pIPYGVMGFOGVgSlKnAjJ%2FMw0n5BBDivZ0f4E1wjFs%3D&amp;reserved=0\" data-mce-href=\"https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fusgs.gov%2F&amp;data=05%7C01%7Cjtran%40usgs.gov%7C2acc9ccfe04c490508e208db57150e3b%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C638199520171483214%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&amp;sdata=M5pIPYGVMGFOGVgSlKnAjJ%2FMw0n5BBDivZ0f4E1wjFs%3D&amp;reserved=0\">U.S. Geological Survey</a><br>Building 19, 350 N. Akron Rd.<br>P.O. Box 158<br>Moffett Field, CA 94035</p>","tableOfContents":"<ul><li>Introduction</li><li>Physiographic and Geologic Setting</li><li>Previous Quaternary Studies</li><li>Mapping Methods</li><li>Explanation of Map Units</li><li>Neotectonic Deformation</li><li>Description of Map Units</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-12-05","noUsgsAuthors":false,"publicationDate":"2023-12-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Menges, Christopher M. 0000-0002-8045-2933 cmmenges@usgs.gov","orcid":"https://orcid.org/0000-0002-8045-2933","contributorId":167644,"corporation":false,"usgs":true,"family":"Menges","given":"Christopher","email":"cmmenges@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":889259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cossette, Pamela M. 0000-0002-9608-6595 pcossette@usgs.gov","orcid":"https://orcid.org/0000-0002-9608-6595","contributorId":1458,"corporation":false,"usgs":true,"family":"Cossette","given":"Pamela","email":"pcossette@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":889260,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70261284,"text":"70261284 - 2023 - Geophysical mapping of the Great Lakes Tectonic Zone and surrounding Precambrian geology in the central Upper Peninsula, Michigan","interactions":[],"lastModifiedDate":"2024-12-04T15:39:20.098701","indexId":"70261284","displayToPublicDate":"2023-12-01T09:33:40","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geophysical mapping of the Great Lakes Tectonic Zone and surrounding Precambrian geology in the central Upper Peninsula, Michigan","docAbstract":"<p>The Great Lakes Tectonic Zone (GLTZ) forms the boundary between the Wawa-Abitibi subprovince (north side) and Minnesota River Valley subprovince (south side) within the Archean Superior Province. The GLTZ is concealed for all of its 1100 km length, except south of Marquette in the central Upper Peninsula of Michigan (Sims, 1991; Sims and Day, 1993). Near KI Sawyer, it is exposed as a NW-striking, 2.3 km wide mylonite zone along a strike length of about 11 km, with a mylonitic foliation that dips steeply to the SW (Sims, 1993). The location extent of the GLTZ is unknown to the east where it is concealed beneath Paleozoic sedimentary rocks. We use legacy aeromagnetic data (Daniels et al., 2009) in combination with modern aeromagnetic data (Drenth and Brown, 2020) and ground gravity data to geophysically characterize the GLTZ and map its eastward extent under cover and map additional nearby covered Precambrian tectonic elements. </p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Institute on Lake Superior Geology proceedings, 69th annual meeting, Eau Claire, Wisconsin, part 1 - Abstracts and proceedings","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Institute on Lake Superior Geology","usgsCitation":"Drenth, B.J., and Cannon, W.F., 2023, Geophysical mapping of the Great Lakes Tectonic Zone and surrounding Precambrian geology in the central Upper Peninsula, Michigan, <i>in</i> Institute on Lake Superior Geology proceedings, 69th annual meeting, Eau Claire, Wisconsin, part 1 - Abstracts and proceedings, p. 27-28.","productDescription":"2 p.","startPage":"27","endPage":"28","ipdsId":"IP-151526","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":464752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":464741,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcollections.lakeheadu.ca/exhibits/show/ilsg/item/8207"}],"country":"United States","state":"Michigan","otherGeospatial":"Upper Peninsula","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -87.6,\n              46.5\n            ],\n            [\n              -87.6,\n              46\n            ],\n            [\n              -86.5,\n              46\n            ],\n            [\n              -86.5,\n              46.5\n            ],\n            [\n              -87.6,\n              46.5\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":920217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cannon, William F. 0000-0002-2699-8118","orcid":"https://orcid.org/0000-0002-2699-8118","contributorId":201972,"corporation":false,"usgs":true,"family":"Cannon","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":920218,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70264392,"text":"70264392 - 2023 - A management-focused population viability analysis for North Atlantic right whales","interactions":[],"lastModifiedDate":"2025-03-14T14:18:14.086582","indexId":"70264392","displayToPublicDate":"2023-12-01T09:10:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"NMFS-NEFSC 307","title":"A management-focused population viability analysis for North Atlantic right whales","docAbstract":"<p>The North Atlantic right whale (<i>Eubalaena glacialis</i>) is among the most endangered whale species in the world and has been in decline since 2010. Considerable effort is directed toward its recovery by striving to remove threats. In this report, we describe the development of a population viability analysis for right whales that is designed to assess the current status, evaluate the contributions of various threats, and explore the management interventions needed to achieve recovery. The individual-based model that underlies this analysis accounts for age- and stagespecific survival and reproductive rates, the effects of severe injury from entanglement or vessel strike, and future changes in prey availability and accessibility. Several new or updated empirical analyses supplied parameter estimates, and parametric uncertainty was carefully incorporated into the model results. </p><p>We find that under the status quo conditions of 2019, prior to the enactment of new regulations by the U.S. and Canada after 2020, the North Atlantic right whale population would be expected to continue to fall, with a median decline of 75% in 100 years (95% projection interval, –98% to +9% change) and a probability of falling below 50 proven females of 0.934 in 100 years. If the recently enacted regulations reduce entanglement risk by 25%, however, the population would be expected to decrease by 42% over 100 years (95% projection interval –92% to +154% change), with a risk of falling below 50 proven females in 100 years of 0.705. If, instead, the recently enacted regulations reduce entanglement risk by 50%, the population would be expected to increase by 52% in 100 years (95% projection interval –83% to +497% change), with a probability of falling below 50 proven females of 0.349. </p><p>Of the 3 primary threats explored in this analysis, the risk of entanglement contributes the most to the long-term risk of quasi-extinction, followed closely by the risk of vessel strike, and much more distantly by a decrease in prey availability. In hypothetical scenarios that fully remove one threat at a time, removal of the entanglement threat alone reduces the probability of falling below 50 proven females in 100 years from 0.934 to 0.053; removal of the vessel strike threat alone reduces it to 0.343; and a return to higher prey conditions, but with both human-related threats still in place, reduces it to 0.875. </p><p>We explored a wide range of management intervention scenarios that changed the rate of entanglement risk (e.g., endline reductions, closures, implementation of ropeless/on-demand gear); the effect of entanglement (through use of weak rope technology); the rate of vessel traffic increase over time; and the severity of vessel strike risk through speed restrictions. We found, for example, that reducing entanglement risk alone by 25% reduces the risk of quasi-extinction from 0.934 to 0.705; reducing vessel strike risk alone by 25% reduces the risk of quasi-extinction from 0.934 to 0.846; but the combination of reducing both entanglement risk and vessel strike risk by 25% reduces the risk of quasi-extinction to 0.528. </p><p>This model and the results it produced are meant to represent an assessment of the current status of North Atlantic right whales using the best available scientific and commercial data and state-of-the-art analytical tools. Our knowledge of the future of the right whale population, however, has limitations. We have endeavored to fully incorporate uncertainty into this model, but there are many areas for continued improvement. We view this model as a living tool that can be improved, adapted, and extended as new data, new methods, and new questions arise. </p>","language":"English","publisher":"National Oceanic and Atmospheric Administration","doi":"10.25923/dqp2-2r71","usgsCitation":"Runge, M.C., Linden, D., Hostetler, J.A., Borggaard, D., Garrison, L.P., Knowlton, A., Lesage, V., Williams, R., and Pace, R., 2023, A management-focused population viability analysis for North Atlantic right whales: NOAA Technical Memorandum NMFS-NEFSC 307, 93 p., https://doi.org/10.25923/dqp2-2r71.","productDescription":"93 p.","ipdsId":"IP-144310","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":483336,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"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":930629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linden, Daniel W.","contributorId":229525,"corporation":false,"usgs":false,"family":"Linden","given":"Daniel W.","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":930630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hostetler, J. A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":11319,"corporation":false,"usgs":true,"family":"Hostetler","given":"J.","middleInitial":"A.","affiliations":[],"preferred":true,"id":930631,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borggaard, Diane L","contributorId":352275,"corporation":false,"usgs":false,"family":"Borggaard","given":"Diane L","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":930632,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrison, Lance P.","contributorId":296893,"corporation":false,"usgs":false,"family":"Garrison","given":"Lance","email":"","middleInitial":"P.","affiliations":[{"id":64230,"text":"NOAA-NMFS Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":930633,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knowlton, Amy R.","contributorId":352046,"corporation":false,"usgs":false,"family":"Knowlton","given":"Amy R.","affiliations":[{"id":37373,"text":"New England Aquarium","active":true,"usgs":false}],"preferred":false,"id":930634,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lesage, Véronique","contributorId":352276,"corporation":false,"usgs":false,"family":"Lesage","given":"Véronique","affiliations":[{"id":13677,"text":"Fisheries and Oceans Canada","active":true,"usgs":false}],"preferred":false,"id":930635,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Robert A. 0000-0002-2973-8493","orcid":"https://orcid.org/0000-0002-2973-8493","contributorId":203802,"corporation":false,"usgs":false,"family":"Williams","given":"Robert A.","affiliations":[{"id":36721,"text":"USGS-Emeritus","active":true,"usgs":false}],"preferred":false,"id":930636,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pace, Richard M III","contributorId":352277,"corporation":false,"usgs":false,"family":"Pace","given":"Richard M","suffix":"III","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":930637,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70265060,"text":"70265060 - 2023 - Red Knot stopover population size and migration ecology at Delaware Bay, USA, 2023","interactions":[],"lastModifiedDate":"2025-04-01T14:07:00.224393","indexId":"70265060","displayToPublicDate":"2023-12-01T09:02:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"title":"Red Knot stopover population size and migration ecology at Delaware Bay, USA, 2023","docAbstract":"<p>Red Knots (<i>Calidris canutus rufa</i>) stop at Delaware Bay on the mid-Atlantic coast of North America during northward migration to feed on eggs of horseshoe crabs (<i>Limulus polyphemus</i>). We conducted a mark-recapture-resight investigation to estimate the passage population of Red Knots at Delaware Bay in 2023. We used a Bayesian analysis of a Jolly-Seber model, which accounts for turnover in the population and the probability of detection during surveys. The 2023 passage population size was estimated at 39,361 (95% credible interval: 33,724–47,556). Although there is broad overlap in the credible intervals for population estimates from 2020–2023, the population estimate for 2023 was below 40,000 birds for only the second time since 2011. Horseshoe crabs have been harvested for use as bait in eel (<i>Anguilla rostrata</i>) and whelk (<i>Busycon</i>) fisheries since at least 1990. In the late 1990s and early 2000s, the number of Red Knots counted during aerial surveys at Delaware Bay declined from ~50,000 to ~13,000 and some avian conservation biologists hypothesized that horseshoe crab harvest levels in the 1990s prevented sufficient refueling for successful migration to the Arctic breeding grounds, reproduction, and survival for the remainder of the annual cycle. Since 2013, the harvest of horseshoe crabs in the Delaware Bay region has been managed using an Adaptive Resource Management (ARM) framework. The objective of the ARM framework is to manage sustainable harvest of Delaware Bay horseshoe crabs while maintaining ecosystem integrity and supporting Red Knot recovery with adequate stopover habitat for Red Knots and other migrating shorebirds. For annual harvest recommendations, the ARM framework requires annual estimates of horseshoe crab population size and the Red Knot stopover population size. The 2023 population size estimate will inform harvest recommendations in the next management cycle for decision making by the Atlantic States Marine Fisheries Commission.</p>","language":"English","publisher":"Delaware Division of Fish and Wildlife","usgsCitation":"Lyons, J.E., 2023, Red Knot stopover population size and migration ecology at Delaware Bay, USA, 2023, 15 p.","productDescription":"15 p.","ipdsId":"IP-159297","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":484058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":484043,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://dnrec.alpha.delaware.gov/fish-wildlife/conservation/shorebirds/research/"}],"country":"United States","state":"Delaware, New Jersey","otherGeospatial":"Delaware Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -75.08367028503963,\n              38.719590525784895\n            ],\n            [\n              -74.91863610562206,\n              38.97012711441013\n            ],\n            [\n              -74.8543007475435,\n              39.15256976333487\n            ],\n            [\n              -75.3829695595777,\n              39.44695257658836\n            ],\n            [\n              -75.51443746521609,\n              39.64539134375613\n            ],\n            [\n              -75.65429693929858,\n              39.619540213656876\n            ],\n            [\n              -75.56198968640427,\n              39.36698574058866\n            ],\n            [\n              -75.42772459128453,\n              39.14606207448017\n            ],\n            [\n              -75.3745779911329,\n              38.9679523390096\n            ],\n            [\n              -75.08367028503963,\n              38.719590525784895\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lyons, James E. 0000-0002-9810-8751","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":222844,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":932440,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250176,"text":"fs20233041 - 2023 - The 3D Elevation Program—Supporting Montana’s economy","interactions":[],"lastModifiedDate":"2024-02-02T13:54:05.100124","indexId":"fs20233041","displayToPublicDate":"2023-11-30T13:15:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-3041","displayTitle":"The 3D Elevation Program—Supporting Montana’s Economy","title":"The 3D Elevation Program—Supporting Montana’s economy","docAbstract":"<h1>Introduction</h1><p>Montana, America’s fourth largest State with an area of 147,040 square miles, is defined by its diverse terrain. The western two-fifths of the State falls within the Rocky Mountains and the eastern three-fifths is in the Great Plains. Because of its location along the Continental Divide, the rivers in Montana drain into either the Pacific Ocean or the Gulf of Mexico. Montana is often called the Treasure State due to its mineral wealth, which includes oil, gas, and coal, but the State’s primary economic activity is agriculture. Other economic activities include natural resources conservation, water supply and quality, infrastructure and construction management, flood risk management, and geologic resource assessment and hazard mitigation. 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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>12201 Sunrise Valley Drive, Mail Stop 511<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>Status of 3DEP in Montana</li><li>Agriculture and Precision Farming</li><li>Flood Risk Management</li><li>Geologic Resource Assessment and Hazard Mitigation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-11-30","noUsgsAuthors":false,"publicationDate":"2023-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Carlson, Tom 0000-0002-5682-8988","orcid":"https://orcid.org/0000-0002-5682-8988","contributorId":304658,"corporation":false,"usgs":true,"family":"Carlson","given":"Tom","email":"","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":888663,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70250366,"text":"70250366 - 2023 - Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui","interactions":[],"lastModifiedDate":"2023-12-05T13:13:51.187375","indexId":"70250366","displayToPublicDate":"2023-11-30T07:05:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui","docAbstract":"<p class=\"abstract_block\">Haleakalā National Park and montane areas on east Maui, Hawaiian Archipelago, support critical nesting habitat for endangered ‘ua‘u Hawaiian petrel<span>&nbsp;</span><i>Pterodroma sandwichensis</i>. Habitat loss, non-native predators, and damage by feral ungulates are limiting factors for ground-nesting petrels at Haleakalā and throughout Hawai‘i. Because nesting habitats differ among the Hawaiian Islands, habitat distribution modeling for Hawaiian petrel has been island specific. Based on 2453 known nest site locations, we provide the first landscape-scale predictive model describing relative abundance and habitat available for nesting petrels throughout upper Haleakalā (1830 to 3055 m). We evaluated (principal components analyses and Pearson’s correlation) 13 spatial landscape and climate predictor variables associated with nest sites and the background landscape followed by random forest modeling to predict nest site density. Six variables (elevation, slope, topographic position index at 2 scales, heat load index, presence-absence ash/cinder, and presence-absence vegetation) indicated nest sites occurred non-randomly throughout the central part of the summit and crater; greatest concentrations were predicted along the crater rim and a ridgeline extending southwest from the summit. Moderately high predicted density occurred in the northeastern and northern crater. Lower elevations to the north, west, and south flanks of Haleakalā had relatively fewer predicted nest sites. Although we focused on higher elevations on Haleakalā, there is no reason to suspect that conservation efforts would not be successful at lower elevations, provided nesting petrels were protected from invasive predators, grazing ungulates, and significant land alteration.</p>","language":"English","publisher":"Inter-Research Science Publisher","doi":"10.3354/esr01280","usgsCitation":"Adams, J., Felis, J., Klinger, R.C., Kelsey, E.C., Tamayose, J., Kaholoa’a, R., Bailey, C.N., Penniman, J.F., Learned, J., Ganter, C., Medeiros, J., and Chen, H., 2023, Predicted distribution of ‘ua‘u (Hawaiian petrel Pterodroma sandwichensis) nest sites on Haleakalā, Maui: Endangered Species Research, v. 52, p. 231-246, https://doi.org/10.3354/esr01280.","productDescription":"16 p.","startPage":"231","endPage":"246","ipdsId":"IP-148421","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":441525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01280","text":"Publisher Index Page"},{"id":423239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Haleakalā, Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -156.31986912490262,\n              20.79241841577982\n            ],\n            [\n              -156.31986912490262,\n              20.617670800708467\n            ],\n            [\n              -156.03010472060575,\n              20.617670800708467\n            ],\n            [\n              -156.03010472060575,\n              20.79241841577982\n            ],\n            [\n              -156.31986912490262,\n              20.79241841577982\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Josh 0000-0003-3056-925X","orcid":"https://orcid.org/0000-0003-3056-925X","contributorId":213442,"corporation":false,"usgs":true,"family":"Adams","given":"Josh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889570,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felis, Jonathan J. 0000-0002-0608-8950","orcid":"https://orcid.org/0000-0002-0608-8950","contributorId":332148,"corporation":false,"usgs":false,"family":"Felis","given":"Jonathan J.","affiliations":[{"id":17847,"text":"USGS-WERC","active":true,"usgs":false}],"preferred":false,"id":889571,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889572,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelsey, Emily C. 0000-0002-0107-3530 ekelsey@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3530","contributorId":206505,"corporation":false,"usgs":true,"family":"Kelsey","given":"Emily","email":"ekelsey@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":889573,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tamayose, Joy","contributorId":332150,"corporation":false,"usgs":false,"family":"Tamayose","given":"Joy","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":889574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kaholoa’a, Raina","contributorId":332151,"corporation":false,"usgs":false,"family":"Kaholoa’a","given":"Raina","email":"","affiliations":[{"id":36245,"text":"NPS","active":true,"usgs":false}],"preferred":false,"id":889575,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bailey, Cathleen Natividad","contributorId":220473,"corporation":false,"usgs":false,"family":"Bailey","given":"Cathleen","email":"","middleInitial":"Natividad","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":889576,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Penniman, Jay F.","contributorId":332154,"corporation":false,"usgs":false,"family":"Penniman","given":"Jay","email":"","middleInitial":"F.","affiliations":[{"id":79395,"text":"Maui Nui Seabird Recovery Project","active":true,"usgs":false}],"preferred":false,"id":889577,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Learned, Jennifer","contributorId":332155,"corporation":false,"usgs":false,"family":"Learned","given":"Jennifer","email":"","affiliations":[{"id":79395,"text":"Maui Nui Seabird Recovery Project","active":true,"usgs":false}],"preferred":false,"id":889578,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ganter, Ciara","contributorId":332156,"corporation":false,"usgs":false,"family":"Ganter","given":"Ciara","email":"","affiliations":[{"id":79397,"text":"Hawai'i State of Dep. of Land and Natural Resources","active":true,"usgs":false}],"preferred":false,"id":889579,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Medeiros, John","contributorId":167591,"corporation":false,"usgs":false,"family":"Medeiros","given":"John","email":"","affiliations":[{"id":24766,"text":"4. State of Hawaii, Division of Forestry and Wildlife-Maui, 54 South High Street # 101, Wailuku, HI 96793.","active":true,"usgs":false}],"preferred":false,"id":889580,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Chen, Huisheng","contributorId":332157,"corporation":false,"usgs":false,"family":"Chen","given":"Huisheng","email":"","affiliations":[{"id":79398,"text":"NPS; University of Hawai'i","active":true,"usgs":false}],"preferred":false,"id":889581,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70250696,"text":"70250696 - 2023 - FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA","interactions":[],"lastModifiedDate":"2023-12-27T12:54:08.529","indexId":"70250696","displayToPublicDate":"2023-11-30T06:50:51","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA","docAbstract":"This report on baseline assessment of fish community assemblage and migratory patterns of fishes in the lower Boardman River (LBR; Traverse City, MI (USA)) is one of four assessment projects conceived circa 2017 after the Boardman (Ottaway) River was selected by the Great Lakes Fishery Commission (GLFC) and collaborating agencies as the future site of the Selective Bi-directional Fish Passage (FishPass) project. This report describes the results from\nfisheries community sampling from 2017-2021 and the concurrent bio-telemetry project aimed at understanding phenological changes in the fish community and movement and space-use of a variety of large-bodied fishes in the LBR against which selective fish passage treatments will be developed and evaluated.\nFish migration in riverine environments is a growing area of concern as mounting anthropogenic influences, particularly fragmentation from dams and barriers, constitute a major threat to global river species diversity. Specifically, In the Laurentian Great Lakes basin, more than 250,000 dams, weirs, culverts, and other significant obstructions prevent the movement of species both between the Great Lakes and rivers, and within rivers. Barriers\nimpede the movement of fishes between areas critical to the completion of their lifecycle, affecting both population and ecosystem viability. However, a conundrum arises in that the same barriers can also prevent the upstream invasion of non-native or undesirable species (most notably the sea lamprey Petromyzon marinus in the Great Lakes),prevent the transfer of contaminants and diseases, halt deleterious genes, provide recreational opportunities, or\ngenerate power. As a result, fish passage solutions with the capability of selectively passing desirable taxa while restricting the dispersal of undesirable taxa (selective connectivity) are sought to solve this connectivity conundrum. FishPass is a multi-agency initiative planned to replace the Union Street Dam on the Boardman River in Traverse City,MI (USA), aimed at developing and implementing automatic or semiautomatic selective bi-directional fish guidance,\nsorting, and passage techniques and technologies. Pivotal to both the successful development of selective connectivity and assessment of its effects is a more complete understanding of the Boardman River’s fishery. Specifically, understanding the species and size composition of the fish community, fish movement phenology and the associated abiotic conditions.\n\nFish community sampling confirmed the presence of 28 unique species in the LBR (Boardman River reach below Union Street Dam). Passive Integrated Transponder (PIT) tag telemetry increased the resolution of phenological shifts in the fish community that could not have been captured from periodic fish sampling. This data demonstrates large variation within species and overlap between species presence. However, discrete periods of presence were identified across most species when considering the central tendencies in the distribution of their presence. Rainbow trout Oncorhynchus mykiss were found to be omni-present in the river while brown trout Salmo trutta and smallmouth bass Micropterus dolomieu also persisted throughout a majority of the year; all of which will require continually sorting at FishPass. PIT tag telemetry also provided the important understanding that individuals (3-64%) of all species return to\nthe LBR across multiple years.\n\nRadio telemetry (RT) proved useful in refining the entry and exit timing and in evaluating the proportion of individuals that encountered the current Union Street Dam and Kid’s Creek (the only tributary confluence below the Union Street Dam) across six species (common white sucker Catostomus commersonii, rainbow trout, smallmouth bass, walleye Sander vitreus, brown trout, and common carp Cyprinus carpio). The RT results show that these species are present in FishPass Research Publication: baseline assessment\nof fish community assemblage and migratory pattern in the Boardman River, Traverse City, Michigan, USA November 2023 7 between April and August. Our analysis also demonstrated that not all fish that entered the river proceeded to the Union Street Dam, but those that did, did so prior to being detected encountering Kid’s Creek. Common white sucker and rainbow trout were the only species to be detected encountering Kid’s Creek.\n\nCollectively, the results of this study provide a baseline understanding of the seasonal fish diversity and relative abundance of fishes in the LBR, and a basic description of observed movement patterns of a subset of species in the context of seasonal phenology, entry and exit behavior within the LBR, and the propensity at which telemetered individuals encounter the Union Street dam and/or Kid’s Creek.","language":"English","publisher":"Great Lakes Fishery Commission","collaboration":"Great Lakes Fisheries Commission","usgsCitation":"Swanson, R.G., Zielinski, D.P., Castro-Santos, T., and Muir, A., 2023, FishPass baseline assessment of fish community assemblage and migratory patterns in in the Boardman River, Traverse City, Michigan, USA, 49 p.","productDescription":"49 p.","ipdsId":"IP-155321","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":423903,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":423897,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"http://www.glfc.org/pubs/pdfs/research/FishPassResearchPublication2023-CommunityAssemblage.pdf"}],"country":"United States","state":"Michigan","city":"Traverse City","otherGeospatial":"Boardman River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.7182012975478,\n              44.78761727288912\n            ],\n            [\n              -85.7182012975478,\n              44.70666411909653\n            ],\n            [\n              -85.53349365594626,\n              44.70666411909653\n            ],\n            [\n              -85.53349365594626,\n              44.78761727288912\n            ],\n            [\n              -85.7182012975478,\n              44.78761727288912\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Swanson, Reid G.","contributorId":332833,"corporation":false,"usgs":false,"family":"Swanson","given":"Reid","email":"","middleInitial":"G.","affiliations":[{"id":65273,"text":"GLFC","active":true,"usgs":false}],"preferred":false,"id":891020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zielinski, Daniel P.","contributorId":211034,"corporation":false,"usgs":false,"family":"Zielinski","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":34820,"text":"Great Lakes Fisheries Commission, Ann Arbor, MI","active":true,"usgs":false}],"preferred":false,"id":891021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore 0000-0003-2575-9120","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":315433,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":891022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muir, Andrew M.","contributorId":103933,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew M.","affiliations":[],"preferred":false,"id":891023,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70243997,"text":"70243997 - 2023 - Aging contrast: A contrastive learning framework for fish re-identification across seasons and years.","interactions":[],"lastModifiedDate":"2024-02-29T15:44:48.92704","indexId":"70243997","displayToPublicDate":"2023-11-27T09:34:21","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Aging contrast: A contrastive learning framework for fish re-identification across seasons and years.","docAbstract":"<p><span>The fields of biology, ecology, and fisheries management are witnessing a growing demand for distinguishing individual fish. In recent years, deep learning methods have emerged as a promising tool for image-based fish recognition. Our study is focused on the re-identification of masu salmon from Japan, wherein fish were individually marked and photographed to evaluate discriminative body characteristics. Unlike previous studies where fish were sampled during the same time period, we evaluated individual re-identification across seasons and years to address challenges due to aging, seasonal variation, and other factors. In this paper, we propose a new contrastive learning framework called&nbsp;</span><u>Ag</u><span>ing&nbsp;</span><u>Co</u><span>ntrast (AgCo) and evaluate its performance on the masu salmon dataset. Our analysis indicates that, unlike large changes in body size over time, the pattern of parr marks on the lateral line of the fish body remains relatively stable, despite some change in coloration across seasons. AgCo accounts for such seasonally-invariant features and performs re-identification based on the cosine similarity of these features. Extensive experiments show that our AgCo method outperforms other state-of-the-art methods.</span></p>","conferenceTitle":"AI 2023: Advances in Artificial Intelligence: 36th Australasian Joint Conference on Artificial Intelligence, AI 2023","conferenceDate":"November 28-December 1, 2023","conferenceLocation":"Brisbane, Australia","language":"English","publisher":"Springer","doi":"10.1007/978-981-99-8388-9_21","usgsCitation":"Shi, W., Zhou, Z., Letcher, B., Hitt, N.P., Kanno, Y., Futamura, R., Kishida, O., Morita, K., and Li, S., 2023, Aging contrast: A contrastive learning framework for fish re-identification across seasons and years., AI 2023: Advances in Artificial Intelligence: 36th Australasian Joint Conference on Artificial Intelligence, AI 2023, v. 14471, Brisbane, Australia, November 28-December 1, 2023, p. 252-264, https://doi.org/10.1007/978-981-99-8388-9_21.","productDescription":"13 p.","startPage":"252","endPage":"264","ipdsId":"IP-150815","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":426128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14471","noUsgsAuthors":false,"publicationDate":"2023-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Shi, Weili","contributorId":305925,"corporation":false,"usgs":false,"family":"Shi","given":"Weili","email":"","affiliations":[{"id":25492,"text":"University of Virginia","active":true,"usgs":false}],"preferred":false,"id":874101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhou, Z.","contributorId":305926,"corporation":false,"usgs":false,"family":"Zhou","given":"Z.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":874102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":238185,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"","middleInitial":"P.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":874103,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kanno, Yoichiro ykanno@usgs.gov","contributorId":4876,"corporation":false,"usgs":true,"family":"Kanno","given":"Yoichiro","email":"ykanno@usgs.gov","affiliations":[],"preferred":true,"id":874105,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Futamura, R.","contributorId":305928,"corporation":false,"usgs":false,"family":"Futamura","given":"R.","email":"","affiliations":[{"id":16855,"text":"Hokkaido University","active":true,"usgs":false}],"preferred":false,"id":874106,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kishida, O.","contributorId":305927,"corporation":false,"usgs":false,"family":"Kishida","given":"O.","email":"","affiliations":[{"id":16855,"text":"Hokkaido University","active":true,"usgs":false}],"preferred":false,"id":895666,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morita, K.","contributorId":305929,"corporation":false,"usgs":false,"family":"Morita","given":"K.","email":"","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":874108,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Li, Sheng","contributorId":297449,"corporation":false,"usgs":false,"family":"Li","given":"Sheng","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":874109,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70250161,"text":"70250161 - 2023 - Deer management generally reduces densities of nymphal Ixodes scapularis, but not prevalence of infection with Borrelia burgdorferi sensu stricto","interactions":[],"lastModifiedDate":"2023-11-24T12:54:19.730004","indexId":"70250161","displayToPublicDate":"2023-11-24T06:43:39","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5082,"text":"Ticks and Tick-borne Diseases","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Deer management generally reduces densities of nymphal <i>Ixodes scapularis</i>, but not prevalence of infection with <i>Borrelia burgdorferi</i> sensu stricto","title":"Deer management generally reduces densities of nymphal Ixodes scapularis, but not prevalence of infection with Borrelia burgdorferi sensu stricto","docAbstract":"<p><span>Human Lyme disease–primarily caused by the bacterium&nbsp;</span><span><i>Borrelia burgdorferi</i></span><span>&nbsp;sensu stricto (s.s.) in North America–is the most common vector-borne disease in the United States. Research on risk mitigation strategies during the last three decades has emphasized methods to reduce densities of the primary vector in eastern North America, the blacklegged tick (</span><span><i>Ixodes scapularis</i></span><span>). Controlling white-tailed&nbsp;deer&nbsp;populations has been considered a potential method for reducing tick densities, as white-tailed deer are important hosts for blacklegged tick reproduction. However, the feasibility and efficacy of white-tailed deer management to impact acarological risk of encountering infected ticks (namely, density of host-seeking infected nymphs; DIN) is unclear. We investigated the effect of white-tailed deer density and management on the density of host-seeking nymphs and&nbsp;</span><i>B. burgdorferi</i><span>&nbsp;s.s. infection prevalence using surveillance data from eight national parks and park regions in the eastern United States from 2014–2022. We found that deer density was significantly positively correlated with the density of nymphs (nymph density increased by 49% with a 1 standard deviation increase in deer density) but was not strongly correlated with the prevalence of&nbsp;</span><i>B. burgdorferi</i><span>&nbsp;s.s. infection in nymphal ticks. Further, while white-tailed deer reduction efforts were followed by a decrease in the density of&nbsp;</span><i>I. scapularis</i><span>&nbsp;nymphs in parks, deer removal had variable effects on&nbsp;</span><i>B. burgdorferi</i><span>&nbsp;s.s. infection prevalence, with some parks experiencing slight declines and others slight increases in prevalence. Our findings suggest that managing white-tailed deer densities alone may not be effective in reducing DIN in all situations but may be a useful tool when implemented in integrated management regimes.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ttbdis.2023.102202","usgsCitation":"Martin, A., Buttke, D., Raphael, J., Taylor, K., Maes, S., Parise, C.M., Ginsberg, H., and Cross, P., 2023, Deer management generally reduces densities of nymphal Ixodes scapularis, but not prevalence of infection with Borrelia burgdorferi sensu stricto: Ticks and Tick-borne Diseases, v. 14, no. 5, 102202, 15 p., https://doi.org/10.1016/j.ttbdis.2023.102202.","productDescription":"102202, 15 p.","ipdsId":"IP-146009","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441555,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ttbdis.2023.102202","text":"Publisher Index Page"},{"id":435115,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LSI8K9","text":"USGS data release","linkHelpText":"Blacklegged tick nymph densities, tickborne pathogen prevalence, and white-tailed deer densities in eight national parks in the eastern United States from 2014-2022"},{"id":422883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Pennsylvania, Virginia, West Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -77.04185662081417,\n              38.07679669581978\n            ],\n            [\n              -77.04185662081417,\n              40.08490092740237\n            ],\n            [\n              -77.97369181209007,\n              40.08490092740237\n            ],\n            [\n              -77.97369181209007,\n              38.07679669581978\n            ],\n            [\n              -77.04185662081417,\n              38.07679669581978\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, Alynn 0000-0002-6603-2385","orcid":"https://orcid.org/0000-0002-6603-2385","contributorId":224233,"corporation":false,"usgs":true,"family":"Martin","given":"Alynn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":888616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buttke, Danielle","contributorId":225082,"corporation":false,"usgs":false,"family":"Buttke","given":"Danielle","affiliations":[],"preferred":false,"id":888617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raphael, Jordan","contributorId":218631,"corporation":false,"usgs":false,"family":"Raphael","given":"Jordan","email":"","affiliations":[{"id":39877,"text":"National Park Service, Fire Island National Seashore","active":true,"usgs":false}],"preferred":false,"id":888618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Kelsey","contributorId":194103,"corporation":false,"usgs":false,"family":"Taylor","given":"Kelsey","email":"","affiliations":[],"preferred":false,"id":888619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maes, Sarah","contributorId":331731,"corporation":false,"usgs":false,"family":"Maes","given":"Sarah","email":"","affiliations":[],"preferred":false,"id":888641,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Parise, Christina M.","contributorId":331732,"corporation":false,"usgs":false,"family":"Parise","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":888642,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ginsberg, Howard 0000-0002-4933-2466","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":15473,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":888620,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":218820,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":888621,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70262313,"text":"70262313 - 2023 - Response of Tiger Salamanders (Ambystoma t. tigrinum) to wetland restoration in a midwestern agricultural landscape, U.S.A.","interactions":[],"lastModifiedDate":"2025-01-22T17:19:20.260328","indexId":"70262313","displayToPublicDate":"2023-11-21T10:13:38","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9341,"text":"Ichthyology & Herpetology","active":true,"publicationSubtype":{"id":10}},"title":"Response of Tiger Salamanders (Ambystoma t. tigrinum) to wetland restoration in a midwestern agricultural landscape, U.S.A.","docAbstract":"<p><span>Since the early 1990s, &gt; 3,000 ha of wetlands (and adjacent prairie) have been restored on the row-crop agricultural landscape of Winnebago County, Iowa, U.S.A. From 2014–2016, we surveyed 45 wetlands among 19 easements for occupancy by Eastern Tiger Salamanders (</span><i>Ambystoma tigrinum tigrinum</i><span>) and used radio-telemetry to measure their patterns of movement and habitat use. Rates of occupancy increased with wetland age, from &lt; 25% for wetlands 1–2 years old to ∼75% for wetlands &gt; 11 years old. A two-year survey (2014 and 2015) of ten wetlands restored in 2013 showed that nine were occupied after two years; we did not find a relationship between distance to the nearest salamander population and occupancy of newly restored wetlands by salamanders. We tracked 30 salamanders after they left their breeding wetlands for an average of 69±37 d (range = 14–109 d) and relocated them a total of 393 times. Typically, once a salamander left its breeding wetland, it traveled 50–350 m over several days, found a suitable burrow, then remained for much of the rest of the season. Mean daily distances traveled by salamanders were 7.9±5.6 m (range = 0–135 m); the range of maximum straight-line distances moved was 26–659 m; only one individual salamander traveled in a statistically linear path, relative to a random walk. While ∼90% of the landscape was composed of row-crop fields, salamanders used protective grassy habitats (e.g., restored prairie, road ditches) on ∼88% of our observations. Only three salamanders used row-crop fields, and two of them were killed by heavy equipment. Regardless of the terrestrial habitat types used by salamanders, we found them underground on 336 (84.8%) of our observations.</span></p>","language":"English","publisher":"BioOne","doi":"10.1643/h2020083","usgsCitation":"Bartelt, P., Devries, A., and Klaver, R.W., 2023, Response of Tiger Salamanders (Ambystoma t. tigrinum) to wetland restoration in a midwestern agricultural landscape, U.S.A.: Ichthyology & Herpetology, v. 111, no. 4, p. 571-583, https://doi.org/10.1643/h2020083.","productDescription":"13 p.","startPage":"571","endPage":"583","ipdsId":"IP-116927","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":480939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Winnebago County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.9691,43.5044],[-93.6782,43.5047],[-93.6485,43.5045],[-93.4964,43.504],[-93.4971,43.4347],[-93.4971,43.3446],[-93.4977,43.2568],[-93.6184,43.2572],[-93.7354,43.257],[-93.853,43.2568],[-93.9699,43.2573],[-93.9705,43.3447],[-93.9699,43.4334],[-93.9691,43.5044]]]},\"properties\":{\"name\":\"Winnebago\",\"state\":\"IA\"}}]}","volume":"111","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bartelt, Paul E.","contributorId":348825,"corporation":false,"usgs":false,"family":"Bartelt","given":"Paul E.","affiliations":[{"id":56262,"text":"Waldorf University","active":true,"usgs":false}],"preferred":false,"id":923810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devries, Alyse T.","contributorId":348826,"corporation":false,"usgs":false,"family":"Devries","given":"Alyse T.","affiliations":[{"id":56262,"text":"Waldorf University","active":true,"usgs":false}],"preferred":false,"id":923811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923809,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250205,"text":"70250205 - 2023 - Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty","interactions":[],"lastModifiedDate":"2023-11-28T13:21:31.650315","indexId":"70250205","displayToPublicDate":"2023-11-20T07:08:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5213,"text":"Epidemics","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41467-023-42680-x","usgsCitation":"Howerton, E., Contamin, L., Mullany, L.C., Qin, M., Reich, N.G., Bents, S., Borchering, R.K., Jung, S., Loo, S.L., Smith, C.P., Levander, J., Kerr, J., Espino, J., van Panhuis, W., Hochheiser, H., Galanti, M., Yamana, T.K., Pei, S., Shaman, J.L., Rainwater-Lovett, K., Kinsey, M., Tallaksen, K., Wilson, S., Shin, L., Lemaitre, J.C., Kaminsky, J., Dent Hulse, J., Lee, E.C., McKee, C., Hill, A., Karlen, D., Chinazzi, M., Davis, J.T., Mu, K., Xiong, X., Pastore Piontti, A., Vespignani, A., Rosenstrom, E.T., Ivy, J.S., Mayorga, M.E., Swann, J.L., Espana, G., Cavany, S., Moore, S., Perkins, A., Hladish, T.J., Pillai, A.N., Ben Toh, K., Longini, I., Chen, S., Paul, R., Janies, D., Thill, J., Bouchnita, A., Bi, K., Lachmann, M., Fox, S., Ancel Meyers, L., Srivastava, A., Porebski, P., Venkatramanan, S., Adiga, A., Lewis, B., Klahn, B., Outten, J., Hurt, B., Chen, J., Mortveit, H., Wilson, A., Marathe, M., Hoops, S., Bhattacharya, P., Machi, D., Gunnels, B.L., Healy, J.M., Slayton, R.B., Johansson, M.A., Biggerstaff, M., Truelove, S., Runge, M.C., Shea, K., Viboud, C., and Lessler, J., 2023, Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty: Epidemics, v. 14, 7260, 15 p., https://doi.org/10.1038/s41467-023-42680-x.","productDescription":"7260, 15 p.","ipdsId":"IP-154417","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441580,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-023-42680-x","text":"Publisher Index 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C","contributorId":301869,"corporation":false,"usgs":false,"family":"Mullany","given":"Luke","email":"","middleInitial":"C","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":888824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Qin, Michelle","contributorId":296526,"corporation":false,"usgs":false,"family":"Qin","given":"Michelle","email":"","affiliations":[],"preferred":false,"id":888825,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reich, Nicholas G.","contributorId":258146,"corporation":false,"usgs":false,"family":"Reich","given":"Nicholas","email":"","middleInitial":"G.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":888826,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bents, 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,{"id":70250104,"text":"70250104 - 2023 - Chemistry and petrography of early 19th century basaltic andesites and basalts from the Kamakaiʻa Hills in the Southwest Rift Zone of Kīlauea volcano, Hawaiʻi","interactions":[],"lastModifiedDate":"2023-11-20T12:43:18.922812","indexId":"70250104","displayToPublicDate":"2023-11-20T06:33:27","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Chemistry and petrography of early 19th century basaltic andesites and basalts from the Kamakaiʻa Hills in the Southwest Rift Zone of Kīlauea volcano, Hawaiʻi","docAbstract":"<p id=\"sp0070\"><span>Kīlauea is a frequently active, open-system volcano on the Island of Hawaiʻi known for erupting olivine-dominated&nbsp;tholeiitic basalt&nbsp;compositions. On rare occasions it erupts more differentiated&nbsp;magmas&nbsp;(&lt;1% of erupted volume), such as basaltic&nbsp;andesites&nbsp;and andesites, from its&nbsp;rift zones. These differentiated magmas offer an opportunity to understand better the&nbsp;petrology, magma storage, magma mixing, and eruptive triggers that occur in Kīlauea's rift zone reservoirs. This study focuses on an eruption from the Southwest Rift Zone of Kīlauea, which is dominantly basaltic andesite with subordinate&nbsp;basalt. This eruption originated at the Kamakaiʻa Hills during the early 19th century and has two eruptive phases: 1) an early ‘a‘ā phase that is primarily exposed in the eastern part of the flow field, with minor western lobes, and 2) a late pāhoehoe phase that makes up most of the western part of the flow field. The early ‘a‘ā phase covers at least 5.8&nbsp;km</span><sup>2</sup><span>&nbsp;</span>with an erupted volume of ∼150&nbsp;×&nbsp;10<sup>6</sup>&nbsp;m<sup>3</sup><span>&nbsp;</span>and consists of uniform composition basaltic andesites with 3.72–4.15&nbsp;wt% MgO over its ∼7&nbsp;km flow length. The late pāhoehoe phase reached &gt;10&nbsp;km from its vent, covers an area of ∼7.1&nbsp;km<sup>2</sup>, has a volume of ∼100&nbsp;×&nbsp;10<sup>6</sup>&nbsp;m<sup>3</sup><span>, and initially erupted basaltic andesite near its vent (4.50–5.64&nbsp;wt% MgO extending to 3.8&nbsp;km from vent) with channel and tube-fed basalt (6.21–12.38&nbsp;wt% MgO sampled at &gt;3.8&nbsp;km from vent) emplaced during its waning stages. Most Kamakaiʻa Hills lavas are crystal-poor, containing ≤1.5% glomerocrysts and individual&nbsp;phenocrysts&nbsp;of plagioclase +&nbsp;clinopyroxene&nbsp;+ Fe</span><img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\"><span>Ti oxides ±&nbsp;orthopyroxene, as well as olivine in lavas with &gt;6&nbsp;wt% MgO.</span></p><p id=\"sp0075\">Major-oxide and trace-element concentrations throughout the Kamakaiʻa Hills lavas demonstrate the involvement of three distinct magmatic processes. First, the basaltic andesites of the early ‘a‘ā phase are the products of fractionation of plagioclase + clinopyroxene + Fe<img src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\" alt=\"single bond\" data-mce-src=\"https://sdfestaticassets-us-east-1.sciencedirectassets.com/shared-assets/55/entities/sbnd.gif\">Ti oxides ± orthopyroxene, indicative of magmas that have been stored in rift zone reservoirs for decades or longer. Second, the near-vent (within ∼400&nbsp;m of vent) basaltic andesites of the late pāhoehoe phase yield chemical concentrations that indicate magma mixing with a more differentiated magma (of a similar evolved composition to basaltic andesites at ∼55–56&nbsp;wt% SiO<sub>2</sub><span>&nbsp;</span>and&nbsp;∼3.4–4.1&nbsp;wt% MgO that erupted in the lower East Rift Zone in 2018). Third, the progressively more mafic magma (containing olivine + plagioclase + clinopyroxene) that continued to erupt throughout the waning stages of activity suggests an eruptive triggering process whereby an intruding summit or uprift reservoir basalt overpressurized and forced out the stored, differentiated magma of the Kamakaiʻa Hills rift zone reservoir.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2023.107967","usgsCitation":"Downs, D.T., Sas, M., and Hazlett, R.W., 2023, Chemistry and petrography of early 19th century basaltic andesites and basalts from the Kamakaiʻa Hills in the Southwest Rift Zone of Kīlauea volcano, Hawaiʻi: Journal of Volcanology and Geothermal Research, v. 444, 107967, 19 p., https://doi.org/10.1016/j.jvolgeores.2023.107967.","productDescription":"107967, 19 p.","ipdsId":"IP-148287","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":435120,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TLM9YD","text":"USGS data release","linkHelpText":"Major- and trace-element chemical analyses of whole-rock and glass from the Kamakaiʻa Hills of the Southwest Rift Zone of Kīlauea volcano, Hawaiʻi"},{"id":422713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaiʻi","otherGeospatial":"Kamakaiʻa Hills, Kīlauea Volcano, Southwest Rift Zone","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.53595307076637,\n              19.09998767098206\n            ],\n            [\n              -155.5226475641525,\n              19.108725037100598\n            ],\n            [\n              -155.50845458316687,\n              19.117944797569507\n            ],\n            [\n       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Center","active":true,"usgs":true}],"preferred":true,"id":888365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sas, May","contributorId":194298,"corporation":false,"usgs":false,"family":"Sas","given":"May","email":"","affiliations":[],"preferred":false,"id":888366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazlett, Richard W. 0000-0002-8841-0906","orcid":"https://orcid.org/0000-0002-8841-0906","contributorId":214066,"corporation":false,"usgs":false,"family":"Hazlett","given":"Richard","email":"","middleInitial":"W.","affiliations":[{"id":38976,"text":"Pomona College, Claremont, CA; UH Hilo, Hilo HI; Department of Interior","active":true,"usgs":false}],"preferred":false,"id":888367,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70250099,"text":"sir20235066 - 2023 - Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013","interactions":[],"lastModifiedDate":"2026-03-09T16:53:50.063749","indexId":"sir20235066","displayToPublicDate":"2023-11-17T13:55:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5066","displayTitle":"Updates to the Regional Groundwater-Flow Model of the New Jersey Coastal Plain, 1980–2013","title":"Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013","docAbstract":"<p>A 21-layer three-dimensional transient groundwater-flow model of the New Jersey Coastal Plain was developed and calibrated by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection to simulate groundwater-flow conditions during 1980–2013, incorporating average annual groundwater withdrawals and average annual groundwater recharge. This model is the third version of the New Jersey Coastal Plain regional groundwater-flow model that was initially developed as part of the USGS Regional Aquifer System Analysis (RASA) program. The model simulates groundwater flow in 11 aquifers and 10 intervening confining units of the New Jersey Coastal Plain to provide a regional overview of groundwater conditions. Averaged groundwater withdrawal data for 1980 to 2013 were used in the model. The 11 aquifers in New Jersey are, from shallowest to deepest, the Holly Beach water-bearing zone and the confined Cohansey aquifer in Cape May County; the Rio Grande water-bearing zone; the Atlantic City 800-foot sand; the Piney Point, Vincentown, and Wenonah-Mount Laurel aquifers; the Englishtown aquifer system; and the upper, middle, and lower aquifers of the Potomac-Raritan-Magothy (PRM) aquifer system.</p><p>The model was developed with the MODFLOW–2005 numerical code and the UCODE parameter estimation technique and calibrated using water-level and base-flow observations. A total of 3,453 water-level observations from 392 wells in New Jersey and 48 wells in Delaware from 1983 to 2013 were used in model calibration, which includes historical water-level trends for 29 wells in New Jersey during 1980–2013 presented in time-series hydrographs. In addition, derived observations also were included by calculating the vertical gradient at 33 pairs of nested observation wells in New Jersey, for a total of 210 observations. Changes in water levels over time were calculated for 134 wells in New Jersey and four wells in Delaware where water levels had varied substantially (approximately 10 ft) over the 30-year span of synoptic water-level measurements, for a total of 767 observations. A total of 1,485 base-flow observations in 47 surface-water basins in New Jersey from 1980 to 2013 were used in model calibration.</p><p>Updates to the groundwater-flow model include the conversion to a fully three-dimensional model from the previous quasi-three-dimensional model. The new model will allow for potential future uses such as particle tracking or simulation of variable-density groundwater flow that could not be accomplished with earlier versions of the model. Spatially and temporally variable recharge estimated by using a soil-water balance model resulted in a spatially and temporally finer discretization. The Rio Grande water-bearing zone was added to the model as an aquifer layer to refine estimates of simulated flow in Atlantic and Cape May Counties, New Jersey. Hydrogeologic parameters were updated to include the confining units in New Jersey and corresponding hydrogeologic units in Delaware and eastern Maryland.</p><p>The simulated water levels for the New Jersey Coastal Plain aquifers were compared to water-level measurements made during 1980–2013. The average residual for 4,243 water-level observations for New Jersey (simulated water levels minus measured water levels) is 1.5 feet. The simulated water-level contours for the confined aquifers for 2013 were compared to potentiometric surfaces produced from water levels measured during 2013. Simulated water levels generally matched the 2013 potentiometric surfaces of the confined aquifers in the areas of large withdrawals. Hydrographs of wells in the confined Coastal Plain aquifers of New Jersey show that simulated water levels generally match the magnitude and seasonal variation of the observed water levels. Hydrographs of base flow for the 47 streamgaging stations in New Jersey indicate that most of the simulated and estimated data match reasonably well.</p><p>Groundwater withdrawals are an important resource for water supply, agricultural, industrial, and commercial needs in the New Jersey Coastal Plain. Groundwater withdrawals from the New Jersey Coastal Plain aquifers have resulted in persistent, regionally extensive cones of depression in the Englishtown aquifer system and Wenonah-Mount Laurel aquifer in Ocean and Monmouth Counties; Wenonah-Mount Laurel and upper, middle, and lower PRM aquifers in Camden County; and Atlantic City 800-foot sand in Atlantic County. Because hydrologic stresses and water-management needs change with time, periodic updates to the groundwater-flow model are required to provide current information about hydrologic conditions in the New Jersey Coastal Plain and to maintain its usefulness as a tool to manage water resources and develop water-resource strategies. The current updates will support the continued application of this model as a tool for evaluating the regional effects of changes in groundwater withdrawals and of current and potential future water-management strategies on groundwater levels in the New Jersey Coastal Plain.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235066","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Gordon, A.D., and Carleton, G.B., 2023, Updates to the regional groundwater-flow model of the New Jersey Coastal Plain, 1980–2013: U.S. Geological Survey Scientific Investigations Report 2023–5066, 116 p., https://doi.org/10.3133/sir20235066","productDescription":"Report: xii, 116 p.; Data Release","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-127396","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":500947,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115639.htm","linkFileType":{"id":5,"text":"html"}},{"id":422695,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5066/images/"},{"id":422693,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235066/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5066"},{"id":422696,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W6RXFC","text":"USGS data release","linkHelpText":"MODFLOW-2005 model used to simulate the regional groundwater flow system in the updated New Jersey Coastal Plain model, 1980-2013"},{"id":422694,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.XML"},{"id":422692,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5066/sir20235066.pdf","text":"Report","size":"25.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5066"},{"id":422691,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5066/coverthb.jpg"}],"country":"United States","otherGeospatial":"New Jersey Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74.49018324613056,\n              41.03712838002892\n            ],\n            [\n              -75.25922621488034,\n              41.417217443631785\n            ],\n            [\n              -77.41254652738019,\n              39.17183412365296\n            ],\n            [\n              -75.22626723050551,\n              37.8132834585617\n            ],\n            [\n              -72.98505629300531,\n              40.4043207917766\n            ],\n            [\n              -74.49018324613056,\n              41.03712838002892\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\" data-mce-href=\"https://www.usgs.gov/centers/new-jersey-water-science-center\">New Jersey Water Science Center</a><br>3450 Princeton Pike, Suite 110<br>Lawrenceville, New Jersey 08648</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"https://pubs.er.usgs.gov/contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Simulation of Groundwater Flow</li><li>Summary</li><li>References Cited</li><li>Appendix 1: Soil-Water Balance Methodology</li></ul>","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2023-11-17","noUsgsAuthors":false,"publicationDate":"2023-11-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Gordon, Alison D. 0000-0002-9502-8633","orcid":"https://orcid.org/0000-0002-9502-8633","contributorId":221457,"corporation":false,"usgs":true,"family":"Gordon","given":"Alison","email":"","middleInitial":"D.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":888330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carleton, Glen B. 0000-0002-7666-4407","orcid":"https://orcid.org/0000-0002-7666-4407","contributorId":306147,"corporation":false,"usgs":false,"family":"Carleton","given":"Glen","email":"","middleInitial":"B.","affiliations":[{"id":36206,"text":"Retired","active":true,"usgs":false}],"preferred":false,"id":888331,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70250250,"text":"70250250 - 2023 - Expanding our view of the cold-water coral niche and accounting of the ecosystem services of the reef habitat","interactions":[],"lastModifiedDate":"2023-11-30T13:22:47.885472","indexId":"70250250","displayToPublicDate":"2023-11-09T07:20:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Expanding our view of the cold-water coral niche and accounting of the ecosystem services of the reef habitat","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Coral reefs are iconic ecosystems that support diverse, productive communities in both shallow and deep waters. However, our incomplete knowledge of cold-water coral (CWC) niche space limits our understanding of their distribution and precludes a complete accounting of the ecosystem services they provide. Here, we present the results of recent surveys of the CWC mound province on the Blake Plateau off the U.S. east coast, an area of intense human activity including fisheries and naval operations, and potentially energy and mineral extraction. At one site, CWC mounds are arranged in lines that total over 150&nbsp;km in length, making this one of the largest reef complexes discovered in the deep ocean. This site experiences rapid and extreme shifts in temperature between 4.3 and 10.7&nbsp;°C, and currents approaching 1&nbsp;m&nbsp;s<sup>−1</sup>. Carbon is transported to depth by mesopelagic micronekton and nutrient cycling on the reef results in some of the highest nitrate concentrations recorded in the region. Predictive models reveal expanded areas of highly suitable habitat that currently remain unexplored. Multidisciplinary exploration of this new site has expanded understanding of the cold-water coral niche, improved our accounting of the ecosystem services of the reef habitat, and emphasizes the importance of properly managing these systems.</p></div></div>","language":"English","publisher":"Nature","doi":"10.1038/s41598-023-45559-5","usgsCitation":"Cordes, E.E., Demopoulos, A., Davies, A.J., Gasbarro, R., Rhoads, A.C., Loebeker, E., Sowers, D., Chaytor, J., Morrison, C., Weinnig, A., Brooke, S., Lunden, J.J., Mienis, F., Joye, S.B., Quattrini, A., Sutton, T.T., McFadden, C.S., Bourque, J.R., McClain Counts, J., Andrews, B.D., Betters, M.J., Etnoyer, P.J., Wolff, G.A., Bernard, B.B., Brooks, J., Rasser, M.K., and Adams, C., 2023, Expanding our view of the cold-water coral niche and accounting of the ecosystem services of the reef habitat: Scientific Reports, v. 13, 19482, 14 p., https://doi.org/10.1038/s41598-023-45559-5.","productDescription":"19482, 14 p.","ipdsId":"IP-115439","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":441637,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-023-45559-5","text":"Publisher Index Page"},{"id":435125,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PDH0OR","text":"USGS data release","linkHelpText":"Oceanographic conditions at Richardson reef reveal new suitable habitat for cold-water corals"},{"id":423090,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -82.56271441298479,\n              34.13164722790161\n            ],\n            [\n              -82.56271441298479,\n              24.493964227477008\n            ],\n            [\n              -75.79513628798475,\n              24.493964227477008\n            ],\n            [\n              -75.79513628798475,\n              34.13164722790161\n            ],\n            [\n              -82.56271441298479,\n              34.13164722790161\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2023-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":889076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":222192,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davies, Andrew J.","contributorId":331892,"corporation":false,"usgs":false,"family":"Davies","given":"Andrew","email":"","middleInitial":"J.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":889078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gasbarro, Ryan","contributorId":331607,"corporation":false,"usgs":false,"family":"Gasbarro","given":"Ryan","email":"","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":889079,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rhoads, Alexandria C.","contributorId":331896,"corporation":false,"usgs":false,"family":"Rhoads","given":"Alexandria","email":"","middleInitial":"C.","affiliations":[{"id":6922,"text":"University of Rhode Island","active":true,"usgs":false}],"preferred":false,"id":889080,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loebeker, Elizabeth","contributorId":331916,"corporation":false,"usgs":false,"family":"Loebeker","given":"Elizabeth","email":"","affiliations":[{"id":79299,"text":"Kongsberg Underwater Technology","active":true,"usgs":false}],"preferred":false,"id":889081,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sowers, Derek","contributorId":214036,"corporation":false,"usgs":false,"family":"Sowers","given":"Derek","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":889082,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chaytor, Jason 0000-0001-8135-8677 jchaytor@usgs.gov","orcid":"https://orcid.org/0000-0001-8135-8677","contributorId":140095,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":889083,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":239844,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":889084,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Weinnig, Alexis M.","contributorId":331901,"corporation":false,"usgs":false,"family":"Weinnig","given":"Alexis M.","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":889085,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brooke, Sandra","contributorId":150169,"corporation":false,"usgs":false,"family":"Brooke","given":"Sandra","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":889086,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lunden, Jay J.","contributorId":146489,"corporation":false,"usgs":false,"family":"Lunden","given":"Jay","email":"","middleInitial":"J.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":889087,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mienis, Furu","contributorId":150166,"corporation":false,"usgs":false,"family":"Mienis","given":"Furu","email":"","affiliations":[{"id":17924,"text":"Royal Netherlands Institute for Sea Research","active":true,"usgs":false}],"preferred":false,"id":889088,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Joye, Samantha B.","contributorId":172702,"corporation":false,"usgs":false,"family":"Joye","given":"Samantha","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":889089,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Quattrini, Andrea M. 0000-0002-4247-3055","orcid":"https://orcid.org/0000-0002-4247-3055","contributorId":62339,"corporation":false,"usgs":false,"family":"Quattrini","given":"Andrea M.","affiliations":[],"preferred":false,"id":889090,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Sutton, Tracey T.","contributorId":331904,"corporation":false,"usgs":false,"family":"Sutton","given":"Tracey","email":"","middleInitial":"T.","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":889091,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"McFadden, Catherine S.","contributorId":331906,"corporation":false,"usgs":false,"family":"McFadden","given":"Catherine","email":"","middleInitial":"S.","affiliations":[{"id":32976,"text":"Harvey Mudd College","active":true,"usgs":false}],"preferred":false,"id":889092,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Bourque, Jill R. 0000-0003-3809-2601","orcid":"https://orcid.org/0000-0003-3809-2601","contributorId":215719,"corporation":false,"usgs":true,"family":"Bourque","given":"Jill","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889093,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"McClain Counts, Jennifer 0000-0002-3383-5472","orcid":"https://orcid.org/0000-0002-3383-5472","contributorId":219233,"corporation":false,"usgs":true,"family":"McClain Counts","given":"Jennifer","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":889094,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Andrews, Brian D. 0000-0003-1024-9400 bandrews@usgs.gov","orcid":"https://orcid.org/0000-0003-1024-9400","contributorId":201662,"corporation":false,"usgs":true,"family":"Andrews","given":"Brian","email":"bandrews@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":889095,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Betters, Melissa J.","contributorId":331917,"corporation":false,"usgs":false,"family":"Betters","given":"Melissa","email":"","middleInitial":"J.","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":889096,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Etnoyer, Peter J.","contributorId":331911,"corporation":false,"usgs":false,"family":"Etnoyer","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":40398,"text":"NOAA National Centers for Coastal Ocean Science","active":true,"usgs":false}],"preferred":false,"id":889097,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Wolff, Gary A.","contributorId":331912,"corporation":false,"usgs":false,"family":"Wolff","given":"Gary","email":"","middleInitial":"A.","affiliations":[{"id":79252,"text":"TDI-Brooks International","active":true,"usgs":false}],"preferred":false,"id":889098,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Bernard, Bernie B.","contributorId":331913,"corporation":false,"usgs":false,"family":"Bernard","given":"Bernie","email":"","middleInitial":"B.","affiliations":[{"id":79252,"text":"TDI-Brooks International","active":true,"usgs":false}],"preferred":false,"id":889099,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Brooks, James M.","contributorId":331914,"corporation":false,"usgs":false,"family":"Brooks","given":"James M.","affiliations":[{"id":79252,"text":"TDI-Brooks International","active":true,"usgs":false}],"preferred":false,"id":889100,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Rasser, Michael K.","contributorId":331915,"corporation":false,"usgs":false,"family":"Rasser","given":"Michael","email":"","middleInitial":"K.","affiliations":[{"id":20318,"text":"Bureau of Ocean Energy Management","active":true,"usgs":false}],"preferred":false,"id":889101,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Adams, Caitlin","contributorId":213693,"corporation":false,"usgs":false,"family":"Adams","given":"Caitlin","email":"","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":889102,"contributorType":{"id":1,"text":"Authors"},"rank":27}]}}
,{"id":70250986,"text":"70250986 - 2023 - Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate","interactions":[],"lastModifiedDate":"2024-01-18T11:47:53.770787","indexId":"70250986","displayToPublicDate":"2023-11-09T05:46:03","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Migratory waterfowl are an important resource for consumptive and non-consumptive users alike and provide tremendous economic value in North America. These birds rely on a complex matrix of public and private land for forage and roosting during migration and wintering periods, and substantial conservation effort focuses on increasing the amount and quality of target habitat. Yet, the value of habitat is a function not only of a site's resources but also of its geographic position and weather. To quantify this value, we used a continental-scale energetics-based model of daily dabbling duck movement to assess the marginal value of lands across the contiguous United States during the non-breeding period (September to May). We examined effects of eliminating each habitat node (32 × 32 km) in both a particularly cold and a particularly warm winter, asking which nodes had the largest effect on survival. The marginal value of habitat nodes for migrating dabbling ducks was a function of forage and roosting habitat but, more importantly, of geography (especially latitude and region). Irrespective of weather, nodes in the Southeast, central East Coast, and California made the largest positive contributions to survival. Conversely, nodes in the Midwest, Northeast, Florida, and the Pacific Northwest had consistent negative effects. Effects (positive and negative) of more northerly nodes occurred in late fall or early spring when climate was often severe and was most variable. Importance and effects of many nodes varied considerably between a cold and a warm winter. Much of the Midwest and central Great Plains benefited duck survival in a warm winter, and projected future warming may improve the value of lands in these regions, including many National Wildlife Refuges, for migrating dabbling ducks. Our results highlight the geographic variability in habitat value, as well as shifts that may occur in these values due to climate change.</p></div></div>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.10632","usgsCitation":"Burner, R.C., Golas, B.D., Aagaard, K.J., Lonsdorf, E.V., and Thogmartin, W.E., 2023, Marginal value analysis reveals shifting importance of migration habitat for waterfowl under a changing climate: Ecology and Evolution, v. 13, no. 11, e10632, 25 p., https://doi.org/10.1002/ece3.10632.","productDescription":"e10632, 25 p.","ipdsId":"IP-145212","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":441655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.10632","text":"Publisher Index Page"},{"id":424552,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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          -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                49\n              ],\n              [\n                -113,\n                49\n              ],\n              [\n                -110.05,\n                49\n              ],\n              [\n                -107.05,\n                49\n              ],\n              [\n                -104.04826,\n                48.99986\n              ],\n              [\n                -100.65,\n                49\n              ],\n              [\n                -97.22872,\n                49.0007\n              ],\n              [\n                -95.15907,\n                49\n              ],\n              [\n                -95.15609,\n                49.38425\n              ],\n              [\n                -94.81758,\n                49.38905\n              ]\n            ]\n          ]\n        ]\n      },\n      \"properties\": {\n        \"name\": \"United States\"\n      }\n    }\n  ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2023-11-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Burner, Ryan C. 0000-0002-7314-9506","orcid":"https://orcid.org/0000-0002-7314-9506","contributorId":304152,"corporation":false,"usgs":true,"family":"Burner","given":"Ryan","email":"","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":892664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Golas, Benjamin Donald 0000-0003-0568-6702","orcid":"https://orcid.org/0000-0003-0568-6702","contributorId":333396,"corporation":false,"usgs":true,"family":"Golas","given":"Benjamin","email":"","middleInitial":"Donald","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":892665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aagaard, Kevin J.","contributorId":302397,"corporation":false,"usgs":false,"family":"Aagaard","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":39887,"text":"Colorado Parks and Wildlife","active":true,"usgs":false}],"preferred":false,"id":892666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lonsdorf, Eric V.","contributorId":149495,"corporation":false,"usgs":false,"family":"Lonsdorf","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":17752,"text":"Chicago Botanic Garden","active":true,"usgs":false}],"preferred":false,"id":892667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":892668,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70274329,"text":"70274329 - 2023 - Magnetotelluric insights into the formation and reactivation of trans-crustal shear zones in Precambrian basement of the eastern U.S. Midcontinent","interactions":[],"lastModifiedDate":"2026-03-26T17:08:24.080638","indexId":"70274329","displayToPublicDate":"2023-11-07T00:00:00","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Magnetotelluric insights into the formation and reactivation of trans-crustal shear zones in Precambrian basement of the eastern U.S. Midcontinent","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>Three-dimensional inversion of regional long-period magnetotelluric (MT) data reveals the presence of two distinct sets of high-conductivity belts in the Precambrian basement of the eastern U.S. Midcontinent. One set, beneath Missouri, Illinois, Indiana, and western Ohio, is defined by northwest–southeast-oriented conductivity structures; the other set, beneath Kentucky, West Virginia, western Virginia, and eastern Ohio, includes structures that are generally oriented northeast–southwest. The northwest-trending belts occur mainly in Paleoproterozoic crust, and we suggest that their high conductivity values are due to graphite precipitated within trans-crustal shear zones from intrusion-related CO</span><sub>2</sub><span>-rich fluids. Our MT inversion results indicate that some of these structures dip steeply through the crust and intersect the Moho, which supports an interpretation that the shear zones originated as “leaky” transcurrent faults or transforms during the late Paleoproterozoic or the early Mesoproterozoic. The northeast-trending belts are associated with Grenvillian orogenesis and also potentially with Iapetan rifting, although further work is needed to verify the latter possibility. We interpret the different geographic positions of these two sets of conductivity belts as reflecting differences in origin and/or crustal rheology, with the northwest-trending belts largely confined to older, stable, pre-Grenville cratonic Laurentia, and the northeast-trending belts largely having formed in younger, weaker marginal crust. Notably, these high-conductivity zones spatially correlate with Midcontinent fault-and-fold zones that affect Phanerozoic strata. Stratigraphic evidence indicates that Midcontinent fault-and-fold zones were particularly active during Phanerozoic orogenic events, and some remain seismically active today, so the associated high-conductivity belts likely represent long-lived weaknesses that transect the crust.</span></span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B37099.1","usgsCitation":"Murphy, B.S., DeLucia, M.S., Marshak, S., Ravat, D., and Bedrosian, P.A., 2023, Magnetotelluric insights into the formation and reactivation of trans-crustal shear zones in Precambrian basement of the eastern U.S. Midcontinent: Geological Society of America Bulletin, v. 136, no. 7-8, p. 2661-2675, https://doi.org/10.1130/B37099.1.","productDescription":"15 p.","startPage":"2661","endPage":"2675","ipdsId":"IP-156454","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":501615,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/b37099.1","text":"Publisher Index Page"},{"id":501591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kentucky, Michigan, Missouri, Ohio, Tennessee, Virginia, West Virginia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -96.56385155199473,\n              43.58838657273898\n            ],\n            [\n              -94.89342352797115,\n              36.665741391167515\n            ],\n            [\n              -90.1632867900763,\n              36.40918959165568\n            ],\n            [\n              -90.1822818596265,\n              35.19325938384543\n            ],\n            [\n              -82.50702489905923,\n              35.09029830465867\n            ],\n            [\n              -81.72015275766472,\n              36.414903288152516\n            ],\n            [\n              -75.94724335361846,\n              36.6343891406775\n            ],\n            [\n              -78.22364477580007,\n              39.341914933866796\n            ],\n            [\n              -83.87679948786644,\n              45.80918107937691\n            ],\n            [\n              -86.49918682600257,\n              44.950592730464656\n            ],\n            [\n              -87.74442475620134,\n              42.792743875212764\n            ],\n            [\n              -90.2357236948469,\n              42.584968113049044\n            ],\n            [\n              -91.44396187965609,\n              43.610837609280644\n            ],\n            [\n              -96.56385155199473,\n              43.58838657273898\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"136","issue":"7-8","noUsgsAuthors":false,"publicationDate":"2023-11-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Murphy, Benjamin Scott 0000-0001-7636-3711","orcid":"https://orcid.org/0000-0001-7636-3711","contributorId":242928,"corporation":false,"usgs":true,"family":"Murphy","given":"Benjamin","email":"","middleInitial":"Scott","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":957907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeLucia, Michael S.","contributorId":367930,"corporation":false,"usgs":false,"family":"DeLucia","given":"Michael","middleInitial":"S.","affiliations":[{"id":87645,"text":"Department of Geology and Environmental Geoscience, College of Charleston","active":true,"usgs":false}],"preferred":false,"id":957908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marshak, Stephen","contributorId":367931,"corporation":false,"usgs":false,"family":"Marshak","given":"Stephen","affiliations":[{"id":40647,"text":"Department of Geology, University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":957909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ravat, Dhananjay","contributorId":367932,"corporation":false,"usgs":false,"family":"Ravat","given":"Dhananjay","affiliations":[{"id":87646,"text":"Department of Earth and Environmental Sciences, University of Kentucky","active":true,"usgs":false}],"preferred":false,"id":957910,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":957911,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70249877,"text":"70249877 - 2023 - Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast","interactions":[],"lastModifiedDate":"2024-01-04T14:49:45.971708","indexId":"70249877","displayToPublicDate":"2023-11-03T06:35:23","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast","docAbstract":"<p><i>Context </i>Tidal saline wetlands (TSWs) are highly threatened from climate-change effects of sea-level rise. Studies of TSWs along the East Coast U.S. and elsewhere suggest significant likely losses over coming decades but needed are analytic tools gauged to Pacific Coast U.S. wetlands.</p><p><i>Objectives </i>We predict the impacts of sea-level rise (SLR) on the elevation capital (vertical) and migration potential (lateral) resilience of TSWs along the Pacific Coast U.S. over the period 2020 to 2150 under a 1.5-m SLR scenario, and identified TSWs at risk of most rapid loss of resilience. Here, we define vertical resilience as the amount of elevation capital and lateral resilience as the amount of TSW displacement area relative to existing area.</p><p><i>Methods </i>We used Bayesian network (BN) modeling to predict changes in resilience of TSWs as probabilities which can be useful in risk analysis and risk management. We developed the model using a database sample of 26 TSWs with 147 sediment core samples, among 16 estuary drainage areas along coastal California, Oregon, and Washington.</p><p><i>Results </i>We found that all TSW sites would lose at least 50% of their elevation capital resilience by 2060 to just before 2100, and 100% by 2070 to 2130, depending on the site. Under a 1.5-m sea-level rise scenario, nearly all sites in California will lose most or all of their lateral migration resilience. Resilience losses generally accelerated over time. In the BN model, elevation capital resilience is most sensitive to elevation capital at time t, mean tide level at time t, and change in sea level from time 0 to time t.</p><p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><i>Conclusions </i></span>All TSW sites were projected with declines in resilience. Our model can further aid decision-making such as prioritizing sites for potential management adaptation strategies. We also identified variables most influencing resilience predictions and thus those potentially prioritized for monitoring or development of strategies to prevent loss regionally.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10980-023-01762-3","usgsCitation":"Marcot, B.G., Thorne, K., Carr, J., and Guntenspergen, G.R., 2023, Foundations of modeling resilience of tidal saline wetlands to sea-level rise along the U.S. Pacific Coast: Landscape Ecology, v. 38, p. 3061-3080, https://doi.org/10.1007/s10980-023-01762-3.","productDescription":"20 p.","startPage":"3061","endPage":"3080","ipdsId":"IP-148063","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":441704,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10980-023-01762-3","text":"Publisher Index 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