We implemented concepts of field geology at great ocean depths by constructing virtual outcrops from a string of overlapping video frames collected by remotely operated vehicles (ROVs). This lower-cost alternative to drilling boreholes allows stratigraphic extension into the offshore and regional interpretation of marine seismic profiles. The imagery was collected along a dive transect on the western wall of Mona Rift, a deep and narrow rift northwest of Puerto Rico, between water depths of 1560 m and 3927 m. The northern coast of Puerto Rico and its large offshore area are underlain by a mid-Eocene and younger forearc basin topped by a thick carbonate platform. There are no drill holes offshore, and tying seismic lines across the shoreline there is problematic. We describe our virtual outcrop and constrain its age and stratigraphy using seven rock samples collected by ROV and compare the outcrop's stratigraphy to deep boreholes and outcrops on land. Our formation descriptions and ages agree, for the most part, with those on land, but we identified a 100-m-thick section that is represented on land by an unconformity. Our stratigraphic interpretation indicates lateral variations in formation thicknesses and establishes a cross-section for additional sampling of the Eocene–Pliocene geology. It also suggests that Mona Rift has formed since the mid-Pliocene. The presence or absence of ferromanganese (Fe-Mn) crust on rocks along the transect may be correlated with the smoothness of the rock surface.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02762.1","usgsCitation":"ten Brink, U.S., Bialik, O.M., Chaytor, J., Flores, C., and Purkey Phillips, M., 2024, Field geology under the sea with a remotely operated vehicle: Mona Rift, Puerto Rico: Geosphere, v. 20, no. 6, p. 1575-1597, https://doi.org/10.1130/GES02762.1.","productDescription":"23 p.","startPage":"1575","endPage":"1597","ipdsId":"IP-163240","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466794,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges02762.1","text":"Publisher Index Page"},{"id":465282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mona Rift, Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.6333,\n 18.8333\n ],\n [\n -67.6333,\n 18.6833\n ],\n [\n -67.4583,\n 18.6833\n ],\n [\n -67.4583,\n 18.8333\n ],\n [\n -67.6333,\n 18.8333\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"6","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"ten Brink, Uri S. 0000-0001-6858-3001","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":201741,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri","email":"","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bialik, Or M.","contributorId":347344,"corporation":false,"usgs":false,"family":"Bialik","given":"Or","email":"","middleInitial":"M.","affiliations":[{"id":25445,"text":"University of Münster","active":true,"usgs":false}],"preferred":false,"id":921436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flores, Claudia 0000-0003-0676-7061 cflores@usgs.gov","orcid":"https://orcid.org/0000-0003-0676-7061","contributorId":304396,"corporation":false,"usgs":true,"family":"Flores","given":"Claudia","email":"cflores@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":921438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Purkey Phillips, Marcie","contributorId":346790,"corporation":false,"usgs":false,"family":"Purkey Phillips","given":"Marcie","affiliations":[{"id":29861,"text":"The University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":921439,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70262024,"text":"70262024 - 2024 - Penguin colony georegistration using camera pose estimation and phototourism","interactions":[],"lastModifiedDate":"2025-01-10T16:30:20.637582","indexId":"70262024","displayToPublicDate":"2024-10-30T10:26:02","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Penguin colony georegistration using camera pose estimation and phototourism","docAbstract":"Satellite-based remote sensing and uncrewed aerial imagery play increasingly important roles in the mapping of wildlife populations and wildlife habitat, but the availability of imagery has been limited in remote areas. At the same time, ecotourism is a rapidly growing industry and can yield a vast catalog of photographs that could be harnessed for monitoring purposes, but the inherently ad-hoc and unstructured nature of these images make them difficult to use. To help address this, a subfield of computer vision known as phototourism has been developed to leverage a diverse collection of unstructured photographs to reconstruct a georeferenced three-dimensional scene capturing the environment at that location. Here we demonstrate the use of phototourism in an application involving Antarctic penguins, sentinel species whose dynamics are closely tracked as a measure of ecosystem functioning, and introduce a semi-automated pipeline for aligning and registering ground photographs using a digital elevation model (DEM) and satellite imagery. We employ the Segment Anything Model (SAM) for the interactive identification and segmentation of penguin colonies in these photographs. By creating a textured 3D mesh from the DEM and satellite imagery, we estimate camera poses to align ground photographs with the mesh and register the segmented penguin colony area to the mesh, achieving a detailed representation of the colony. Our approach has demonstrated promising performance, though challenges persist due to variations in image quality and the dynamic nature of natural landscapes. Nevertheless, our method offers a straightforward and effective tool for the georegistration of ad-hoc photographs in natural landscapes, with additional applications such as monitoring glacial retreat.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0311038","usgsCitation":"Wu, H., Flynn, C., Hall, C., Che-Castaldo, C., Samaras, D., Schwaller, M., and Lynch, H., 2024, Penguin colony georegistration using camera pose estimation and phototourism: PLoS ONE, v. 19, no. 10, e0311038, 18 p., https://doi.org/10.1371/journal.pone.0311038.","productDescription":"e0311038, 18 p.","ipdsId":"IP-160209","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":466795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0311038","text":"Publisher Index Page"},{"id":465996,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Haoyu","contributorId":347903,"corporation":false,"usgs":false,"family":"Wu","given":"Haoyu","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flynn, Clare","contributorId":347904,"corporation":false,"usgs":false,"family":"Flynn","given":"Clare","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Carole","contributorId":347905,"corporation":false,"usgs":false,"family":"Hall","given":"Carole","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Che-Castaldo, Christian Joseph 0000-0002-7670-2178","orcid":"https://orcid.org/0000-0002-7670-2178","contributorId":347906,"corporation":false,"usgs":true,"family":"Che-Castaldo","given":"Christian Joseph","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":922743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Samaras, Dimitris","contributorId":347907,"corporation":false,"usgs":false,"family":"Samaras","given":"Dimitris","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922744,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schwaller, Mathew","contributorId":347909,"corporation":false,"usgs":false,"family":"Schwaller","given":"Mathew","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922745,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynch, Heather J.","contributorId":347911,"corporation":false,"usgs":false,"family":"Lynch","given":"Heather J.","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":922746,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70259868,"text":"fs20243034 - 2024 - Assessment of undiscovered conventional oil and gas resources in the Norphlet Formation, U.S. Gulf Coast region, 2023","interactions":[],"lastModifiedDate":"2025-12-22T20:21:53.699711","indexId":"fs20243034","displayToPublicDate":"2024-10-30T09:45:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3034","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources in the Norphlet Formation, U.S. Gulf Coast Region, 2023","title":"Assessment of undiscovered conventional oil and gas resources in the Norphlet Formation, U.S. Gulf Coast region, 2023","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey (USGS) estimated undiscovered, technically recoverable mean resources of 16 million barrels of oil and 348 billion cubic feet of gas in conventional reservoirs of the Norphlet Formation in the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20243034","programNote":"National and Global Petroleum Assessment","usgsCitation":"Counts, J.W., Craddock, W.H., Gooley, J.T., Buursink, M., Mercier, T.J., Woodall, C.A., and Schenk, C.J., 2024, Assessment of undiscovered conventional oil and gas resources in the Norphlet Formation, U.S. Gulf Coast region, 2023: U.S. Geological Survey Fact Sheet 2024–3034, 4 p., https://doi.org/10.3133/fs20243034.","productDescription":"Report: 4 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-157745","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":463490,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243034/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3034"},{"id":463435,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3034/fs20243034.xml"},{"id":463434,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3034/images"},{"id":463200,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3034/fs20243034.pdf","text":"Report","size":"1.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3034"},{"id":463207,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P132OJPA","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Norphlet Formation: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":463199,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3034/coverthb.jpg"},{"id":497885,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117741.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alabama, Florida, Mississippi","otherGeospatial":"Norphlet Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.11177492185513,\n 34.53401166961133\n ],\n [\n -91.11177492185513,\n 29.73879554891593\n ],\n [\n -85.30780523167681,\n 29.73879554891593\n ],\n [\n -85.30780523167681,\n 34.53401166961133\n ],\n [\n -91.11177492185513,\n 34.53401166961133\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Geology, Energy & Minerals Science Center
U.S. Geological Survey
956 National Center
Reston, VA 20192
Oxbow lakes are highly productive waterbodies that host multiple life stages of many freshwater aquatic species. These lakes also provide foraging and rearing habitat to the invasive silver carp (Hypophthalmichthys molitrix) enabling populations to grow in biomass and abundance that can add propagule pressure to connected waterways and oxbows within the Mississippi River Basin. Ecologically these fish are undesirable because they overlap in diet and may compete for resources with native fishes and negatively impact recreational fisheries. Our goal was to evaluate silver carp distribution patterns in a major Mississippi River oxbow lake to inform removal programs and precision harvesting. We implanted 35 adult silver carp with acoustic tags and released them into the lake. Periodic tracking over 365 d revealed that fish were predominantly found in lake areas with water depths ranging from 2.0 to 5.9 m during all seasons, despite the availability of shallower and deeper water. Silver carp tended to aggregate in the wintertime (December–February) relative to other seasons. This information about lake area uses and seasonal aggregations could inform removal efforts in invaded waterbodies by exploiting natural behavioral and temporal vulnerabilities of this highly invasive and difficult-to-capture fish.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2024.15.4.03","usgsCitation":"Besson, J., Miranda, L.E., Colvin, M.E., Dunn, C.G., and Riecke, D., 2024, Spatial distribution patterns of invasive silver carp can inform removal efforts in an oxbow lake of the Mississippi River: Management of Biological Invasions, v. 15, no. 4, p. 505-518, https://doi.org/10.3391/mbi.2024.15.4.03.","productDescription":"14 p.","startPage":"505","endPage":"518","ipdsId":"IP-161587","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":481053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2024.15.4.03","text":"Publisher Index Page"},{"id":480994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Moon Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.56421475590851,\n 34.466966058199986\n ],\n [\n -90.56421475590851,\n 34.393119426569285\n ],\n [\n -90.49028391694011,\n 34.393119426569285\n ],\n [\n -90.49028391694011,\n 34.466966058199986\n ],\n [\n -90.56421475590851,\n 34.466966058199986\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Besson, Jordan C.","contributorId":349791,"corporation":false,"usgs":false,"family":"Besson","given":"Jordan C.","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":924815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":924816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colvin, Michael E. 0000-0002-6581-4764","orcid":"https://orcid.org/0000-0002-6581-4764","contributorId":331490,"corporation":false,"usgs":true,"family":"Colvin","given":"Michael","email":"","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":924817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":924818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riecke, Dennis K.","contributorId":349837,"corporation":false,"usgs":false,"family":"Riecke","given":"Dennis K.","affiliations":[],"preferred":false,"id":924911,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","interactions":[{"subject":{"id":70261121,"text":"70261121 - 2024 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261121","publicationYear":"2024","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"predicate":"SUPERSEDED_BY","object":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"id":1}],"supersededBy":{"id":70261880,"text":"70261880 - 2025 - Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","indexId":"70261880","publicationYear":"2025","noYear":false,"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways"},"lastModifiedDate":"2025-01-27T17:18:30.964189","indexId":"70261121","displayToPublicDate":"2024-10-30T08:30:41","publicationYear":"2024","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19836,"text":"Authorea","active":true,"publicationSubtype":{"id":32}},"title":"Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways","docAbstract":"The Central Valley of California (CVC) and Mid-Atlantic (MA) in the U.S. are both critical sites for nationwide food security (California Poultry Federation 2016, Prosser et al. 2017), and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using Boosted Regression Tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.","language":"English","publisher":"Authorea","doi":"10.22541/au.173030440.00154170/v1","usgsCitation":"Hardy, M., Williams, C.K., Ladman, B.S., Pitesky, M.E., Overton, C.T., Casazza, M.L., Matchett, E., Prosser, D.J., and Buler, J.J., 2024, Examining inter-regional and intra-seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways: Authorea, https://doi.org/10.22541/au.173030440.00154170/v1.","productDescription":"51 p.","ipdsId":"IP-172616","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466797,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/au.173030440.00154170/v1","text":"External Repository"},{"id":466796,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.22541/au.173030440.00154170/v1","text":"External Repository"},{"id":464459,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hardy, Matthew J.","contributorId":343392,"corporation":false,"usgs":false,"family":"Hardy","given":"Matthew J.","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":919360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Christopher K.","contributorId":202263,"corporation":false,"usgs":false,"family":"Williams","given":"Christopher","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":919361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ladman, Brian S.","contributorId":337102,"corporation":false,"usgs":false,"family":"Ladman","given":"Brian","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":919362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":919363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919364,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919365,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Matchett, Elliott 0000-0001-5095-2884 ematchett@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-2884","contributorId":5541,"corporation":false,"usgs":true,"family":"Matchett","given":"Elliott","email":"ematchett@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919366,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":919367,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Buler, Jeffrey J.","contributorId":194648,"corporation":false,"usgs":false,"family":"Buler","given":"Jeffrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":919368,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70260933,"text":"70260933 - 2024 - Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands","interactions":[],"lastModifiedDate":"2024-11-15T14:33:52.68755","indexId":"70260933","displayToPublicDate":"2024-10-30T08:26:46","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands","docAbstract":"One of the world’s largest “blue carbon” ecosystems, Louisiana’s tidal wetlands on the US Gulf of Mexico coast, is rapidly being lost. Louisiana’s strong legal, regulatory, and monitoring framework, developed for one of the world’s largest tidal wetland systems, provides an opportunity for a programmatic approach to blue carbon accreditation to support restoration of these ecologically and economically important tidal wetlands. Louisiana’s coastal wetlands span ∼1.4 million ha and accumulate 5.5–7.3 Tg yr−1 of blue carbon (organic carbon), ∼6%–8% of tidal marsh blue carbon accumulation globally. Louisiana has a favorable governance framework to advance blue carbon accreditation, due to centralized restoration planning, long term coastal monitoring, and strong legal and regulatory frameworks around carbon. Additional restoration efforts, planned through Louisiana’s Coastal Master Plan, over 50 years are projected to create, or avoid loss of, up to 81,000 ha of wetland. Current restoration funding, primarily from Deepwater Horizon oil spill settlements, will be fully committed by the early 2030s and additional funding sources are required. Existing accreditation methodologies have not been successfully applied to coastal Louisiana’s ecosystem restoration approaches or herbaceous tidal wetland types. Achieving financial viability for accreditation of these restoration and wetland types will require expanded application of existing blue carbon crediting methodologies. It will also require expanded approaches for predicting the future landscape without restoration, such as numerical modeling, to be validated. Additional methodologies (and/or standards) would have many common elements with those currently available but may be beneficial, depending on the goals and needs of both the state of Louisiana and potential purchasers of Louisiana tidal wetland carbon credits. This study identified twenty targeted needs that will address data and knowledge gaps to maximize financial viability of blue carbon accreditation for Louisiana’s tidal wetlands. Knowledge needs were identified in five categories: legislative and policy, accreditation methodologies and standards, soil carbon flux, methane flux, and lateral carbon flux. Due to the large spatial scale and diversity of tidal wetlands, it is expected that progress in coastal Louisiana has high potential to be generalized to similar wetland ecosystems across the northern Gulf of Mexico and globally.
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Indices of benthic macroinvertebrate integrity have declined in urban areas across the Chesapeake Bay watershed (CBW), and more information is needed about whether these declines may be due to elevated conductivity. A predictive SC model for the CBW was developed using monitoring data from the National Water Quality Portal. Predictor variables representing SC sources were compiled for nontidal reaches across the CBW. Random forests modeling was conducted to predict SC at four time periods (1999–2001, 2004–2006, 2009–2011, and 2014–2016), which were then compared to a national data set of background SC to quantify departures from background SC. Carbonate geology, impervious cover, forest cover, and snow depth were the most important variables for predicting SC. Observations and modeled results showed snow depth amplified the effect of impervious cover on SC. Elevated SC was predicted in two-thirds of reaches in the CBW, and these elevated conditions persisted over time in many areas. These results can be used in stressor identification assessments to prioritize future monitoring and to determine where management activities could be implemented to reduce salinization.
The lack of consolidated information regarding the response of wild bird species to infection with avian influenza virus (AIV) is a challenge to both conservation managers and researchers alike, with related sectors also impacted, such as public health and commercial poultry. Using two independent searches, we reviewed published literature for studies describing wild bird species experimentally infected with avian influenza to assess host species’ relative susceptibility to AIVs. Additionally, we summarize broad-scale parameters for elements such as shedding duration and minimum infectious dose that can be used in transmission modelling efforts. Our synthesis shows that waterfowl (i.e. Anatidae) compose the vast majority of published AIV pathobiology studies, whereas gulls and passerines are less represented in research despite evidence that they also are susceptible and contribute to highly pathogenic avian influenza disease dynamics. This study represents the first comprehensive effort to compile available literature regarding the pathobiology of AIVs in all wild birds in over a decade. This database can now serve as a tool to all researchers, providing generalized estimates of pathobiology parameters for a variety of wild avian families and an opportunity to critically examine and assess what is known and identify where further insight is needed.
Dryland restoration requires plant materials capable of performing well despite difficult growing conditions. Selecting plant materials with higher intraspecific trait variability (ITV) may support successful outcomes by enhancing the performance of those materials in restoration settings. However, maintaining ITV from wild populations is not well understood and requires further investigation if ITV is to be incorporated into native plant materials, which are often developed from wild-collected seed grown in agricultural settings. We used two perennial plant species to explore whether (1) ITV measured at field sites predicts ITV in a common garden, (2) rankings of ITV among populations remain stable over time, and (3) higher levels of ITV promote survival and reproductive effort in a common garden. We measured ITV in specific leaf area and height for Bouteloua curtipendula and Heterotheca villosa at field sites and over 2 years in a common garden, as well as survival and flower production in the common garden. We also calculated climate distance between field sites, where seeds were originally sourced, and the common garden to account for the impact of climatic differences on ITV. We found that (1) ITV measured at field sites did not predict ITV in the common garden, (2) rankings of ITV across populations were inconsistent, and (3) relationships between ITV and performance were rare and differed by species. Our findings indicate that the utility of ITV in wild populations as a predictive tool may be limited.
","language":"English","publisher":"Wiley","doi":"10.1111/rec.14322","usgsCitation":"Samuel, E.M., Mitchell, R., Winkler, D.E., Davidson, Z.M., Lencioni, S.J., and Massatti, R., 2024, Intraspecific trait variability in wild populations predicts neither variability nor performance in a common garden: Restoration Ecology, e14322, 11 p., https://doi.org/10.1111/rec.14322.","productDescription":"e14322, 11 p.","ipdsId":"IP-164808","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":466801,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rec.14322","text":"Publisher Index Page"},{"id":463786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2024-10-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Samuel, Ella M.","contributorId":346114,"corporation":false,"usgs":false,"family":"Samuel","given":"Ella","email":"","middleInitial":"M.","affiliations":[{"id":82776,"text":"School of Earth and Sustainability, Northern Arizona University, 624 S. Knoles Dr, Flagstaff, AZ 86011","active":true,"usgs":false}],"preferred":false,"id":918135,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mitchell, Rachel M.","contributorId":300516,"corporation":false,"usgs":false,"family":"Mitchell","given":"Rachel M.","affiliations":[{"id":65185,"text":"School of Earth and Sustainability, Northern Arizona University, Flagstaff, Arizona, USA","active":true,"usgs":false}],"preferred":false,"id":918136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winkler, Daniel E. 0000-0003-4825-9073","orcid":"https://orcid.org/0000-0003-4825-9073","contributorId":206786,"corporation":false,"usgs":true,"family":"Winkler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":918137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davidson, Zoe M.","contributorId":346115,"corporation":false,"usgs":false,"family":"Davidson","given":"Zoe","email":"","middleInitial":"M.","affiliations":[{"id":82777,"text":"Bureau of Land Management New Mexico State Office, 301 Dinosaur Trail, Santa Fe, NM 87508","active":true,"usgs":false}],"preferred":false,"id":918138,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lencioni, Shannon Joy 0000-0002-7267-7585","orcid":"https://orcid.org/0000-0002-7267-7585","contributorId":346116,"corporation":false,"usgs":true,"family":"Lencioni","given":"Shannon","email":"","middleInitial":"Joy","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":918139,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Massatti, Robert","contributorId":219513,"corporation":false,"usgs":true,"family":"Massatti","given":"Robert","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":918158,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70268261,"text":"70268261 - 2024 - Inventorying ponds through novel size-adaptive object mapping using Sentinel-1/2 time series","interactions":[],"lastModifiedDate":"2025-06-18T15:03:04.772207","indexId":"70268261","displayToPublicDate":"2024-10-30T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Inventorying ponds through novel size-adaptive object mapping using Sentinel-1/2 time series","docAbstract":"Ponds are an important source of greenhouse gases (GHGs) to the atmosphere, yet evaluating their role in global biogeochemical cycling is currently hampered by limitations in quantifying their global distribution. Existing satellite-derived estimates of lake distributions have difficulty identifying small lakes (5–10 ha) and ponds (<5 ha) due to limitations in satellite resolution and challenges extracting individual small waterbodies from low-albedo surfaces, vegetated water, and lotic water systems including rivers and streams. In this study, we developed generalizable pond mapping strategies based on their spatial-temporal-spectral characteristics to fully exploit accessible medium-resolution optical and synthetic aperture radar (SAR) time series to identify ponds. Our novel approach entails: (1) making full use of ponds' characteristics from an object-based perspective; (2) extracting pond objects using seeds of prominent water pixels defined by the SAR VH signal; (3) constructing training samples of ponds with high representativeness; and (4) improving inter-class discrimination by combining features from optical and SAR data. We designed a novel Optical-SAR Pond Object Mapper (OptiSAR-POM) to achieve an improved estimate of pond size distribution by incorporating mapping strategies into the object-based image analysis framework. We generated landscape objects through an elaborate water-focused segmentation approach, which adaptively aligned the segmentation parameters with the size and distribution patterns of ponds to identify small waterbodies and increase inter-class variability. We further introduced an interactive learning process to construct random forests for object-based classification, which incorporated adaptive empirical thresholds to identify potential pond objects and select representative training samples of varying sizes. We tested the OptiSAR-POM framework using Sentinel-1/2 time series at three county-level study sites and three supplementary watershed-level study sites in the United States and China. Our approach yielded high overall accuracy (>95 %) for all sites and highlighted the ability of Sentinel-1/2 imagery to accurately detect small ponds (0.1–1 ha) across diverse landscapes. The average producer's accuracy for small ponds at county-level sites improved by ∼45 % compared to that of all other products with a 10-m or higher spatial resolution, addressing the absence of such information in existing regional and global datasets. The generated county-level pond maps revealed the numerical dominance of ponds in lentic waters, their substantial area contribution in human-impacted regions, and the relevance of studying biogeochemical processes in smaller waterbodies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2024.114484","usgsCitation":"Liu, D., Zhu, X., Holgerson, M., Bansal, S., and Xu, X., 2024, Inventorying ponds through novel size-adaptive object mapping using Sentinel-1/2 time series: Remote Sensing of Environment, v. 315, 114484, 21 p., https://doi.org/10.1016/j.rse.2024.114484.","productDescription":"114484, 21 p.","ipdsId":"IP-167730","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":490911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"315","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Liu, Denghong","contributorId":357052,"corporation":false,"usgs":false,"family":"Liu","given":"Denghong","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":940631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Xioalin","contributorId":357055,"corporation":false,"usgs":false,"family":"Zhu","given":"Xioalin","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":940632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holgerson, Meredith","contributorId":218790,"corporation":false,"usgs":false,"family":"Holgerson","given":"Meredith","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":940633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xu, Xiangtao","contributorId":348758,"corporation":false,"usgs":false,"family":"Xu","given":"Xiangtao","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":940635,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70259581,"text":"fs20243029 - 2024 - Developments in African industrial minerals for renewable energy","interactions":[],"lastModifiedDate":"2024-10-30T21:16:35.700196","indexId":"fs20243029","displayToPublicDate":"2024-10-29T13:20:00","publicationYear":"2024","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-3029","displayTitle":"Developments in African Industrial Minerals for Renewable Energy","title":"Developments in African industrial minerals for renewable energy","docAbstract":"Africa is emerging as a leading source for minerals used in the manufacture of batteries for electric vehicles and in other renewable energy applications. New graphite, lithium, and rare-earth mines have or could be opened in African countries from 2017 through 2026.
Estimates of production capacities for graphite, lithium, and rare-earth mines for 2023 and beyond are based upon supply-side assumptions, such as announced plans for new capacity construction and bankable feasibility studies, as well as projected trends that could affect current producing facilities in 2023 and planned new facilities projected to come online by 2026. Forward-looking information, including estimates of future production capacities, graphite flake distributions, and timing of the start of operations, are subject to risk factors and uncertainties that could cause actual events or results to differ significantly from expected outcomes. Projects listed in this report are presented as an indication of industry plans and are not a U.S. Geological Survey (USGS) prediction of what will take place. Only projects with planned startup dates are included in this report; ther graphite, lithium, and rare-earth projects in Africa without startup dates were known to be in various stages of development but are not included in this fact sheet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20243029","usgsCitation":"Yager, T., 2024, Developments in African industrial minerals for renewable energy: U.S. Geological Survey Fact Sheet 2024–3029, 6 p., https://doi.org/10.3133/fs20243029","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-153789","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":463121,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20243029/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2024-3029 HTML"},{"id":463122,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2024/3029/fs20243029.XML","description":"FS 2024-3029 XML"},{"id":463123,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2024/3029/images"},{"id":462885,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2024/3029/coverthb2.jpg"},{"id":462886,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2024/3029/fs20243029.pdf","text":"Report","size":"1.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2024-3029 PDF"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -23.381408491331456,\n 38.850454189324125\n ],\n [\n -23.381408491331456,\n -38.520184226294504\n ],\n [\n 53.96234150866863,\n -38.520184226294504\n ],\n [\n 53.96234150866863,\n 38.850454189324125\n ],\n [\n -23.381408491331456,\n 38.850454189324125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"National Minerals Information Center
U.S. Geological Survey
988 National Center
12201 Sunrise Valley Drive
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Email: nmicrecordsmgt@usgs.gov
The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American raptors, songbirds, and other small avian species. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on avian species, and measures to reduce noise emissions. We follow the organization first established in U.S. Geological Survey Scientific Investigations Report 2023-5114, in which the report sections align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. The effects of human-caused noise on songbirds are well researched, whereas, among raptors, only owl species have been well-studied in relation to noise. Several studies have established that noise can reduce owl hunting success because many owl species are heavily reliant on hearing prey when hunting. The effects of noise on songbirds depend on several factors. Typically, birds that rely on vocal communication for mating, predator detection, and spatial orientation, and that are less able to adjust the frequencies of their vocalizations, are more vulnerable to behavioral changes and decreased fitness in noisy areas. Techniques suggested in the literature for reducing noise emissions include artificial sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference to find literature or identify gaps in the literature about the effects of noise from oil and gas development on raptors and songbirds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245087","programNote":"Prepared in cooperation with the Bureau of Land Management and the U.S. Fish and Wildlife Service","usgsCitation":"Maxwell, L.M., Rutherford, T.K., Kleist, N.J., Teige, E.C., Lehrter, R.J., Gilbert, M.A., Wood, D.J.A., Johnston, A.N., Tull, J.C., Haby, T.S., and Carter, S.K., 2024, Effects of noise from oil and gas development on raptors and songbirds—A science synthesis to inform National Environmental Policy Act analyses: U.S. Geological Survey Scientific Investigations Report 2024–5087, 66 p., https://doi.org/10.3133/sir20245087.","productDescription":"xi, 99 p.","onlineOnly":"Y","ipdsId":"IP-154746","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":463505,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245087/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5087"},{"id":463364,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5087/sir20245087.xml"},{"id":463363,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5087/images"},{"id":463212,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235132","text":"Effects of Culverts on Habitat Connectivity in Streams—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":463211,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20235114","text":"Effects of Noise from Oil and Gas Development on Ungulates and Small Mammals—A Science Synthesis to Inform National Environmental Policy Act Analyses"},{"id":463210,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20243028","text":"Structured Science Syntheses to Inform Decision Making on Federal Public Lands"},{"id":463209,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5087/sir20245087.pdf","text":"Report","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5087"},{"id":463208,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5087/coverthb.jpg"},{"id":497884,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_117742.htm","linkFileType":{"id":5,"text":"html"}}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
We present 230Th-238U crystallization ages and trace element compositions for zircons spanning the late Pleistocene to Holocene rhyolite eruptive record at South Sister volcano in the central Oregon Cascade Range. Most zircon ages are between 100 and 20 ka, with very few in secular equilibrium (>350 ka). The weighted mean of zircon ages for the two oldest South Sister rhyolites, 31.5 ± 2.1 and 39.1 ± 2.4 ka, are significantly younger than the associated 40Ar/39Ar ages, 47.4 ± 9.7 and 51.4 ± 9.7 ka. We propose that these 40Ar/39Ar dates, performed on plagioclase separates, are compromised by a subtle amount of excess Ar and therefore the younger weighted mean zircon ages yield more reliable eruption ages. These results imply that the interval of rhyolite eruption at South Sister during the late Pleistocene was both shorter and more productive than previously thought and that eruption at South Sister initiated after Middle Sister. Compositionally, zircons from the Pleistocene rhyolites are broadly similar and show down-temperature zircon and plagioclase crystallization trends. However, we argue that destabilized amphibole and titanite in a common mush also exert leverage on the Pleistocene zircon trace element compositions. Divergence in the Eu/Eu* ratio between the Pleistocene and Holocene lavas implies chemically distinct magma reservoirs originating from the Pleistocene rhyolite eruptive sequence and the Holocene eruptive sequence. This work suggests a higher flux of rhyolite volcanism than previously thought and characterizes magmatic storage distinctions between the Pleistocene and Holocene rhyolites, aiding in the assessment of future eruptive hazards at South Sister volcano.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GC011680","usgsCitation":"Dechert, A.E., Andersen, N.L., Dufek, J., and Jilly-Rehak, C.E., 2024, Zircon constraints on the eruptive sequence and magma evolution of rhyolites at South Sister volcano, Oregon: Geochemistry, Geophysics, Geosystems, v. 25, no. 8, e2024GC011680, 16 p., https://doi.org/10.1029/2024GC011680.","productDescription":"e2024GC011680, 16 p.","ipdsId":"IP-166341","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gc011680","text":"Publisher Index Page"},{"id":463333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"South Sister Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.4687761419247,\n 44.8843098669841\n ],\n [\n -122.4687761419247,\n 43.77976481541276\n ],\n [\n -120.91024228397475,\n 43.77976481541276\n ],\n [\n -120.91024228397475,\n 44.8843098669841\n ],\n [\n -122.4687761419247,\n 44.8843098669841\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"8","noUsgsAuthors":false,"publicationDate":"2024-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Dechert, Annika E.","contributorId":345692,"corporation":false,"usgs":false,"family":"Dechert","given":"Annika","email":"","middleInitial":"E.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":917269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andersen, Nathan Lee 0000-0002-4152-4914","orcid":"https://orcid.org/0000-0002-4152-4914","contributorId":345693,"corporation":false,"usgs":true,"family":"Andersen","given":"Nathan","email":"","middleInitial":"Lee","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dufek, Josef","contributorId":194001,"corporation":false,"usgs":false,"family":"Dufek","given":"Josef","email":"","affiliations":[],"preferred":false,"id":917271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jilly-Rehak, Christine E.","contributorId":344651,"corporation":false,"usgs":false,"family":"Jilly-Rehak","given":"Christine","email":"","middleInitial":"E.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":917272,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70260828,"text":"70260828 - 2024 - Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water","interactions":[],"lastModifiedDate":"2024-11-12T15:09:09.782218","indexId":"70260828","displayToPublicDate":"2024-10-29T09:05:58","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5925,"text":"Environmental Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water","docAbstract":"In freshwater environments, low-micrometer microplastics (LMMPs) have captured significant attention due to their prevalence and toxicity. Yet, rapid detection of LMMPs (1–10 μm) at the single-particle level within complex freshwater matrices remains a hurdle. We developed an adaptable plasmonic membrane sensor for fast detection of individual LMMPs in eutrophic lake waters. The plasmonic membrane sensor functions both as a membrane filter and as a sensor for LMMP collection and analysis. Among the four types of membrane sensors, polycarbonate track-etch (PCTE) membrane sensors exhibit superior imaging quality for LMMPs due to their flat and homogeneous surfaces. Besides the significantly improved imaging contrast and reduced background interferences, the Raman intensity of LMMPs is enhanced by 48% ± 25% on PCTE membrane sensors compared to unmodified membranes. The increased Raman intensities of a chemical probe with an increasing gold layer thickness and a decreasing membrane pore size suggest a surface-enhanced Raman scattering effect from the membrane sensors. The membrane sensors achieve a detection limit of 1 μg/L and an ultrafast scanning time of 0.01 s for individual LMMPs across natural eutrophic lake water. The developed membrane sensors offer an adaptable tool for the swift and reliable detection of individual LMMPs in complex environmental matrices.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.4c06503","usgsCitation":"Wu, Z., Janssen, S., Tate, M., Wei, H., and Qin, M., 2024, Adaptable plasmonic membrane sensors for fast and reliable detection of trace low micrometer microplastics in lake water: Environmental Science and Technology, v. 58, no. 45, p. 20172-20180, https://doi.org/10.1021/acs.est.4c06503.","productDescription":"9 p.","startPage":"20172","endPage":"20180","ipdsId":"IP-171215","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":466803,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.4c06503","text":"Publisher Index Page"},{"id":463868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"45","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Wu, Ziyan","contributorId":346132,"corporation":false,"usgs":false,"family":"Wu","given":"Ziyan","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janssen, Sarah E. 0000-0003-4432-3154","orcid":"https://orcid.org/0000-0003-4432-3154","contributorId":210991,"corporation":false,"usgs":true,"family":"Janssen","given":"Sarah E.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":918231,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wei, Hoaran","contributorId":346133,"corporation":false,"usgs":false,"family":"Wei","given":"Hoaran","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918232,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Qin, Mohan","contributorId":346134,"corporation":false,"usgs":false,"family":"Qin","given":"Mohan","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":918233,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260429,"text":"70260429 - 2024 - Dynamics, monitoring and forecasting of tephra in the atmosphere","interactions":[],"lastModifiedDate":"2024-11-01T13:54:00.975813","indexId":"70260429","displayToPublicDate":"2024-10-29T08:52:42","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3283,"text":"Reviews of Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics, monitoring and forecasting of tephra in the atmosphere","docAbstract":"Explosive volcanic eruptions inject hot mixtures of solid particles (tephra) and gasses into the atmosphere. Entraining ambient air, these mixtures can form plumes rising tens of kilometers until they spread laterally, forming umbrella clouds. While the largest clasts tend to settle in proximity to the volcano, the smallest fragments, commonly referred to as ash (≤2 mm in diameter), can be transported over long distances, forming volcanic clouds. Tephra plumes and clouds pose significant hazards to human society, affecting infrastructure, and human health through deposition on the ground or airborne suspension at low altitudes. Additionally, volcanic clouds are a threat to aviation, during both high-risk actions such as take-off and landing and at standard cruising altitudes. The ability to monitor and forecast tephra plumes and clouds is fundamental to mitigate the hazard associated with explosive eruptions. To that end, various monitoring techniques, ranging from ground-based instruments to sensors on-board satellites, and forecasting strategies, based on running numerical models to track the position of volcanic clouds, are efficiently employed. However, some limitations still exist, mainly due to the high unpredictability and variability of explosive eruptions, as well as the multiphase and complex nature of volcanic plumes. In the next decades, advances in monitoring and computational capabilities are expected to address these limitations and significantly improve the mitigation of the risk associated with tephra plumes and clouds.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023RG000808","usgsCitation":"Pardini, F., Barsotti, S., Bonadonna, C., de’ Michieli Vitturi, M., Folch, A., Mastin, L.G., Osores, S., and Prata, A.T., 2024, Dynamics, monitoring and forecasting of tephra in the atmosphere: Reviews of Geophysics, v. 62, e2023RG000808, 68 p., https://doi.org/10.1029/2023RG000808.","productDescription":"e2023RG000808, 68 p.","ipdsId":"IP-160162","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":466804,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023rg000808","text":"Publisher Index Page"},{"id":463533,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Pardini, Federica","contributorId":345831,"corporation":false,"usgs":false,"family":"Pardini","given":"Federica","email":"","affiliations":[{"id":82720,"text":"Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione di Pisa, Pisa, Italy","active":true,"usgs":false}],"preferred":false,"id":917656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barsotti, Sara","contributorId":199711,"corporation":false,"usgs":false,"family":"Barsotti","given":"Sara","email":"","affiliations":[],"preferred":false,"id":917657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bonadonna, Contanza 0000-0002-2368-2193","orcid":"https://orcid.org/0000-0002-2368-2193","contributorId":339895,"corporation":false,"usgs":false,"family":"Bonadonna","given":"Contanza","email":"","affiliations":[{"id":62805,"text":"Université de Genève","active":true,"usgs":false}],"preferred":false,"id":917658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de’ Michieli Vitturi, Mattia","contributorId":199708,"corporation":false,"usgs":false,"family":"de’ Michieli Vitturi","given":"Mattia","email":"","affiliations":[],"preferred":false,"id":917659,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Folch, Arnau","contributorId":199712,"corporation":false,"usgs":false,"family":"Folch","given":"Arnau","email":"","affiliations":[],"preferred":false,"id":917660,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mastin, Larry G. 0000-0002-4795-1992","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":265985,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":917661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Osores, Soledad 0009-0002-3352-9245","orcid":"https://orcid.org/0009-0002-3352-9245","contributorId":345832,"corporation":false,"usgs":false,"family":"Osores","given":"Soledad","email":"","affiliations":[{"id":82723,"text":"Servicio Meteorológico Nacional, Buenos Aires, Argentina","active":true,"usgs":false}],"preferred":false,"id":917662,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Prata, Andrew T. 0000-0001-9115-1143","orcid":"https://orcid.org/0000-0001-9115-1143","contributorId":345833,"corporation":false,"usgs":false,"family":"Prata","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":40928,"text":"Oxford University","active":true,"usgs":false}],"preferred":false,"id":917663,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70264867,"text":"70264867 - 2024 - Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications","interactions":[],"lastModifiedDate":"2025-03-26T15:38:39.371491","indexId":"70264867","displayToPublicDate":"2024-10-29T08:30:48","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7565,"text":"Earthquake Spectra Journal","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications","docAbstract":"The US Geological Survey’s (USGS) ShakeMap system provides a rapid characterization of strong ground shaking in areas directly affected by an earthquake. This study focuses on studying the aggregate effects of macroseismic shaking estimates from ShakeMap, expressed in terms of modified Mercalli intensity (MMI), when accounting for the uncertainty in forecasted ground motions. We use a Monte Carlo approach to generate numerous spatially correlated realizations of ground motions by utilizing a combination of circulant embedding and kriging techniques for efficiently handling the correlations. We then assessed the aggregate effects of shaking by looking at bin counts across these realizations. We demonstrate that the aggregate shaking regarding the mean macroseismic intensity estimates (from the ShakeMap output) is a biased representation of the aggregate shaking when shaking uncertainty is included. Incorporating shaking uncertainty can help to improve various downstream earthquake impact applications, such as the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) overall earthquake fatality distribution or estimates of shaking-induced ground failure impacts from consequential earthquakes.
","language":"English","publisher":"Sage Publishing","doi":"10.1177/87552930241283201","usgsCitation":"Engler, D.T., Jaiswal, K.S., and Ganesh, M., 2024, Evaluating the impact of uncertainty in ground motion forecasts for post-earthquake impact modeling applications: Earthquake Spectra Journal, v. 41, no. 1, p. 524-546, https://doi.org/10.1177/87552930241283201.","productDescription":"23 p.","startPage":"524","endPage":"546","ipdsId":"IP-160589","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":483880,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Engler, Davis T. 0000-0002-7133-3545","orcid":"https://orcid.org/0000-0002-7133-3545","contributorId":265962,"corporation":false,"usgs":true,"family":"Engler","given":"Davis","email":"","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932100,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932101,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganesh, Mahadevan 0000-0002-7792-4119","orcid":"https://orcid.org/0000-0002-7792-4119","contributorId":352717,"corporation":false,"usgs":false,"family":"Ganesh","given":"Mahadevan","affiliations":[{"id":84292,"text":"Professor, Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":932102,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260375,"text":"70260375 - 2024 - Population structure of Desmophyllum pertusum found along the United States eastern continental margin","interactions":[],"lastModifiedDate":"2024-11-01T14:13:20.307568","indexId":"70260375","displayToPublicDate":"2024-10-29T08:29:55","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":958,"text":"BMC Research Notes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Population structure of Desmophyllum pertusum found along the United States eastern continental margin","title":"Population structure of Desmophyllum pertusum found along the United States eastern continental margin","docAbstract":"The connectivity and genetic structuring of populations throughout a region influence a species’ resilience and probability of recovery from anthropogenic impacts. By gaining a comprehensive understanding of population connectivity, more effective management can be prioritized. To assess the connectivity and population genetic structure of a common cold-water coral species, Desmophyllum pertusum (Lophelia pertusa), we performed Restriction-site Associated DNA Sequencing (RADseq) on individuals from nine sites ranging from submarine canyons off New England to the southeastern coast of the United States (SEUS) and the Gulf of Mexico (GOM). Fifty-seven individuals and 3,180 single-nucleotide polymorphisms (SNPs) were used to assess genetic differentiation.
High connectivity exists among populations along the SEUS, yet these populations were differentiated from those to the north off New England and in Norfolk Canyon along the North Atlantic coast of the United States, as well as those in the GOM. Interestingly, Norfolk Canyon, located just north of North Carolina, and GOM populations exhibited low levels of genetic differentiation, corroborating previous microsatellite analyses and signifying gene flow between these populations. Increasing sample sizes from existing populations and including additional sampling sites over a larger geographic range would help define potential source populations and reveal fine-scale connectivity patterns among D. pertusum populations.
","language":"English","publisher":"Springer Nature","doi":"10.1186/s13104-024-06977-4","usgsCitation":"Weinnig, A.M., Aunins, A.W., Salamone, V.J., Quattrini, A., Nizinski, M.S., and Morrison, C., 2024, Population structure of Desmophyllum pertusum found along the United States eastern continental margin: BMC Research Notes, v. 17, no. 1, 326, 7 p., https://doi.org/10.1186/s13104-024-06977-4.","productDescription":"326, 7 p.","ipdsId":"IP-157145","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":466805,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13104-024-06977-4","text":"Publisher Index Page"},{"id":463535,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Unites States","otherGeospatial":"Atlantic coastal margin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.71142930127395,\n 28.923532210772052\n ],\n [\n -87.20770794927337,\n 29.778273658658676\n ],\n [\n -88.12002541768051,\n 29.69258193898787\n ],\n [\n -89.23879681191622,\n 28.44134714528691\n ],\n [\n -86.44254662826377,\n 27.912389547448754\n ],\n [\n -85.71142930127395,\n 28.923532210772052\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.9239384814065,\n 42.20254040148441\n ],\n [\n -67.63438293096546,\n 43.58902192305143\n ],\n [\n -69.21544486232233,\n 42.68212319523596\n ],\n [\n -69.57393034494278,\n 40.17025194363276\n ],\n [\n -73.58827669330255,\n 38.91808684375454\n ],\n [\n -74.60625646365936,\n 36.588016013722694\n ],\n [\n -75.5834673460983,\n 34.46068678372583\n ],\n [\n -79.47920624257769,\n 31.99090849493018\n ],\n [\n -80.4000384261637,\n 31.00478268172816\n ],\n [\n -79.478750607929,\n 26.481859079129094\n ],\n [\n -63.15489504288122,\n 42.1372460985159\n ],\n [\n -64.9239384814065,\n 42.20254040148441\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2024-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Weinnig, Alexis Marie 0000-0001-8858-4837","orcid":"https://orcid.org/0000-0001-8858-4837","contributorId":331476,"corporation":false,"usgs":true,"family":"Weinnig","given":"Alexis","email":"","middleInitial":"Marie","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":917476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aunins, Aaron 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":917477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Salamone, Veronica J. 0000-0002-6274-6401","orcid":"https://orcid.org/0000-0002-6274-6401","contributorId":293174,"corporation":false,"usgs":true,"family":"Salamone","given":"Veronica","email":"","middleInitial":"J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":917478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quattrini, Andrea M.","contributorId":333886,"corporation":false,"usgs":false,"family":"Quattrini","given":"Andrea M.","affiliations":[{"id":80003,"text":"Department of Invertebrate Zoology, Smithsonian Institution, Washington DC, United States of America","active":true,"usgs":false}],"preferred":false,"id":917479,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nizinski, Martha S.","contributorId":174770,"corporation":false,"usgs":false,"family":"Nizinski","given":"Martha","email":"","middleInitial":"S.","affiliations":[{"id":27510,"text":"NMFS National Systematics Laboratory, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":917480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morrison, Cheryl 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":202644,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":917481,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267297,"text":"70267297 - 2024 - The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator","interactions":[],"lastModifiedDate":"2025-05-20T16:19:44.225742","indexId":"70267297","displayToPublicDate":"2024-10-29T00:00:00","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator","docAbstract":"Perturbations in ecological processes can occur when wildlife alter their spatiotemporal activity patterns to avoid human activities that they perceive as a risk. Such perturbations can have cascading effects throughout wildlife communities. For greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse), nest predation plays an important role in population dynamics. Domestic cattle (Bos taurus) grazing has been hypothesized to increase nest predation by reducing grass height, and therefore reducing nest concealment, which may facilitate nest detection by predators. Grass height is lower on grazed pastures, but sage-grouse nest success appears similar on pastures grazed at varying intensities in several recent studies. Any reductions in nest concealment caused by grazing could potentially be offset by a localized response of one or more nest predators to the presence of cattle (i.e., the cattle avoidance hypothesis). A reduction in nest predator density or relative use within pastures could explain similar patterns of nest success on pastures grazed at varying intensities. Also, wildlife can potentially partition themselves temporally to avoid risks associated with human activities. For example, a shift in diel activity patterns by nest predators in response to cattle could result in predators being active during portions of the day when they are less efficient at locating sage-grouse nests. Thus, the effects of grazing could be offset by a temporal avoidance of cattle by predators. We deployed motion sensor cameras across six pastures to evaluate whether coyotes (Canis latrans; a primary sage-grouse nest predator) altered spatiotemporal activity patterns in response to cattle. We found that the probability of detecting coyotes had a positive relationship with cattle detections at camera sites (β = 0.22; 95% CI = 0.14,0.30). We also found that coyotes did not shift their diel activity patterns in response to cattle being in the pastures. Thus, in our system, similar sage-grouse nest success among pastures with different grazing intensities cannot be explained by the cattle avoidance hypothesis, at least for coyotes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.08.012","usgsCitation":"Helmstetter, N., Conway, C.J., Roberts, S., Makela, P., and Waits, L., 2024, The influence of grazing on the spatiotemporal activity patterns of a primary sage-grouse nest predator: Rangeland Ecology and Management, v. 98, p. 316-323, https://doi.org/10.1016/j.rama.2024.08.012.","productDescription":"8 p.","startPage":"316","endPage":"323","ipdsId":"IP-158843","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486230,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Big Butte, Pahsimeroi Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.07468470534926,\n 44.658252472114754\n ],\n [\n -114.07468470534926,\n 43.66884810770594\n ],\n [\n -112.78891524952729,\n 43.66884810770594\n ],\n [\n -112.78891524952729,\n 44.658252472114754\n ],\n [\n -114.07468470534926,\n 44.658252472114754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"98","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Helmstetter, Nolan A.","contributorId":355566,"corporation":false,"usgs":false,"family":"Helmstetter","given":"Nolan A.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937659,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937660,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Shane","contributorId":355567,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":937661,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Makela, Paul D.","contributorId":355569,"corporation":false,"usgs":false,"family":"Makela","given":"Paul D.","affiliations":[{"id":84780,"text":"United States Department of Interior","active":true,"usgs":false}],"preferred":false,"id":937663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waits, Lisette P.","contributorId":355568,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette P.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":937662,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70260112,"text":"70260112 - 2024 - The projected exposure and response of a natural barrier island system to climate-driven coastal hazards","interactions":[],"lastModifiedDate":"2024-10-30T21:25:08.166742","indexId":"70260112","displayToPublicDate":"2024-10-28T10:09:48","publicationYear":"2024","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":"The projected exposure and response of a natural barrier island system to climate-driven coastal hazards","docAbstract":"Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.
","language":"English","publisher":"Nature","doi":"10.1038/s41598-024-76749-4","usgsCitation":"Thomas, J.A., Barnard, P.L., Vitousek, S., Erikson, L.H., Parker, K.A., Nederhoff, K., Befus, K.M., and Shirzaei, M., 2024, The projected exposure and response of a natural barrier island system to climate-driven coastal hazards: Scientific Reports, v. 14, 25814, 16 p., https://doi.org/10.1038/s41598-024-76749-4.","productDescription":"25814, 16 p.","ipdsId":"IP-159766","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":466806,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-024-76749-4","text":"Publisher Index Page"},{"id":463350,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Lookout National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.00044575785073,\n 35.04289907218657\n ],\n [\n -76.06277684124831,\n 35.10241453299423\n ],\n [\n -76.46792888333269,\n 34.74467160307489\n ],\n [\n -76.53025996672974,\n 34.6678097189927\n ],\n [\n -76.6705049043746,\n 34.7105195823093\n ],\n [\n -76.69128193217362,\n 34.637899706102985\n ],\n [\n -76.4939001680816,\n 34.55666100513659\n ],\n [\n -76.00044575785073,\n 35.04289907218657\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationDate":"2024-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Jennifer Anne 0000-0002-8338-0146","orcid":"https://orcid.org/0000-0002-8338-0146","contributorId":297988,"corporation":false,"usgs":true,"family":"Thomas","given":"Jennifer","email":"","middleInitial":"Anne","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917041,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917042,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917047,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parker, Kai Alexander 0000-0002-0268-3891","orcid":"https://orcid.org/0000-0002-0268-3891","contributorId":292869,"corporation":false,"usgs":true,"family":"Parker","given":"Kai","email":"","middleInitial":"Alexander","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":917044,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nederhoff, Kees 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":334091,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Kees","affiliations":[{"id":39963,"text":"Deltares-USA","active":true,"usgs":false}],"preferred":true,"id":917045,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Befus, Kevin M.","contributorId":242636,"corporation":false,"usgs":false,"family":"Befus","given":"Kevin","email":"","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":917046,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shirzaei, Manoochehr 0000-0003-0086-3722","orcid":"https://orcid.org/0000-0003-0086-3722","contributorId":245637,"corporation":false,"usgs":false,"family":"Shirzaei","given":"Manoochehr","email":"","affiliations":[{"id":49242,"text":"Dept. of Geosciences, Virginia Tech Univ.","active":true,"usgs":false}],"preferred":false,"id":917048,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263169,"text":"70263169 - 2024 - Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","interactions":[],"lastModifiedDate":"2025-01-30T16:14:56.157932","indexId":"70263169","displayToPublicDate":"2024-10-28T10:08:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","title":"Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens","docAbstract":"In Lake Erie, yellow perch Perca flavescens support vast commercial and recreational fisheries, yet populations have recently declined. Using N = 5889 yellow perch stomachs collected from 1997 to 2021, we explored trends in the feeding ecology and trophic level of yellow perch with generalized additive models. Models revealed a significant decrease in yellow perch trophic level (−0.15 trophic levels in the last decade), and significant dietary shifts. Yellow perch have shifted away from feeding on piscine prey and round goby Neogobius melanostomus over the 25-year period, and now feed on invertebrates more frequently—including invasive waterfleas (Bythotrephes longimanus and Cercopagis pengoi) and chironomids. Dietary patterns appear to reflect broad ecological changes—invasive waterfleas have proliferated while populations of forage fish and round goby have declined. Furthermore, hypoxia events have increased in duration and severity, which may explain observed increases in chironomid consumption, which are hypoxia tolerant. This study demonstrates trophic adaptability in yellow perch, which have changed feeding behavior and trophic position in response to novel invaders and changing environmental conditions.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2023-0348","usgsCitation":"Schmitt, J., Gorman, A., Knight, C., Dufour, M.R., Roberts, J., and Hartman, T., 2024, Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens: Canadian Journal of Fisheries and Aquatic Sciences, v. 81, no. 11, p. 1560-1580, https://doi.org/10.1139/cjfas-2023-0348.","productDescription":"21 p.","startPage":"1560","endPage":"1580","ipdsId":"IP-140880","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":489855,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2023-0348","text":"Publisher Index Page"},{"id":481508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.56325919457086,\n 41.96883002032561\n ],\n [\n -80.71352325852209,\n 42.13778067147925\n ],\n [\n -81.1801985471471,\n 42.12256709658425\n ],\n [\n -82.40972750390958,\n 41.63184115572025\n ],\n [\n -82.53711113456517,\n 41.3996082733955\n ],\n [\n -82.45403485370326,\n 41.382988331945285\n ],\n [\n -82.0829607991845,\n 41.49923867953902\n ],\n [\n -81.86223827452686,\n 41.48020592339866\n ],\n [\n -81.73401076664092,\n 41.482825773508495\n ],\n [\n -81.3851200399411,\n 41.68976914941442\n ],\n [\n -80.56325919457086,\n 41.96883002032561\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"81","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Schmitt, Joseph 0000-0002-8354-4067","orcid":"https://orcid.org/0000-0002-8354-4067","contributorId":221020,"corporation":false,"usgs":true,"family":"Schmitt","given":"Joseph","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":925739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorman, Ann Marie","contributorId":350334,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann Marie","affiliations":[],"preferred":false,"id":925740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Carey","contributorId":214230,"corporation":false,"usgs":false,"family":"Knight","given":"Carey","affiliations":[{"id":16232,"text":"Ohio Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":925741,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dufour, Mark Richard 0000-0001-6930-7666","orcid":"https://orcid.org/0000-0001-6930-7666","contributorId":291450,"corporation":false,"usgs":true,"family":"Dufour","given":"Mark","email":"","middleInitial":"Richard","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":925742,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, James J. 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":925743,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hartman, Travis","contributorId":220316,"corporation":false,"usgs":false,"family":"Hartman","given":"Travis","email":"","affiliations":[{"id":37332,"text":"Ohio Department of Natural Resources, Division of Wildlife","active":true,"usgs":false}],"preferred":false,"id":925744,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266311,"text":"70266311 - 2024 - Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells","interactions":[],"lastModifiedDate":"2025-05-05T14:44:40.283853","indexId":"70266311","displayToPublicDate":"2024-10-28T09:41:24","publicationYear":"2024","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":"Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells","docAbstract":"Greater sage-grouse (hereafter sage-grouse; Centrocercus urophasianus) populations have declined across their range. Increased nest predation as a result of anthropogenic land use is one mechanism proposed to explain these declines. However, sage-grouse contend with a diverse suite of nest predators that vary in functional traits (e.g., search tactics or hunting mode) and abundance. Consequently, generalizing about factors influencing nest fate is challenging. Identifying the explicit predator species responsible for nest predation events is, therefore, critical to understanding causal mechanisms linking land use to patterns of sage-grouse nest success. Cattle grazing is often assumed to adversely affect sage-grouse recruitment by reducing grass height (and hence cover), thereby facilitating nest detection by predators. However, recent evidence found little support for the hypothesized effect of grazing on nest fate at the pasture scale. Rather, nest success appears to be similar on pastures grazed at varying intensities. One possible explanation for the lack of observed effect involves a localized response by one or more nest predators. The presence of cattle may cause a temporary reduction in predator density and/or use within a pasture (the cattle avoidance hypothesis). The cattle avoidance hypothesis predicts a decreased probability of at least one sage-grouse nest predator predating sage-grouse nests in pastures with livestock relative to pastures without livestock present during the nesting season. To test the cattle avoidance hypothesis, we collected predator DNA from eggshells from predated nests and used genetic methods to identify the sage-grouse nest predator(s) responsible for the predation event. We evaluated the influence of habitat and grazing on predator-specific nest predation. We evaluated the efficacy of our genetic method by deploying artificial nests with trail cameras and compared the results of our genetic method to the species captured via trail camera. Our molecular methods identified at least one nest predator captured predating artificial nests via trail camera for 33 of 35 (94%) artificial nests. We detected nest predators via our molecular analysis at 76 of 114 (67%) predated sage-grouse nests. The primary predators detected at sage-grouse nests were coyotes (Canis latrans) and corvids (Corvidea). Grazing did not influence the probability of nest predation by either coyotes or corvids. Sagebrush canopy cover was negatively associated with the probability a coyote predated a nest, distance to water was positively associated with the probability a corvid predated a nest, and average minimum temperature was negatively associated with the probability that either a coyote or a corvid predated a nest. Our study provides a framework for implementing an effective, non-invasive method for identifying sage-grouse nest predators that can be used to better understand how management actions at local and regional scales may impact an important component of sage-grouse recruitment.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.70213","usgsCitation":"Helmstetter, N.A., Conway, C.J., Roberts, S., Adams, J., Makela, P., and Waits, L., 2024, Predator-specific mortality of sage-grouse nests based on predator DNA on eggshells: Ecology and Evolution, v. 14, no. 10, e70213, 19 p., https://doi.org/10.1002/ece3.70213.","productDescription":"e70213, 19 p.","ipdsId":"IP-166147","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.70213","text":"Publisher Index Page"},{"id":485377,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.84878592693147,\n 44.720752546676636\n ],\n [\n -116.22953206733101,\n 44.720752546676636\n ],\n [\n -116.22953206733101,\n 41.995370325478774\n ],\n [\n -112.84878592693147,\n 41.995370325478774\n ],\n [\n -112.84878592693147,\n 44.720752546676636\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"14","issue":"10","noUsgsAuthors":false,"publicationDate":"2024-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Helmstetter, Nolan A.","contributorId":287004,"corporation":false,"usgs":false,"family":"Helmstetter","given":"Nolan","email":"","middleInitial":"A.","affiliations":[{"id":39599,"text":"ui","active":true,"usgs":false}],"preferred":false,"id":935533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":935534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Shane","contributorId":279606,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":935535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Adams, Jennifer R.","contributorId":341225,"corporation":false,"usgs":false,"family":"Adams","given":"Jennifer R.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Makela, Paul D.","contributorId":354380,"corporation":false,"usgs":false,"family":"Makela","given":"Paul D.","affiliations":[{"id":37086,"text":"U.S. Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":935537,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Waits, Lisette P.","contributorId":338452,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette P.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":935538,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70260180,"text":"70260180 - 2024 - Tissue distribution and temporal and spatial assessment of per- and polyfluoroalkyl substances (PFAS) in smallmouth bass (Micropterus dolomieu) in the mid-Atlantic United States","interactions":[],"lastModifiedDate":"2024-10-30T13:35:44.534951","indexId":"70260180","displayToPublicDate":"2024-10-28T08:27:57","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1564,"text":"Environmental Science and Pollution Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Tissue distribution and temporal and spatial assessment of per- and polyfluoroalkyl substances (PFAS) in smallmouth bass (Per- and polyfluoroalkyl substances (PFAS) have become an environmental issue worldwide. A first step to assessing potential adverse effects on fish populations is to determine if concentrations of concern are present in a region and if so, in which watersheds. Hence, plasma from adult smallmouth bass Micropterus dolomieu collected at 10 sites within 4 river systems in the mid-Atlantic region of the United States, from 2014 to 2019, was analyzed for 13 PFAS. These analyses were directed at better understanding the presence and associations with land use attributes in an important sportfish. Four substances, PFOS, PFDA, PFUnA, and PFDoA, were detected in every plasma sample, with PFOS having the highest concentrations. Sites with mean plasma concentrations of PFOS below 100 ng/ml had the lowest percentage of developed landcover in the upstream catchments. Sites with moderate plasma concentrations (mean PFOS concentrations between 220 and 240 ng/ml) had low (< 7.0) percentages of developed land use but high (> 30) percentages of agricultural land use. Sites with mean plasma concentrations of PFOS > 350 ng/ml had the highest percentage of developed land use and the highest number PFAS facilities that included military installations and airports. Four of the sites were part of a long-term monitoring project, and PFAS concentrations of samples collected in spring 2017, 2018, and 2019 were compared. Significant annual differences in plasma concentrations were noted that may relate to sources and climatic factors. Samples were also collected at two sites for tissue (plasma, whole blood, liver, gonad, muscle) distribution analyses with an expanded analyte list of 28 PFAS. Relative tissue distributions were not consistent even within one species of similar ages. Although the long-chained legacy PFAS were generally detected more frequently and at higher concentrations, emerging compounds such as 6:2 FTS and GEN X were detected in a variety of tissues.
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viability is critical for successful long-term recovery of target ecosystems and species. However, often it is difficult to quantify conservation action efficacy because of the complex, dynamic nature of ecosystem processes and practical limitations associated with assessing target species’ population dynamics. Here, we present an analytical framework that allows for quantification of conservation action efficacy using greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) within the Bi-State Distinct Population Segment which borders Nevada and California. This framework utilizes web-based repositories of conservation efforts carried out in sagebrush ecosystems and readily fits within contemporary sagebrush conservation design strategies. We employed a state-space model within a Bayesian framework to estimate abundance (N) as inputs for a progressive change before-after-control-impact paired series (BACIPS) design. Count data from 57 leks (monitored between 2003–2021) coupled with 85 unique actions (initiated between 2012–2019) provided clear evidence that conservation actions increased population abundance, on average, by 4.4% annually across the study area, resulting in a 37.4% cumulative increase since 2012. Population gains varied by the type of conservation action and according to the number of lag years following its implementation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rama.2024.08.007","usgsCitation":"Coates, P.S., Prochazka, B.G., Webster, S.C., Weise, C.L., Aldridge, C., O’Donnell, M.S., Wiechman, L.A., Doherty, K., and Tull, J.C., 2024, Cooperative conservation actions improve sage-grouse population performance within the Bi-State Distinct Population Segment: Rangeland Ecology & Management, v. 97, no. 1, p. 135-145, https://doi.org/10.1016/j.rama.2024.08.007.","productDescription":"11 p.","startPage":"135","endPage":"145","ipdsId":"IP-146505","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":466809,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rama.2024.08.007","text":"Publisher Index Page"},{"id":464340,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.04744073936212,\n 39.58975622408602\n ],\n [\n -120.04744073936212,\n 37.73670490749031\n ],\n [\n -118.51467511686786,\n 37.73670490749031\n ],\n [\n -118.51467511686786,\n 39.58975622408602\n ],\n [\n -120.04744073936212,\n 39.58975622408602\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"97","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":918999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prochazka, Brian G. 0000-0001-7270-5550 bprochazka@usgs.gov","orcid":"https://orcid.org/0000-0001-7270-5550","contributorId":174839,"corporation":false,"usgs":true,"family":"Prochazka","given":"Brian","email":"bprochazka@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webster, Sarah C. 0000-0003-4981-2010","orcid":"https://orcid.org/0000-0003-4981-2010","contributorId":302117,"corporation":false,"usgs":true,"family":"Webster","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":919001,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weise, Cali L.","contributorId":305785,"corporation":false,"usgs":false,"family":"Weise","given":"Cali","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":919002,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":213471,"corporation":false,"usgs":false,"family":"Aldridge","given":"Cameron L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":919003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":919004,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wiechman, Lief A. 0000-0002-3804-4426","orcid":"https://orcid.org/0000-0002-3804-4426","contributorId":184047,"corporation":false,"usgs":true,"family":"Wiechman","given":"Lief","email":"","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":919005,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Doherty, Kevin E.","contributorId":177793,"corporation":false,"usgs":false,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":919006,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tull, John C. 0000-0002-0680-008X","orcid":"https://orcid.org/0000-0002-0680-008X","contributorId":201650,"corporation":false,"usgs":false,"family":"Tull","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":919007,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70261313,"text":"70261313 - 2024 - Self-potential tomography preconditioned by particle swarm optimization— Application to monitoring hyporheic exchange in a bedrock river","interactions":[],"lastModifiedDate":"2024-12-06T14:15:01.195444","indexId":"70261313","displayToPublicDate":"2024-10-27T09:42:06","publicationYear":"2024","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Self-potential tomography preconditioned by particle swarm optimization— Application to monitoring hyporheic exchange in a bedrock river","docAbstract":"A self-potential (SP) data-inversion algorithm was developed and tested on an analytical model of electrical-potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP-monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock-lined riverbed. The algorithm combined stochastic source-localization by particle-swarm-optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least-squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical-model data to evaluate the algorithm performance. Results indicated that true parameters of single-source models were inverted and approximated with small residual error, whereas inversion of analytical-model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non-uniqueness of the inverse-model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point-scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP-monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.
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