{"pageNumber":"60","pageRowStart":"1475","pageSize":"25","recordCount":184605,"records":[{"id":70268228,"text":"70268228 - 2025 - Long-term geomorphic response of a southwestern USA river following establishment and removal of an invasive riparian tree","interactions":[],"lastModifiedDate":"2025-06-18T14:56:38.018529","indexId":"70268228","displayToPublicDate":"2025-06-15T07:48:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Long-term geomorphic response of a southwestern USA river following establishment and removal of an invasive riparian tree","docAbstract":"<p><span>Invasion of non-native riparian vegetation along southwestern USA rivers is associated with channel narrowing and simplification, prompting numerous and varied removal efforts. Channel width and migration rate often, but not always, increase following treatment. The cause of this variability and the duration of response is poorly understood. Using flow records and aerial imagery we quantified measurement uncertainty, change in channel width and rates of floodplain formation and erosion relative to annual peak flows before and during the invasion of Russian olive (</span><i>Elaeagnus angustifolia</i><span>&nbsp;L.), and following removal, along the Escalante River, Utah, over a fifty-year period. Prior to the invasion, the Escalante River was undergoing a decades-long narrowing process following large, turn-of-the-20th-century floods. Russian olive created a unique geomorphic shift in the observed pattern of channel change. Dense, channel-edge establishment and morphological traits including dense, inflexible branches, resulted in enhanced channel narrowing. Because the initial spread of Russian olive was from upstream to downstream, the Russian olive forest was wider and older upstream than downstream. Consequently, channel narrowing was greater and floodplain erosion rates had already decreased in upstream reaches compared to downstream. Russian olive removal increased channel width and floodplain erosion rates in upstream reaches, where Russian olive was most abundant. In contrast, downstream reaches continued to narrow. Small but detectable increases in rates of floodplain erosion across all reaches, and increased sinuosity in some, suggest the channel is becoming more mobile in the absence of Russian olive. Results indicate channel adjustment to Russian olive removal is spatially variable and may take a decade or more. With continued expansion of native riparian vegetation, future narrowing is likely during sustained low peak flows and large-scale widening is unlikely in the absence of extreme floods or physical removal of existing riparian vegetation.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/esp.70103","usgsCitation":"Scott, M., Williams, E., Friedman, J.M., Spencer, J.R., and McNeally, P., 2025, Long-term geomorphic response of a southwestern USA river following establishment and removal of an invasive riparian tree: Earth Surface Processes and Landforms, v. 50, no. 7, e70103, 14 p., https://doi.org/10.1002/esp.70103.","productDescription":"e70103, 14 p.","ipdsId":"IP-172419","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Utah","otherGeospatial":"Escalante River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.17585792672376,\n              38.01010705838269\n            ],\n            [\n              -112.17585792672376,\n              36.95034966991763\n            ],\n            [\n              -111.12572415681755,\n              36.95034966991763\n            ],\n            [\n              -111.12572415681755,\n              38.01010705838269\n            ],\n            [\n              -112.17585792672376,\n              38.01010705838269\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"50","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-06-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Scott, Michael L.","contributorId":244803,"corporation":false,"usgs":false,"family":"Scott","given":"Michael L.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":940528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, Erin","contributorId":356952,"corporation":false,"usgs":false,"family":"Williams","given":"Erin","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":940529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedman, Jonathan M. 0000-0002-1329-0663 friedmanj@usgs.gov","orcid":"https://orcid.org/0000-0002-1329-0663","contributorId":2473,"corporation":false,"usgs":true,"family":"Friedman","given":"Jonathan","email":"friedmanj@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":940530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spencer, John R.","contributorId":167381,"corporation":false,"usgs":false,"family":"Spencer","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":940531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McNeally, Phoebe B.","contributorId":356955,"corporation":false,"usgs":false,"family":"McNeally","given":"Phoebe B.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":940532,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70268234,"text":"70268234 - 2025 - The nonpoint source challenge: Obstacles and opportunities for meeting nutrient reduction goals in the Chesapeake Bay watershed","interactions":[],"lastModifiedDate":"2025-06-18T15:29:41.526931","indexId":"70268234","displayToPublicDate":"2025-06-14T10:25:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":20192,"text":"JAWRA Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"The nonpoint source challenge: Obstacles and opportunities for meeting nutrient reduction goals in the Chesapeake Bay watershed","docAbstract":"<p><span>This document examines the Chesapeake Bay watershed response to nutrient and sediment reduction efforts under the Clean Water Act's total maximum daily load (TMDL) regulation. As the 2025 Chesapeake Bay TMDL deadline approaches, water quality goals remain unmet, primarily because of nonpoint source pollution, the largest remaining source of nutrients and sediment, and the primary obstacle to meeting the TMDL. We focus on the factors influencing the gap between the expected effect of management to reduce nonpoint source loads reaching the Bay and empirical evidence suggesting that decades of effort have not produced the expected improvement. This gap may be caused by both insufficient scale and type of implemented water quality management practices and by an overestimation of practice effectiveness. Reasons water quality goals remain unmet include legacy nutrients and lag times masking or delaying the effects of management efforts, areas with large nutrient mass imbalances contributing disproportionate loads, and the difficulty of incentivizing behavior change in voluntary nonpoint source programs. Closing the response gap may require fundamental changes to nonpoint source programs. Apart from seeking additional funding, nonpoint source programs could develop policies to more effectively incentivize behavior change, identify and target treatment of high loading areas with appropriate management actions, and address nutrient mass imbalances.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.70034","usgsCitation":"Easton, Z.M., Stephenson, K., Benhem, B., Bohlke, J., Buda, A.R., Collick, A.S., Fowler, L., Gilinsky, E., Miller, A., Noe, G.E., Palm-Forster, L., Shabman, L., and Wynn-Thompson, T., 2025, The nonpoint source challenge: Obstacles and opportunities for meeting nutrient reduction goals in the Chesapeake Bay watershed: JAWRA Journal of the American Water Resources Association, v. 61, no. 3, e70034, 19 p., https://doi.org/10.1111/1752-1688.70034.","productDescription":"e70034, 19 p.","ipdsId":"IP-172234","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence 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,{"id":70269051,"text":"70269051 - 2025 - Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record","interactions":[],"lastModifiedDate":"2025-07-15T17:01:10.189577","indexId":"70269051","displayToPublicDate":"2025-06-14T09:58:42","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6453,"text":"Journal of Geophysical Research Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record","docAbstract":"Large surface-rupturing intraplate earthquakes in stable continental regions (SCRs) are uncommon globally and have recurrence intervals of thousands to hundreds of thousands of years based on the paleoseismic and geomorphic record, challenging accurate active fault identification in these regions. To constrain the timescales of preservation for scarps created by surface ruptures from dip-slip earthquakes, we use a two-dimensional scarp diffusion model for typical intraplate settings and explore which parameters influence fault scarp preservation. These parameters include the coseismic vertical surface offset, the recurrence interval of similar magnitude earthquakes, diffusivity (as a proxy for mean annual precipitation rate), and the erodibility of the surficial material. We constrain parameter ranges from a compilation of historical surface ruptures in intraplate settings in a variety of climates, including the Central and Eastern United States, Australia, Europe, Central Asia (Mongolia, China), India, and West Africa. The timescales of scarp preservation from landscape evolution modeling agree well with observations of scarp preservation in low-strain SCR and intraplate tectonic settings, with some notable exceptions for Australian scarps. We find that the erodibility of the surficial material and earthquake recurrence interval have a stronger effect on the timescales of scarp preservation than diffusivity or coseismic vertical surface offset. Our model results may aid in identifying and characterizing subtle, slow-moving active faults in low-strain SCR and intraplate tectonic settings for different tectonic, geomorphic, and climatic characteristics. Accurate fault locations and characterization from the landscape record has implications for both probabilistic seismic and fault displacement hazard analyses.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JB029966","usgsCitation":"Jobe, J.A., and Reitman, N.G., 2025, Timescales of surface faulting preservation in low-strain intraplate regions from landscape evolution modeling and the geomorphic and historical record: Journal of Geophysical Research Solid Earth, v. 130, no. 6, e2024JB029966, 26 p., https://doi.org/10.1029/2024JB029966.","productDescription":"e2024JB029966, 26 p.","ipdsId":"IP-169391","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":492286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Jobe, Jessica Ann Thompson 0000-0001-5574-4523","orcid":"https://orcid.org/0000-0001-5574-4523","contributorId":295377,"corporation":false,"usgs":true,"family":"Jobe","given":"Jessica","email":"","middleInitial":"Ann Thompson","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reitman, Nadine G. 0000-0002-6730-2682 nreitman@usgs.gov","orcid":"https://orcid.org/0000-0002-6730-2682","contributorId":5816,"corporation":false,"usgs":true,"family":"Reitman","given":"Nadine","email":"nreitman@usgs.gov","middleInitial":"G.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":943117,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70268397,"text":"70268397 - 2025 - An Eastern Ribbonsnake, Thamnophis sauritus (Linnaeus, 1766), scavenging on a roadkilled Cuban Treefrog, Osteopilus septentrionalis, (Duméril & Bibron, 1841), in Everglades National Park, Florida, USA","interactions":[],"lastModifiedDate":"2025-06-25T14:47:25.091099","indexId":"70268397","displayToPublicDate":"2025-06-13T09:42:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1899,"text":"Herpetology Notes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"An Eastern Ribbonsnake, <i>Thamnophis sauritus</i> (Linnaeus, 1766), scavenging on a roadkilled Cuban Treefrog, <i>Osteopilus septentrionalis</i>, (Duméril & Bibron, 1841), in Everglades National Park, Florida, USA","title":"An Eastern Ribbonsnake, Thamnophis sauritus (Linnaeus, 1766), scavenging on a roadkilled Cuban Treefrog, Osteopilus septentrionalis, (Duméril & Bibron, 1841), in Everglades National Park, Florida, USA","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Societas Europaea Herpetologica","usgsCitation":"Payne, S., Lane, E., Dunlap, F., Vasquez, M., Metcalf, M., McBride, L.M., Sherburne, S., Romagosa, C., Kissel, A.M., Yackel Adams, A.A., and Sandfoss, M.R., 2025, An Eastern Ribbonsnake, Thamnophis sauritus (Linnaeus, 1766), scavenging on a roadkilled Cuban Treefrog, Osteopilus septentrionalis, (Duméril & Bibron, 1841), in Everglades National Park, Florida, USA: Herpetology Notes, v. 18, p. 387-388.","productDescription":"2 p.","startPage":"387","endPage":"388","ipdsId":"IP-172869","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":491263,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://herpetologynotes.org/index.php/hn/article/view/39","linkFileType":{"id":5,"text":"html"}},{"id":491280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.4580147465973,\n              25.760457647318646\n            ],\n            [\n              -81.24533893973542,\n              25.760457647318646\n            ],\n            [\n              -81.24533893973542,\n              25.09603821180491\n            ],\n            [\n              -80.4580147465973,\n              25.09603821180491\n            ],\n            [\n              -80.4580147465973,\n              25.760457647318646\n    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Florida","active":true,"usgs":false}],"preferred":false,"id":941208,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vasquez, Madison","contributorId":357331,"corporation":false,"usgs":false,"family":"Vasquez","given":"Madison","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":941209,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Metcalf, Matthew Fox 0000-0002-5413-5192","orcid":"https://orcid.org/0000-0002-5413-5192","contributorId":356279,"corporation":false,"usgs":true,"family":"Metcalf","given":"Matthew Fox","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":941210,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McBride, Lisa Marie 0000-0003-4558-5391","orcid":"https://orcid.org/0000-0003-4558-5391","contributorId":303824,"corporation":false,"usgs":true,"family":"McBride","given":"Lisa","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":941211,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sherburne, Sarah Rae 0000-0002-2351-769X","orcid":"https://orcid.org/0000-0002-2351-769X","contributorId":356280,"corporation":false,"usgs":true,"family":"Sherburne","given":"Sarah Rae","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":941212,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Romagosa, Christina 0000-0003-1900-5648","orcid":"https://orcid.org/0000-0003-1900-5648","contributorId":299306,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":941213,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kissel, Amanda Marie 0000-0002-6346-7455","orcid":"https://orcid.org/0000-0002-6346-7455","contributorId":334356,"corporation":false,"usgs":true,"family":"Kissel","given":"Amanda","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":941214,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yackel Adams, Amy A. 0000-0002-7044-8447 yackela@usgs.gov","orcid":"https://orcid.org/0000-0002-7044-8447","contributorId":3116,"corporation":false,"usgs":true,"family":"Yackel Adams","given":"Amy","email":"yackela@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":941215,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sandfoss, Mark Robert 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,{"id":70262138,"text":"70262138 - 2025 - Sustainability trade-offs across modeled floating solar waterscapes of the Northeastern United States","interactions":[],"lastModifiedDate":"2025-08-04T15:52:31.715077","indexId":"70262138","displayToPublicDate":"2025-06-13T09:38:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21644,"text":"Cell Reports Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Sustainability trade-offs across modeled floating solar waterscapes of the Northeastern United States","docAbstract":"<p><span>Expansion of floating photovoltaic (FPV) solar systems provides a low-conflict renewable energy option to help mitigate climate change while sparing land, but potential sustainability trade-offs remain unquantified. We compare the technical potential of maximum FPV deployment to address the climate crisis with FPV-buildout scenarios that prioritize biodiversity and social values across waterscapes. FPV deployment on all technically suitable waterbodies (3.5% of available sites) in the Northeastern US could generate nearly a quarter of the region’s solar energy while offsetting all the land required for solar by 2050, but trade-offs, including maintenance of freshwater biodiversity and recreational benefits, exist. Avoidance of socioenvironmental interactions yields FPV-electricity generation potential equal to a 5% increase in regional solar generation while sparing water for biodiversity and social values, though opportunities for co-location make this a conservative estimate. Our framework extends technical potential assessments to holistically inform FPV siting and support diverse Sustainable Development Goals.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.crsus.2025.100423","usgsCitation":"Gallaher, A., Kalies, E., and Grodsky, S.M., 2025, Sustainability trade-offs across modeled floating solar waterscapes of the Northeastern United States: Cell Reports Sustainability, v. 2, no. 7, 100423, 15 p., https://doi.org/10.1016/j.crsus.2025.100423.","productDescription":"100423, 15 p.","ipdsId":"IP-166158","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":491012,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.crsus.2025.100423","text":"Publisher Index Page"},{"id":490768,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia, West 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 \"}}]}","volume":"2","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Gallaher, Adam","contributorId":348210,"corporation":false,"usgs":false,"family":"Gallaher","given":"Adam","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":923251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalies, Elizabeth L.","contributorId":348212,"corporation":false,"usgs":false,"family":"Kalies","given":"Elizabeth L.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":923252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grodsky, Steven Mark 0000-0003-0846-7230","orcid":"https://orcid.org/0000-0003-0846-7230","contributorId":328517,"corporation":false,"usgs":true,"family":"Grodsky","given":"Steven","email":"","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":923253,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70268216,"text":"70268216 - 2025 - Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system","interactions":[],"lastModifiedDate":"2025-06-17T14:39:24.788639","indexId":"70268216","displayToPublicDate":"2025-06-13T09:30:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system","docAbstract":"<p><span>Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO</span><sub>3</sub><span>) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552&nbsp;km</span><sup>2</sup><span>&nbsp;region in Colorado's Lower Arkansas River Valley (LARV) over 14&nbsp;years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile&nbsp;=&nbsp;30&nbsp;μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44&nbsp;% of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124&nbsp;μg/L and 60&nbsp;μg/L, respectively, compared with 112&nbsp;μg/L and 62&nbsp;μg/L for measured values. The average 85th percentile U concentration is 222&nbsp;μg/L in the aquifer and 82&nbsp;μg/L in the river. Average simulated U mass loading to the river is 0.17&nbsp;kg/day per km, compared to an estimated 0.23&nbsp;kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.179861","usgsCitation":"Qurban, I., Gates, T., Morway, E.D., Cox, J., White, J., Bailey, R.T., and Fienen, M., 2025, Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system: Science of the Total Environment, v. 989, 179861, 22 p., https://doi.org/10.1016/j.scitotenv.2025.179861.","productDescription":"179861, 22 p.","ipdsId":"IP-165259","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":490987,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.179861","text":"Publisher Index Page"},{"id":490832,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Arkansas River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -104.84418826977637,\n              38.499618485687876\n            ],\n            [\n              -104.84418826977637,\n              37.73373680491562\n            ],\n            [\n              -102.09264905018665,\n              37.73373680491562\n            ],\n            [\n              -102.09264905018665,\n              38.499618485687876\n            ],\n            [\n              -104.84418826977637,\n              38.499618485687876\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"989","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Qurban, Ibraheem A.","contributorId":356917,"corporation":false,"usgs":false,"family":"Qurban","given":"Ibraheem A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gates, Timothy K. 0000-0003-4702-4395","orcid":"https://orcid.org/0000-0003-4702-4395","contributorId":356920,"corporation":false,"usgs":false,"family":"Gates","given":"Timothy K.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cox, John T. 0000-0002-2956-0285","orcid":"https://orcid.org/0000-0002-2956-0285","contributorId":356923,"corporation":false,"usgs":false,"family":"Cox","given":"John T.","affiliations":[{"id":85282,"text":"W.W. Wheeler & Associates","active":true,"usgs":false}],"preferred":false,"id":940476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Jeremy T. 0000-0002-4950-1469","orcid":"https://orcid.org/0000-0002-4950-1469","contributorId":248830,"corporation":false,"usgs":false,"family":"White","given":"Jeremy T.","affiliations":[{"id":50032,"text":"GNS New Zealand","active":true,"usgs":false}],"preferred":false,"id":940477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bailey, Ryan T. 0000-0002-6539-1474","orcid":"https://orcid.org/0000-0002-6539-1474","contributorId":204129,"corporation":false,"usgs":false,"family":"Bailey","given":"Ryan","email":"","middleInitial":"T.","affiliations":[{"id":36859,"text":"Colorado State University, Department of Civil and Environmental Engineerring","active":true,"usgs":false}],"preferred":false,"id":940478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fienen, Michael N. 0000-0002-7756-4651","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":245632,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940479,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70268218,"text":"70268218 - 2025 - Origins and fluxes of gas emissions from the Central Volcanic Zone of the Andes","interactions":[],"lastModifiedDate":"2025-06-17T14:30:11.472409","indexId":"70268218","displayToPublicDate":"2025-06-13T09:19:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Origins and fluxes of gas emissions from the Central Volcanic Zone of the Andes","docAbstract":"<p><span>We present geochemical data from gas samples from ∼1200&nbsp;km of arc in the Central Volcanic Zone of the Andes (CVZA), the volcanic arc with the thickest (∼70&nbsp;km) continental crust globally. The primary goals of this study are to characterize and understand how magmatic gases interact with hydrothermal systems, assess the origins of the major gas species, and constrain gas emission rates. To this end, we use gas chemistry, isotope compositions of H, O, He, C, and S, and SO</span><sub>2</sub><span>&nbsp;fluxes from the CVZA. Gas and isotope ratios (CO</span><sub>2</sub><span>/S</span><sub>T</sub><span>, CO</span><sub>2</sub><span>/CH</span><sub>4</sub><span>, H</span><sub>2</sub><span>O/S</span><sub>T</sub><span>, δ</span><sup>13</sup><span>C, δ</span><sup>34</sup><span>S,&nbsp;</span><sup>3</sup><span>He/</span><sup>4</sup><span>He) vary dramatically as magmatic gases are progressively affected by hydrothermal processes, reflecting removal and crustal sequestration of reactive species (e.g., S) and addition of less reactive meteoric and crustal components (e.g., He). The observed variations are similar in magnitude to those expected during the magmatic reactivation of volcanoes with hydrothermal systems. Carbon and sulfur isotope compositions of the highest temperature emissions (97–408&nbsp;°C) are typical of arc magmatic gases. Helium isotope compositions reach values similar to upper mantle in some volcanic gases indicating that transcustal magma systems are effective conduits for volatiles, even through very thick continental crust. However, He isotopes are highly sensitive to even low degrees of hydrothermal interaction and radiogenic overprinting. Previous work has significantly underestimated volatile fluxes from the CVZA; however, emission rates from this study also appear to be lower than typical arcs, which may be related to crustal thickness.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2025.108382","usgsCitation":"de Moor, J., Barry, P., Rodriguez, A., Aguilera, F., Aguilera, M., Gonzalez, C., Layana, S., Chiodi, A., Apaza, F., Masias, P., Kern, C., Barnes, J., Cullen, J.T., Bastoni, D., Bastianoni, A., Cascone, M., Jimenez, C., Salas-Navarro, J., Ramirez, C., Jessen, G., Giovannelli, D., and Lloyd, K., 2025, Origins and fluxes of gas emissions from the Central Volcanic Zone of the Andes: Journal of Volcanology and Geothermal Research, v. 466, 108382, 18 p., https://doi.org/10.1016/j.jvolgeores.2025.108382.","productDescription":"108382, 18 p.","ipdsId":"IP-170019","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":490986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2025.108382","text":"Publisher Index Page"},{"id":490831,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina, Bolivia, Chile, Peru","otherGeospatial":"Central Volcanic Zone of the Andes","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -74,\n              -14\n            ],\n            [\n              -74,\n              -28\n            ],\n            [\n              -64,\n              -28\n            ],\n            [\n              -64,\n              -14\n            ],\n            [\n              -74,\n              -14\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"466","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"de Moor, J. Maarten","contributorId":353456,"corporation":false,"usgs":false,"family":"de Moor","given":"J. Maarten","affiliations":[{"id":38348,"text":"Observatorio Vulcanológico y Sismológico de Costa Rica, Universidad Nacional, Heredia, Costa Rica","active":true,"usgs":false}],"preferred":false,"id":940484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barry, Peter","contributorId":267752,"corporation":false,"usgs":false,"family":"Barry","given":"Peter","affiliations":[{"id":13294,"text":"Woods Hole Oceanographic Institute","active":true,"usgs":false}],"preferred":false,"id":940485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez, Alejandro","contributorId":356931,"corporation":false,"usgs":false,"family":"Rodriguez","given":"Alejandro","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":940486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aguilera, Felipe","contributorId":256986,"corporation":false,"usgs":false,"family":"Aguilera","given":"Felipe","email":"","affiliations":[{"id":51939,"text":"Universidad de Atacama, Chile","active":true,"usgs":false}],"preferred":false,"id":940487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aguilera, Mauricio","contributorId":335911,"corporation":false,"usgs":false,"family":"Aguilera","given":"Mauricio","email":"","affiliations":[{"id":80578,"text":"Millennium Institute on Volcanic Risk Research - Ckelar Volcanoes; Universidad Católica del Norte","active":true,"usgs":false}],"preferred":false,"id":940488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gonzalez, Cristobal","contributorId":356934,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Cristobal","affiliations":[{"id":85288,"text":"Ckelar Volcanoes","active":true,"usgs":false}],"preferred":false,"id":940489,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Layana, Susana 0000-0002-0185-373X","orcid":"https://orcid.org/0000-0002-0185-373X","contributorId":335908,"corporation":false,"usgs":false,"family":"Layana","given":"Susana","email":"","affiliations":[{"id":80576,"text":"Millennium Institute on Volcanic Risk Research - Ckelar Volcanoes","active":true,"usgs":false}],"preferred":false,"id":940490,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Chiodi, Agostina","contributorId":356935,"corporation":false,"usgs":false,"family":"Chiodi","given":"Agostina","affiliations":[{"id":85291,"text":"Instituto de Bio y Geociencias del NOA","active":true,"usgs":false}],"preferred":false,"id":940491,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Apaza, Fredy","contributorId":190927,"corporation":false,"usgs":false,"family":"Apaza","given":"Fredy","email":"","affiliations":[],"preferred":false,"id":940492,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Masias, Pablo","contributorId":190934,"corporation":false,"usgs":false,"family":"Masias","given":"Pablo","email":"","affiliations":[],"preferred":false,"id":940493,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":940494,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Barnes, Jaime D.","contributorId":140886,"corporation":false,"usgs":false,"family":"Barnes","given":"Jaime D.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":940495,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Cullen, Jeffrey T.","contributorId":140885,"corporation":false,"usgs":false,"family":"Cullen","given":"Jeffrey","email":"","middleInitial":"T.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":940496,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bastoni, Deborah","contributorId":356936,"corporation":false,"usgs":false,"family":"Bastoni","given":"Deborah","affiliations":[{"id":47714,"text":"University of Naples","active":true,"usgs":false}],"preferred":false,"id":940497,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Bastianoni, Alessia","contributorId":356937,"corporation":false,"usgs":false,"family":"Bastianoni","given":"Alessia","affiliations":[{"id":47714,"text":"University of Naples","active":true,"usgs":false}],"preferred":false,"id":940498,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Cascone, Martina","contributorId":356938,"corporation":false,"usgs":false,"family":"Cascone","given":"Martina","affiliations":[{"id":47714,"text":"University of Naples","active":true,"usgs":false}],"preferred":false,"id":940499,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Jimenez, Christofer","contributorId":356939,"corporation":false,"usgs":false,"family":"Jimenez","given":"Christofer","affiliations":[{"id":37066,"text":"OVSICORI","active":true,"usgs":false}],"preferred":false,"id":940500,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Salas-Navarro, Jessica","contributorId":356940,"corporation":false,"usgs":false,"family":"Salas-Navarro","given":"Jessica","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":940501,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Ramirez, Carlos","contributorId":177061,"corporation":false,"usgs":false,"family":"Ramirez","given":"Carlos","email":"","affiliations":[],"preferred":false,"id":940502,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Jessen, Gerdhard","contributorId":356941,"corporation":false,"usgs":false,"family":"Jessen","given":"Gerdhard","affiliations":[{"id":37760,"text":"Universidad Austral de Chile","active":true,"usgs":false}],"preferred":false,"id":940503,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Giovannelli, Donato","contributorId":356942,"corporation":false,"usgs":false,"family":"Giovannelli","given":"Donato","affiliations":[{"id":85292,"text":"Woods Hole","active":true,"usgs":false}],"preferred":false,"id":940504,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Lloyd, Karen","contributorId":355874,"corporation":false,"usgs":false,"family":"Lloyd","given":"Karen","affiliations":[{"id":47795,"text":"USC","active":true,"usgs":false}],"preferred":false,"id":940505,"contributorType":{"id":1,"text":"Authors"},"rank":22}]}}
,{"id":70268357,"text":"70268357 - 2025 - Canopy and surface fuels measurement using terrestrial lidar single-scan approach in the Mogollon highlands of Arizona","interactions":[],"lastModifiedDate":"2025-06-23T14:08:47.814199","indexId":"70268357","displayToPublicDate":"2025-06-13T09:03:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2083,"text":"International Journal of Wildland Fire","active":true,"publicationSubtype":{"id":10}},"title":"Canopy and surface fuels measurement using terrestrial lidar single-scan approach in the Mogollon highlands of Arizona","docAbstract":"<div class=\"section\"><strong>Background</strong><p id=\"d6e253\">Fuel monitoring data are essential to evaluate wildfire risk, plan management activities and evaluate fuel treatment effects. Terrestrial light detection and ranging (lidar) is a field-based 3D scanning technology with great potential to reduce labor-intensive field measurements and provide new depths of vegetation structure data.</p></div><div class=\"section\"><strong>Aims</strong><p id=\"d6e258\">To facilitate the integration of terrestrial lidar into fuel monitoring programs, we developed a model, training process, and Python program that produces canopy fuel, surface fuel and terrain metrics commonly used in fire behavior and fire risk modeling.</p></div><div class=\"section\"><strong>Methods</strong><p id=\"d6e263\">We estimated canopy and surface fuel metrics from terrestrial lidar using a semi-empirical model incorporating physically based modeling of leaf area density and occlusion and a non-destructive model calibration process leveraging Bayesian regression. We compared lidar-derived fuel estimates with conventional fuel estimates across diverse conditions in semi-arid shrubland, woodland and forest in Arizona. We also compared estimates using single- and multiple-scan modes.</p></div><div class=\"section\"><strong>Key results</strong><p id=\"d6e268\">In single-scan mode, our lidar-derived fuel estimates were significantly related to conventional estimates of total canopy fuel load, maximum canopy bulk density, downed surface fuel load and standing surface fuel load.</p></div><div class=\"section\"><strong>Implications</strong><p id=\"d6e273\">Our methods provide opportunities to increase the scalability of fuel monitoring to better understand wildfire risk and treatment effectiveness.</p></div>","language":"English","publisher":"CSIRO Publishing","doi":"10.1071/WF24221","usgsCitation":"Tenny, J., Sankey, T.T., Munson, S.M., Sánchez Meador, A., and Goetz, S.J., 2025, Canopy and surface fuels measurement using terrestrial lidar single-scan approach in the Mogollon highlands of Arizona: International Journal of Wildland Fire, v. 34, no. 7, WF24221, 15 p., https://doi.org/10.1071/WF24221.","productDescription":"WF24221, 15 p.","ipdsId":"IP-172468","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":491454,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1071/wf24221","text":"Publisher Index Page"},{"id":491095,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Mogollon Highlands","volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Tenny, Johnathan T.","contributorId":357286,"corporation":false,"usgs":false,"family":"Tenny","given":"Johnathan T.","affiliations":[{"id":85397,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, 1298 S. Knoles Drive, Flagstaff, AZ 86011, United States","active":true,"usgs":false}],"preferred":false,"id":941069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sankey, Temuulen Tsagaan","contributorId":149290,"corporation":false,"usgs":false,"family":"Sankey","given":"Temuulen","email":"","middleInitial":"Tsagaan","affiliations":[],"preferred":false,"id":941070,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":941071,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sánchez Meador, Andrew J.","contributorId":357287,"corporation":false,"usgs":false,"family":"Sánchez Meador","given":"Andrew J.","affiliations":[{"id":85399,"text":"School of Forestry, Northern Arizona University, Flagstaff, Arizona, United States; Ecological Restoration Institute, Northern Arizona University, Flagstaff, Arizona, United States","active":true,"usgs":false}],"preferred":false,"id":941072,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goetz, Scott J.","contributorId":222547,"corporation":false,"usgs":false,"family":"Goetz","given":"Scott","email":"","middleInitial":"J.","affiliations":[{"id":40559,"text":"School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":941073,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70268346,"text":"70268346 - 2025 - Diamondback terrapin resource use in a seagrass-dominated coastal bay varies by life stage","interactions":[],"lastModifiedDate":"2025-06-23T14:02:40.885581","indexId":"70268346","displayToPublicDate":"2025-06-13T08:58:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Diamondback terrapin resource use in a seagrass-dominated coastal bay varies by life stage","docAbstract":"<p><span>Diamondback terrapins, hereafter referred to as terrapins, are the only estuarine turtle species native to North America. However, terrapins are also occasionally found in marine habitats, such as seagrass beds, and yet little is known about how they use those marine habitats. We sampled epidermis from terrapins (</span><i>Malaclemys terrapin macrospilota</i><span>) inhabiting a seagrass-dominated coastal bay in Northwest Florida and compared resource use among terrapin sexes and life-history stages using the isotopic niche and mixing models. Terrapins were generalist foragers, and their diets varied by sex and life stage, as has been reported elsewhere. Basal resource mixing models indicated the terrapin food web was based primarily on&nbsp;</span><i>Thalassia testudinum</i><span>&nbsp;for adult females (50.0%) and&nbsp;</span><i>Spartina alterniflora</i><span>&nbsp;for adult males (49.7%) and juvenile females (42.2%). Dietary mixing models indicated the adult female diet included a relatively high proportion of&nbsp;</span><i>Thalassia testudinum</i><span>&nbsp;(31.3%), suggesting a strong reliance on seagrass dominated prey and not necessarily large consumption of seagrass, followed by lower proportions of gastropods (26.6%) and crustaceans (19.1%). Primary diet items for juvenile females and adult males included relatively equal proportions of echinoderms, gastropods, crustaceans, ascidians, and porifera. Body and head size of terrapins may drive differences in diet, as interpreted from mixing model results. Although mangroves are expanding their range northward along the Gulf of America coast and have become established at our study site, it does not appear that terrapins are foraging within these newly established mangrove forests. Finally, the terrapin niche, particularly for adult females, may overlap with the sea turtle niche in seagrass-dominated bays. Whether sea turtles impact terrapin populations, including through direct predation, is unknown.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s12237-025-01568-3","usgsCitation":"Lamont, M., Arends, C.L., Catizone, D.J., and Vander Zanden, H.B., 2025, Diamondback terrapin resource use in a seagrass-dominated coastal bay varies by life stage: Estuaries and Coasts, v. 48, no. 5, 132, 12 p., https://doi.org/10.1007/s12237-025-01568-3.","productDescription":"132, 12 p.","ipdsId":"IP-169842","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":491453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-025-01568-3","text":"Publisher Index Page"},{"id":491094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St. Joseph Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -85.42067407815058,\n              29.88845033015012\n            ],\n            [\n              -85.42067407815058,\n              29.67807911729524\n            ],\n            [\n              -85.28516563300288,\n              29.67807911729524\n            ],\n            [\n              -85.28516563300288,\n              29.88845033015012\n            ],\n            [\n              -85.42067407815058,\n              29.88845033015012\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":206817,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":940893,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arends, Carson L. 0000-0001-9962-8647","orcid":"https://orcid.org/0000-0001-9962-8647","contributorId":296689,"corporation":false,"usgs":true,"family":"Arends","given":"Carson","email":"","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":940894,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catizone, Daniel J. 0000-0002-7030-4208","orcid":"https://orcid.org/0000-0002-7030-4208","contributorId":248817,"corporation":false,"usgs":true,"family":"Catizone","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":940895,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vander Zanden, Hannah B.","contributorId":138885,"corporation":false,"usgs":false,"family":"Vander Zanden","given":"Hannah","email":"","middleInitial":"B.","affiliations":[{"id":12562,"text":"Department of Geology and Geophysics, University of Utah; Archie Carr Center for Sea Turtle Research, University of Florida","active":true,"usgs":false}],"preferred":false,"id":940896,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70267356,"text":"ofr20251015 - 2025 - Black abalone (Haliotis cracherodii) population density, recruitment, size structure, and population growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22","interactions":[],"lastModifiedDate":"2025-07-01T13:38:36.909712","indexId":"ofr20251015","displayToPublicDate":"2025-06-13T08:54:57","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1015","displayTitle":"Black Abalone (<em>Haliotis cracherodii</em>) Population Density, Recruitment, Size Structure, and Population Growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22","title":"Black abalone (Haliotis cracherodii) population density, recruitment, size structure, and population growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22","docAbstract":"<p><span>The range of the endangered black abalone (</span><i>Haliotis cracherodii</i><span>) is divided into the North Central California region, the Central California region, the Southern California Mainland region, the Channel Islands region, and the Baja California region by the National Marine Fisheries Service for management purposes. San Nicolas Island is one of eight subregions of the Channel Islands region. The black abalone recovery plan establishes five demographic criteria for the possible delisting or downlisting of the species. The U.S. Geological Survey monitors nine long-term intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. This report uses data collected between 2013 and 2022 and the delisting criteria to analyze and describe the density, recruitment, size structure, and population trends at the nine U.S. Geological Survey monitoring sites at San Nicolas Island.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251015","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Land Management Research Program and Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2025, Black abalone (<em>Haliotis cracherodii</em>) population density, recruitment, size structure, and population growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22: U.S. Geological Survey Open-File Report 2025–1015, 10 p., https://doi.org/10.3133/ofr20251015.","productDescription":"vi, 10 p.","onlineOnly":"Y","ipdsId":"IP-174146","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490728,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20251014","text":"Open-File Report 2025-1014","description":"OFR 2025-1014","linkHelpText":"- Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2022 annual report"},{"id":486255,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1015/ofr20251015.XML"},{"id":486254,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1015/images"},{"id":486253,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251015/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1015"},{"id":486252,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1015/ofr20251015.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1015"},{"id":486251,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1015/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Naval Base Ventura County, San Nicolas Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.41565036125932,\n              33.22855822061233\n            ],\n            [\n              -119.4322978602211,\n              33.233849792002204\n            ],\n            [\n              -119.46292925831023,\n              33.2600242059834\n            ],\n            [\n              -119.53051810409356,\n              33.29036557133239\n            ],\n            [\n              -119.58545485066676,\n              33.281459107969354\n            ],\n            [\n              -119.57180390151814,\n              33.25000088849947\n            ],\n            [\n              -119.54217135336674,\n              33.228836776039614\n            ],\n            [\n              -119.47857790733391,\n              33.21379600415082\n            ],\n            [\n              -119.45160895901617,\n              33.21379600415082\n            ],\n            [\n              -119.41565036125932,\n              33.22855822061233\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br>U.S. Geological Survey<br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods and Results</li><li>Discussion</li><li>References Cited</li></ul>","publishedDate":"2025-06-13","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937958,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":937959,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70268146,"text":"70268146 - 2025 - Multi-model comparison of salt marsh longevity under relative sea-level rise","interactions":[],"lastModifiedDate":"2025-06-16T13:57:23.958198","indexId":"70268146","displayToPublicDate":"2025-06-13T08:52:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Multi-model comparison of salt marsh longevity under relative sea-level rise","docAbstract":"<p><span>Understanding salt marsh resilience under increasing sea levels can inform for management decisions. We compared temporal projections from various wetland process-based models and a geospatially derived metric (i.e., marsh lifespan) to understand key considerations and uncertainties about salt marsh resilience when using these products for decision-making. The influences of lidar topographic correction and marsh surface sediment accretion were explored across a suite of relative sea level rise (RSLR) projections to assess differences in the timing and amount of habitat change for each modeling approach. All models were run for a small coastal wetland site located in the Chesapeake Bay, Maryland, USA, to assess potential change in marsh habitat, and timing of marsh loss due to RSLR. All modeling results agreed that marsh longevity was threatened by RSLR but they varied in the time of predicted marsh submergence between the years 2070 and 2100 depending on the initial marsh surface elevation and accretion rates. Models with similar accretion rates predicted similar years until marsh submergence. Removing a positive elevation bias from lidar surveys in densely vegetated marsh areas for these models resulted in onset of submergence ~ 7 years earlier. Because there are many tradeoffs to each model type, end users need to evaluate management questions, overall goals, the amount of effort involved in model parameterization, and the amount of uncertainty in the model that they are willing to accept.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s12237-025-01559-4","usgsCitation":"Martinez, M., Buffington, K., Ganju, N., Defne, Z., Ackerman, K., Thorne, K., Guntenspergen, G.R., and Carr, J., 2025, Multi-model comparison of salt marsh longevity under relative sea-level rise: Estuaries and Coasts, v. 48, 131, 17 p., https://doi.org/10.1007/s12237-025-01559-4.","productDescription":"131, 17 p.","ipdsId":"IP-175115","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":491006,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-025-01559-4","text":"Publisher Index Page"},{"id":490750,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Kent County","otherGeospatial":"Eastern Neck Island National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.24030263498597,\n              39.05092670969253\n            ],\n            [\n              -76.2464251064265,\n              39.02623477098268\n            ],\n            [\n              -76.22111104181657,\n              39.0091277190638\n            ],\n            [\n              -76.20939592819497,\n              39.005880153850384\n            ],\n            [\n              -76.19532601786523,\n              39.010317858728\n            ],\n            [\n              -76.20639356239224,\n              39.05275533676962\n            ],\n            [\n              -76.22099330198093,\n              39.05568114506616\n            ],\n            [\n              -76.24030263498597,\n              39.05092670969253\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Melinda 0000-0001-6652-9220","orcid":"https://orcid.org/0000-0001-6652-9220","contributorId":290467,"corporation":false,"usgs":true,"family":"Martinez","given":"Melinda","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":940339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buffington, Kevin J. 0000-0001-9741-1241 kbuffington@usgs.gov","orcid":"https://orcid.org/0000-0001-9741-1241","contributorId":4775,"corporation":false,"usgs":true,"family":"Buffington","given":"Kevin","email":"kbuffington@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":940340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ackerman, Kate 0000-0003-3925-721X","orcid":"https://orcid.org/0000-0003-3925-721X","contributorId":293631,"corporation":false,"usgs":true,"family":"Ackerman","given":"Kate","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940343,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":940344,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940345,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940346,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70268760,"text":"70268760 - 2025 - Rapid risk assessment framework to estimate potential for spillback at human-wildlife interfaces","interactions":[],"lastModifiedDate":"2025-07-10T14:57:17.754452","indexId":"70268760","displayToPublicDate":"2025-06-13T08:50:55","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3849,"text":"Transboundary and Emerging Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Rapid risk assessment framework to estimate potential for spillback at human-wildlife interfaces","docAbstract":"<p><span>More than 60% of emerging infectious diseases of humans have a wildlife origin, and when these diseases spread through human populations to new geographical areas, there is a considerable risk of spillback from humans to wildlife species. Spillback events can have severe consequences for wildlife populations, where the disease may cause morbidity and mortality, and human populations, where the establishment in wildlife may lead to prolonged transmission or new exposures in humans. Mitigating these consequences requires identifying the key risk factors that lead to human–wildlife transmission events and implementing risk-reducing actions, a challenge given that cross-species transmission events are rare and often data deficient. To identify potential species and locations that are most likely to lead to these rare events, we developed a spatially explicit, rapid risk assessment framework that incorporates three components of the spillback process: wildlife susceptibility, wildlife exposure, and pathogen introduction pressure. To demonstrate the broad applicability of our framework, we conducted a rapid risk assessment on two recent emerging zoonotic pathogens in humans, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and mpox, to determine the relative spillback risk to wild mammalian species in the continental United States. The rapid risk assessment identified both species and locations with higher than expected spillback risk, providing managers and researchers with valuable information to prioritize surveillance and risk-mitigation actions. Our framework represents a rapid and flexible approach to assess the risks of spillback to wildlife populations during rapidly evolving zoonotic disease outbreaks.</span></p>","language":"English","publisher":"PubMed Central","doi":"10.1155/tbed/4334954","usgsCitation":"Mcdevitt-Galles, T., Fry, T., Richgels, K., and Grear, D.A., 2025, Rapid risk assessment framework to estimate potential for spillback at human-wildlife interfaces: Transboundary and Emerging Diseases, v. 2025, 4334954, 15 p., https://doi.org/10.1155/tbed/4334954.","productDescription":"4334954, 15 p.","ipdsId":"IP-160096","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":492090,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1155/tbed/4334954","text":"Publisher Index Page"},{"id":491808,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -125.97084947037874,\n              48.633322740164715\n            ],\n            [\n              -124.7392146445165,\n              37.00758771879266\n            ],\n            [\n              -118.2521345151965,\n              32.82119172303341\n            ],\n            [\n              -107.8473648454318,\n              30.862675765777055\n            ],\n            [\n              -98.46601775789239,\n              26.182786928741095\n            ],\n            [\n              -79.55043816735622,\n              24.502682268282584\n            ],\n            [\n              -80.16713782720478,\n              31.37578863952467\n            ],\n            [\n              -74.7558728135753,\n              35.46079116327094\n            ],\n            [\n              -67.1408314266174,\n              43.72777509706573\n            ],\n            [\n              -67.67002630536457,\n              47.164807560194056\n            ],\n            [\n              -81.40402452012242,\n              42.203163887439615\n            ],\n            [\n              -82.68676846828293,\n              45.67835235914693\n            ],\n            [\n              -90.32310194724667,\n              48.78125858148974\n            ],\n            [\n              -125.97084947037874,\n              48.633322740164715\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"2025","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Mcdevitt-Galles, Travis 0000-0002-4929-5431","orcid":"https://orcid.org/0000-0002-4929-5431","contributorId":315374,"corporation":false,"usgs":true,"family":"Mcdevitt-Galles","given":"Travis","email":"","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":941875,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fry, Tricia L.","contributorId":357592,"corporation":false,"usgs":false,"family":"Fry","given":"Tricia L.","affiliations":[{"id":85464,"text":"Midwest Association for Fish and Wildlife Agencies","active":true,"usgs":false}],"preferred":false,"id":941876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richgels, Katherine 0000-0003-2834-9477 krichgels@usgs.gov","orcid":"https://orcid.org/0000-0003-2834-9477","contributorId":167016,"corporation":false,"usgs":true,"family":"Richgels","given":"Katherine","email":"krichgels@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":941877,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":189819,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":941878,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70268148,"text":"70268148 - 2025 - Not all spatially structured populations are metapopulations: Re-examining paradigms for a threatened shorebird","interactions":[],"lastModifiedDate":"2025-06-16T13:43:43.023749","indexId":"70268148","displayToPublicDate":"2025-06-13T08:35:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Not all spatially structured populations are metapopulations: Re-examining paradigms for a threatened shorebird","docAbstract":"<p><span>For at-risk species, understanding population vital rates is imperative for developing informed conservation strategies and population models. Managers often assume that species that are spatially distributed among patches of suitable habitat meet the criteria of a metapopulation. Metapopulation dynamics are determined not only by within-patch birth and death processes but also by between-patch dispersal movements of individuals that are infrequent but critical to maintaining population viability across space and time. To conserve and manage such species, an understanding of all these vital rates, including connectivity, is required. The degree to which the northern Great Plains piping plover (</span><i>Charadrius melodus</i><span>) breeding population functions as a metapopulation depends, in part, on the rate of movement among patchily distributed breeding areas. Here, we examined annual adult survival and breeding dispersal probabilities for 2582 individuals at two spatial scales within the northern Great Plains piping plover breeding population between 2014 and 2019. Inconsistent with a metapopulation structure, annual survival varied minimally among breeding regions but did vary across years. We also found that breeding dispersal probabilities were temporally variable, high, and unbalanced at both spatial scales examined, suggesting high connectivity in contrast to metapopulation dynamics. Further, we detected context-dependent effects of reproductive success on dispersal decisions. Individuals were more likely to disperse from the northern Missouri River to the US Alkali Wetlands following nest failure due to inundation or severe storms (including in the year prior to dispersal), whereas dispersal from the US Alkali Wetlands to the northern Missouri River decreased following successful nest attempts. Individuals also decreased dispersal from the US Alkali Wetlands to the northern Missouri River in response to renesting attempts in both the year of interest and the year prior to dispersal. Our results contradict the paradigm that northern Great Plains piping plovers are structured as a metapopulation and instead suggest a patchily distributed, likely panmictic, population. Our findings have implications for the conservation and management of this listed species and are also a general reminder that in the absence of robust knowledge of movement, spatial variation in birth and death processes across patches should not be conflated with a metapopulation structure.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70037","usgsCitation":"Swift, R.J., Anteau, M.J., Ellis, K.S., MacDonald, G.J., Ring, M., Sherfy, M.H., Toy, D.L., and Koons, D.N., 2025, Not all spatially structured populations are metapopulations: Re-examining paradigms for a threatened shorebird: Ecological Applications, v. 35, no. 4, e70037, 22 p., https://doi.org/10.1002/eap.70037.","productDescription":"e70037, 22 p.","ipdsId":"IP-159633","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":491308,"rank":1,"type":{"id":30,"text":"Data 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N.","contributorId":28137,"corporation":false,"usgs":false,"family":"Koons","given":"David","email":"","middleInitial":"N.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":940361,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70268057,"text":"ofr20251014 - 2025 - Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2022 annual report","interactions":[],"lastModifiedDate":"2025-07-01T16:55:19.83033","indexId":"ofr20251014","displayToPublicDate":"2025-06-13T07:39:45","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1014","displayTitle":"Black Abalone Surveys at Naval Base Ventura County, San Nicolas Island, California—2022 Annual Report","title":"Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2022 annual report","docAbstract":"<p>The U.S. Geological Survey monitors a suite of intertidal black abalone (<i>Haliotis cracherodii</i>) sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential effect of translocated southern sea otters (<i>Enhydra lutris nereis</i>) on the intertidal black abalone population at San Nicolas Island. The sites were monitored, typically annually or biennially, from 1981 to 1997. Monitoring resumed in 2001 and has been completed annually thereafter. Since 2018, the monitoring has been carried out by the U.S. Geological Survey Western Ecological Research Center. The study sites became particularly important from a management perspective after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992, and during the next few years, withering syndrome reduced the black abalone population on San Nicolas Island by more than 99 percent. The black abalone was subsequently listed as endangered under the Endangered Species Act in 2009.</p><p>The subject of this report is the 2022 survey of the sites and the status of the measured population of black abalone in comparison to long-term patterns (based on data collected since 1981) at San Nicolas Island. Between the years 2000 and 2022, the total monitored black abalone population on the island has grown from roughly 200 to more than 2,000, approximately a ten-fold increase following the disease-related decline. Since it was first consistently measured in 2005, the distance between adjacent black abalone has decreased substantially from approximately 50 centimeters to less than 15 centimeters, indicating that black abalone are sufficiently close together at several of the sites to reproduce successfully. The total black abalone count in 2022 was 2,156, which was 7.9 percent lower than the total count in 2020 but 6.6 percent higher than in 2021. There were increases and decreases among the sites and transects within each site in 2022, but six of the nine sites had higher counts than in the previous year. The 2022 count is one of the highest since 1993, second only to the 2020 count. In 2022, the annual recruitment rate, defined as the percentage of measured black abalone with a shell length of 3 centimeters or less, was the second highest recorded, only slightly less than in 2017.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251014","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Land Management Research Program and Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2025, Black abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2022 annual report: U.S. Geological Survey Open-File Report 2025–1014, 34 p., https://doi.org/10.3133/ofr20251014.","productDescription":"viii, 34 p.","onlineOnly":"Y","ipdsId":"IP-159889","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":490412,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1014/images"},{"id":491626,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20251015","text":"Open-File Report 2025-1015","description":"OFR 2025-1015","linkHelpText":"- Black abalone (<em>Haliotis cracherodii</em>) population density, recruitment, size structure, and population growth at Naval Base Ventura County, San Nicolas Island, California, 2013–22"},{"id":490413,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1014/ofr20251014.XML"},{"id":490410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1014/ofr20251014.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1014"},{"id":490411,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251014/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1014"},{"id":490409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1014/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Naval Base, Ventura County, San Nicolas Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -119.41565036125932,\n              33.22855822061233\n            ],\n            [\n              -119.4322978602211,\n              33.233849792002204\n            ],\n            [\n              -119.46292925831023,\n              33.2600242059834\n            ],\n            [\n              -119.53051810409356,\n              33.29036557133239\n            ],\n            [\n              -119.58545485066676,\n              33.281459107969354\n            ],\n            [\n              -119.57180390151814,\n              33.25000088849947\n            ],\n            [\n              -119.54217135336674,\n              33.228836776039614\n            ],\n            [\n              -119.47857790733391,\n              33.21379600415082\n            ],\n            [\n              -119.45160895901617,\n              33.21379600415082\n            ],\n            [\n              -119.41565036125932,\n              33.22855822061233\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/werc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/werc\">Western Ecological Research Center</a><br>U.S. Geological Survey<br>3020 State University Drive East<br>Sacramento, California 95819</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Sites</li><li>Results</li><li>Conclusion</li><li>References Cited</li></ul>","publishedDate":"2025-06-13","noUsgsAuthors":false,"publicationDate":"2025-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Kenner, Michael C. 0000-0003-4659-461X","orcid":"https://orcid.org/0000-0003-4659-461X","contributorId":208151,"corporation":false,"usgs":true,"family":"Kenner","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":940075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yee, Julie L. 0000-0003-1782-157X julie_yee@usgs.gov","orcid":"https://orcid.org/0000-0003-1782-157X","contributorId":3246,"corporation":false,"usgs":true,"family":"Yee","given":"Julie","email":"julie_yee@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":940076,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70268056,"text":"sir20255036 - 2025 - Cascading consequences and interventions for hazards after wildfire in Okanogan County, Washington","interactions":[],"lastModifiedDate":"2025-06-13T22:02:50.732528","indexId":"sir20255036","displayToPublicDate":"2025-06-12T17:30:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5036","displayTitle":"Cascading Consequences and Interventions for Hazards After Wildfire in Okanogan County, Washington","title":"Cascading consequences and interventions for hazards after wildfire in Okanogan County, Washington","docAbstract":"<p>This report details the application of the chains of consequences method within the postfire hazard context after the 2021 Cedar Creek and Muckamuck Fires around Okanogan County, Washington. The U.S. Geological Survey Social and Economic Analysis branch convened 20 stakeholders with content- and context-specific knowledge related to these fires and their postfire hazards in an April 2023 Postfire Hazards Chains of Consequences Workshop. Guided by U.S. Geological Survey facilitators, workshop participants identified the cascading consequences of a specific postfire hazard scenario before brainstorming interventions to reduce the likelihood and severity of those consequences. The participants worked across disciplinary boundaries to identify gaps in understanding around cascading postfire hazard consequences and to brainstorm multidisciplinary interventions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20255036","programNote":"Land Management Research Program","usgsCitation":"Goldwyn, B.H., Meldrum, J.R., and Schuster, R.M., 2025, Cascading consequences and interventions for hazards after wildfire in Okanogan County, Washington: U.S. Geological Survey Scientific Investigations Report 2025–5036, 26 p., https://doi.org/10.3133/sir20255036.","productDescription":"Report: vi, 26 p.; 1 Plate: 70.65 x 17.38 inches","onlineOnly":"Y","ipdsId":"IP-157692","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490734,"rank":6,"type":{"id":39,"text":"HTML 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<a href=\"https://www.usgs.gov/centers/fort-collins-science-center/\" data-mce-href=\"https://www.usgs.gov/centers/fort-collins-science-center/\">Fort Collins Science Center</a><br>U.S. Geological Survey<br>2150 Centre Ave., Bldg. C<br>Fort Collins, CO 80526-8118</p>","tableOfContents":"<ul><li>Acknowledgments </li><li>Abstract</li><li>Introduction</li><li>Background</li><li>Purpose and Scope</li><li>Methods</li><li>Results</li><li>Discussion </li><li>Summary</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Detailed Method Overview</li></ul>","publishedDate":"2025-06-12","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Goldwyn, Briar H. 0000-0003-2866-045X","orcid":"https://orcid.org/0000-0003-2866-045X","contributorId":356792,"corporation":false,"usgs":true,"family":"Goldwyn","given":"Briar H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":940072,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":940073,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schuster, Rudy 0000-0003-2353-8500 schusterr@usgs.gov","orcid":"https://orcid.org/0000-0003-2353-8500","contributorId":3119,"corporation":false,"usgs":true,"family":"Schuster","given":"Rudy","email":"schusterr@usgs.gov","affiliations":[],"preferred":true,"id":940074,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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As the science arm of the Department of the Interior, the USGS has a primary role in providing scientific information to natural resource managers and policymakers across the United States. This “Pollinator Science Strategy” was drafted by a team of USGS pollinator researchers and was further developed through feedback from Federal, State, Tribal, nongovernmental organizations, and industry partners. This “Pollinator Science Strategy” highlights the USGS’s role in the research to promote healthy pollinator populations and address partner information gaps so they can make more informed management decisions. By outlining the importance of USGS science in addressing the information needs of other agencies, organizations, and the public, the “Pollinator Science Strategy” reaffirms the USGS’s commitment to pollinator research and showcases our research priorities for 2025–35.</p><p>With more than 300 research centers nationally, the USGS is equipped to address pollinator science across scales of complexity and geographic range. 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These research goals include synthesizing and modernizing the latest information on pollinator threats, developing research that assists managers with habitat design and restoration, providing training to partners on native bee identification and monitoring design, and developing new technologies for assessing the status and trends of our nation’s pollinators.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1556","usgsCitation":"Otto, C.R.V., Graves, T.A., Robertson-Thompson, D., Pearse, I., Thogmartin, W.E., Murphy, C., Webb, L., Droege, S., Steinkamp, M., and Grundel, R., 2025, U.S. Geological Survey Pollinator Science Strategy, 2025–35—A review and look forward (ver. 1.1, June 26, 2025): U.S. Geological Survey Circular 1556, 16 p., https://doi.org/10.3133/cir1556.","productDescription":"vi, 16 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-172990","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":5057,"text":"NGTOC Reston","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true},{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":490448,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/circ/1556/images/"},{"id":490447,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1556/circ1556.XML"},{"id":490449,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/cir1556/full"},{"id":490446,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1556/circ1556.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Cir 1556"},{"id":490445,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1556/coverthb4.jpg"},{"id":491238,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1556/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: June 12, 2025; Version 1.1: June 26, 2025","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/npwrc\" data-mce-href=\"https://www.usgs.gov/centers/npwrc\">Northern Prairie Wildlife Research Center</a><br>U.S. Geological Survey<br>8711 37th Street Southeast<br>Jamestown, ND 58401</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Executive Summary</li><li>U.S. Geological Survey Pollinator Science Mission Statement</li><li>Importance of Pollinators</li><li>Need for Pollinator Science</li><li>U.S. Geological Survey Role in Pollinator Science</li><li>U.S. Geological Survey Pollinator Science Themes</li><li>U.S. Geological Survey Partner Science</li><li>Future Research Objectives, Actions, and Benefits</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-06-12","revisedDate":"2025-06-26","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":940092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson-Thompson, Desi 0009-0003-6878-2539","orcid":"https://orcid.org/0009-0003-6878-2539","contributorId":356794,"corporation":false,"usgs":true,"family":"Robertson-Thompson","given":"Desi","affiliations":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":940093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearse, Ian S. 0000-0001-7098-0495","orcid":"https://orcid.org/0000-0001-7098-0495","contributorId":216680,"corporation":false,"usgs":true,"family":"Pearse","given":"Ian","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":940094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":940095,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Caroline E. 0009-0001-9485-4730","orcid":"https://orcid.org/0009-0001-9485-4730","contributorId":334933,"corporation":false,"usgs":true,"family":"Murphy","given":"Caroline","email":"","middleInitial":"E.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":940096,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Webb, Elisabeth B. 0000-0003-3851-6056 ewebb@usgs.gov","orcid":"https://orcid.org/0000-0003-3851-6056","contributorId":3981,"corporation":false,"usgs":true,"family":"Webb","given":"Elisabeth","email":"ewebb@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":940097,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Droege, Sam 0000-0003-4393-0403","orcid":"https://orcid.org/0000-0003-4393-0403","contributorId":64185,"corporation":false,"usgs":true,"family":"Droege","given":"Sam","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":940098,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Steinkamp, Melanie J. 0000-0001-9322-609X","orcid":"https://orcid.org/0000-0001-9322-609X","contributorId":292474,"corporation":false,"usgs":true,"family":"Steinkamp","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":5057,"text":"NGTOC Reston","active":true,"usgs":true}],"preferred":true,"id":940101,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Grundel, Ralph 0000-0002-2949-7087 rgrundel@usgs.gov","orcid":"https://orcid.org/0000-0002-2949-7087","contributorId":2444,"corporation":false,"usgs":true,"family":"Grundel","given":"Ralph","email":"rgrundel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":940100,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70268059,"text":"cir1558 - 2025 - U.S. Geological Survey science strategy to address highly pathogenic avian influenza and its effects on wildlife health 2025–29","interactions":[],"lastModifiedDate":"2025-07-01T13:42:24.652181","indexId":"cir1558","displayToPublicDate":"2025-06-12T12:08:05","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1558","displayTitle":"U.S. Geological Survey Science Strategy to Address Highly Pathogenic Avian Influenza and Its Effects on Wildlife Health 2025–29","title":"U.S. Geological Survey science strategy to address highly pathogenic avian influenza and its effects on wildlife health 2025–29","docAbstract":"<h1>Executive Summary</h1><p>Highly pathogenic avian influenza (HPAI) is an ecologically and economically important animal disease that can also directly affect humans (a “zoonotic” disease). HPAI was once limited almost exclusively to domestic poultry but has rapidly adapted to diverse animal hosts. Viruses causing HPAI now appear to be maintained and dispersed by wild birds largely independent of poultry, though HPAI continues to cause considerable economic losses and supply chain disruptions in the domestic poultry trade. Coincident with the adaptation of HPAI viruses to wild birds, particularly waterfowl and gulls, increasingly diverse wild bird hosts are becoming exposed to HPAI, often resulting in disease and death. More sporadically, HPAI has caused mass mortality events, particularly among seabirds. Furthermore, viral spillover to wild and domestic mammals has become more common. Spillover to wild mammals has resulted in mortality among diverse terrestrial and marine taxa, including episodic losses of such scale as to represent potential conservation challenges. Since approximately March 2024, HPAI has also affected dairy cows, which represents a new threat to the agricultural economy. Lastly, HPAI has increasingly affected humans through domestic animal exposures, exemplifying the considerable implications of this disease beyond animal health.</p><p>Rapid changes in the ecology of HPAI are currently outpacing research efforts. For example, it is not entirely clear which newly established hosts may become reservoirs for HPAI viruses (in other words, capable of maintaining HPAI viruses within a broad population indefinitely) and how this may influence viral evolution and dissemination. As a result, there are considerable information gaps regarding HPAI in wildlife that, if filled, would improve the ability of scientists, managers, agricultural industry representatives, and healthcare professionals to understand and to anticipate the effects of HPAI on wild animal, domestic animal, environmental, and human health (“One Health”).</p><p>The U.S. Geological Survey (USGS) is the lead Federal agency providing scientific research on avian influenza viruses (AIVs), including HPAI viruses, that affect wildlife for which the Department of the Interior (DOI) has management authority. States have jurisdiction over wildlife on Federal lands within their borders (43 CFR § 24.3), so the USGS Ecosystems Mission Area (EMA) coordinates with State natural resource management agencies. The EMA focuses its research on HPAI through priorities identified by the USGS Avian Influenza Science Team (<span>app. 1</span>). Priorities identified by the USGS Avian Influenza Science Team are based on Administration priorities, Congressional direction, and discussions with State, Federal, and Tribal natural resource management agencies that identify specific scientific gaps that need to be filled to inform sound wildlife management decisions. Notable non-DOI Federal partners include the U.S. Department of Agriculture, the lead for the HPAI regulatory response in poultry and livestock, and the Centers for Disease Control and Prevention (CDC), the lead agency for the HPAI response pertaining to human health.</p><p>The USGS offers unique expertise and capacity pertaining to research on diseases affecting free-ranging wildlife populations. This expertise has been critical to interjurisdictional surveillance and capacity-building efforts, including programs administered by the U.S. Department of Agriculture and the CDC. The USGS also provides resources, guidance, and tools to inform surveillance and interventions conducted by natural resource management agencies. More specifically, the USGS EMA provides objective and rigorous scientific data for inferring (1) the utility of new methods to detect and characterize AIVs, including those maintained in wildlife and the environment; (2) effects of HPAI on wildlife; (3) spatiotemporal patterns of wildlife host and AIV dispersal; (4) the presence and persistence of AIVs in the environment; (5) how HPAI in wildlife influences consumptive and nonconsumptive utilization of wildlife; (6) how new tools and scientific methods may promote sound management decisions for HPAI-affected wildlife, particularly species of conservation concern; and (7) the combined effects of HPAI and other stressors on ecosystem health and resiliency.</p><p>This science strategy builds upon research outlined in a previous USGS science strategy for HPAI (2016–20) by <span>Harris and others (2016)</span>. This strategy also details research priorities identified by the Administration (for example, <span>U.S. Department of Agriculture, 2025</span>) and others based on USGS Avian Influenza Science Team discussions with natural resource management agencies to address HPAI and wildlife health over the next 5 years (2025–29). This strategy presents 7 goals and 26 objectives that focus USGS and partner efforts on priorities that will fill data gaps regarding the effects of HPAI on wildlife managed by or co-managed with the U.S. Department of the Interior such that agencies and partners might anticipate or limit adverse effects on public resources. This strategy also identifies research priorities intended to address HPAI in wildlife and wildlife habitat that are anticipated to support interjurisdictional One Health efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1558","usgsCitation":"Ramey, A.M., Prosser, D.J., Hubbard, L.E., Vazquez-Meves, G., George, A., and Hopkins, M.C., 2025, U.S. Geological Survey science strategy to address highly pathogenic avian influenza and its effects on wildlife health 2025–29:\nU.S. Geological Survey Circular 1558, 26 p., https://doi.org/10.3133/cir1558.","productDescription":"vi, 26 p.","onlineOnly":"Y","ipdsId":"IP-174779","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":490570,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161121","text":"Open-File Report 2016-1121","description":"OFR 2016-1121","linkHelpText":"- U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)"},{"id":490421,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/circ/1558/cir1558.XML"},{"id":490420,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1558/cir1558.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1558"},{"id":490419,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1558/coverthb.jpg"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/alaska-science-center\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/alaska-science-center\">Alaska Science Center</a><br>4210 University Drive<br>Anchorage, Alaska 99508</p>","tableOfContents":"<ul><li>Acknowledgements</li><li>Executive Summary</li><li>Introduction</li><li>Congressional Mandates</li><li>U.S. Department of Homeland Security’s Federal Emergency Management Agency National Response and Recovery Frameworks</li><li>USGS Avian Influenza Science Strategy</li><li>Goals and Objectives</li><li>Performance Review of the Science Strategy</li><li>Appendix 1. Names and Affiliations of USGS Avian Influenza Science Team Members</li><li>Appendix 2. USGS Publications on Avian Influenza</li></ul>","publishedDate":"2025-06-12","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":940085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":940086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hubbard, Laura E. 0000-0003-3813-1500 lhubbard@usgs.gov","orcid":"https://orcid.org/0000-0003-3813-1500","contributorId":4221,"corporation":false,"usgs":true,"family":"Hubbard","given":"Laura","email":"lhubbard@usgs.gov","middleInitial":"E.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vazquez-Meves, Guelaguetza 0000-0001-8100-2945","orcid":"https://orcid.org/0000-0001-8100-2945","contributorId":346127,"corporation":false,"usgs":true,"family":"Vazquez-Meves","given":"Guelaguetza","email":"","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":940088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"George, Amy 0000-0003-1150-8646 ageorge@usgs.gov","orcid":"https://orcid.org/0000-0003-1150-8646","contributorId":356793,"corporation":false,"usgs":false,"family":"George","given":"Amy","email":"ageorge@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":false,"id":940089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hopkins, M. Camille 0000-0003-1465-6038 mcharris@usgs.gov","orcid":"https://orcid.org/0000-0003-1465-6038","contributorId":175471,"corporation":false,"usgs":true,"family":"Hopkins","given":"M.","email":"mcharris@usgs.gov","middleInitial":"Camille","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":false,"id":940090,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70268122,"text":"70268122 - 2025 - Applying the resist-accept-direct (RAD) framework to wildlife health management","interactions":[],"lastModifiedDate":"2025-06-13T15:19:34.297776","indexId":"70268122","displayToPublicDate":"2025-06-12T10:11:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Applying the resist-accept-direct (RAD) framework to wildlife health management","docAbstract":"<p><span>Wildlife diseases can have substantial impacts on wildlife populations as well as on human and domestic animal health and well-being. Although many agencies and stakeholders share a goal of supporting wildlife health, reducing wildlife disease burden is complicated by a scarcity of effective interventions for wildlife, competition for funds, and conflicting priorities. As a result, agencies are unlikely to avoid the impacts of wildlife diseases in all contexts and need to evaluate where resisting disease is most feasible and beneficial. The resist–accept–direct (RAD) framework is a tool that assists natural resource managers in exploring and communicating about management interventions, including in situations where resisting ecological changes may not be possible. In the present article, we discuss how the RAD framework could be adapted to wildlife disease contexts to address several outstanding challenges in wildlife health management.</span></p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biaf061","usgsCitation":"Moss, W.E., Schuurman, G.W., Almberg, E.S., Buttke, D., Galloway, N.L., Gibbs, S., Hubbs, A., Richgels, K., White, C.L., and Cross, P., 2025, Applying the resist-accept-direct (RAD) framework to wildlife health management: BioScience, https://doi.org/10.1093/biosci/biaf061.","ipdsId":"IP-171833","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":490998,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biaf061","text":"Publisher Index Page"},{"id":490710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"Online First","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Moss, Wynne Emily 0000-0002-2813-1710","orcid":"https://orcid.org/0000-0002-2813-1710","contributorId":338331,"corporation":false,"usgs":true,"family":"Moss","given":"Wynne","email":"","middleInitial":"Emily","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":940275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schuurman, Gregor W. 0000-0002-9304-7742","orcid":"https://orcid.org/0000-0002-9304-7742","contributorId":147698,"corporation":false,"usgs":false,"family":"Schuurman","given":"Gregor","email":"","middleInitial":"W.","affiliations":[{"id":16909,"text":"U.S. National Park Service, Natural Resource Stewardship and Science, Fort Collins, CO, 80525, USA","active":true,"usgs":false}],"preferred":false,"id":940276,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Almberg, Emily S.","contributorId":198304,"corporation":false,"usgs":false,"family":"Almberg","given":"Emily","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":940277,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buttke, Danielle","contributorId":225082,"corporation":false,"usgs":false,"family":"Buttke","given":"Danielle","affiliations":[],"preferred":false,"id":940278,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galloway, Nathan L.","contributorId":276042,"corporation":false,"usgs":false,"family":"Galloway","given":"Nathan","email":"","middleInitial":"L.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":940279,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gibbs, Samantha E.J.","contributorId":127739,"corporation":false,"usgs":false,"family":"Gibbs","given":"Samantha E.J.","affiliations":[{"id":7128,"text":"Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA 01536, USA.","active":true,"usgs":false}],"preferred":false,"id":940280,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hubbs, Anne","contributorId":356856,"corporation":false,"usgs":false,"family":"Hubbs","given":"Anne","affiliations":[{"id":85260,"text":"Alberta Environment and Protected Areas","active":true,"usgs":false}],"preferred":false,"id":940281,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Richgels, Katherine 0000-0003-2834-9477 krichgels@usgs.gov","orcid":"https://orcid.org/0000-0003-2834-9477","contributorId":167016,"corporation":false,"usgs":true,"family":"Richgels","given":"Katherine","email":"krichgels@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":940282,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"White, C. LeAnn 0000-0002-5004-5165 clwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-5004-5165","contributorId":4315,"corporation":false,"usgs":true,"family":"White","given":"C.","email":"clwhite@usgs.gov","middleInitial":"LeAnn","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":940283,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cross, Paul C. 0000-0001-8045-5213","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":204814,"corporation":false,"usgs":true,"family":"Cross","given":"Paul C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":940284,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70268224,"text":"70268224 - 2025 - Hydraulic connectivity and hydrochemistry influence microbial community structure in agriculturally-affected alluvial aquifers in the Midwestern United States","interactions":[],"lastModifiedDate":"2025-07-10T14:55:33.936187","indexId":"70268224","displayToPublicDate":"2025-06-12T09:53:23","publicationYear":"2025","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":"Hydraulic connectivity and hydrochemistry influence microbial community structure in agriculturally-affected alluvial aquifers in the Midwestern United States","docAbstract":"<p><span>Alluvial aquifers can provide ecosystem services and drinking water, but much remains unknown about human effects on aquifer microbiomes. Therefore, we used amplicon sequencing and hydrochemical characterization to pair microbial communities with environmental conditions across 37 alluvial aquifer wells. The study region spanned eastern Iowa and southern Minnesota (USA) and contained a combination of drinking water and monitoring wells. In terms of microbial ecology, dominant phyla across the wells included Proteobacteria, Bacteroidota, Patescibacteria, Planctomycetota, and Nitrospirota. Tritium, an indicator of infiltration and surface water influence, was the highest correlated variable with the Shannon index (α-diversity) by the Spearman rank sum (ρ = 0.60) and one of only four significant environmental variables in the constrained correspondence analysis. We built random forest regression models to predict tritium concentrations from microbial family relative abundance (held-out testing coefficient of determination (</span><i>R</i><sup>2</sup><span>) = 0.77 and mean absolute percentage error = 7%) and interpreted the models with Shapley additive explanation values. The most important families for predicting tritium concentrations were&nbsp;</span><i>Nitrosopumilaceae</i><span>&nbsp;and&nbsp;</span><i>Methylomirabilaceae</i><span>. Upwelling methane could contribute to the unusual coupling of ammonia oxidation by&nbsp;</span><i>Nitrosopumilaceae</i><span>&nbsp;with simultaneous nitrite-dependent methane oxidation by&nbsp;</span><i>Methylomirabilaceae</i><span>. Taken together, we illuminate the relationship among hydrochemistry, hydraulic connectivity, and alluvial aquifer microbiomes.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.5c03155","usgsCitation":"Schroer, H., Markland, K.M., Ling, F., and Just, C.L., 2025, Hydraulic connectivity and hydrochemistry influence microbial community structure in agriculturally-affected alluvial aquifers in the Midwestern United States: Environmental Science and Technology, v. 59, no. 24, p. 12279-12291, https://doi.org/10.1021/acs.est.5c03155.","productDescription":"13 p.","startPage":"12279","endPage":"12291","ipdsId":"IP-169344","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":490912,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":490985,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.5c03155","text":"Publisher Index Page"}],"country":"United States","state":"Iowa, Minnesota","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.83164241356687,\n              40.76134763192243\n            ],\n            [\n              -91.10093521849011,\n              40.76936587633509\n            ],\n            [\n              -90.98444609847996,\n              41.11334070983898\n            ],\n            [\n              -91.07975626082516,\n              41.37610567914743\n            ],\n            [\n              -90.60321047132624,\n              41.542769354616865\n            ],\n            [\n              -90.25374320174629,\n              41.8669244399662\n            ],\n            [\n              -93.07065717548669,\n              43.93016784084011\n            ],\n            [\n              -93.73782127267788,\n              43.983536010475774\n            ],\n            [\n              -93.97079768432694,\n              42.314858946682534\n            ],\n            [\n              -93.85431056836552,\n              41.92210428808144\n            ],\n            [\n              -91.83164241356687,\n              40.76134763192243\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"59","issue":"24","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Schroer, Hunter","contributorId":356950,"corporation":false,"usgs":false,"family":"Schroer","given":"Hunter","affiliations":[{"id":85293,"text":"Civil, Architectural and Environmental Engineering, Missouri University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":940520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Markland, Kendra M. 0000-0002-0276-8684 kmarkland@usgs.gov","orcid":"https://orcid.org/0000-0002-0276-8684","contributorId":306212,"corporation":false,"usgs":true,"family":"Markland","given":"Kendra","email":"kmarkland@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":940521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ling, Fangqiong","contributorId":356951,"corporation":false,"usgs":false,"family":"Ling","given":"Fangqiong","affiliations":[{"id":85296,"text":"Department of Energy, Environmental, & Chemical Engineering, Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":940522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Just, Craig L.","contributorId":178037,"corporation":false,"usgs":false,"family":"Just","given":"Craig","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":940523,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70268380,"text":"70268380 - 2025 - Assimilation of reduced carbon triggers platinum alloy saturation in mafic and ultramafic magmas","interactions":[],"lastModifiedDate":"2025-08-04T15:53:27.169903","indexId":"70268380","displayToPublicDate":"2025-06-12T09:09:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Assimilation of reduced carbon triggers platinum alloy saturation in mafic and ultramafic magmas","docAbstract":"<p><span>It is generally observed that magmatic sulfide ores have higher ratios of Pd/Pt than the mantle-like values of their parental magmas. This discrepancy has defied simple explanation because the partitioning behavior of both elements between sulfide and silicate liquids is very similar. Assimilation of sulfur- and carbon-rich country rocks by mafic and ultramafic magmas is considered a critical, if not essential, step in the formation of magmatic base metal sulfide deposits. Although there is general consensus that the assimilation of external sulfur and carbon promotes sulfide saturation, the effect of carbon assimilation on the solubilities of platinum-group elements in natural S-bearing silicate melt has been overlooked. In this study, we investigate the variations of platinum and palladium solubilities during assimilation of graphite and methane through thermodynamic modeling, in comparison with data from an array of highly distinctive magmatic sulfide ore systems representing ages from Archean to Paleozoic, melt compositions from komatiite to basalt, and magmatic settings including lavas, hypabyssal intrusions, plutonic continental arc roots, and plutonic layered intrusions, namely: Raglan, Norilsk-Talnakh, Lac des Iles, and the J-M Reef of the Stillwater Complex. We model assimilation-fractional crystallization processes to estimate the reduction of oxygen fugacity (</span><span class=\"inline-formula no-formula-id\">⁠fO2⁠</span><span>) of the melt due to incorporation of graphite and methane. The simulations show that although Pd remains highly soluble during the progressive assimilation of reduced carbon, Pt solubility decreases significantly as the silicate melt becomes increasingly reduced. With less than 8</span><i>%</i><span>&nbsp;of sediment assimilation, Pt alloy may saturate and then deviate from sulfide-undersaturated silicate melts, concomitantly increasing the Pd/Pt value of the remaining melts of the Raglan and Norilsk-Talnakh systems. For the Lac des Iles and Stillwater systems, a higher extent of assimilation is needed to reach Pt saturation because of the relatively carbon-poor nature of the lower crustal rocks. The assimilation of methane volatiles is shown to be more effective than graphite assimilation, and it provides a pathway to Pt alloy fractionation in the absence of detectable amounts of bulk host-rock assimilation. High Pd/Pt values have been documented in many world-class magmatic sulfide deposits whose parental magmas have demonstrably experienced crustal contamination. Our model suggests that although anomalous Pd/Pt values may be explained by other mechanisms such as incongruent melting of preexisting sulfide or differences in the diffusivities of the metals within achieving equilibration, the assimilation of graphite or methane may play an important role in the global occurrence of magmatic sulfide ores with elevated Pd/Pt values.</span></p>","language":"English","publisher":"Society of Economic Geologists","doi":"10.5382/econgeo.5165","usgsCitation":"Li, Y., Smith, W.D., Jenkins, M., Yao, Z., and Mungall, J.E., 2025, Assimilation of reduced carbon triggers platinum alloy saturation in mafic and ultramafic magmas: Economic Geology, v. 120, no. 4, p. 1025-1036, https://doi.org/10.5382/econgeo.5165.","productDescription":"12 p.","startPage":"1025","endPage":"1036","ipdsId":"IP-151208","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":491179,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"120","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Ying Zhou","contributorId":357308,"corporation":false,"usgs":false,"family":"Li","given":"Ying Zhou","affiliations":[{"id":85402,"text":"Carleton University; Saskatchewan Geological Survey","active":true,"usgs":false}],"preferred":false,"id":941157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, William D.","contributorId":335361,"corporation":false,"usgs":false,"family":"Smith","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":941158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkins, Michael 0000-0002-4261-409X mjenkins@usgs.gov","orcid":"https://orcid.org/0000-0002-4261-409X","contributorId":172433,"corporation":false,"usgs":true,"family":"Jenkins","given":"Michael","email":"mjenkins@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":941159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yao, Zhuosen","contributorId":357309,"corporation":false,"usgs":false,"family":"Yao","given":"Zhuosen","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":941160,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mungall, James E. 0000-0001-9726-8545","orcid":"https://orcid.org/0000-0001-9726-8545","contributorId":269537,"corporation":false,"usgs":false,"family":"Mungall","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":941161,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70268974,"text":"70268974 - 2025 - A generalized deep learning model to detect and classify volcano seismicity","interactions":[],"lastModifiedDate":"2025-07-11T13:50:23.102749","indexId":"70268974","displayToPublicDate":"2025-06-12T08:44:58","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"A generalized deep learning model to detect and classify volcano seismicity","docAbstract":"<p><span>Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] (</span>10.1029/2024JB029194<span>) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network (</span><code>VOISS-Net</code><span>) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized&nbsp;</span><code>VOISS-Net</code><span>&nbsp;model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized&nbsp;</span><code>VOISS-Net</code><span>&nbsp;model to be applicable in both research and operational volcano monitoring settings.</span></p>","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol/rjss1878","usgsCitation":"Fee, D., Tan, D., Lyons, J.J., Sciotto, M., Cannata, A., Hotovec-Ellis, A.J., Girona, T., Wech, A., Roman, D., Haney, M.M., and De Angelis, S., 2025, A generalized deep learning model to detect and classify volcano seismicity: Volcanica, v. 8, no. 1, p. 305-323, https://doi.org/10.30909/vol/rjss1878.","productDescription":"19 p.","startPage":"305","endPage":"323","ipdsId":"IP-178152","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":492467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol/rjss1878","text":"Publisher Index Page"},{"id":492124,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":942772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tan, Darren 0000-0001-8210-6041","orcid":"https://orcid.org/0000-0001-8210-6041","contributorId":304978,"corporation":false,"usgs":false,"family":"Tan","given":"Darren","email":"","affiliations":[{"id":66199,"text":"Geophysical Institute and Alaska Volcano Observatory, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":942773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lyons, John J. 0000-0001-5409-1698 jlyons@usgs.gov","orcid":"https://orcid.org/0000-0001-5409-1698","contributorId":5394,"corporation":false,"usgs":true,"family":"Lyons","given":"John","email":"jlyons@usgs.gov","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":942774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sciotto, Mariangela","contributorId":357890,"corporation":false,"usgs":false,"family":"Sciotto","given":"Mariangela","affiliations":[{"id":85561,"text":"Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo – Sezione di Catania, Catania, Italy.","active":true,"usgs":false}],"preferred":false,"id":942775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cannata, Andrea","contributorId":236652,"corporation":false,"usgs":false,"family":"Cannata","given":"Andrea","email":"","affiliations":[{"id":47495,"text":"Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Universit`a Degli Studi di Catania, Catania, Italy","active":true,"usgs":false}],"preferred":false,"id":942776,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hotovec-Ellis, Alicia J. 0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":942777,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Girona, Tarsilo","contributorId":229679,"corporation":false,"usgs":false,"family":"Girona","given":"Tarsilo","email":"","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false},{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":true,"id":942778,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wech, Aaron awech@usgs.gov","contributorId":194832,"corporation":false,"usgs":true,"family":"Wech","given":"Aaron","email":"awech@usgs.gov","affiliations":[],"preferred":true,"id":942792,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Roman, Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":942779,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":942780,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"De Angelis, Silvio","contributorId":172953,"corporation":false,"usgs":false,"family":"De Angelis","given":"Silvio","affiliations":[{"id":27128,"text":"Univ. of Liverpool","active":true,"usgs":false}],"preferred":false,"id":942781,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70268112,"text":"70268112 - 2025 - Evaluating the influence of constructed subtidal reefs on marsh shoreline erosion, sediment deposition, and wave energy","interactions":[],"lastModifiedDate":"2025-06-13T15:47:27.571244","indexId":"70268112","displayToPublicDate":"2025-06-12T08:31:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the influence of constructed subtidal reefs on marsh shoreline erosion, sediment deposition, and wave energy","docAbstract":"<p><span>Salt marshes play a critical role in providing economic and ecological benefits but are susceptible to shoreline erosion. Natural and nature-based features (NNBF), such as breakwater reefs, are often used to reduce shoreline exposure to wave action and provide biogenic benefits. However, waves and water level are also responsible for the sediment supply necessary for marsh accretion, a critical component of marsh resilience to sea level rise. The goal of this study was to evaluate the effects of two subtidal breakwater reefs on wave energy, marsh shoreline erosion, and sediment deposition onto the marsh platform. As a restoration intervention, oyster shell and limestone gravel reefs were constructed within the nearshore zone of a high-energy shoreline where active shoreline erosion is causing marsh habitat loss. Although both sediment deposition and shoreline erosion were reduced after reef installation at all sites, the reefs demonstrated a statistically significant reduction in sediment deposition, whereas its effect on decreasing shoreline erosion was less pronounced. This variability in erosion reduction may be partly influenced by the physical dimensions of the reefs, affecting wave attenuation and leeward circulation. Wave measurements indicate that the reef reduced wave energy, particularly during south and southeast winds that could lead to the largest onshore waves. Given that these strong onshore winds are seasonal, extending the duration of data collection could provide deeper insights into the reef's influence on marsh shoreline erosion. This study is novel in that there are limited experimental or observational studies quantifying the wave reduction capacity and effects of subtidal reefs on marsh shoreline erosion and sediment dynamics. Studies such as these are critical to evaluate the capacity of subtidal reefs to protect marsh shorelines from erosion, but also to measure their impact on accretion processes necessary for the marsh to maintain elevation under future sea level rise.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s12237-025-01564-7","usgsCitation":"Smith, K., Pitchford, J.L., Sparks, E., Archer, M., Virden, M., Terrano, J.F., and Smith, C., 2025, Evaluating the influence of constructed subtidal reefs on marsh shoreline erosion, sediment deposition, and wave energy: Estuaries and Coasts, v. 48, 128, 19 p., https://doi.org/10.1007/s12237-025-01564-7.","productDescription":"128, 19 p.","ipdsId":"IP-166569","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":491001,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-025-01564-7","text":"Publisher Index Page"},{"id":490713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","otherGeospatial":"Grand Bay National Estuarine Research Reserve, Point Aux Chenes Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -88.45901043533199,\n              30.376549622657805\n            ],\n            [\n              -88.45901043533199,\n              30.326593096623256\n            ],\n            [\n              -88.40111942768058,\n              30.326593096623256\n            ],\n            [\n              -88.40111942768058,\n              30.376549622657805\n            ],\n            [\n              -88.45901043533199,\n              30.376549622657805\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2025-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Kathryn E.L. 0000-0002-7521-7875 kelsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-7521-7875","contributorId":173264,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn","email":"kelsmith@usgs.gov","middleInitial":"E.L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pitchford, Jonathan L.","contributorId":301251,"corporation":false,"usgs":false,"family":"Pitchford","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[{"id":52643,"text":"Grand Bay National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":940245,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sparks, Eric L.","contributorId":356848,"corporation":false,"usgs":false,"family":"Sparks","given":"Eric L.","affiliations":[{"id":85257,"text":"Mississippi-Alabama Sea Grant","active":true,"usgs":false}],"preferred":false,"id":940246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Archer, Michael J.","contributorId":356849,"corporation":false,"usgs":false,"family":"Archer","given":"Michael J.","affiliations":[{"id":52643,"text":"Grand Bay National Estuarine Research Reserve","active":true,"usgs":false}],"preferred":false,"id":940247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Virden, Matthew","contributorId":350892,"corporation":false,"usgs":false,"family":"Virden","given":"Matthew","affiliations":[{"id":83862,"text":"Mississippi State University, Mississippi","active":true,"usgs":false}],"preferred":false,"id":940248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Terrano, Joseph F. 0000-0003-3060-7682 jterrano@usgs.gov","orcid":"https://orcid.org/0000-0003-3060-7682","contributorId":173263,"corporation":false,"usgs":true,"family":"Terrano","given":"Joseph","email":"jterrano@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940249,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Christopher G. 0000-0002-8075-4763","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":218439,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940250,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70273217,"text":"70273217 - 2025 - Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast","interactions":[],"lastModifiedDate":"2025-12-22T15:27:13.439704","indexId":"70273217","displayToPublicDate":"2025-06-12T08:20:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast","docAbstract":"<p><span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span>We use the Third Uniform California Earthquake Rupture Forecast Epidemic Type Aftershock Sequence model, which is fully time-dependent in terms of including spatiotemporal clustering, to evaluate the effects of the Poisson assumption and declustering algorithms on statewide loss exceedance curves. The model is simulation based, meaning it produces synthetic catalogs that exhibit realistic behavior with respect to aftershocks and multi-fault earthquakes. A Poisson version of the model was constructed by randomizing event times, and the influence of two declustering algorithms was examined as well. We demonstrate that the probability of one-or-more loss exceedances (occurrence exceedance probability) is greater for the Poisson model because it has fewer seismically quiet time windows. The discrepancy between dollar loss estimates with a given exceedance probability is up to a factor of 32% but varies depending on the loss threshold (the x-axis value) and the forecast duration (we examined a range between 24 h and 50 years, with the discrepancy for the latter being negligible). We discuss how the one-or-more loss exceedance metric is questionable because it ignores all but the maximum loss experienced in each timeframe. An alternative metric based on total aggregate loss in each time window (aggregate exceedance probability) was therefore also examined, for which the Poisson model again implies higher risk at intermediate losses but lower risk at higher losses (because large, triggered events now contribute to total aggregate losses for the fully time-dependent model). We also argue that declustering is not a scientifically justifiable way to deal with full time dependence, in agreement with a chorus from other recent studies. It is difficult to draw generally applicable conclusions from our study, in part because application specific details will likely be important, but our results highlight how full time dependence can be reckoned with once authoritative forecast models are made available.</span></span></p>","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1177/87552930251340677","usgsCitation":"Field, E.H., Milner, K., and Porter, K.A., 2025, Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast: Earthquake Spectra, v. 41, no. 3, p. 1977-1997, https://doi.org/10.1177/87552930251340677.","productDescription":"21 p.","startPage":"1977","endPage":"1997","ipdsId":"IP-175972","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":497866,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70268461,"text":"70268461 - 2025 - Expanding national-scale wildlife disease surveillance systems with research networks","interactions":[],"lastModifiedDate":"2025-06-26T16:27:53.503661","indexId":"70268461","displayToPublicDate":"2025-06-11T11:17:40","publicationYear":"2025","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":"Expanding national-scale wildlife disease surveillance systems with research networks","docAbstract":"<p><span>Efficient learning about disease dynamics in free-ranging wildlife systems can benefit from active surveillance that is standardized across different ecological contexts. For example, active surveillance that targets specific individuals and populations with standardized sampling across ecological contexts (landscape-scale targeted surveillance) is important for developing a mechanistic understanding of disease emergence, which is the foundation for improving risk assessment of zoonotic or wildlife-livestock disease outbreaks and predicting hotspots of disease emergence. However, landscape-scale targeted surveillance systems are rare and challenging to implement. Increasing experience and infrastructure for landscape-scale targeted surveillance will improve readiness for rapid deployment of this type of surveillance in response to new disease emergence events. Here, we describe our experience developing and rapidly deploying a landscape-scale targeted surveillance system for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in two free-ranging deer species across their ranges in the United States. Our surveillance system was designed to collect data across individual, population, and landscape scales for future analyses aimed at understanding mechanisms and risk factors of SARS-CoV-2 transmission, evolution, and persistence. Our approach leveraged partnerships between state and federal public service sectors and academic researchers in a landscape-scale targeted surveillance research network. Methods describe our approach to developing the surveillance network and sampling design. Results report challenges with implementing our intended sampling design, specifically how the design was adapted as different challenges arose and summarize the sampling design that has been implemented thus far. In the discussion, we describe strategies that were important for the successful deployment of landscape-scale targeted surveillance, development and operation of the research network, construction of similar networks in the future, and analytical approaches for the data based on the sampling design.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71492","usgsCitation":"Pepin, K.M., Combs, M., Bastille-Rousseau, G., Craft, M., Cross, P., Diuk-Wasser, M., Gagne, R., Gallo, T., Garwood, T., Heale, J., Hewitt, J., Hoy-Petersen, J., Malmberg, J., Mullinax, J.M., Plimpton, L., Smith, L., VanAcker, M., Chandler, J., Walter, W., WIlson-Henjum, G., Wittemyer, G., and Manlove, K.R., 2025, Expanding national-scale wildlife disease surveillance systems with research networks: Ecology and Evolution, v. 15, no. 6, e71492, 21 p., https://doi.org/10.1002/ece3.71492.","productDescription":"e71492, 21 p.","ipdsId":"IP-167320","costCenters":[{"id":199,"text":"Coop Res Unit 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