{"pageNumber":"34","pageRowStart":"825","pageSize":"25","recordCount":46619,"records":[{"id":70266002,"text":"70266002 - 2025 - Complex staged emplacement of a basaltic lava: The example of the July 1974 flow of Kīlauea","interactions":[],"lastModifiedDate":"2025-04-23T14:27:13.610544","indexId":"70266002","displayToPublicDate":"2025-03-31T09:21:18","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1109,"text":"Bulletin of Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Complex staged emplacement of a basaltic lava: The example of the July 1974 flow of Kīlauea","docAbstract":"<p><span>Basaltic lava flows can be highly destructive. Forecasting the future path and/or behavior of an active lava flow is challenging because topography is often poorly constrained and lava has a complex rheology and emplacement history. Preserved lavas are an important source of information which, combined with observations of active flows, underpins conceptual models of lava flow emplacement. However, the value of preserved lavas is limited because pre-eruptive topography and, thus, syn-eruptive lava flow geometry are usually not known. Here, we use tree-mold data to constrain pre-eruptive topography and syn-eruptive lava flow geometry of the July 1974 flow of Kīlauea (USA). Tree molds, which are formed after advancing lava encloses standing trees, preserve the lava inundation height and the final preserved thickness of lava. We used data from 282 tree molds to reconstruct the temporal and spatial evolution of the ~ 2.1&nbsp;km-long July 1974 flow. The tree mold dataset yields a detailed dynamic picture of staged emplacement, separated by intervals of ponding. In some ponded areas, flow depth during emplacement (~ 5&nbsp;m) was twice the preserved thickness of the final lava (2–3&nbsp;m). Drainage of the ponds led to episodic surges in flow advancement, decoupled from fluctuations in vent discharge rate. We infer that the final breakout occurred after the cessation of fountaining. Such complex emplacement histories may be common for pāhoehoe lavas at Kīlauea and elsewhere in situations where the terrain is of variable slope, and/or where lava is temporarily perched and stored.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00445-025-01817-0","usgsCitation":"Biass, S., Houghton, B.F., Llewellin, E.W., Curran, K., Thordarson, T., Orr, T., Parcheta, C., and Mouginis-Mark, P.J., 2025, Complex staged emplacement of a basaltic lava: The example of the July 1974 flow of Kīlauea: Bulletin of Volcanology, v. 87, 30, 14 p., https://doi.org/10.1007/s00445-025-01817-0.","productDescription":"30, 14 p.","ipdsId":"IP-106014","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488501,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00445-025-01817-0","text":"Publisher Index Page"},{"id":484914,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilaueau volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.28799286883776,\n              19.435261686847895\n            ],\n            [\n              -155.28799286883776,\n              19.272560860056274\n            ],\n            [\n              -155.1179644435753,\n              19.272560860056274\n            ],\n            [\n              -155.1179644435753,\n              19.435261686847895\n            ],\n            [\n              -155.28799286883776,\n              19.435261686847895\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"87","noUsgsAuthors":false,"publicationDate":"2025-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Biass, Sebastian","contributorId":353667,"corporation":false,"usgs":false,"family":"Biass","given":"Sebastian","affiliations":[{"id":84453,"text":"University of Geneva, Geneva, Switzerland","active":true,"usgs":false}],"preferred":false,"id":934281,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houghton, Bruce F. 0000-0002-7532-9770","orcid":"https://orcid.org/0000-0002-7532-9770","contributorId":140077,"corporation":false,"usgs":false,"family":"Houghton","given":"Bruce","email":"","middleInitial":"F.","affiliations":[{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false},{"id":13351,"text":"University of Hawaii Cooperative Studies Unit","active":true,"usgs":false}],"preferred":false,"id":934282,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Llewellin, Edward W.","contributorId":353668,"corporation":false,"usgs":false,"family":"Llewellin","given":"Edward","middleInitial":"W.","affiliations":[{"id":25252,"text":"Durham University","active":true,"usgs":false}],"preferred":false,"id":934283,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Curran, Kristine C","contributorId":353669,"corporation":false,"usgs":false,"family":"Curran","given":"Kristine C","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":934284,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thordarson, Thorvaldur","contributorId":197925,"corporation":false,"usgs":false,"family":"Thordarson","given":"Thorvaldur","email":"","affiliations":[{"id":35089,"text":"Institute of Earth Sciences, Nordvulk, University of Iceland","active":true,"usgs":false}],"preferred":false,"id":934285,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orr, Tim R. 0000-0003-1157-7588","orcid":"https://orcid.org/0000-0003-1157-7588","contributorId":26365,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":true,"id":934286,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Parcheta, Carolyn 0000-0001-6556-4630 cparcheta@usgs.gov","orcid":"https://orcid.org/0000-0001-6556-4630","contributorId":215617,"corporation":false,"usgs":true,"family":"Parcheta","given":"Carolyn","email":"cparcheta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":934287,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mouginis-Mark, Peter J. 0000-0002-7173-6141","orcid":"https://orcid.org/0000-0002-7173-6141","contributorId":36793,"corporation":false,"usgs":false,"family":"Mouginis-Mark","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":934288,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70266021,"text":"70266021 - 2025 - The GorDAS Distributed Acoustic Sensing experiment above the Cascadia locked zone and subducted Gorda Slab","interactions":[],"lastModifiedDate":"2025-07-09T15:59:50.150051","indexId":"70266021","displayToPublicDate":"2025-03-31T09:00:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"The GorDAS Distributed Acoustic Sensing experiment above the Cascadia locked zone and subducted Gorda Slab","docAbstract":"<p>The southernmost portion of the Cascadia Subduction zone in Northern California produces high rates of moderate and large earthquakes owing to subduction of the Gorda slab and deformation associated with the Mendocino Triple Junction. Distributed Acoustic Sensing (DAS) is rapidly advancing as a method for detecting earthquakes and imaging crustal structure. We have begun a long-term DAS monitoring experiment on buried telecom fiber in Arcata, California, with the goal of increasing the available recordings of moderate to large earthquakes as well as imaging seismogenic structures. We have recorded over a year's worth of data, including most aftershocks of the 2022 <i>M<sub>w</sub></i>6.4 Ferndale earthquake, though not the mainshock itself. The dataset includes numerous magnitude 3.5 and larger earthquakes including the 2023/01/01 <i>M<sub>w</sub></i>5.4 Rio Dell earthquake. Here we present initial results comparing an earthquake detection algorithm, run in real-time on the processing unit of the interrogator system, with both the ShakeAlert earthquake early warning system as well as a post-processed earthquake catalog developed with deep-learning phase-picker algorithms. The rapid onboard processing of the detector demonstrates the potential utility of DAS-based edge computing for earthquake early warning. We also verify the quality of the strain waveforms both in terms of peak amplitudes and waveform similarity using about five months of nodal seismometer data. These instruments were deployed roughly every 300 m along the ~15km long cable and validate large variations in peak strain over short distances that are seen in the DAS data. All data from time windows surrounding both the local and teleseismic earthquakes are publicly available, which will improve our understanding of both the performance of DAS systems in moderate earthquakes and earthquake hazards associated with the Gorda subduction zone.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220240415","usgsCitation":"McGuire, J., Barbour, A.J., Stewart, C., Yartsev, V., Karrenbach, M., Hemphill-Haley, M., McPherson, R.C., Stockdale, K., Yoon, C., and Sawi, T., 2025, The GorDAS Distributed Acoustic Sensing experiment above the Cascadia locked zone and subducted Gorda Slab: Seismological Research Letters, v. 96, no. 4, p. 2489-2503, https://doi.org/10.1785/0220240415.","productDescription":"15 p.","startPage":"2489","endPage":"2503","ipdsId":"IP-171005","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":484911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cascadia locked zone, Gorda slab","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -126,\n              42\n            ],\n            [\n              -126,\n              39.5\n            ],\n            [\n              -122,\n              39.5\n            ],\n            [\n              -122,\n              42\n            ],\n            [\n              -126,\n              42\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"96","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":934338,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbour, Andrew J. 0000-0002-6890-2452","orcid":"https://orcid.org/0000-0002-6890-2452","contributorId":215339,"corporation":false,"usgs":true,"family":"Barbour","given":"Andrew","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":934339,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stewart, Connie","contributorId":222103,"corporation":false,"usgs":false,"family":"Stewart","given":"Connie","email":"","affiliations":[{"id":18889,"text":"University of New Brunswick","active":true,"usgs":false}],"preferred":false,"id":934340,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yartsev, Victor","contributorId":350345,"corporation":false,"usgs":false,"family":"Yartsev","given":"Victor","affiliations":[{"id":83720,"text":"Luna, Inc","active":true,"usgs":false}],"preferred":false,"id":934341,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karrenbach, Martin","contributorId":353682,"corporation":false,"usgs":false,"family":"Karrenbach","given":"Martin","affiliations":[{"id":84462,"text":"Seismics Unuusal","active":true,"usgs":false}],"preferred":false,"id":934342,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hemphill-Haley, Mark","contributorId":295931,"corporation":false,"usgs":false,"family":"Hemphill-Haley","given":"Mark","affiliations":[{"id":63943,"text":"Cal Poly Humboldt","active":true,"usgs":false}],"preferred":false,"id":934343,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McPherson, Robert C.","contributorId":350346,"corporation":false,"usgs":false,"family":"McPherson","given":"Robert","middleInitial":"C.","affiliations":[{"id":83721,"text":"Cal Poly Humboldt Univ.","active":true,"usgs":false}],"preferred":false,"id":934344,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stockdale, Kari","contributorId":352201,"corporation":false,"usgs":false,"family":"Stockdale","given":"Kari","affiliations":[{"id":39079,"text":"NYSDEC","active":true,"usgs":false}],"preferred":false,"id":934345,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yoon, Clara 0000-0003-4521-3889","orcid":"https://orcid.org/0000-0003-4521-3889","contributorId":222019,"corporation":false,"usgs":true,"family":"Yoon","given":"Clara","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":934346,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sawi, Theresa Marie 0000-0001-5938-6743","orcid":"https://orcid.org/0000-0001-5938-6743","contributorId":350347,"corporation":false,"usgs":true,"family":"Sawi","given":"Theresa Marie","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":934347,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70265069,"text":"70265069 - 2025 - Assessment of western Oregon debris-flow hazards in burned and unburned environments","interactions":[],"lastModifiedDate":"2025-04-01T15:02:09.946731","indexId":"70265069","displayToPublicDate":"2025-03-30T07:56:10","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":"Assessment of western Oregon debris-flow hazards in burned and unburned environments","docAbstract":"<p><span>In the steep and mountainous environment of western Oregon, debris flows pose a considerable threat to property, infrastructure and life. Wildfire is commonly known to increase the susceptibility of steep slopes to debris flows, but the extent of this process in the western Cascades is not well understood. The US Geological Survey (USGS) currently estimates postfire debris-flow likelihood and triggering rainfall thresholds using a model calibrated to a southern California inventory of debris flows generated by excess runoff within the first year after fire. Because of a lack of available data, this model has not been tested in western Oregon, or in locations where postfire debris flows initiate via other mechanisms (e.g., shallow landslides or in-channel failures). Using repeat field observations and aerial imagery, we developed two new debris-flow inventories within and adjacent to the perimeters of five 2020 wildfires in western Oregon: Archie Creek, Holiday Farm, Beachie Creek, Lionshead and Riverside. The first inventory focuses on postfire debris flows (2020–2022); the second focuses on debris flows prior to fires (1995–2020). Our inventories of prefire and postfire debris flows were used to document initiation mechanisms in Oregon's western Cascades and to evaluate the effects of wildfire. We found that wildfire changed the distribution of debris-flow initiation mechanisms in the western Cascades. After the wildfires, annual rates of runoff-generated debris flows increased by 22% and the number of shallow landslide-initiated debris flows decreased by 17% relative to before the wildfires. Despite this shift, shallow landsliding was the dominant debris-flow initiation mechanism in both unburned and burned environments. We found the performance of the current USGS debris-flow likelihood model was degraded relative to other previously tested locations across the intermountain western United States. Our results highlight the need for improved postfire hazard assessment in western Oregon based on regional model calibration that is tuned to the dominant debris-flow initiation mechanisms.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ESP.70045","usgsCitation":"Selander, B., Calhoun, N.C., Burns, W., Kean, J.W., and Rengers, F.K., 2025, Assessment of western Oregon debris-flow hazards in burned and unburned environments: Earth Surface Processes and Landforms, v. 50, no. 4, e70045, 15 p., https://doi.org/10.1002/ESP.70045.","productDescription":"e70045, 15 p.","ipdsId":"IP-170327","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":488659,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.70045","text":"Publisher Index Page"},{"id":484065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"western Oregon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.57278320768603,\n              46.34148488781506\n            ],\n            [\n              -124.57278320768603,\n              42.016342483468776\n            ],\n            [\n              -121.87720015148463,\n              42.016342483468776\n            ],\n            [\n              -121.87720015148463,\n              46.34148488781506\n            ],\n            [\n              -124.57278320768603,\n              46.34148488781506\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"50","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Selander, Brittany Danielle 0000-0002-3332-1068","orcid":"https://orcid.org/0000-0002-3332-1068","contributorId":344520,"corporation":false,"usgs":true,"family":"Selander","given":"Brittany Danielle","affiliations":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"preferred":true,"id":932462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Calhoun, Nancy C.","contributorId":216331,"corporation":false,"usgs":false,"family":"Calhoun","given":"Nancy","email":"","middleInitial":"C.","affiliations":[{"id":39395,"text":"DOGAMI","active":true,"usgs":false}],"preferred":false,"id":932463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, William 0000-0002-4379-6198","orcid":"https://orcid.org/0000-0002-4379-6198","contributorId":344522,"corporation":false,"usgs":false,"family":"Burns","given":"William","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":932464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932465,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rengers, Francis K. 0000-0002-1825-0943 frengers@usgs.gov","orcid":"https://orcid.org/0000-0002-1825-0943","contributorId":150422,"corporation":false,"usgs":true,"family":"Rengers","given":"Francis","email":"frengers@usgs.gov","middleInitial":"K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":932466,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70267348,"text":"70267348 - 2025 - Do watershed conditions or local climate play a larger role in determining regional stream salamander distributions?","interactions":[],"lastModifiedDate":"2025-09-09T14:37:07.042308","indexId":"70267348","displayToPublicDate":"2025-03-28T10:34:43","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"Do watershed conditions or local climate play a larger role in determining regional stream salamander distributions?","docAbstract":"<p><span>Anthropogenic influences like land use and climate variability interact with natural heterogeneity to influence the persistence of stream salamanders. Using occupancy modeling in the southern Appalachian Mountains, we investigated the influence of land use, climate, and physical context (e.g., drainage area, elevation) on stream salamander occupancy, noting species, and life stage specific responses. Our results illustrate that forest loss is a better predictor of salamander occupancy than physical context (elevation) or climate. Across the gradients in this dataset, precipitation did not have a significant influence on salamander occupancy, potentially due to the observed narrow, wet gradient. Temperature had little effect on&nbsp;</span><i>Eurycea wilderae</i><span>&nbsp;occupancy; however, temperature negatively affected adult but not larval&nbsp;</span><i>Desmognathus amphileucus</i><span>&nbsp;occupancy</span><i>.</i><span>&nbsp;Spatial thermal variability in this study was larger than projected increases due to climate change, suggesting that local mechanisms (e.g., behavior or physiological plasticity) may facilitate salamander resilience to climate change. However, the negative effects of forest loss coupled with rising temperatures (e.g., increased solar radiation, warmer stream runoff) underscore the importance of riparian forests in mitigating climate stressors. Preserving forest cover is critical for maintaining stream salamander populations and may offer opportunities for maintaining resilience in the face of additional stressors like rising temperatures or drought.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10750-025-05848-8","collaboration":"USFWS","usgsCitation":"Cecala, K.K., Halstead, B., McGrory, J., and Maerz, J.C., 2025, Do watershed conditions or local climate play a larger role in determining regional stream salamander distributions?: Hydrobiologia, v. 852, p. 4053-4067, https://doi.org/10.1007/s10750-025-05848-8.","productDescription":"15 p.","startPage":"4053","endPage":"4067","ipdsId":"IP-114382","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":486222,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, North Carolina","otherGeospatial":"Upper Little Tennessee watersheds","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -84.2386909895219,\n              35.52532859216157\n            ],\n            [\n              -84.25914633148402,\n              34.38251830455587\n            ],\n            [\n              -82.90909376196274,\n              34.37126510334987\n            ],\n            [\n              -82.90909376196274,\n              35.52532859216157\n            ],\n            [\n              -84.2386909895219,\n              35.52532859216157\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"852","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Cecala, Kristen K.","contributorId":171762,"corporation":false,"usgs":false,"family":"Cecala","given":"Kristen","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":937824,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":937825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGrory, James S.","contributorId":355637,"corporation":false,"usgs":false,"family":"McGrory","given":"James S.","affiliations":[{"id":84785,"text":"University of the South","active":true,"usgs":false}],"preferred":false,"id":937826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maerz, John C.","contributorId":341635,"corporation":false,"usgs":false,"family":"Maerz","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":937827,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70265930,"text":"70265930 - 2025 - A crustal thermal model of the conterminous U.S. constrained by multiple data sets: A Monte-Carlo approach","interactions":[],"lastModifiedDate":"2025-04-22T15:33:21.230287","indexId":"70265930","displayToPublicDate":"2025-03-28T10:31:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"A crustal thermal model of the conterminous U.S. constrained by multiple data sets: A Monte-Carlo approach","docAbstract":"<p><span>The thermal structure of the continental crust plays a critical role in understanding its elastic and rheologic properties as well as its dynamic processes. Thermal parameter data sets on continental scales have been used to constrain the crustal thermal structure, including both the direct (e.g. temperature, heat flux and heat conductivity measured at the surface) and indirect (e.g. seismically derived Mohorovičić discontinuity (Moho) temperature, geomagnetically derived Curie depth) observations. In this study, we present a new continental scale crustal heat generation model with additional information from seismologically inferred crustal composition. Together with previous direct and indirect thermal parameter data sets in the conterminous United States, we use the new crustal heat generation model to construct a 3-D crustal temperature model under a newly developed Bayesian framework. Specifically, we first derive profiles of crustal heat generation based on an empirical geochemical relationship at 1683 locations where seismologically derived crustal composition information is available. Then for each of these locations, the average heat generation values in the upper, middle and lower crust are combined with other thermal parameters through a Markov Chain Monte-Carlo inversion for a conductive, vertically smooth temperature profile. The results, posterior distributions of temperature profiles, are used to generate a 3-D crustal thermal model with the uncertainties systematically assessed. The new temperature model overall exhibits similar patterns to that from the U.S. Geological Survey National Crustal Model, but also reduces possible biases and the model's dependence on a single thermal parameter.</span></p>","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggaf118","usgsCitation":"Sui, S., Shen, W., and Boyd, O.S., 2025, A crustal thermal model of the conterminous U.S. constrained by multiple data sets: A Monte-Carlo approach: Geophysical Journal International, v. 241, no. 3, p. 1711-1724, https://doi.org/10.1093/gji/ggaf118.","productDescription":"14 p.","startPage":"1711","endPage":"1724","ipdsId":"IP-173069","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":488479,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggaf118","text":"Publisher Index 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]\n}","volume":"241","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Sui, Siyuan","contributorId":353596,"corporation":false,"usgs":false,"family":"Sui","given":"Siyuan","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":934053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shen, Weisen","contributorId":353597,"corporation":false,"usgs":false,"family":"Shen","given":"Weisen","affiliations":[{"id":36488,"text":"Stony Brook University","active":true,"usgs":false}],"preferred":false,"id":934054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":934055,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70268306,"text":"70268306 - 2025 - Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach","interactions":[],"lastModifiedDate":"2025-06-20T15:18:04.082324","indexId":"70268306","displayToPublicDate":"2025-03-28T10:11:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><div id=\"abspara0010\" class=\"u-margin-s-bottom\">Robust and reliable models are needed to understand how coastlines will evolve over the coming decades, driven by both natural variability and climate change. This study evaluated how accurately five popular ‘reduced-complexity’ models replicate multi-decadal shoreline change at Narrabeen-Collaroy Beach, a sandy embayment in Sydney, Australia. Measured shoreline positions derived from approximately monthly field surveys were used for 20-year calibration and 20-year validation periods. The models performed similarly on average but with large variability between transects. The set-up of several models was modified to compensate for their sensitivity to imperfect input wave data, and further site-specific improvements were identified. Capturing interannual to decadal-scale variability in cross-shore and longshore dynamics at this site was challenging for all five models. Models appeared to aggregate key processes at this timescale into parameter values rather than representing them directly. This suggests time-varying parameters or changes to model structure may be necessary for decadal-scale simulations.</div></div></div></div><ul id=\"issue-navigation\" class=\"issue-navigation u-margin-s-bottom u-bg-grey1\"></ul>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2025.104738","usgsCitation":"Repina, O., Carvalho, R., Coco, G., Antolínez, J., de Santiago, I., Harley, M., Jaramillo, C., Splinter, K., Vitousek, S., and Woodroffe, C., 2025, Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach: Coastal Engineering, v. 199, 104738, 24 p., https://doi.org/10.1016/j.coastaleng.2025.104738.","productDescription":"104738, 24 p.","ipdsId":"IP-175917","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":498029,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2025.104738","text":"Publisher Index Page"},{"id":491029,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"199","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Repina, Oxana","contributorId":357144,"corporation":false,"usgs":false,"family":"Repina","given":"Oxana","affiliations":[{"id":37474,"text":"University of Wollongong","active":true,"usgs":false}],"preferred":false,"id":940758,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carvalho, Rafael C.","contributorId":357146,"corporation":false,"usgs":false,"family":"Carvalho","given":"Rafael C.","affiliations":[{"id":85339,"text":"University of Wollongong, University of Newcastle","active":true,"usgs":false}],"preferred":false,"id":940759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coco, Giovanni","contributorId":357148,"corporation":false,"usgs":false,"family":"Coco","given":"Giovanni","affiliations":[{"id":38833,"text":"University of Auckland","active":true,"usgs":false}],"preferred":false,"id":940760,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Antolínez, Jose","contributorId":357149,"corporation":false,"usgs":false,"family":"Antolínez","given":"Jose","affiliations":[{"id":17614,"text":"Delft University of Technology","active":true,"usgs":false}],"preferred":false,"id":940761,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"de Santiago, Iñaki","contributorId":357150,"corporation":false,"usgs":false,"family":"de Santiago","given":"Iñaki","affiliations":[{"id":85342,"text":"AZTI Marine Research","active":true,"usgs":false}],"preferred":false,"id":940762,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Harley, Mitchell D.","contributorId":357151,"corporation":false,"usgs":false,"family":"Harley","given":"Mitchell D.","affiliations":[{"id":80179,"text":"UNSW Sydney","active":true,"usgs":false}],"preferred":false,"id":940763,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jaramillo, Camilo","contributorId":357152,"corporation":false,"usgs":false,"family":"Jaramillo","given":"Camilo","affiliations":[{"id":41638,"text":"University of Cantabria","active":true,"usgs":false}],"preferred":false,"id":940764,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Splinter, Kristen D.","contributorId":357153,"corporation":false,"usgs":false,"family":"Splinter","given":"Kristen D.","affiliations":[{"id":80179,"text":"UNSW Sydney","active":true,"usgs":false}],"preferred":false,"id":940765,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940766,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Woodroffe, Colin D.","contributorId":357154,"corporation":false,"usgs":false,"family":"Woodroffe","given":"Colin D.","affiliations":[{"id":37474,"text":"University of Wollongong","active":true,"usgs":false}],"preferred":false,"id":940767,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70267431,"text":"70267431 - 2025 - Estuarine tidal cycles may preserve thermal refugia as global temperatures increase","interactions":[],"lastModifiedDate":"2025-05-23T16:24:15.426836","indexId":"70267431","displayToPublicDate":"2025-03-28T09:15:04","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":"Estuarine tidal cycles may preserve thermal refugia as global temperatures increase","docAbstract":"<p><span>Climate change is affecting coastal ecosystems worldwide as water temperatures increase, hydrologic regimes change, and sea levels rise. Consequently, estuaries risk declines in ecosystem functioning due to increasing temperatures and other hydrologic factors. Characterizing and predicting estuarine water temperature are challenging because these systems are highly dynamic. Statistical models have been used to accurately assess air temperature-water temperature relationships in lakes and streams but have not been effectively applied to tidally influenced ecosystems like estuaries. We used 6&nbsp;years of continuous monitoring data from the Nisqually River Delta in Puget Sound, Washington, U.S.A., to parameterize and run a non-linear statistical model and generate spatially explicit model predictions. Our goal was to examine spatiotemporal patterns in estuarine water temperature and thermal refugia given current estimates of climactic change. The performance of the parameterized model was similar to that of non-linear stream temperature models (NSE = 0.76; RMSE = 2.34&nbsp;°C). Scenarios incorporating forecasted high-emission air temperatures through the year 2100 (+ 7&nbsp;°C) predicted a corresponding 3.55 ± 0.63&nbsp;°C increase in average water temperatures; however, moderate and high rates of sea-level rise offset temperature increases by 3–20% and substantially reduced the amount of time temperatures exceeded the thermal stress threshold of 20&nbsp;°C for juvenile salmon. These findings demonstrate how the effects of one climate stressor (sea-level rise) may offset another (temperature increases) to maintain thermal refugia for coldwater fishes. Similar exercises may allow managers to explore mitigation options like the planting of riparian vegetation or modified flooding regimes to further offset rising water temperatures.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1007/s12237-025-01510-7","usgsCitation":"Davis, M.J., Woo, I., and De La Cruz, S.E., 2025, Estuarine tidal cycles may preserve thermal refugia as global temperatures increase: Estuaries and Coasts, v. 48, 90, 19 p., https://doi.org/10.1007/s12237-025-01510-7.","productDescription":"90, 19 p.","ipdsId":"IP-129413","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":486525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta, Puget Sound, Salish Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.55330830655157,\n              48.98716401827198\n            ],\n            [\n              -123.55330830655157,\n              47.20224465518157\n            ],\n            [\n              -121.87955279406418,\n              47.20224465518157\n            ],\n            [\n              -121.87955279406418,\n              48.98716401827198\n            ],\n            [\n              -123.55330830655157,\n              48.98716401827198\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"48","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Davis, Melanie J. 0000-0003-1734-7177","orcid":"https://orcid.org/0000-0003-1734-7177","contributorId":202773,"corporation":false,"usgs":true,"family":"Davis","given":"Melanie","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":938184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Woo, Isa 0000-0002-8447-9236 iwoo@usgs.gov","orcid":"https://orcid.org/0000-0002-8447-9236","contributorId":2524,"corporation":false,"usgs":true,"family":"Woo","given":"Isa","email":"iwoo@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":938185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De La Cruz, Susan E.W. 0000-0001-6315-0864","orcid":"https://orcid.org/0000-0001-6315-0864","contributorId":202774,"corporation":false,"usgs":true,"family":"De La Cruz","given":"Susan","email":"","middleInitial":"E.W.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":938186,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70268307,"text":"70268307 - 2025 - Wave driven cross shore and alongshore transport reveal more extreme projections of shoreline change in island environments","interactions":[],"lastModifiedDate":"2025-06-20T14:02:06.25149","indexId":"70268307","displayToPublicDate":"2025-03-28T08:57:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Wave driven cross shore and alongshore transport reveal more extreme projections of shoreline change in island environments","docAbstract":"<p><span>Coastal erosion, intensified by sea level rise, poses significant threats to coastal communities in Hawaiʻi and similar island communities. This study projects long-term shoreline change on the Hawaiian Island of O‘ahu using the data-assimilated CoSMoS-COAST shoreline change model. CoSMoS-COAST models four key shoreline processes: (1) Alongshore transport, (2) Recession due to sea level rise, (3) Cross-shore transport due to waves, and (4) Residual processes represented by a linear trend term. This study marks the first application of CoSMoS-COAST for an oceanic equatorial island with narrow beaches and a dynamic wave climate. The model is informed with a novel combination of shoreline data derived from high-resolution imagery from Planet, Sentinel-2, and Landsat satellites, wave-climate hindcasts specific to Hawai‘i, and regional beach-slope surveys. On a dynamic northern Oʻahu beach, the model achieved a root mean square error of 9.4&nbsp;m between observations and model output. CoSMoS-COAST predicts that 81% of O‘ahu’s sandy beach coastline could experience beach loss by 2100; with 39.8% of this loss happening by 2030. This represents an increase, 43.3%, in net landward shoreline change compared to previous erosion forecasts, for 0.3&nbsp;m of sea level rise (2050). Additionally, dynamic processes such as cross-shore equilibrium processes and alongshore sediment transport, play a large contribution to gross shoreline change within the next decade, particularly on O ‘ahu’s north and west shores. In the long term, we find that recession due to sea level rise and residual processes dominate, but dynamic, wave-driven processes (longshore and cross-shore transport) still account for 34% of shoreline change between present and 2100. We assert dynamic, wave-driven processes are a crucial addition for accurate modeling of island sandy beach environments. These findings have implications for O‘ahu’s coastal planning and development, suggesting updates to shoreline policies that rely upon erosion forecasting, and highlights the importance of incorporating wave and alongshore transport in erosion models for other Pacific islands.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/s41598-025-95074-y","usgsCitation":"Moskvichev, R., Mikkelsen, A., Anderson, T., Vitousek, S., Joel Nicolow, and Fletcher, C., 2025, Wave driven cross shore and alongshore transport reveal more extreme projections of shoreline change in island environments: Scientific Reports, v. 15, 10794, 23 p., https://doi.org/10.1038/s41598-025-95074-y.","productDescription":"10794, 23 p.","ipdsId":"IP-176072","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":491490,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-025-95074-y","text":"Publisher Index Page"},{"id":491019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"O'ahu","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -157.97415529522343,\n              21.740805505081653\n            ],\n            [\n              -158.15139260242358,\n              21.600579083024826\n            ],\n            [\n              -158.2903083296884,\n              21.599465629948895\n            ],\n            [\n              -158.24240635476954,\n              21.479162346928234\n            ],\n            [\n              -158.11187347311537,\n              21.27955194162557\n            ],\n            [\n              -157.87475869726666,\n              21.277320121849456\n            ],\n            [\n              -157.78853514241246,\n              21.229327812614713\n            ],\n            [\n              -157.6687802051152,\n              21.253883970723265\n            ],\n            [\n              -157.62447087831504,\n              21.30744683110042\n            ],\n            [\n              -157.70231158755843,\n              21.41228417679669\n            ],\n            [\n              -157.71069443316924,\n              21.478047962139442\n            ],\n            [\n              -157.79811553739634,\n              21.456873031193922\n            ],\n            [\n              -157.82446162360165,\n              21.49476283830066\n            ],\n            [\n              -157.8172763273639,\n              21.53152880555119\n            ],\n            [\n              -157.97415529522343,\n              21.740805505081653\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Moskvichev, Richelle","contributorId":357155,"corporation":false,"usgs":false,"family":"Moskvichev","given":"Richelle","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mikkelsen, Anna","contributorId":357158,"corporation":false,"usgs":false,"family":"Mikkelsen","given":"Anna","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Tiffany","contributorId":357161,"corporation":false,"usgs":false,"family":"Anderson","given":"Tiffany","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Joel Nicolow","contributorId":357164,"corporation":false,"usgs":false,"family":"Joel Nicolow","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940772,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fletcher, Charles","contributorId":357167,"corporation":false,"usgs":false,"family":"Fletcher","given":"Charles","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":940773,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70265533,"text":"70265533 - 2025 - Multi-scale geophysical imaging of a hydrothermal system in Yellowstone National Park, USA","interactions":[],"lastModifiedDate":"2025-04-15T13:17:57.197981","indexId":"70265533","displayToPublicDate":"2025-03-28T08:12:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale geophysical imaging of a hydrothermal system in Yellowstone National Park, USA","docAbstract":"Little is known about the local plumbing systems that fuel Yellowstone’s famous hot springs, geysers and mud pots. A multi-method, multi-scale geophysical investigation was carried out in the Obsidian Pool Thermal Area (OPTA) to: (i) delineate the lateral extent of the hydrothermal area and associated surface features; (ii) estimate the dimensions of the upflow zone and identify its main controlling structures; (iii) assess fluids circulation pathways from depth to surface. Ground and airborne geophysical data were acquired to connect local and regional scales, from shallow to large depths. Maps of surface electrical resistivity show a strong correlation with hydrothermal features. At in-termediate depths, electrical resistivity permits delineating the upper limit of the upflow zone, while Poisson’s ratio highlights differences in subsurface fluid content. Combining these results with surface observations and topographic information, we speculate that differential mixing of hydrothermal and fresh water could explain the wide diversity of features observed at OPTA. Low electrical resistivity observed at large depths also suggest that a vast upflow zone, controlled by rhyolite flows and conjugate faults, underlies the OPTA. We speculate that hydrothermal fluids rise along fractures and reach the surface in topographic lows to form hydrothermal features. Our results show that synoptic, multi-scale geophysical measurements provide a roadmap for understanding where and how geologic heterogeneity, topography, fluid-gas separation, and the mixing of thermal and meteoric waters conspire to produce the wide variety of Yellowstone’s renowned hydrothermal features.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JB029839","usgsCitation":"Pasquet, S., Holbrook, W.S., Carr, B., Terry, N., Briggs, M.A., Finn, C., Bedrosian, P.A., Auken, E., Pedersen, J., Maurya, P.K., and Sims, K., 2025, Multi-scale geophysical imaging of a hydrothermal system in Yellowstone National Park, USA: JGR Solid Earth, v. 130, no. 4, e2024JB029839, 20 p., https://doi.org/10.1029/2024JB029839.","productDescription":"e2024JB029839, 20 p.","ipdsId":"IP-161584","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":488238,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jb029839","text":"Publisher Index Page"},{"id":484500,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -109.42248124611399,\n              43.840789120104006\n            ],\n            [\n              -109.42248124611399,\n              44.99074567225114\n            ],\n            [\n              -111.04762312859151,\n              44.99074567225114\n            ],\n            [\n              -111.04762312859151,\n              43.840789120104006\n            ],\n            [\n              -109.42248124611399,\n              43.840789120104006\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"130","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Pasquet, Sylvain","contributorId":175484,"corporation":false,"usgs":false,"family":"Pasquet","given":"Sylvain","email":"","affiliations":[],"preferred":false,"id":932959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, W. Steven","contributorId":175481,"corporation":false,"usgs":false,"family":"Holbrook","given":"W.","email":"","middleInitial":"Steven","affiliations":[],"preferred":false,"id":932960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Bradley J.","contributorId":353107,"corporation":false,"usgs":false,"family":"Carr","given":"Bradley J.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":932961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":932962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":210069,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":932963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finn, Carol A. 0000-0002-6178-0405","orcid":"https://orcid.org/0000-0002-6178-0405","contributorId":229711,"corporation":false,"usgs":true,"family":"Finn","given":"Carol A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":932964,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":932965,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Auken, Esben","contributorId":193991,"corporation":false,"usgs":false,"family":"Auken","given":"Esben","email":"","affiliations":[],"preferred":false,"id":932966,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pedersen, Jesper","contributorId":353109,"corporation":false,"usgs":false,"family":"Pedersen","given":"Jesper","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":932967,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Maurya, Pradip Kumar","contributorId":214855,"corporation":false,"usgs":false,"family":"Maurya","given":"Pradip","email":"","middleInitial":"Kumar","affiliations":[{"id":13419,"text":"Aarhus University, Denmark","active":true,"usgs":false}],"preferred":false,"id":932968,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sims, Kenneth 0000-0001-6179-6610","orcid":"https://orcid.org/0000-0001-6179-6610","contributorId":352001,"corporation":false,"usgs":false,"family":"Sims","given":"Kenneth","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":932969,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70266766,"text":"70266766 - 2025 - Assessing microplastics, per- and polyfluoroalkyl substances (PFAS), and other contaminants of global concern in wadable agricultural streams","interactions":[],"lastModifiedDate":"2025-05-29T13:10:29.985307","indexId":"70266766","displayToPublicDate":"2025-03-28T07:46:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9161,"text":"Environmental Science: Processes & Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Assessing microplastics, per- and polyfluoroalkyl substances (PFAS), and other contaminants of global concern in wadable agricultural streams","docAbstract":"Microplastics, per- and polyfluoroalkyl substances (PFAS), antibiotic resistance genes (ARGs), pharmaceuticals and personal care products (PPCPs), and pesticides may lead to unintended environmental contamination through many pathways in multiple matrices. This statewide, multi-matrix study of contaminants of global concern (CGCs) in agricultural streams across Iowa (United States) is the first to examine multiple CGCs in water, bed sediment, and fish to understand their occurrence in small streams located in regions of intense agriculture activity. Iowa plays a pivotal role in agriculture, with more than 85% of Iowa’s landscape devoted to agriculture making it an ideal location for determining the prevalence of CGCs to provide critical baseline exposure data. Fifteen sites were sampled across a range of predominant land uses (e.g., poultry, swine); all sites had detections of microplastics in all matrices. Concentrations of PFAS varied but were detected in water and sediment; all fish had detections of perfluorooctanesulfonate (PFOS), a type of PFAS. More than 50% of water and bed sediment samples had detections of ARGs. The most frequently detected PPCP was metformin. No sites had a cumulative exposure activity ratio greater than 1.0 for chemical exposures; 13 sites were above the 0.001 precautionary threshold. Toxicity quotients calculated using Aquatic Life Benchmarks were below the 0.1 moderate risk threshold for chemical exposures for all but one site. For fish, all sites exceeded the moderate and high-risk thresholds proposed for microplastic particles for food dilution (both chronic and acute exposures) and all sites exceeded the microplastic moderate threshold proposed for chronic tissue translocation, and two sites exceeded the threshold for acute tissue translocation.","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D4EM00753K","usgsCitation":"Meppelink, S.M., Kolpin, D., LeFevre, G., Cwiertny, D., Givens, C.E., Green, L., Hubbard, L.E., Iwanowicz, L.R., Lane, R.F., Mianecki, A., O’Shea, P.S., Raines, C.D., Scott, J., Thompson, D., Wilson, M.C., and Gray, J.L., 2025, Assessing microplastics, per- and polyfluoroalkyl substances (PFAS), and other contaminants of global concern in wadable agricultural streams: Environmental Science: Processes & Impacts, v. 27, p. 1401-1422, https://doi.org/10.1039/D4EM00753K.","productDescription":"22 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0000-0003-1568-4073","orcid":"https://orcid.org/0000-0003-1568-4073","contributorId":353174,"corporation":false,"usgs":false,"family":"Scott","given":"John W.","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":936726,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thompson, Darrin A. 0000-0002-6398-1067","orcid":"https://orcid.org/0000-0002-6398-1067","contributorId":353177,"corporation":false,"usgs":false,"family":"Thompson","given":"Darrin A.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":936727,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wilson, Michaelah C. 0000-0001-7052-9506","orcid":"https://orcid.org/0000-0001-7052-9506","contributorId":229469,"corporation":false,"usgs":true,"family":"Wilson","given":"Michaelah","email":"","middleInitial":"C.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":936728,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":205658,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"","middleInitial":"L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":936729,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70264758,"text":"sir20245110 - 2025 - A trend analysis and model comparison of total phosphorus concentrations and loads in the Boise River near Parma, southwestern Idaho, water years 2003–21","interactions":[],"lastModifiedDate":"2025-08-07T20:28:08.885943","indexId":"sir20245110","displayToPublicDate":"2025-03-27T11:37:27","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":"2024-5110","displayTitle":"A Trend Analysis and Model Comparison of Total Phosphorus Concentrations and Loads in the Boise River near Parma, Southwestern Idaho, Water Years 2003–21","title":"A trend analysis and model comparison of total phosphorus concentrations and loads in the Boise River near Parma, southwestern Idaho, water years 2003–21","docAbstract":"<p>Total phosphorus (TP) concentrations and loads in the Boise River near Parma, Idaho, were examined to identify changes by month over a 19-year period from water year 2003 through water year 2021 and to evaluate the performance of three common water-quality models. Mean annual TP concentrations and loads were estimated to have reduced by approximately 60 percent over the study period. Mean annual TP concentrations were reduced from 0.42 milligrams per liter in 2003 to 0.18 milligrams per liter in 2021. Mean annual TP loads were reduced from 816 kilograms per day in 2003 to 302 kilograms per day in 2021. Mean annual concentrations and loads reduced by approximately 3 percent per year with the largest changes occurring in the non-irrigation season of October through April. The TP load remained highest in May across the model period while peak concentration shifted from January to March.</p><p>High-frequency TP data collected with an automated sampler every 49 hours enabled detailed model performance evaluation of the Load Estimator (LOADEST), Weighted Regressions on Time, Discharge, and Season (WRTDS), and WRTDS method with Kalman filtering (WRTDS_K) water-quality models generated with near-monthly data. All three models were generally able to reproduce the observed concentrations, with the largest errors occurring in the spring when observed concentrations were most variable. Annual TP loads varied by up to 27 percent, or approximately 128,000 kilograms, between the three models calibrated on monthly data. In this system with highly variable concentrations, we note that performance metrics for WRTDS_K based on monthly calibration data masked serious errors that were only revealed by comparing results against higher frequency (49-hour) autosampler data. This emphasizes the value of high frequency validation data to quantify uncertainty in water-quality models when applied to systems where concentrations change rapidly. Lastly, we identify that hydraulic routing may be a valuable addition to discharge, season, and time in water-quality modeling for systems with significant human intervention in natural hydro-biogeochemical processes.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245110","collaboration":"Prepared in cooperation with the City of Boise","programNote":"National Water Quality Program","usgsCitation":"King, T.V., and Yoder, A.M., 2025, A trend analysis and model comparison of total phosphorus concentrations and loads in the Boise River near Parma, southwestern Idaho, water years 2003–21: U.S. Geological Survey Scientific Investigations Report 2024–5110, 41 p., https://doi.org/10.3133/sir20245110.","productDescription":"Report: vi, 41p.; Data Release","onlineOnly":"Y","ipdsId":"IP-140444","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":493739,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118504.htm","linkFileType":{"id":5,"text":"html"}},{"id":483669,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5110/sir20245110.XML"},{"id":483668,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5110/images"},{"id":483667,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98DMTAN","text":"USGS data release","description":"USGS data release","linkHelpText":"Water quality modeling results of total phosphorus for the lower Boise River near Parma, Idaho 2002 - 2021"},{"id":483666,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245110/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5110"},{"id":483665,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5110/sir20245110.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5110"},{"id":483664,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5110/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Parma","otherGeospatial":"Boise River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -117.25,\n              44\n            ],\n            [\n              -117.25,\n              43\n            ],\n            [\n              -115.75,\n              43\n            ],\n            [\n              -115.75,\n              44\n            ],\n            [\n              -117.25,\n              44\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_id@usgs.gov\" data-mce-href=\"mailto:dc_id@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/id-water\" data-mce-href=\"https://www.usgs.gov/centers/id-water\">Idaho Water Science Center</a><br>U.S. Geological Survey<br>230 Collins Road<br>Boise, Idaho 83702-4250</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Previous Investigations</li><li>Datasets</li><li>Trend Analysis of Discharge and Total Phosphorus</li><li>Water-Quality Model Comparison</li><li>Summary</li><li>References Cited</li></ul>","publishedDate":"2025-03-27","noUsgsAuthors":false,"publicationDate":"2025-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"King, Tyler V. 0000-0002-5785-3077","orcid":"https://orcid.org/0000-0002-5785-3077","contributorId":352514,"corporation":false,"usgs":false,"family":"King","given":"Tyler V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":931550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yoder, Alysa M. 0000-0002-3683-6729","orcid":"https://orcid.org/0000-0002-3683-6729","contributorId":352515,"corporation":false,"usgs":false,"family":"Yoder","given":"Alysa M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":931551,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70265009,"text":"ofr20211030U - 2025 - System characterization report on Resourcesat-2A Linear Imaging Self Scanning-4 sensor","interactions":[{"subject":{"id":70265009,"text":"ofr20211030U - 2025 - System characterization report on Resourcesat-2A Linear Imaging Self Scanning-4 sensor","indexId":"ofr20211030U","publicationYear":"2025","noYear":false,"chapter":"U","displayTitle":"System Characterization Report on Resourcesat-2A Linear Imaging Self Scanning-4 Sensor","title":"System characterization report on Resourcesat-2A Linear Imaging Self Scanning-4 sensor"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2025-03-28T13:40:14.359635","indexId":"ofr20211030U","displayToPublicDate":"2025-03-27T11:18:33","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":"2021-1030","chapter":"U","displayTitle":"System Characterization Report on Resourcesat-2A Linear Imaging Self Scanning-4 Sensor","title":"System characterization report on Resourcesat-2A Linear Imaging Self Scanning-4 sensor","docAbstract":"<h1>Executive Summary&nbsp;</h1><p>This report documents the system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-4 (LISS–4) sensor. It is part of a series of system characterization reports produced by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports describe the methodology and procedures used for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.</p><p>Resourcesat-2A was launched in 2016 on the Polar Satellite Launch Vehicle-C36; it is identical to Resourcesat-2, and together, they decrease imaging revisit time from 5 days to 2–3 days, providing data continuity and improved temporal resolution. Resouresat-2 and 2A carry the Advanced Wide Field Sensor, Linear Imaging Self Scanning-3, and LISS–4 medium-resolution imaging sensors, continuing the legacy of the Indian Space Research Organisation’s Indian Remote Sensing-1C/1D/P3 satellite programs. More information about the Indian Space Research Organisation’s satellites and sensors is available through the Joint Agency Commercial Imagery Evaluation Earth Observing Satellites Online Compendium at <a href=\"https://calval.cr.usgs.gov/apps/compendium/\" data-mce-href=\"https://calval.cr.usgs.gov/apps/compendium/\">https://calval.cr.usgs.gov/apps/compendium/</a> and from the manufacturer at <a href=\"https://www.isro.gov.in/\" data-mce-href=\"https://www.isro.gov.in/\">https://www.isro.gov.in/</a>.</p><p>The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team assessed the geometric, radiometric, and spatial performances of the Resourcesat-2A LISS–4 sensor. Geometric performance is divided into the interior geometric performance of band-to-band registration and the exterior geometric performance of geolocation accuracy. The interior geometric performance had mean offsets in the range of −0.118 to 0.024 pixel in easting and −0.053 to 0.022 pixel in northing with root mean square error values from 0.067 to 0.230 pixel in easting and from 0.087 to 0.2 pixel in northing. The exterior geometric performance had offsets in the range of 2.55 to 7.85 meters (m) in easting and −6.15 to 11.15 m in northing with root mean square error values in the range of 2.6 to 8.2 m in easting and 6.35 to 11.8 m in northing compared to the U.S. Department of Agriculture National Agriculture Imagery Program and WorldView-3 orthoimages. The measured radiometric performance had offsets from 0.003 to 0.024 and slopes from 0.736 to 0.952, and spatial performance was in the range of 1.633 to 1.903 pixels for the full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.0529 to 0.0952.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030U","usgsCitation":"Shrestha, M., Sampath, A., Kim, M., Park, S., and Clauson, J., 2025, System characterization report on Resourcesat-2A Linear Imaging Self Scanning-4 sensor, chap. U <em>of</em> Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 16 p., https://doi.org/10.3133/ofr20211030U.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-170098","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":483933,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/u/coverthb.jpg"},{"id":483934,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/u/ofr20211030u.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-U"},{"id":483935,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/u/ofr20211030u.XML"},{"id":483936,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/u/images/"},{"id":483938,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030U/full"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eros\" data-mce-href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center</a><br>U.S. Geological Survey<br>47914 252nd Street<br>Sioux Falls, SD 57198</p><p><a href=\"https://pubs.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Purpose and Scope</li><li>System Description</li><li>Procedures</li><li>Measurements</li><li>Analysis</li><li>Summary and Conclusions</li><li>Selected References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2025-03-27","noUsgsAuthors":false,"publicationDate":"2025-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Shrestha, Mahesh 0000-0002-8368-6399 mshrestha@contractor.usgs.gov","orcid":"https://orcid.org/0000-0002-8368-6399","contributorId":259303,"corporation":false,"usgs":false,"family":"Shrestha","given":"Mahesh","email":"mshrestha@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":932245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sampath, Aparajithan 0000-0002-6922-4913 asampath@usgs.gov","orcid":"https://orcid.org/0000-0002-6922-4913","contributorId":3622,"corporation":false,"usgs":true,"family":"Sampath","given":"Aparajithan","email":"asampath@usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":932240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":932246,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Park, Seonkyung 0000-0003-3203-1998","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":223182,"corporation":false,"usgs":true,"family":"Park","given":"Seonkyung","email":"","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":932247,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clauson, Jeffrey 0000-0003-3406-4988","orcid":"https://orcid.org/0000-0003-3406-4988","contributorId":352867,"corporation":false,"usgs":false,"family":"Clauson","given":"Jeffrey","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":932248,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70265062,"text":"70265062 - 2025 - Reconstructing relative abundance indices for Atlantic sturgeon using hierarchical ecological models","interactions":[],"lastModifiedDate":"2025-05-12T15:42:38.797222","indexId":"70265062","displayToPublicDate":"2025-03-27T09:34:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Reconstructing relative abundance indices for Atlantic sturgeon using hierarchical ecological models","docAbstract":"<div class=\" sec\"><div class=\"title\">Objective</div><p class=\"chapter-para\">The Atlantic Sturgeon<span>&nbsp;</span><i>Acipenser oxyrinchus</i><span>&nbsp;</span>is a wide-ranging, long-lived diadromous fish that is endangered in most of its range. Our objective was to develop and apply long-term, detection-corrected indices of relative abundance for juvenile and adult Atlantic Sturgeon in the Hudson River, New York, United States, to support population monitoring and stock assessment.</p></div><div class=\" sec\"><div class=\"title\">Methods</div><p class=\"chapter-para\">We used long-term gill-net catches to estimate relative abundances of juvenile and adult Atlantic Sturgeon while accounting for imperfect detection within an<span>&nbsp;</span><i>N-</i>mixture modeling framework. We validated the model framework using a simulation–estimation framework based on mean parameter estimates from the adult Atlantic Sturgeon relative abundance index.</p></div><div class=\" sec\"><div class=\"title\">Results</div><p class=\"chapter-para\">Simulation testing indicated that absolute abundance estimates may be biased low due to poor characterization of detection probabilities. However, model estimates of relative abundance tracked simulated abundance trends well. Juvenile relative abundance estimates followed similar trends as raw gill-net catches but were less variable among years when corrected for detection probability. Relative abundance of juveniles increased from 2004 to 2015 prior to declining through 2022, with little evidence for change between the start and end of the survey. Detection-corrected indices for adult sturgeon indicated a consistent increase in relative abundance that was not readily apparent in raw catch indices.</p></div><div class=\" sec\"><div class=\"title\">Conclusions</div><p class=\"chapter-para\">Detection-corrected catch indices can provide improved characterization of Atlantic Sturgeon relative abundance dynamics over raw gill-net catches through use of<span>&nbsp;</span><i>N-</i>mixture models. The approach has broad applicability to data types that are commonly collected for understanding population trends in stock assessment. Estimation of absolute abundance and other population demographics germane to management would benefit from alternative or auxiliary data collected through approaches such as side-scan sonar or acoustic telemetry, which are increasingly common for monitoring sturgeon populations.</p></div>","language":"English","publisher":"Oxford Academic","doi":"10.1093/tafafs/vnae005","usgsCitation":"Stich, D.S., Fox, D., Higgs, A., Kazyak, D.C., Pendleton, R., and Sethi, S.A., 2025, Reconstructing relative abundance indices for Atlantic sturgeon using hierarchical ecological models: Transactions of the American Fisheries Society, v. 154, no. 2, p. 134-142, https://doi.org/10.1093/tafafs/vnae005.","productDescription":"9 p.","startPage":"134","endPage":"142","ipdsId":"IP-172614","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":490114,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/tafafs/vnae005","text":"Publisher Index Page"},{"id":484062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Hudson River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -73.91330947473485,\n              40.66606917951091\n            ],\n            [\n              -73.72942268426407,\n              41.17642727450354\n            ],\n            [\n              -73.36165681223804,\n              43.183479467941055\n            ],\n            [\n              -76.13764009146252,\n              43.64841032319694\n            ],\n            [\n              -76.6716190407147,\n              43.304550466073295\n            ],\n            [\n              -76.16239408248754,\n              42.886227560392854\n            ],\n            [\n              -74.96712994442633,\n              42.70198813130807\n            ],\n            [\n              -74.22450960551923,\n              41.33593439003246\n            ],\n            [\n              -74.15378391687688,\n              40.71969364472585\n            ],\n            [\n              -73.91330947473485,\n              40.66606917951091\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"154","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Stich, Daniel S.","contributorId":280276,"corporation":false,"usgs":false,"family":"Stich","given":"Daniel","email":"","middleInitial":"S.","affiliations":[{"id":33660,"text":"SUNY Oneonta","active":true,"usgs":false}],"preferred":false,"id":932441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fox, Dewayne","contributorId":340954,"corporation":false,"usgs":false,"family":"Fox","given":"Dewayne","affiliations":[{"id":37219,"text":"Delaware State University","active":true,"usgs":false}],"preferred":false,"id":932442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higgs, Amanda","contributorId":225402,"corporation":false,"usgs":false,"family":"Higgs","given":"Amanda","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":932443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kazyak, David C. 0000-0001-9860-4045","orcid":"https://orcid.org/0000-0001-9860-4045","contributorId":140409,"corporation":false,"usgs":true,"family":"Kazyak","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pendleton, Richard","contributorId":348720,"corporation":false,"usgs":false,"family":"Pendleton","given":"Richard","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":932445,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sethi, Suresh A","contributorId":171843,"corporation":false,"usgs":false,"family":"Sethi","given":"Suresh","email":"","middleInitial":"A","affiliations":[{"id":26952,"text":"U.S. Fish and Wildlife Service, Anchorage, AK; Fisheries, Aquatic Science and Technology Lab, Alaska Pacific University, Anchorage, AK and  U.S. Geological Survey New York Cooperative Fish and Wildlife Research Unit, Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":932446,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70265232,"text":"70265232 - 2025 - Too much and not enough data: Challenges and solutions for generating information in freshwater research and monitoring","interactions":[],"lastModifiedDate":"2025-04-02T14:39:00.889559","indexId":"70265232","displayToPublicDate":"2025-03-27T09:27:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Too much and not enough data: Challenges and solutions for generating information in freshwater research and monitoring","docAbstract":"<p><span>Evaluating progress toward achieving freshwater conservation and sustainability goals requires transforming diverse types of data into useful information for scientists, managers, and other interest groups. Despite substantial increases in the volume of freshwater data collected worldwide, many regions and ecosystems still lack sufficient data collection and/or data access. We illustrate how these data challenges result from a diverse set of underlying mechanisms and propose solutions that can be applied by individuals or organizations. We discuss creative approaches to address data scarcity, including the use of community science, remote-sensing, environmental sensors, and legacy datasets. We highlight the importance of coordinated data collection efforts among groups and training programs to improve data access. At the institutional level, we emphasize the power of prioritizing data curation, incentivizing data publication, and promoting research that enhances data coverage and representativeness. Some of these strategies involve technological and analytical approaches, but many necessitate shifting the priorities and incentives of organizations such as academic and government research institutions, monitoring groups, journals, and funding agencies. Our overarching goal is to stimulate discussion to narrow the data disparities hindering the understanding of freshwater processes and their change across spatial scales.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70205","collaboration":"none","usgsCitation":"Smits, A., Hall, E., Deemer, B., Scordo, F., Barbosa, C.C., Carlson, S.M., Cawley, K.M., Grossart, H., Kelly, P.T., Mammola, S., Pintar, M., Robbins, C., Vidal, A., and Sacco, M., 2025, Too much and not enough data: Challenges and solutions for generating information in freshwater research and monitoring: Ecosphere, v. 16, no. 3, e70205, 19 p., https://doi.org/10.1002/ecs2.70205.","productDescription":"e70205, 19 p.","ipdsId":"IP-162033","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70205","text":"Publisher Index Page"},{"id":484131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina, United States","otherGeospatial":"Nahuel Huapi Lake, Lake Tahoe","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.47520389752921,\n              39.3888302058302\n            ],\n            [\n              -120.47520389752921,\n              38.773664326154886\n            ],\n            [\n              -119.56046785633012,\n              38.773664326154886\n            ],\n            [\n              -119.56046785633012,\n              39.3888302058302\n            ],\n            [\n              -120.47520389752921,\n              39.3888302058302\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -71.91761662863647,\n              -40.646837584942396\n            ],\n            [\n              -71.91761662863647,\n              -41.21142317383106\n            ],\n            [\n              -71.05714462820775,\n              -41.21142317383106\n            ],\n            [\n              -71.05714462820775,\n              -40.646837584942396\n            ],\n            [\n              -71.91761662863647,\n              -40.646837584942396\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"16","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-03-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Smits, Adrianne P.","contributorId":352945,"corporation":false,"usgs":false,"family":"Smits","given":"Adrianne P.","affiliations":[{"id":84313,"text":"Environmental Science and Policy, University of California, Davis, CA, USA 95616","active":true,"usgs":false}],"preferred":false,"id":932554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Ed K","contributorId":156351,"corporation":false,"usgs":false,"family":"Hall","given":"Ed K","affiliations":[{"id":20320,"text":"University of Minnesota, Department of Ecology, Evolution and Behavior","active":true,"usgs":false}],"preferred":false,"id":932555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deemer, Bridget R. 0000-0002-5845-1002 bdeemer@usgs.gov","orcid":"https://orcid.org/0000-0002-5845-1002","contributorId":198160,"corporation":false,"usgs":true,"family":"Deemer","given":"Bridget","email":"bdeemer@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":932556,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Scordo, Facundo","contributorId":298282,"corporation":false,"usgs":false,"family":"Scordo","given":"Facundo","email":"","affiliations":[{"id":64520,"text":"Instituto Argentino de Oceanografía","active":true,"usgs":false}],"preferred":false,"id":932557,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barbosa, Carolina C. 0000-0002-6393-5730","orcid":"https://orcid.org/0000-0002-6393-5730","contributorId":268214,"corporation":false,"usgs":false,"family":"Barbosa","given":"Carolina","email":"","middleInitial":"C.","affiliations":[{"id":55596,"text":"São Carlos School of Engineering, Hydraulics and Sanitation Department","active":true,"usgs":false}],"preferred":false,"id":932558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carlson, Stephanie M.","contributorId":250652,"corporation":false,"usgs":false,"family":"Carlson","given":"Stephanie","email":"","middleInitial":"M.","affiliations":[{"id":6643,"text":"University of California - 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,{"id":70265077,"text":"70265077 - 2025 - Limited directional change in mountaintop plant communities over 19 years in western North America","interactions":[],"lastModifiedDate":"2025-04-01T15:21:50.068321","indexId":"70265077","displayToPublicDate":"2025-03-27T08:15:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Limited directional change in mountaintop plant communities over 19 years in western North America","docAbstract":"<p><span>Plant communities on mountain summits are commonly long-lived, cold-adapted perennials with low dispersal ability. These characteristics in tandem with limited area to track suitable conditions make these mountain communities potentially highly vulnerable to climate change, and indicators of climate change impacts. We investigated temporal changes in plant communities on 29 arid mountain summits across eight study regions in California and Nevada, USA, over 19 years. We analyzed community dynamics in terms of species richness, turnover, gain and loss of functional groups, and relative abundance of functional groups. First, across all summits and regions, we found no change in species richness over time. Second, there was relatively high species turnover (21.7%) between the five-year survey intervals, but turnover was not significantly different from random expectation. Within functional groups, forbs had the greatest proportion of gains and cushions had the greatest proportion of losses. Third, qualitative abundance categories presented a small but consistent signal of decrease in the relative abundance of cushions, graminoids, and shrubs/trees over the study period. Across a broad geographic scale and nearly two decades, community patterns were widely similar, suggesting that climate change has not impacted local colonization or extirpation of mountaintop species in this arid region. These findings support observed differences in response to climate change between temperature-limited and water-limited regions globally, and highlight the lagged and variable nature of high-elevation systems. Our findings fill a major data gap on alpine plant community responses to climate change in the western United States and bolster the importance of long-term ecological monitoring with rapid climate change.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70197","usgsCitation":"Goff, K., Oldfather, M.F., Nachlinger, J., Smithers, B., Koontz, M., Bishop, C., Bishop, J., Burke, M., and Sheth, S., 2025, Limited directional change in mountaintop plant communities over 19 years in western North America: Ecosphere, v. 16, no. 3, e70197, 12 p., https://doi.org/10.1002/ecs2.70197.","productDescription":"e70197, 12 p.","ipdsId":"IP-167489","costCenters":[{"id":40927,"text":"North Central Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":488671,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70197","text":"Publisher Index 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Great Basin","active":true,"usgs":false}],"preferred":false,"id":932483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bishop, Jim","contributorId":352925,"corporation":false,"usgs":false,"family":"Bishop","given":"Jim","affiliations":[{"id":84302,"text":"GLORIA Great Basin","active":true,"usgs":false}],"preferred":false,"id":932484,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Burke, Mary","contributorId":352926,"corporation":false,"usgs":false,"family":"Burke","given":"Mary","affiliations":[{"id":84302,"text":"GLORIA Great Basin","active":true,"usgs":false}],"preferred":false,"id":932485,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sheth, Seema","contributorId":352927,"corporation":false,"usgs":false,"family":"Sheth","given":"Seema","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":932486,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70264757,"text":"fs20253002 - 2025 - Critical Minerals in Ores (CMiO) database","interactions":[],"lastModifiedDate":"2026-01-23T21:37:38.090764","indexId":"fs20253002","displayToPublicDate":"2025-03-26T16:15:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3002","displayTitle":"Critical Minerals in Ores (CMiO) Database","title":"Critical Minerals in Ores (CMiO) database","docAbstract":"<p>Critical minerals are commodities essential to modern industrial and strategic technologies and are highly vulnerable to supply chain disruption. The Critical Minerals Mapping Initiative (CMMI) is a collaboration among the U.S. Geological Survey (USGS), the Geological Survey of Canada, and Geoscience Australia that aims to deepen global understanding of where critical minerals are located. A key output of this initiative is the Critical Minerals in Ores (CMiO) database that is advancing our collective understanding of critical minerals distributions. For instance, publicly available data on the concentrations of many critical minerals are sparse because these commodities can only be produced in small, yet essential, quantities compared to the primary commodities like copper and zinc. The CMiO database helps bridge this gap by offering high-quality, multielement geochemical data from a wide variety of critical mineral-bearing deposits around the world. Importantly, it uses a novel consensus deposit environment, group, and type classification scheme developed by the agencies that allows comparisons among ore deposits from different regions. The CMiO database contains geochemical data for more than 20,000 samples from more than 100 deposit types comprising 10 deposit environments.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253002","collaboration":"Prepared in collaboration with the Geological Survey of Canada and Geoscience Australia","programNote":"Mineral Resources Program","usgsCitation":"Case, G.N.D., Graham, G.E., Lawley, C.J.M., Bastrakov, E., Huston, D.L., Hofstra, A.H., Lisitsin, V., Hawkins, S.G., and Wang, B., 2025, Critical Minerals in Ores (CMiO) database (ver. 1.2, May 2025): U.S. Geological Survey Fact Sheet 2025–3002, 2 p., https://doi.org/10.3133/fs20253002.","productDescription":"Report: 2 p.; Dataset","onlineOnly":"N","ipdsId":"IP-172113","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":493736,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118563.htm","text":"Version 1.1","linkFileType":{"id":5,"text":"html"}},{"id":485219,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2025/3002/versionHist.txt","size":"4.0 KB","linkFileType":{"id":2,"text":"txt"},"description":"FS 2025-3002 version history"},{"id":483999,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253002/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3002"},{"id":483900,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3002/fs20253002.xml"},{"id":483899,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3002/images"},{"id":483682,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pid.geoscience.gov.au/dataset/ga/145496","text":"Critical Minerals in Ores - geochemistry database"},{"id":483671,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3002/fs20253002.pdf","text":"Report","size":"5.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3002"},{"id":483670,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3002/coverthb3.jpg"},{"id":498997,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118502.htm","text":"Version 1.0","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0: March 26, 2025; Version 1.1: April 30, 2025; Version 1.2: May 22, 2025","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/programs/mineral-resources-program\" data-mce-href=\"https://www.usgs.gov/programs/mineral-resources-program\">Mineral Resources Program</a><br>U.S. Geological Survey<br>913 National Center<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>A Global Geochemical Database to Assess Primary and Byproduct Critical Mineral Potential <br></li><li> Quantifying Critical Mineral Abundance in Different Deposit Types</li><li>Contributing Data to the CMiO Database</li><li>References Cited</li></ul>","publishedDate":"2025-03-26","revisedDate":"2025-05-22","noUsgsAuthors":false,"publicationDate":"2025-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Case, George N.D. 0000-0001-9826-5661 gcase@usgs.gov","orcid":"https://orcid.org/0000-0001-9826-5661","contributorId":224941,"corporation":false,"usgs":true,"family":"Case","given":"George","email":"gcase@usgs.gov","middleInitial":"N.D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":931541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Garth E. 0000-0003-0657-0365 ggraham@usgs.gov","orcid":"https://orcid.org/0000-0003-0657-0365","contributorId":1031,"corporation":false,"usgs":true,"family":"Graham","given":"Garth","email":"ggraham@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":931542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawley, Christopher","contributorId":259285,"corporation":false,"usgs":false,"family":"Lawley","given":"Christopher","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":931543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bastrakov, Evgeniy","contributorId":259289,"corporation":false,"usgs":false,"family":"Bastrakov","given":"Evgeniy","email":"","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":931544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huston, David L.","contributorId":259293,"corporation":false,"usgs":false,"family":"Huston","given":"David","middleInitial":"L.","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":931545,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":931546,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lisitsin, Vladimir","contributorId":259280,"corporation":false,"usgs":false,"family":"Lisitsin","given":"Vladimir","email":"","affiliations":[{"id":52346,"text":"Geological Survey of Queensland, Australia","active":true,"usgs":false}],"preferred":false,"id":931547,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hawkins, Steph","contributorId":352513,"corporation":false,"usgs":false,"family":"Hawkins","given":"Steph","affiliations":[{"id":35920,"text":"Geoscience Australia","active":true,"usgs":false}],"preferred":false,"id":931548,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wang, Bronwen 0000-0003-1044-2227","orcid":"https://orcid.org/0000-0003-1044-2227","contributorId":217957,"corporation":false,"usgs":true,"family":"Wang","given":"Bronwen","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":931549,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70265500,"text":"70265500 - 2025 - Greater sage-grouse seasonal habitat associations: A review and considerations for interpretation and management applications","interactions":[],"lastModifiedDate":"2025-06-23T15:20:23.515805","indexId":"70265500","displayToPublicDate":"2025-03-26T08:12:57","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Greater sage-grouse seasonal habitat associations: A review and considerations for interpretation and management applications","docAbstract":"<p><span>Habitat features needed by wildlife can change in composition throughout the year, particularly in temperate ecosystems, leading to distinct seasonal spatial-use patterns. Studies of species-habitat associations therefore often focus on understanding relationships within discrete seasonal periods with common goals of prediction (e.g., habitat mapping) and inference (e.g., interpreting model coefficients). Across the range of the greater sage-grouse (</span><i>Centrocercus urophasianus</i><span>) of western North America, the increasing use of high-frequency tracking devices has led to a surge in habitat association studies covering multiple temporal periods and spatial extents. We reviewed the literature for seasonal habitat association studies corresponding to the second and third orders of selection (Johnson 1980). Our objectives were to summarize the methodological approaches used to estimate habitat associations to aid understanding in cross-study comparisons and identify common habitat features reported as selected or avoided within different seasonal periods. We reviewed 71 second- and third-order studies published from 2007–2023 that evaluated covariates collected in a geographic information system (GIS) and modeled probability of selection or intensity of use. The most common study design evaluated a single level of selection (third-order) and was multi-scale (i.e., covariates were measured at varying spatial grains). The most common model approach estimated habitat associations using resource selection functions (RSFs) fit with logistic regression. Studies mostly focused on the breeding periods and winter, but all seasons throughout the annual cycle were covered. There was clear support for selection of sagebrush and avoidance of trees and rugged terrain across seasons, and strong selection of mesic conditions in summer. However, habitat associations for most covariates were mixed, with proportionally equivalent selection and avoidance reported, even within the same seasons. Different factors hampered cross-study comparisons, including variation in study design, but additional contributors likely included important context-dependent habitat associations, such as functional responses to changing habitat availability. We suggest collaborative studies leveraging multiple datasets can help improve seasonal habitat inference by removing the effects of variable study designs.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70022","usgsCitation":"Wann, G.T., Whipple, A.L., Orning, E.K., McLachlan, M.M., Beck, J.L., Coates, P., Conway, C.J., Dinkins, J.B., Johnston, A.N., Hagen, C., Makela, P., Naugle, D., Schroeder, M.A., Sedinger, J.S., Walker, B.L., Williams, P.J., Inman, R.D., and Aldridge, C.L., 2025, Greater sage-grouse seasonal habitat associations: A review and considerations for interpretation and management applications: Journal of Wildlife Management, v. 89, no. 5, e70022, 33 p., https://doi.org/10.1002/jwmg.70022.","productDescription":"e70022, 33 p.","ipdsId":"IP-154951","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488629,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70022","text":"Publisher Index Page"},{"id":484325,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -123.85259667955762,\n              49.62627448300293\n            ],\n            [\n              -123.85259667955762,\n              33.76025294128375\n            ],\n            [\n              -104.85728560371575,\n              33.76025294128375\n            ],\n            [\n              -104.85728560371575,\n              49.62627448300293\n            ],\n            [\n              -123.85259667955762,\n              49.62627448300293\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"89","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":932830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whipple, Ashley L. 0000-0002-0304-7643","orcid":"https://orcid.org/0000-0002-0304-7643","contributorId":300552,"corporation":false,"usgs":true,"family":"Whipple","given":"Ashley","email":"","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":932831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orning, Elizabeth Kari 0000-0002-1376-729X","orcid":"https://orcid.org/0000-0002-1376-729X","contributorId":315548,"corporation":false,"usgs":true,"family":"Orning","given":"Elizabeth","email":"","middleInitial":"Kari","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":932832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McLachlan, Megan M.","contributorId":300301,"corporation":false,"usgs":false,"family":"McLachlan","given":"Megan","email":"","middleInitial":"M.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":932833,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beck, Jeffrey L.","contributorId":287806,"corporation":false,"usgs":false,"family":"Beck","given":"Jeffrey","middleInitial":"L.","affiliations":[{"id":12729,"text":"UW","active":true,"usgs":false}],"preferred":false,"id":932834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coates, Peter S. 0000-0003-2672-9994","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":352181,"corporation":false,"usgs":true,"family":"Coates","given":"Peter S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":932835,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":932836,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dinkins, Jonathan B.","contributorId":177565,"corporation":false,"usgs":false,"family":"Dinkins","given":"Jonathan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":932837,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Johnston, Aaron N. 0000-0003-4659-0504","orcid":"https://orcid.org/0000-0003-4659-0504","contributorId":201768,"corporation":false,"usgs":true,"family":"Johnston","given":"Aaron","email":"","middleInitial":"N.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":932838,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hagen, Christian A.","contributorId":287181,"corporation":false,"usgs":false,"family":"Hagen","given":"Christian A.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":932839,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Makela, Paul","contributorId":338000,"corporation":false,"usgs":false,"family":"Makela","given":"Paul","email":"","affiliations":[],"preferred":false,"id":932840,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Naugle, David","contributorId":341484,"corporation":false,"usgs":false,"family":"Naugle","given":"David","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":932841,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Schroeder, Michael A","contributorId":221131,"corporation":false,"usgs":false,"family":"Schroeder","given":"Michael","email":"","middleInitial":"A","affiliations":[{"id":12438,"text":"Washington Department of Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":932842,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sedinger, James S.","contributorId":84861,"corporation":false,"usgs":false,"family":"Sedinger","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":932843,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Walker, Brett L.","contributorId":82964,"corporation":false,"usgs":true,"family":"Walker","given":"Brett","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":932844,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":932845,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Inman, Richard D. 0000-0002-1982-7791 rdinman@usgs.gov","orcid":"https://orcid.org/0000-0002-1982-7791","contributorId":187754,"corporation":false,"usgs":true,"family":"Inman","given":"Richard","email":"rdinman@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":932846,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":932847,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70264859,"text":"70264859 - 2025 - Shortening migration by 4500 km does not affect nesting phenology or increase nest success for black brant (Branta bernicla nigricans) breeding in Arctic and subarctic Alaska","interactions":[],"lastModifiedDate":"2025-03-26T15:30:46.139491","indexId":"70264859","displayToPublicDate":"2025-03-25T10:22:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Shortening migration by 4500 km does not affect nesting phenology or increase nest success for black brant (<i>Branta bernicla nigrica</i>) breeding in Arctic and subarctic Alaska","title":"Shortening migration by 4500 km does not affect nesting phenology or increase nest success for black brant (Branta bernicla nigricans) breeding in Arctic and subarctic Alaska","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Since the 1980s, Pacific Black Brant (<i>Branta bernicla nigricans</i>, hereafter brant) have shifted their winter distribution northward from Mexico to Alaska (approximately 4500&nbsp;km) with changes in climate. Alongside this shift, the primary breeding population of brant has declined. To understand the population-level implications of the changing migration strategy of brant, it is important to connect movement and demographic data. Our objectives were to calculate migratory connectivity, a measure of spatial and temporal overlap during the non-breeding period, for Arctic and subarctic breeding populations of brant, and to determine if variation in migration strategies affected nesting phenology and nest survival.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Methods</h3><p>We derived a migratory network using light-level geolocator migration tracks from an Arctic site&nbsp;(Colville River Delta) and a&nbsp;subarctic site (Tutakoke River) in Alaska. Using this network, we quantified the migratory connectivity of the two populations during the winter. We also compared nest success rates among brant that used different combinations of winter sites and breeding sites.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>The two breeding populations were well mixed during the winter, as indicated by a migratory connectivity score close to 0 (− 0.06) at the primary wintering sites of Izembek Lagoon, Alaska (n = 11 brant) and Baja California, Mexico (n = 48). However, Arctic birds were more likely to migrate the shorter distance to Izembek (transition probability = 0.24) compared to subarctic birds (transition probability = 0.09). Nest survival for both breeding populations was relatively high (0.88–0.92), and we did not detect an effect of wintering site on nest success the following year.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>Nest survival of brant did not differ among brant that used wintering sites despite a 4500&nbsp;km difference in migration distances. Our results also suggested that the growing Arctic breeding population is unlikely to compensate for declines in the larger breeding population of brant in the subarctic. However, this study took place in 2011–2014 and wintering at Izembek Lagoon may have greater implications for reproductive success under future climate conditions.</p>","language":"English","publisher":"Biomed Central","doi":"10.1186/s40462-025-00530-z","usgsCitation":"Matsuoka, T., Patil, V.P., Hupp, J., Leach, A.G., Reed, J., Sedinger, J.S., and Ward, D., 2025, Shortening migration by 4500 km does not affect nesting phenology or increase nest success for black brant (Branta bernicla nigricans) breeding in Arctic and subarctic Alaska: Movement Ecology, v. 13, 21, 13 p., https://doi.org/10.1186/s40462-025-00530-z.","productDescription":"21, 13 p.","ipdsId":"IP-165239","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":488665,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-025-00530-z","text":"Publisher Index Page"},{"id":483879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -113.81790807363556,\n              25.109390075267115\n            ],\n            [\n              -111.12577320220554,\n              27.35015894013445\n            ],\n            [\n              -120.0723516818312,\n              35.91671872458075\n            ],\n            [\n              -123.33332088662812,\n              40.09627486987472\n            ],\n            [\n              -121.76064748127651,\n              47.98998229927324\n            ],\n            [\n              -130.2791770051045,\n              55.04657100955589\n            ],\n            [\n              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vpatil@usgs.gov","orcid":"https://orcid.org/0000-0002-9357-194X","contributorId":203676,"corporation":false,"usgs":true,"family":"Patil","given":"Vijay","email":"vpatil@usgs.gov","middleInitial":"P.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":932068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Jerry W. 0000-0002-6439-3910","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":339472,"corporation":false,"usgs":false,"family":"Hupp","given":"Jerry W.","affiliations":[{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":932069,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leach, Alan G.","contributorId":203591,"corporation":false,"usgs":false,"family":"Leach","given":"Alan","email":"","middleInitial":"G.","affiliations":[{"id":36666,"text":"Department of Natural Resources and Environmental Science, University of Nevada-Reno","active":true,"usgs":false}],"preferred":false,"id":932070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, John 0000-0002-3239-6906","orcid":"https://orcid.org/0000-0002-3239-6906","contributorId":214852,"corporation":false,"usgs":true,"family":"Reed","given":"John","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":932071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sedinger, James S.","contributorId":84861,"corporation":false,"usgs":false,"family":"Sedinger","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":932072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ward, David H.","contributorId":352708,"corporation":false,"usgs":false,"family":"Ward","given":"David H.","affiliations":[{"id":84288,"text":"U.S. Geological Survey Alaska Science Center (Emeritus)","active":true,"usgs":false}],"preferred":false,"id":932073,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70266111,"text":"70266111 - 2025 - The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models","interactions":[],"lastModifiedDate":"2025-04-25T15:31:50.116638","indexId":"70266111","displayToPublicDate":"2025-03-24T10:29:01","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21214,"text":"Peer Community Journal","active":true,"publicationSubtype":{"id":10}},"title":"The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models","docAbstract":"<p><span>Survival is a key life history parameter that can inform management decisions and basic life history research. Because true survival is often confounded with emigration from the study area, many studies are forced to estimate apparent survival (i.e., probability of surviving and remaining inside the study area), which can be much lower than true survival for highly mobile species.&nbsp; One method for estimating true survival is the Barker joint live-recapture/live-resight (JLRLR) model, which combines capture data from a study area (hereafter the ‘capture site’) with resighting data from a broader geographic area. This model assumes that live resights occur throughout the entire area where animals can disperse to and this assumption is often not met in practice. Here we use simulation to evaluate survival bias from a JLRLR model under study design scenarios that differ in the site selection for resights: global, random, fixed including the capture site, and fixed excluding the capture site. Simulation results indicate that fixed designs that included the capture site showed negative survival bias, whereas fixed designs that excluded the capture site exhibited positive survival bias. The magnitude of the bias was dependent on movement and survival, where scenarios with high survival and frequent movement had minimal bias. In an effort to help minimize bias, we developed a multistate version of the JLRLR and demonstrated reductions in survival bias compared to the single-state version for most designs. Our results suggest minimizing bias can be accomplished by: 1) using a random resight design when feasible if global sampling is not possible, 2) using the multistate JLRLR model when appropriate, 3) including the capture site in the resight sampling frame when possible, and 4) reporting survival as apparent survival if fixed sites are used for resight with the single state JLRLR model.</span></p>","language":"English","publisher":"PeerJ","doi":"10.24072/pcjournal.533","usgsCitation":"Dzul, M.C., Yackulic, C., and Kendall, W.L., 2025, The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models: Peer Community Journal, v. 5, e34, 24 p., https://doi.org/10.24072/pcjournal.533.","productDescription":"e34, 24 p.","ipdsId":"IP-158705","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":487775,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.24072/pcjournal.533","text":"Publisher Index Page"},{"id":485061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":934619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":934620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70265081,"text":"70265081 - 2025 - Planting seeds for thriving data management","interactions":[],"lastModifiedDate":"2025-04-01T15:28:49.893757","indexId":"70265081","displayToPublicDate":"2025-03-24T10:27:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7602,"text":"Eos, American Geophysical Union","active":true,"publicationSubtype":{"id":10}},"title":"Planting seeds for thriving data management","docAbstract":"The volumes and varieties of data coming from all types of scientific instrumentation around the globe and beyond are rapidly growing. To reuse and capitalize on these data effectively, scientists must be able to share and access them efficiently, which requires the data to be well managed. \nMany scientists intuit that research data management (RDM) done well does not mean using dusty USB drives or aging laptops for storage. Yet the path to strong data management is not always clear. How is RDM done? Who does it? For science to advance, we need to bolster cyberinfrastructure and human capacity to ensure that the data being collected are reusable by both humans and machines.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025EO250109","usgsCitation":"Benson, A., Beaulieu, S., Bishop, B., Diggs, S., and Formel, S., 2025, Planting seeds for thriving data management: Eos, American Geophysical Union, HTML Document, https://doi.org/10.1029/2025EO250109.","productDescription":"HTML Document","ipdsId":"IP-172647","costCenters":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":488673,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025eo250109","text":"Publisher Index Page"},{"id":484072,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Abigail 0000-0002-4391-107X","orcid":"https://orcid.org/0000-0002-4391-107X","contributorId":352933,"corporation":false,"usgs":false,"family":"Benson","given":"Abigail","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":932501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beaulieu, Stace 0000-0002-2609-5453","orcid":"https://orcid.org/0000-0002-2609-5453","contributorId":352935,"corporation":false,"usgs":false,"family":"Beaulieu","given":"Stace","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":false,"id":932502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bishop, Bradley Wade 0000-0002-5022-2707","orcid":"https://orcid.org/0000-0002-5022-2707","contributorId":352937,"corporation":false,"usgs":false,"family":"Bishop","given":"Bradley Wade","affiliations":[{"id":63836,"text":"University of Tennessee, Knoxville","active":true,"usgs":false}],"preferred":false,"id":932503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diggs, Stephen C. 0000-0003-3814-6104","orcid":"https://orcid.org/0000-0003-3814-6104","contributorId":352939,"corporation":false,"usgs":false,"family":"Diggs","given":"Stephen C.","affiliations":[{"id":84309,"text":"University of California Office of the President","active":true,"usgs":false}],"preferred":false,"id":932504,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Formel, Stephen Killfoile 0000-0001-7418-1244","orcid":"https://orcid.org/0000-0001-7418-1244","contributorId":338237,"corporation":false,"usgs":true,"family":"Formel","given":"Stephen Killfoile","affiliations":[{"id":38128,"text":"Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":932500,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70264851,"text":"70264851 - 2025 - An enhanced national-scale urban tree canopy cover dataset for the United States","interactions":[],"lastModifiedDate":"2025-03-26T15:27:52.723666","indexId":"70264851","displayToPublicDate":"2025-03-24T08:13:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"An enhanced national-scale urban tree canopy cover dataset for the United States","docAbstract":"<p><span>Moderate-resolution (30-m) national map products have limited capacity to represent fine-scale, heterogeneous urban forms and processes, yet improvements from incorporating higher resolution predictor data remain rare. In this study, we applied random forest models to high-resolution land cover data for 71 U.S. urban areas, moderate-resolution National Land Cover Database (NLCD) Tree Canopy Cover (TCC), and additional explanatory climatic and structural data to develop an enhanced urban TCC dataset for U.S. urban areas. With a coefficient of determination (R</span><sup>2</sup><span>) of 0.747, our model estimated TCC within 3% for 62 urban areas and added 13.4% more city-level TCC on average, compared to the native NLCD TCC product. Cross validations indicated model stability suitable for building a national-scale TCC dataset (median R</span><sup>2</sup><span>&nbsp;of 0.752, 0.675, and 0.743 for 1,000-fold cross validation, urban area leave-one-out cross validation, and cross validation by Census block group median year built, respectively). Additionally, our model code can be used to improve moderate-resolution TCC in other parts of the world where high-resolution land cover data have limited spatiotemporal availability.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41597-025-04816-0","usgsCitation":"Corro, L.M., Bagstad, K.J., Heris, M., Ibsen, P.C., Schleeweis, K., Diffendorfer, J., Troy, A., Megown, K., and O'Neil-Dunne, J., 2025, An enhanced national-scale urban tree canopy cover dataset for the United States: Scientific Data, v. 12, 490, 14 p., https://doi.org/10.1038/s41597-025-04816-0.","productDescription":"490, 14 p.","ipdsId":"IP-166001","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":488662,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-025-04816-0","text":"Publisher Index Page"},{"id":483878,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n                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,{"id":70265612,"text":"70265612 - 2025 - Ranking river basins for stream temperature research and monitoring in the contiguous United States","interactions":[],"lastModifiedDate":"2025-04-14T16:30:55.176106","indexId":"70265612","displayToPublicDate":"2025-03-23T09:24:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Ranking river basins for stream temperature research and monitoring in the contiguous United States","docAbstract":"There is a need to prioritize research and data collection in river basins by integrating information from environmental, ecological, and socioeconomic datasets to maintain acceptable water quality for human uses and ecosystem health. Multiple anthropogenic and natural stressors are responsible for driving changes in stream temperatures that can alter ecosystems and degrade water quality. These stressors are variable spatially and temporally, which can be challenging for prioritizing monitoring and research. In this study, an evaluation of variables related to stream temperature was performed for 163 candidate basins of the contiguous United States to highlight potential focal areas. Thirty variables were combined in six components: anthropogenic forcing, natural forcing, climate change, ecological sensitivity, socioeconomic sensitivity, and data availability. The components were incorporated into three themes: vulnerability of streams to thermal change, vulnerability of ecosystems, and vulnerability of communities. By evaluating each theme separately, patterns of vulnerability and potential resiliency were identified as well as consistency in ranks within the themes. For example, results of the national scale ranking indicated the Southern California Coastal basin (within California-Nevada region) was the highest-ranking priority in vulnerability of streams to thermal change and vulnerability of ecosystems. The analysis also identified vulnerable basins with gaps in monitoring. For example, the Missouri-Oahe basin (within the Northern High Plains region) was the highest-ranking priority for vulnerable communities with limitations in data availability. The ranking approach provides insight into basins that are resilient and are ideal candidates for monitoring and research.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2025.133163","usgsCitation":"Naranjo, R.C., Johnson, Z., Lucas, L., Baker, N.T., and Green, C., 2025, Ranking river basins for stream temperature research and monitoring in the contiguous United States: Journal of Hydrology, v. 658, 133163, 15 p., https://doi.org/10.1016/j.jhydrol.2025.133163.","productDescription":"133163, 15 p.","ipdsId":"IP-157155","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":488228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2025.133163","text":"Publisher Index Page"},{"id":484513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n  \"type\": 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rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Zachary 0000-0002-0149-5223 zjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-0149-5223","contributorId":190399,"corporation":false,"usgs":true,"family":"Johnson","given":"Zachary","email":"zjohnson@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":933109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Lisa 0000-0001-7797-5517 llucas@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-5517","contributorId":260498,"corporation":false,"usgs":true,"family":"Lucas","given":"Lisa","email":"llucas@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":933110,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, Nancy T. 0000-0002-7979-5744","orcid":"https://orcid.org/0000-0002-7979-5744","contributorId":222870,"corporation":false,"usgs":true,"family":"Baker","given":"Nancy","email":"","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933111,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Green, Christopher 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,{"id":70266168,"text":"70266168 - 2025 - Predicting bat roosts in bridges using Bayesian Additive Regression Trees","interactions":[],"lastModifiedDate":"2025-04-30T14:55:09.773729","indexId":"70266168","displayToPublicDate":"2025-03-22T08:11:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Predicting bat roosts in bridges using Bayesian Additive Regression Trees","docAbstract":"Human-built structures can provide important habitat for wildlife, but predicting which structures are most likely to be used remains challenging. To evaluate the predictive capabilities of data-driven ensemble modeling approaches, we conducted surveys for bats and signs of bat use, such as urine and guano staining, at bridges across the southwestern United States. We developed a bat roost discovery tool using Bayesian Additive Regression Trees (BART) and evaluated the predictive ability of this model against other commonly used approaches. We found that the lack of nearby water resources was associated with a lower predicted probability of bat presence or signs of bat use at bridges. While the presence of nearby water resources was associated with higher average predicted probability of bat presence or signs of bat use, high uncertainty surrounding these estimates indicates that other factors also play a role in determining which bridge roosts bats are more likely to use. As such, our model could be particularly useful for predicting which bridges can be excluded from survey efforts due to low probability of bat presence or signs of bat use. We extrapolated our model to unsurveyed bridges across the study region and provide an interactive dashboard application interface for the exploration of these results. Overall, this study demonstrates the application of BART as a predictive tool for prioritizing future bridge surveys for bats roosting in transportation structures.","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03551","usgsCitation":"Oram, J., Wray, A.K., Davis, H.T., de Wit, L., Frick, W.F., Hoegh, A.B., Irvine, K.M., Pollock, P., Schuhmann, A.N., Tousley, F.C., and Reichert, B., 2025, Predicting bat roosts in bridges using Bayesian Additive Regression Trees: Global Ecology and Conservation, v. 60, e03551, 12 p., https://doi.org/10.1016/j.gecco.2025.e03551.","productDescription":"e03551, 12 p.","ipdsId":"IP-176127","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":490934,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14HVQHW","text":"USGS data release","linkHelpText":"North American Bat Monitoring Program (NABat) OneHealth (ver. 2.0, June 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Patrick","contributorId":353945,"corporation":false,"usgs":false,"family":"Pollock","given":"Patrick","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":934787,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schuhmann, Andrea Nichole 0009-0005-8244-4303","orcid":"https://orcid.org/0009-0005-8244-4303","contributorId":329059,"corporation":false,"usgs":true,"family":"Schuhmann","given":"Andrea","email":"","middleInitial":"Nichole","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":934788,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tousley, Frank Charles 0000-0002-6859-7558","orcid":"https://orcid.org/0000-0002-6859-7558","contributorId":304216,"corporation":false,"usgs":true,"family":"Tousley","given":"Frank","middleInitial":"Charles","affiliations":[{"id":291,"text":"Fort Collins Science 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,{"id":70265231,"text":"70265231 - 2025 - Linking environmental variability to long-term demographic change of an endangered species using integrated population models","interactions":[],"lastModifiedDate":"2025-05-12T15:43:41.572164","indexId":"70265231","displayToPublicDate":"2025-03-21T09:21:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Linking environmental variability to long-term demographic change of an endangered species using integrated population models","docAbstract":"<ol class=\"\"><li>Understanding how species populations change with environmental conditions is important for implementing effective habitat management and conservation strategies. Challenges to evaluating population-level responses to environmental conditions arise when data are sparse or not spatiotemporally aligned, especially for at-risk species with small, declining numbers.</li><li>We synthesized 30 years (1992–2021) of three partially aligned data sets to build a Bayesian integrated population model (IPM) and evaluate demographic and environmental drivers of growth rates for six separately managed ‘subpopulations’ (A–F) of the federally endangered Cape Sable seaside sparrow endemic to the Florida Everglades.</li><li>We found that juvenile survival peaked at inundation periods (hydroperiods) around 100–220 days and dropped sharply outside those values, while adult survival increased with longer periods of water depth &lt;20 cm, but not with longer periods of water depth &gt;20 cm. Fecundity increased when water depths were more stable, more area was dry, intervals between fires were longer and less area was burned.</li><li>Changes in population growth rates tended to occur in years that juvenile and adult survival were associated with hydroperiod, especially in the two largest subpopulations B and E. Population growth rates were also associated with hydrologic conditions during the breeding season and fire dynamics through changes in fecundity, most notably in the smaller subpopulations A, C/F and D.</li><li><i>Synthesis and applications</i>. Our IPM represents the first long-term population analysis of the Cape Sable seaside sparrow connecting demographic processes to environmental factors. Our results suggest that sustaining periods of shallow water year-round may enhance Cape Sable seaside sparrow survival and population growth. Also, limiting water depth variability and maintaining dry conditions during the breeding season and inhibiting fires in consecutive years may increase fecundity and population growth. Identifying the mechanistic links between environmental and population dynamics could inform how species are expected to respond to management decisions and anticipated ecosystem changes.</li></ol>","language":"English","publisher":"British Ecological Society","doi":"10.1111/1365-2664.70038","collaboration":"U.S. Fish and Wildlife Service, National Park Service","usgsCitation":"Martinez, M.T., D’Acunto, L., and Romanach, S., 2025, Linking environmental variability to long-term demographic change of an endangered species using integrated population models: Journal of Applied Ecology, v. 62, no. 5, p. 1137-1151, https://doi.org/10.1111/1365-2664.70038.","productDescription":"15 p.","startPage":"1137","endPage":"1151","ipdsId":"IP-163974","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488471,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.70038","text":"Publisher Index Page"},{"id":484130,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -81.27756478832899,\n              25.9167\n            ],\n            [\n              -81.27756478832899,\n              25.0833\n            ],\n            [\n              -80.40679117600436,\n              25.0833\n            ],\n            [\n              -80.40679117600436,\n              25.9167\n            ],\n            [\n              -81.27756478832899,\n              25.9167\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"62","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Martinez, Marisa Takada 0000-0002-1915-6019","orcid":"https://orcid.org/0000-0002-1915-6019","contributorId":304805,"corporation":false,"usgs":true,"family":"Martinez","given":"Marisa","email":"","middleInitial":"Takada","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D’Acunto, Laura 0000-0001-6227-0143","orcid":"https://orcid.org/0000-0001-6227-0143","contributorId":215343,"corporation":false,"usgs":true,"family":"D’Acunto","given":"Laura","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Romanach, Stephanie 0000-0003-0271-7825","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":223479,"corporation":false,"usgs":true,"family":"Romanach","given":"Stephanie","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":932553,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70264694,"text":"ofr20251004 - 2025 - Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States","interactions":[],"lastModifiedDate":"2025-03-26T19:46:15.392167","indexId":"ofr20251004","displayToPublicDate":"2025-03-20T13:10:17","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":"2025-1004","displayTitle":"Science Needs for Determining the Effects of Climate Change on Harmful Algal Blooms in the Southeastern United States","title":"Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States","docAbstract":"<p>The Southeastern United States has many lakes, streams, and reservoirs that serve as important drinking water sources with recreational, agricultural, and ecological uses. However, harmful algal blooms (HABs) are becoming more common in these waters, causing health issues for humans and animals. HABs have been listed as a contaminant of emerging concern, and the magnitude, frequency, and duration of HABs appear to be increasing at the global scale. While it is well known that nutrients stimulate algae growth, it is not clear how climate change and other parameters stimulate the development of toxin production by HABs. The scientific literature describes parameters, such as storm occurrence, temperature, dissolved metals, erosion of soils, increasing length of growing season, discharge, and hydroperiod, that may affect algae growth and toxin production. Climate and hydrologic models address many of the physical and environmental parameters that influence HABs, but no climate models directly address HABs. This report compiles information from the existing literature pertaining to HABs and the modeling and forecasting of HABS. This compilation is done through the incorporation of climate change models. HAB research that involves climate change will require multiple disciplines that bring together ecologists, hydrologists, climatologists, engineers, economists, and new technology. Resource managers could use geographic data about the occurrence and distribution of HABs to develop models that identify waterbodies more vulnerable to HAB events. Development of such models will require teams capable of integrating biological, chemical, and physical factors. Model development will require additional research that can resolve anthropogenic and climate-related environmental factors to identify trends in freshwater HABs. The complexity and interconnectedness of the parameters that influence HAB occurrences will make model development challenging and require rigorous regional calibration.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251004","issn":"2331-1258","collaboration":"Prepared in cooperation with the Southeast Climate Adaptation Science Center and  Tennessee State University","usgsCitation":"Byl, T.D., Moore, D.M., Cunningham, C., and Young, D., 2025, Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States: U.S. Geological Survey Open-File Report 2025–1004, 29 p., https://doi.org/10.3133/ofr20251004.","productDescription":"vii, 29 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-156959","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":483554,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251004/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1004 HTML"},{"id":483549,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1004/coverthb.jpg"},{"id":483553,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1004/ofr20251004.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1004 XML"},{"id":483551,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1004/ofr20251004.pdf","size":"7.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1004"},{"id":483550,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1004/images"}],"contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\" href=\"https://www.usgs.gov/centers/lmg-water/\">Lower Mississippi-Gulf Water Science Center</a><br>U.S. Geological Survey<br>640 Grassmere Park, Suite 100<br>Nashville, TN 37211<br></p><p><a id=\"LPlnkOWAb30f03cb-e6c0-c412-988f-235c353ce0b0\" class=\"OWAAutoLink\" href=\"https://pubs.usgs.gov/contact\" data-auth=\"NotApplicable\" data-olk-copy-source=\"MailCompose\" data-mce-href=\"../contact\">Contact Us- USGS Publications Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Background on HABs and Cyanobacteria</li><li>Drivers of HAB Events</li><li>Development of Models</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2025-03-20","noUsgsAuthors":false,"publicationDate":"2025-03-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Byl, Tom D. 0000-0001-6907-9149","orcid":"https://orcid.org/0000-0001-6907-9149","contributorId":352440,"corporation":false,"usgs":true,"family":"Byl","given":"Tom D.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":931296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moore, Devin M. 0009-0003-6919-8625","orcid":"https://orcid.org/0009-0003-6919-8625","contributorId":352441,"corporation":false,"usgs":false,"family":"Moore","given":"Devin M.","affiliations":[{"id":13370,"text":"Tennessee State University","active":true,"usgs":false}],"preferred":true,"id":931297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cunningham, Champagne 0000-0001-6318-5434","orcid":"https://orcid.org/0000-0001-6318-5434","contributorId":352442,"corporation":false,"usgs":true,"family":"Cunningham","given":"Champagne","affiliations":[],"preferred":true,"id":931301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, De’Etra","contributorId":352443,"corporation":false,"usgs":false,"family":"Young","given":"De’Etra","affiliations":[{"id":13370,"text":"Tennessee State University","active":true,"usgs":false}],"preferred":true,"id":931300,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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