Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225
The geologic history and anthropogenic modifications of Minnesota’s Wild Rice River have caused major morphological adjustments, which induce erosion and excess fluvial sediment transport. The excess sediment deposits in the lower Wild Rice River, exacerbating flooding. To help mitigate these problems, the Wild Rice Watershed District has future plans to implement a river restoration on the lower Wild Rice River. The Wild Rice Watershed District collaborated with the U.S. Geological Survey to measure and analyze sediment transport along the Wild Rice River’s Main and South Branches to assess any potential changes in sediment transport among sites and time periods. Time differencing results indicated that all suspended-sediment constituents showed a significant difference between the two sampling periods at one South Branch site but not at the Main Branch site. Piecewise regression analysis better matched the suspended-sediment constituents transport process at most sites by differentiating no relation between suspended-sediment constituents at lower streamflows and a positive relation at higher streamflows at most Wild Rice River sites. Five of the sites showed elevated sediment transport with increasing streamflow. In contrast, the site farthest downstream showed a negative relation with increasing streamflow, indicating that that the lower Wild Rice River is supply limited and deposition is likely occurring upstream and (or) near the site. Overall, the uncertainty in results indicates the complexity of sediment transport in a river when using streamflow as the sole explanatory variable and suggests a need for multisite, multiyear, and multifaceted data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251008","collaboration":"Prepared in cooperation with the Wild Rice Watershed District","usgsCitation":"Groten, J.T., Levin, S.B., Storey, G.G., Coenen, E.N., Blount, J.D., Lund, J.W., and Brannon, D.J., 2025, Suspended sediment and bedload transport along the Main and South Branches, Wild Rice River, northwestern Minnesota, 1979 through 2023: U.S. Geological Survey Open-File Report 2025–1008, 38 p., https://doi.org/10.3133/ofr20251008.","productDescription":"Report: vii, 38 p.; Dataset","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-154644","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":493754,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118525.htm","linkFileType":{"id":5,"text":"html"}},{"id":483763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1008/coverthb.jpg"},{"id":483764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1008/ofr20251008.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1008"},{"id":483765,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1008/ofr20251008.XML"},{"id":483766,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1008/images/"},{"id":483767,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":483768,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251008/full"}],"country":"United States","state":"Minnesota","otherGeospatial":"Wild Rice River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97,\n 47.5833\n ],\n [\n -97,\n 47\n ],\n [\n -95.25,\n 47\n ],\n [\n -95.25,\n 47.5833\n ],\n [\n -97,\n 47.5833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
Water temperature can vary substantially even across short distances within the same sub-watershed. Accurate prediction of stream water temperature at fine spatial resolutions (i.e., fine scales, ≤ 1 km) enables precise interventions to maintain water quality and protect aquatic habitats. Although spatiotemporal models have made substantial progress in spatially coarse time series modeling, challenges persist in predicting at fine spatial scales due to the lack of data at that scale. To address the problem of insufficient fine-scale data, we propose a Multi-Scale Graph Learning (MSGL) method. This method employs a multi-task learning framework where coarse-scale graph learning, bolstered by larger datasets, simultaneously enhances fine-scale graph learning. Although existing multi-scale or multi-resolution methods integrate data from different spatial scales, they often overlook the spatial correspondences across graph structures at various scales. To address this, our MSGL introduces an additional learning task, cross-scale interpolation learning, which leverages the hydrological connectedness of stream locations across coarse- and fine-scale graphs to establish cross-scale connections, thereby enhancing overall model performance. Furthermore, we have broken free from the mindset that multi-scale learning is limited to synchronous training by proposing an Asynchronous Multi-Scale Graph Learning method (ASYNC-MSGL). Extensive experiments demonstrate the state-of-the-art performance of our method for anti-sparse downscaling of daily stream temperatures in the Delaware River Basin, USA, highlighting its potential utility for water resources monitoring and management.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the AAAI conference on artificial intelligence","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Association for the Advancement of Artificial Intelligence","doi":"10.1609/aaai.v39i27.35014","usgsCitation":"Fan, Y., Yu, R., Barclay, J.R., Appling, A.P., Sun, Y., Xie, Y., and Jia, X., 2025, Multi-Scale Graph Learning for anti-sparse downscaling, in Proceedings of the AAAI conference on artificial intelligence, v. 39, no. 27, p. 27969-27977, https://doi.org/10.1609/aaai.v39i27.35014.","productDescription":"9 p.","startPage":"27969","endPage":"27977","ipdsId":"IP-167502","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":497731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1609/aaai.v39i27.35014","text":"Publisher Index Page"},{"id":497583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"27","noUsgsAuthors":false,"publicationDate":"2025-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Fan, Yingda","contributorId":352470,"corporation":false,"usgs":false,"family":"Fan","given":"Yingda","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yu, Runlong 0000-0003-4080-2377","orcid":"https://orcid.org/0000-0003-4080-2377","contributorId":352471,"corporation":false,"usgs":false,"family":"Yu","given":"Runlong","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barclay, Janet R. 0000-0003-1643-6901 jbarclay@usgs.gov","orcid":"https://orcid.org/0000-0003-1643-6901","contributorId":222437,"corporation":false,"usgs":true,"family":"Barclay","given":"Janet","email":"jbarclay@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":952393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":952394,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sun, Yiming","contributorId":352472,"corporation":false,"usgs":false,"family":"Sun","given":"Yiming","affiliations":[{"id":84236,"text":"Department of Computer Science, University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":952395,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xie, Yiqun","contributorId":297447,"corporation":false,"usgs":false,"family":"Xie","given":"Yiqun","email":"","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":952396,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":952397,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70265521,"text":"ofr20251010 - 2025 - Benthic habitat map of Olowalu Reef, Maui, Hawaii—Geomorphological structure, biological cover, and geologic zonation determined with spectral, lidar, and acoustic data","interactions":[],"lastModifiedDate":"2025-08-07T20:42:30.599263","indexId":"ofr20251010","displayToPublicDate":"2025-04-10T14:01:28","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":"2025-1010","displayTitle":"Benthic Habitat Map of Olowalu Reef, Maui, Hawaii—Geomorphological Structure, Biological Cover, and Geologic Zonation Determined with Spectral, Lidar, and Acoustic Data","title":"Benthic habitat map of Olowalu Reef, Maui, Hawaii—Geomorphological structure, biological cover, and geologic zonation determined with spectral, lidar, and acoustic data","docAbstract":"The fringing coral reef off Olowalu, Maui, Hawaii, has been identified as a local conservation priority site. In 2007, the National Oceanic and Atmospheric Administration (NOAA) produced a benthic habitat map of the Hawaiian Islands that was used as a foundation for this study. To support place-based management of the reef in the future, the U.S. Geological Survey (USGS) mapped the geologic zone, major and dominant geomorphological structure, biological cover type, and percent of biological cover for 11 square kilometers (km2) of Olowalu Reef at a minimum mapping unit (MMU) of 100 square meters (m2) to create a benthic habitat map. Heads-up digitization was employed on 0.50-meter (m) natural color satellite orthoimagery with ancillary 1-m acoustic backscatter imagery from single-scan sonar (sound navigation and ranging). A 1-m, 4-m, and 8-m digital bathymetric model (DBM) was interpolated from bathymetric lidar (light detection and ranging), and various geomorphometric layers derived from the DBMs were used for habitat interpretation. Still-frame imagery of the seafloor extracted from vessel-towed underwater video transects on Olowalu Reef served as ground validation points (n=870) during active mapping and accuracy assessment points (n=216) for thematic accuracy assessment. Thematic accuracy was cross-validated by the Hawai‘i Department of Land and Natural Resources Division of Aquatic Resources. Final thematic accuracy was 88.8 percent for major structure, 85.6 percent for dominant structure, 86.0 percent for major biological cover, and 78.6 percent for type and percent of major biological cover. Reef and hardbottom constituted 52 percent of the total mapped habitat, comprising mostly aggregate reef (31 percent) and pavement (11 percent), with large swaths of spur-and-groove (9 percent). Of this hardbottom, 17 percent was covered with moderate (10 to <50 percent) coral and 27 percent with high coral cover (50 to <90 percent). High (50 to <90 percent) macroalgae cover dominated the continuous sand sheets in offshore bank/shelf zones.
The map created in this study supplements the NOAA 2007 map and expands on the observations made by USGS sampling of the reef. The NOAA 2007 map and our map differed in total areal extent by a negligible 6 m2 and were in general thematic agreement. Our map is intended to serve as a baseline for public access, general research, local-level management, and reef change for future studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251010","usgsCitation":"Heberer, L.N., Alkins, K.A., Storlazzi, C.D., Cochran, S.A., Gibbs, A.E., Sparks, R., Stone, K., Silva, I., Martinez, T., Peralto, C., Levine, A.S., Stow, D., and Maloney, J., 2025, Benthic Habitat Map of Olowalu Reef, Maui, Hawaii—Geomorphological Structure, Biological Cover, and Geologic Zonation Determined with Spectral, Lidar, and Acoustic Data: U.S. Geological Survey Open-File Report 2025–1010, 32 p., https://doi.org/10.3133/ofr20251010.","productDescription":"Report: vi, 32 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-152179","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":493749,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118524.htm","linkFileType":{"id":5,"text":"html"}},{"id":484394,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ICJ7CF","text":"USGS Data Release","description":"Heberer, L.N., Alkins, K.A., Storlazzi, C.D., Cochran, S.A., Gibbs, A.E., Sparks, R., Silva, I., Stone, K., Martinez, T., and Peralto, C., 2025, Benthic habitat map of the geomorphological structure, biological cover, and geologic zonation of Olowalu reef, Maui: U.S. Geological Survey data release, https://doi.org/10.5066/P9ICJ7CF.","linkHelpText":"Benthic habitat map of the geomorphological structure, biological cover, and geologic zonation of Olowalu reef, Maui"},{"id":484407,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1010/covrthb.jpg"},{"id":484408,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1010/ofr20251010.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui, Olowalu Reef","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.66330945257621,\n 20.84439182546096\n ],\n [\n -156.66330945257621,\n 20.763341421657273\n ],\n [\n -156.5212712939503,\n 20.763341421657273\n ],\n [\n -156.5212712939503,\n 20.84439182546096\n ],\n [\n -156.66330945257621,\n 20.84439182546096\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
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Invasive carps continue to spread across the Mississippi River basin, posing significant ecological risk. Identifying technologies to slow their dispersal is critical. The use of sound has been proposed as a method to modify the behavior of Silver Carp Hypophthalmichthys molitrix, offering a nonstructural deterrent strategy.
Silver Carp implanted with acoustic transmitters were released into earthen ponds equipped with telemetry arrays. The fish were exposed to a 30-min playback of three underwater sounds (chirp saw, chirp square, and 100-hp boat motor). Movement trajectories were analyzed using a two-state hidden Markov model to estimate the effects of environmental and experimental variables on fish behavior.
The results of the hidden Markov model supported two behavioral states. State 1 was characterized by longer step lengths (distance between positions) and greater directional persistence in turning angle (change in direction between two intervals), indicative of heighted activity. State 2 was defined by shorter step lengths and less directional persistence, suggesting reduced activity. Silver Carp that were exposed to the chirp square sound had an increased likelihood of entering state 1, whereas the 100-hp boat motor sound promoted transitions to state 2.
Underwater sounds distinctly influenced the movement of Silver Carp in earthen ponds. The chirp square sound elicited heightened activity levels, demonstrating potential for use in acoustic deterrent applications. However, the response of Silver Carp to these sounds may be influenced by the size of the study environment or the absence of natural drivers of fish behavior, such as food or reproduction. This study contributes to the development of nonstructural, species-specific deterrent systems by identifying sounds that influence the behavior of invasive carps. The application of sound-based methods may play a critical role in integrated pest management strategies for invasive carps, potentially limiting their spread while minimizing effects on native species.
Infrastructure along the U.S.-Mexico Border may not be equally permeable to all types of insect pollinators with potential implications for pollen and gene flow between plant populations. Pollinators were observed on their approach to two types of border barriers (slatted and cemented) along the U.S.-Mexico Border from March 2023 to January 2024. Near the barrier, four insect behaviors were observed including 1) flying over the barrier, 2) crossing through the slats of the barrier, 3) not crossing the barrier, or 4) flying parallel to the barrier without crossing. Overall, 90.2% of the pollinators crossed the barrier. Butterflies were most often observed flying over the barrier (86.8%) or sometimes moving through the slats in the barrier (6.8%). It was more common for moths to crawl through the slats than to fly over the barrier based on the occurrence model. On windy days, both butterflies and moths sometimes flew parallel to the barrier without crossing (1.2% and 27.3%, respectively), although moth crossing behavior was not related to the abundance model. Butterfly abundance increased in higher temperatures and decreased in higher wind speeds. Other insect pollinators were also observed (bee, skipper, wasp) but their crossing behavior was not significantly related to the model. Because pollinators support endangered plant species, strategies to facilitate their barrier crossing could support plant conservation in South Texas.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113421","usgsCitation":"Middleton, B., 2025, Insect pollinator crossing of international border barriers along the U.S.-Mexico border: Ecological Indicators, v. 174, 113421, 6 p., https://doi.org/10.1016/j.ecolind.2025.113421.","productDescription":"113421, 6 p.","ipdsId":"IP-168032","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488481,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113421","text":"Publisher Index Page"},{"id":484840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Lower Rio Grande Valley National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.55875994836624,\n 26.271404139036903\n ],\n [\n -98.55875994836624,\n 26.132429205423236\n ],\n [\n -98.36350337883496,\n 26.132429205423236\n ],\n [\n -98.36350337883496,\n 26.271404139036903\n ],\n [\n -98.55875994836624,\n 26.271404139036903\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.13781819292579,\n 26.51105231424154\n ],\n [\n -99.13781819292579,\n 26.361351232862546\n ],\n [\n -98.94225679147117,\n 26.361351232862546\n ],\n [\n -98.94225679147117,\n 26.51105231424154\n ],\n [\n -99.13781819292579,\n 26.51105231424154\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"174","noUsgsAuthors":false,"publicationDate":"2025-04-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Middleton, Beth 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":222689,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":934236,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70265711,"text":"70265711 - 2025 - Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California","interactions":[],"lastModifiedDate":"2025-04-15T15:03:17.346697","indexId":"70265711","displayToPublicDate":"2025-04-10T07:58:12","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2588,"text":"LITHOS","active":true,"publicationSubtype":{"id":10}},"title":"Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California","docAbstract":"The Mountain Pass carbonatite stock is the largest rare earth element (REE) deposit and only active REE mine in the United States. The carbonatite intrusion and spatially associated alkaline silicate intrusions constitute the Mountain Pass Intrusive Suite, which is located within the Mojave Province in California. Both the carbonatite and the alkaline silicate rocks are enriched in large ion lithophile elements and light REEs, and less enriched to depleted in high field strength elements, indicating the mantle source region was metasomatically enriched in incompatible trace elements. The cause of this metasomatic mantle enrichment and the genetic relationship between the carbonatite and the alkaline silicate stocks are poorly understood. In this study, major and trace element geochemical data and isotopic (Rb-Sr, Sm-Nd, and Lu-Hf) data are presented to constrain genesis of the Mountain Pass Intrusive Suite, from mantle source region to the intrusion of the stocks. Our geochemical data are consistent with derivation of the alkaline silicate and carbonatite melts through partial melting from a shared mantle source region rather than through liquid immiscibility or fractional crystallization and separation of a carbothermal fluid. Although the Rb-Sr isotopic system in the Mountain Pass Intrusive Suite is disturbed at the whole-rock scale, the isotopic systems for whole-rock Sm-Nd (εNdi = ‐2.2 ± 0.8) and zircon Lu-Hf (εHfi = 0.1 ± 1.1) are robust and support mantle derivation of the magmas. Geochemical modeling using experimentally derived partition coefficients was used to identify possible causes of enrichment in incompatible elements through metasomatism in the mantle source region. Modeling of metasomatism by melts derived by partial melting of deeply subducted carbonated sediments approximates observed Mountain Pass Intrusive Suite trace element chemistry. Scattered εHfi in inherited zircon (2.8 ± 2.6) is consistent with derivation from an arc-related environment with substantial crustal contamination. Paleotectonic studies in the Mojave Province indicate that regional subduction preceded emplacement of the Mountain Pass Intrusive Suite by ∼300 Ma. Melting of the Mountain Pass source region may have been caused by post-collisional thermal relaxation and extension.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2025.108060","usgsCitation":"Benson, E.K., Watts, K., and Hillenbrand, I.W., 2025, Geochemistry and radiogenic isotopes constrain the mantle source region of the Mountain Pass Intrusive Suite, California: LITHOS, v. 508-509, 108060, 18 p., https://doi.org/10.1016/j.lithos.2025.108060.","productDescription":"108060, 18 p.","ipdsId":"IP-173126","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":488251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.lithos.2025.108060","text":"Publisher Index Page"},{"id":484582,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.29333455287775,\n 36.19312110709426\n ],\n [\n -116.29333455287775,\n 34.7648602212238\n ],\n [\n -114.67184767081949,\n 34.7648602212238\n ],\n [\n -114.67184767081949,\n 36.19312110709426\n ],\n [\n -116.29333455287775,\n 36.19312110709426\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"508-509","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Benson, Erin Kay 0000-0003-3166-6043","orcid":"https://orcid.org/0000-0003-3166-6043","contributorId":346098,"corporation":false,"usgs":true,"family":"Benson","given":"Erin","email":"","middleInitial":"Kay","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":933365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watts, Kathryn E. 0000-0002-6110-7499","orcid":"https://orcid.org/0000-0002-6110-7499","contributorId":204344,"corporation":false,"usgs":true,"family":"Watts","given":"Kathryn E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":933366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hillenbrand, Ian William 0000-0003-2801-3674","orcid":"https://orcid.org/0000-0003-2801-3674","contributorId":299032,"corporation":false,"usgs":true,"family":"Hillenbrand","given":"Ian","email":"","middleInitial":"William","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":933367,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265548,"text":"70265548 - 2025 - The mountains are calling, but will visitors go? Modeling the effect of weather and air quality on visitation to Pacific Northwest parks and protected areas using mobile device data","interactions":[],"lastModifiedDate":"2025-04-14T15:58:28.046525","indexId":"70265548","displayToPublicDate":"2025-04-09T10:55:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16703,"text":"PLOS Climate","active":true,"publicationSubtype":{"id":10}},"title":"The mountains are calling, but will visitors go? Modeling the effect of weather and air quality on visitation to Pacific Northwest parks and protected areas using mobile device data","docAbstract":"We investigated how visitors to federal, state, and local parks and protected areas (PPAs) respond to weather and air quality conditions in the Pacific Northwest (PNW), United States. Specifically, we modeled the relationship between weekly visitation and mean weekly minimum and maximum temperature, precipitation, Air Quality Index (AQI), and particulate matter 2.5 concentration (PM2.5, often used as an indicator of wildfire smoke) during an extended peak visitation season from 2017 to 2021 in 91 PNW PPAs. We used mobile device data from StreetLight Data Inc. to estimate weekly vehicular visitation. Our findings indicate that increasing precipitation corresponded with decreased weekly visitation to all three types of PPAs and rising minimum temperatures corresponded with increased visitation. We found that rising maximum temperatures corresponded with increased visitation in federal and local PPAs, but corresponded with decreased visitation in local PPAs once temperatures reach a maximum threshold. We did not observe a maximum threshold effect in federal or state settings. Further, we found that the effect of air quality and smoke on visitation varies based on the metric used: increased PM2.5 concentrations (possibly indicating the presence of wildfire smoke) in federal and local PPAs corresponded with decreased visitation, while increased AQI in federal PPAs corresponded with increased visitation. These findings indicate that visitors may respond differently to different types of air pollution. Our results have implications for adapting peak- and shoulder- season visitor use management to current and future climate change within and beyond PPAs of the PNW.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pclm.0000537","usgsCitation":"Minehart, K., D'Antonio, A., and Wilkins, E.J., 2025, The mountains are calling, but will visitors go? Modeling the effect of weather and air quality on visitation to Pacific Northwest parks and protected areas using mobile device data: PLOS Climate, v. 4, no. 4, e0000537, 22 p., https://doi.org/10.1371/journal.pclm.0000537.","productDescription":"e0000537, 22 p.","ipdsId":"IP-167823","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pclm.0000537","text":"Publisher Index Page"},{"id":484508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, 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\"}}]}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Minehart, Kira 0009-0006-6007-0782","orcid":"https://orcid.org/0009-0006-6007-0782","contributorId":353124,"corporation":false,"usgs":false,"family":"Minehart","given":"Kira","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":933006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"D'Antonio, Ashley","contributorId":353127,"corporation":false,"usgs":false,"family":"D'Antonio","given":"Ashley","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":933007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkins, Emily J. 0000-0003-3055-4808","orcid":"https://orcid.org/0000-0003-3055-4808","contributorId":328409,"corporation":false,"usgs":true,"family":"Wilkins","given":"Emily","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":933008,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271313,"text":"70271313 - 2025 - Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management","interactions":[],"lastModifiedDate":"2025-09-04T15:13:46.061817","indexId":"70271313","displayToPublicDate":"2025-04-09T08:06:56","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management","docAbstract":"The San Joaquin Valley (SJV) of California is one of the world’s most productive agricultural regions. Reliance on groundwater has led to some of the greatest rates of human-induced land subsidence in the world in the 20th century, as well as more recently. The United States Geological Survey (USGS) has recently developed an integrated surface–subsurface hydrologic model, the Central Valley Hydrologic Model 2 (CVHM2), that represents the major components of the hydrologic system of California’s Central Valley. In this study, CVHM2 was applied as a decision support tool while simulating various management strategies to mitigate the land subsidence caused by the extraction of groundwater. CVHM2 was extended through to 2073 and applied to simulate management scenarios in terms of three primary drivers and their impact on subsidence along the Delta–Mendota Canal (DMC), a critical piece of infrastructure in the western SJV. The drivers considered were agricultural water demands, managed aquifer recharge (MAR), and changes in future climate. The results show that future subsidence is most sensitive to water demands, second most sensitive to future changes in climate, and relatively insensitive to MAR when it is applied as a surface application in the western SJV. However, we demonstrate via proof-of-concept scenarios that the MAR is capable of arresting subsidence when implemented via injection below the Corcoran Clay Member of the Tulare Formation instead of as a surface application. We also examine the uncertainty that is the result of climate variability and how to use the tool to identify the most appropriate strategies to constrain future subsidence to acceptable levels.
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The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Rhode Island. The status of available and in-progress 3DEP baseline lidar data in Rhode Island is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 (https://www.usgs.gov/3dep/lidarspec) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $178,560 in new benefits annually to the State. The top 10 Rhode Island business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.
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U.S. Geological Survey, MS 511
12201 Sunrise Valley Drive
Reston, VA 20192
Email: 3DEP@usgs.gov
","tableOfContents":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Understanding fine-scale habitat selection of endangered Kootenai River white sturgeon (Acipenser transmontanus) is an important component for monitoring and recovery efforts. Fine-scale habitat selection and quantifying temporal changes in suitable habitat contributes to the work of addressing recruitment failure within the Kootenai River population. Habitat suitability indices were developed using over 96 000 acoustic telemetry sturgeon detections and two-dimensional hydrodynamic model simulations near Bonners Ferry, Idaho, USA. The selected habitat was assessed to develop habitat suitability indices for sturgeon; females undergoing spawn migrations and non-spawners. The most frequented locations were 8–9 m deep and water velocities of 0.3–0.7 m·s−1. These observations suggest sturgeon with different spawning capabilities selected similar habitat. Weighted usable area was calculated to understand temporal variability in habitat quality, which showed a positive relationship with increases in flow. Results help understand the habitat limiting factors in regulated hydrologic regimes; provide biologists insight for monitoring efforts in discrete habitat conditions; guidance for water managers and the regulation of upstream water resources; and guidance to restoration practitioners for in-stream structure designs.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2024-0244","usgsCitation":"Dudunake, T., Kenworthy, M.K., Smith, T., Stephenson, S., and Hardy, R.S., 2025, Influence of local river hydraulics on Kootenai River white sturgeon (Acipenser transmontanus) habitat selection during four spawning years, 2017–2020: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, 16 p., https://doi.org/10.1139/cjfas-2024-0244.","productDescription":"16 p.","ipdsId":"IP-150378","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":488244,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2024-0244","text":"Publisher Index Page"},{"id":484574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.30893853974553,\n 48.70438566677956\n ],\n [\n -116.33409421325345,\n 48.70438566677956\n ],\n [\n -116.33409421325345,\n 48.691255343773804\n ],\n [\n -116.30893853974553,\n 48.691255343773804\n ],\n [\n -116.30893853974553,\n 48.70438566677956\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Dudunake, Taylor 0000-0001-7650-2419 tdudunake@usgs.gov","orcid":"https://orcid.org/0000-0001-7650-2419","contributorId":191564,"corporation":false,"usgs":true,"family":"Dudunake","given":"Taylor","email":"tdudunake@usgs.gov","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kenworthy, Megan Kearney 0000-0001-7108-3016","orcid":"https://orcid.org/0000-0001-7108-3016","contributorId":304286,"corporation":false,"usgs":true,"family":"Kenworthy","given":"Megan","email":"","middleInitial":"Kearney","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Troy","contributorId":353368,"corporation":false,"usgs":false,"family":"Smith","given":"Troy","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":933387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephenson, Sarah","contributorId":353369,"corporation":false,"usgs":false,"family":"Stephenson","given":"Sarah","affiliations":[{"id":51972,"text":"British Columbia Ministry of Forests","active":true,"usgs":false}],"preferred":false,"id":933388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardy, Ryan S.","contributorId":167032,"corporation":false,"usgs":false,"family":"Hardy","given":"Ryan","email":"","middleInitial":"S.","affiliations":[{"id":6764,"text":"Idaho Department of Fish and Game, Nampa, Idaho","active":true,"usgs":false}],"preferred":false,"id":933389,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265482,"text":"70265482 - 2025 - How quickly do brook trout lose long-term thermal acclimation?","interactions":[],"lastModifiedDate":"2025-04-08T15:42:42.223359","indexId":"70265482","displayToPublicDate":"2025-04-08T08:37:35","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2476,"text":"Journal of Thermal Biology","active":true,"publicationSubtype":{"id":10}},"title":"How quickly do brook trout lose long-term thermal acclimation?","docAbstract":"Abundances of coldwater adapted stream fish populations are declining largely due to anthropogenic influences, including increased temperature. To persist in streams with unsuitable thermal habitat, fish must move to coldwater patches, acclimate, or adapt to water temperatures above thermal optima. Brook trout, a coldwater adapted salmonid, has previously displayed physiological plasticity and the ability for reversible thermal acclimation when reared at higher temperatures. However, because stream temperatures are not static, it is important to explore the rate at which thermal acclimation occurs to evaluate whether prior thermal experience will influence future thermal performance. To determine the temporal scale in loss of thermal acclimation as water temperatures cool, we acclimated brook trout to three thermal regimes: +0 °C (ambient; mimicking the daily average water temperature of a nearby long-term study site), as well as +2 °C and +4 °C above ambient. After 2 years of being reared under those conditions, fish from the warmer treatments were moved to a common, colder temperature (ambient). We then used critical thermal maximum to measure the loss in acclimation response of fish from each treatment over time. We found that regardless of initial acclimation temperature, thermal tolerance of warm acclimated fish decreased rapidly for 1 week, then gradually decreased, and was completely lost within 42 days. This gradual loss of acclimation may be valuable to persistence in warmer streams and will be important to include in models of the impact climate change has on brook trout and other aquatic ectotherms with significant thermal plasticity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jtherbio.2025.104103","usgsCitation":"O'Donnell, M., Regish, A.M., McCormick, S., and Letcher, B., 2025, How quickly do brook trout lose long-term thermal acclimation?: Journal of Thermal Biology, v. 129, 104103, 7 p., https://doi.org/10.1016/j.jtherbio.2025.104103.","productDescription":"104103, 7 p.","ipdsId":"IP-173670","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":484335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","city":"Whatley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -72.6617758519881,\n 42.46221452312392\n ],\n [\n -72.6617758519881,\n 42.418869656181016\n ],\n [\n -72.59608138561572,\n 42.418869656181016\n ],\n [\n -72.59608138561572,\n 42.46221452312392\n ],\n [\n -72.6617758519881,\n 42.46221452312392\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"129","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Donnell, Matthew J. 0000-0002-9089-2377","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":299019,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Matthew J.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":932809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regish, Amy M. 0000-0003-4747-4265","orcid":"https://orcid.org/0000-0003-4747-4265","contributorId":265360,"corporation":false,"usgs":true,"family":"Regish","given":"Amy","email":"","middleInitial":"M.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, S.D.","contributorId":353071,"corporation":false,"usgs":false,"family":"McCormick","given":"S.D.","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":932811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":932812,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265686,"text":"70265686 - 2025 - A nationwide evaluation of crowd-sourced ambient temperature data","interactions":[],"lastModifiedDate":"2025-04-14T16:38:37.174103","indexId":"70265686","displayToPublicDate":"2025-04-07T09:33:36","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1708,"text":"Frontiers of Environmental Science and Engineering in China","active":true,"publicationSubtype":{"id":10}},"title":"A nationwide evaluation of crowd-sourced ambient temperature data","docAbstract":"Growing concerns about heat in urban areas paired with the sparsity of weather stations have resulted in individuals drawing on data from citizen science sensor networks to fill in data gaps. The PurpleAir are the most widely-used low-cost air quality sensors in the contiguous United States with 14,777 deployed between 1 Jan 2017 and 20 July 2021. Although the air quality data from PurpleAir sensors have been widely studied, less attention has been paid to reported temperature. We compare temperature metrics reported by PurpleAir sensors with a gridded temperature product, the North American Land Data Assimilation System (NLDAS)-2, which although not a gold-standard measure of temperature, is widely used in epidemiologic research. We evaluate the lag between indoor and outdoor PurpleAir temperatures. We report associations of the difference between outdoor PurpleAir temperatures and NLDAS-2 temperatures, an indicator of degradation, and the duration of sensor operation. Finally, based on the temperature range recorded by the outdoor PurpleAir sensors vis.a.vis NLDAS-2 temperatures, we provide a list of 271 (2.5%) sensors potentially misclassified as outdoor and likely located indoors. We observed that outdoor PurpleAir sensors agreed well with NLDAS-2 (R2 > 0.82). This association broke down under warm conditions (daily average NLDAS ≥ 21.1oC). Landcover and climate zone were significant modifiers of the association between PurpleAir and NLDAS-2 temperature metrics with the poorest PurpleAir- NLDAS-2 agreement in urban areas. Indoor PurpleAir temperatures lagged hourly NLDAS temperatures by two hours across almost all climate zones. The mean difference in hourly PurpleAir and NLDAS-2 temperatures increased by 0.57oC for every operational year, suggesting that careful attention must be paid to degradation. Overall, we find for use in epidemiological studies, that the PurpleAir sensor data is a reliable metric of daytime mean air temperature, but researchers should be aware of its limitations when examining extreme heat, or when aggregating sensor data across multiple years.","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2025.1527855","usgsCitation":"deSouza, P., Ibsen, P.C., Westervelt, D., Kahn, R., Zaitchik, B., and Kinney, P., 2025, A nationwide evaluation of crowd-sourced ambient temperature data: Frontiers of Environmental Science and Engineering in China, v. 13, 1527855, 13 p., https://doi.org/10.3389/fenvs.2025.1527855.","productDescription":"1527855, 13 p.","ipdsId":"IP-171526","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":490097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2025.1527855","text":"Publisher Index 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States\"}}]}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"deSouza, Priyanka","contributorId":353306,"corporation":false,"usgs":false,"family":"deSouza","given":"Priyanka","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":933260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":933261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westervelt, Daniel M.","contributorId":353308,"corporation":false,"usgs":false,"family":"Westervelt","given":"Daniel M.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":933262,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kahn, Ralph","contributorId":353311,"corporation":false,"usgs":false,"family":"Kahn","given":"Ralph","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":933263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zaitchik, Benjamin 0000-0002-0698-0658","orcid":"https://orcid.org/0000-0002-0698-0658","contributorId":333708,"corporation":false,"usgs":false,"family":"Zaitchik","given":"Benjamin","email":"","affiliations":[{"id":36717,"text":"Johns Hopkins University","active":true,"usgs":false}],"preferred":false,"id":933264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kinney, Patrick","contributorId":353314,"corporation":false,"usgs":false,"family":"Kinney","given":"Patrick","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":933265,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70265786,"text":"70265786 - 2025 - A synthesis of freshwater forested wetland soil organic carbon storage","interactions":[],"lastModifiedDate":"2025-04-16T14:31:18.998298","indexId":"70265786","displayToPublicDate":"2025-04-07T09:27:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5860,"text":"Frontiers in Forests and Global Change","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of freshwater forested wetland soil organic carbon storage","docAbstract":"Freshwater forested wetlands account for ~76% (918 M ha) of the total global wetland extent. However, freshwater forested wetlands are difficult to distinguish from upland forest due to canopy coverage, the abundance of wetland-nonwetland mosaics, seasonal hydropatterns, and fewer readily observable connections to large surface water bodies relative to marshes and other emergent habitats. Therefore, freshwater forested wetland ecosystems are often misclassified as upland forests in carbon accounting models, underestimating soil organic carbon (SOC) storage. This study highlights freshwater forested wetland SOC accounting challenges and presents SOC densities/stocks from a global literature synthesis across different freshwater forested wetland types. We reviewed 374 forested wetland articles, compiling and calculating carbon densities by depth from 90 freshwater forested wetland studies to construct a database of 334 study sites including nine countries. The median (± median absolute deviation) SOC stock was 91.2 ± 46.4 Mg C ha−1 and 235.3 ± 125.6 Mg C ha−1 in the top 30 cm and 100 cm of soil, respectively. The tidal freshwater forested wetland had highest SOC stock (341.6 ± 98.4 Mg C ha−1) in the upper 100 cm soil profile followed by rainforest (285.6 ± 75.8 Mg C ha−1), non-tidal swamps (229.3 ± 120.4 Mg C ha−1), and floodplain forested wetlands (176.6 ± 84 Mg C ha−1). Within the conterminous United States forest type groups, the Tsuga/Picea group had the highest median SOC stocks (353.6 ± 82.9 Mg ha−1) in the top 100 cm of soil followed by Quercus/Pinus (246.6 ± 82.3 Mg ha−1) and Quercus/Liquidambar/Taxodium (207.9 ± 87.7 Mg ha−1) groups, likely driven by variability in litter degradability, wetland hydroperiod, geomorphic positions, and regional climatic factors. This literature synthesis highlights SOC accounting in freshwater forested wetland carbon pools when estimating carbon stocks and fluxes. Results can be used to improve carbon modeling outcomes, as well as inform regional, national, and global management of wetland carbon resources.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffgc.2025.1528440","usgsCitation":"Sapkota, Y., Berkowitz, J., Stagg, C., and Busby, R., 2025, A synthesis of freshwater forested wetland soil organic carbon storage: Frontiers in Forests and Global Change, v. 8, 1528440, 15 p., https://doi.org/10.3389/ffgc.2025.1528440.","productDescription":"1528440, 15 p.","ipdsId":"IP-176238","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":488264,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffgc.2025.1528440","text":"Publisher Index Page"},{"id":484639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Sapkota, Yadav","contributorId":353419,"corporation":false,"usgs":false,"family":"Sapkota","given":"Yadav","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933528,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkowitz, Jacob F.","contributorId":353422,"corporation":false,"usgs":false,"family":"Berkowitz","given":"Jacob F.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stagg, Camille 0000-0002-1125-7253","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":214880,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":933530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Busby, Ryan R.","contributorId":353425,"corporation":false,"usgs":false,"family":"Busby","given":"Ryan R.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":933531,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273025,"text":"70273025 - 2025 - Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","interactions":[],"lastModifiedDate":"2025-12-15T14:46:55.827369","indexId":"70273025","displayToPublicDate":"2025-04-07T08:38:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","title":"Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon","docAbstract":"The freshwater copepod Salmincola californiensis is an ectoparasite of Pacific salmon and trout (Oncorhynchus spp.). High levels of infection by this parasite can significantly damage gills and result in blood loss, affecting the fitness and survival of hosts, and it may hinder recovery efforts of threatened and endangered salmonids. Juvenile salmonids that rear in reservoirs have been reported to experience higher rates of infection than their stream-dwelling counterparts. To date, the relationship between reservoir environmental conditions and infection rates remains poorly understood. Here, we evaluated sampling methods designed to capture S. californiensis copepodids, the free-swimming infectious life stage of this parasitic copepod, and develop predictive models of parasite abundance in reservoirs. We used light traps to collect 675 zooplankton samples from various sites and depths in Cougar, Lookout Point, and Fall Creek reservoirs, Oregon, USA during five months in 2020. We tested several predictive models of parasite abundance using environmental covariates obtained concurrently during plankton surveys (e.g., temperature, ambient light and water clarity, reservoir plankton profiles, and water flow). Our models showed a strong influence of water temperature on abundance of copepodids, with maximum initial abundance occurring at the mean water temperature 15.2 °C. At that temperature, August abundance was estimated to be 58.6 copepodids per site in Cougar Reservoir, 43.8 copepodids per site in Fall Creek Reservoir, and 3.5 copepodids per site in Lookout Point Reservoir. Water temperature and reservoir outflow both affected population growth of copepodids: increased water temperature was associated with an increase in population growth rate while an increased reservoir outflow was associated with a decrease in population growth rate. The efficacy of our sampling method was influenced by percent of moon fullness, whether the sample site was above or below the thermocline, water temperature, and number of juvenile sculpin fishes (Cottus spp.) captured in the trap. The mean probability of detecting a single copepodid if one was present was 0.042, but detection probability increased to 0.29 under ideal trap set conditions of warmer water, location above the thermocline, and a full moon. Biologists and managers could use these methods to assess the presence and abundance of S. californiensis in other locations, or to inform reservoir operations to reduce potential salmonid infections.
","language":"English","publisher":"Peer J","doi":"10.7717/peerj.19228","usgsCitation":"Antonelli, K., Murphy, C.A., Pollock, A.M., and Arismendi, I., 2025, Environmental conditions influencing the abundance of the salmonid ectoparasite Salmincola californiensis across upper Willamette River Reservoirs, Oregon: Aquatic Biology, v. 13, e19228, 24 p., https://doi.org/10.7717/peerj.19228.","productDescription":"e19228, 24 p.","ipdsId":"IP-172281","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":497701,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.19228","text":"Publisher Index Page"},{"id":497471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"upper Willamette River reservoirs","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.32050813525171,\n 44.19989455893608\n ],\n [\n -123.32050813525171,\n 44.045490802329965\n ],\n [\n -122.8991546943831,\n 44.045490802329965\n ],\n [\n -122.8991546943831,\n 44.19989455893608\n ],\n [\n -123.32050813525171,\n 44.19989455893608\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Antonelli, Kelsi","contributorId":341106,"corporation":false,"usgs":false,"family":"Antonelli","given":"Kelsi","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Christina Amy 0000-0002-3467-6610","orcid":"https://orcid.org/0000-0002-3467-6610","contributorId":335232,"corporation":false,"usgs":true,"family":"Murphy","given":"Christina","email":"","middleInitial":"Amy","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":952113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pollock, Amanda M.M.","contributorId":363932,"corporation":false,"usgs":false,"family":"Pollock","given":"Amanda","middleInitial":"M.M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arismendi, Ivan","contributorId":341108,"corporation":false,"usgs":false,"family":"Arismendi","given":"Ivan","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":952115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70265494,"text":"70265494 - 2025 - Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska","interactions":[],"lastModifiedDate":"2025-04-08T15:11:34.579076","indexId":"70265494","displayToPublicDate":"2025-04-07T08:01:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2328,"text":"Journal of Glaciology","active":true,"publicationSubtype":{"id":10}},"title":"Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska","docAbstract":"The accumulation area ratio (AAR) of a glacier reflects its current state of equilibrium, or disequilibrium, with climate and its vulnerability to future climate change. Here, we present an inventory of glacier-specific annual accumulation areas and equilibrium line altitudes (ELAs) for over 3000 glaciers in Alaska and northwest Canada (88% of the regional glacier area) from 2018 to 2022 derived from Sentinel-2 imagery. We find that the 5 year average AAR of the entire study area is 0.41, with an inter-annual range of 0.25–0.49. More than 1000 glaciers, representing 8% of the investigated glacier area, were found to have effectively no accumulation area. Summer temperature and winter precipitation from ERA5-Land explained nearly 50% of the inter-annual ELA variability across the entire study region (R2 = 0.47). An analysis of future climate scenarios (SSP2-4.5) projects that ELAs will rise by ∼170 m on average by the end of the 21st century. Such changes would result in a loss of 25% of the modern accumulation area, leaving a total of 1900 glaciers (22% of the investigated area) with no accumulation area. These results highlight the current state of glacier disequilibrium with modern climate, as well as glacier vulnerability to projected future warming.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/jog.2024.65","usgsCitation":"Zeller, L., McGrath, D.J., Sass, L., Florentine, C., and Downs, J., 2025, Equilibrium line altitudes, accumulation areas, and the vulnerability of glaciers in Alaska: Journal of Glaciology, v. 71, e28, 13 p., https://doi.org/10.1017/jog.2024.65.","productDescription":"e28, 13 p.","ipdsId":"IP-163494","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":488628,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1017/jog.2024.65","text":"Publisher Index Page"},{"id":484323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":932825,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Florentine, Caitlyn 0000-0002-7028-0963","orcid":"https://orcid.org/0000-0002-7028-0963","contributorId":205964,"corporation":false,"usgs":true,"family":"Florentine","given":"Caitlyn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":932826,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Downs, Jacob 0000-0002-5588-7767","orcid":"https://orcid.org/0000-0002-5588-7767","contributorId":336920,"corporation":false,"usgs":false,"family":"Downs","given":"Jacob","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":932827,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70265447,"text":"70265447 - 2025 - Estimating indicators of cyanobacterial harmful algal blooms in New York State","interactions":[],"lastModifiedDate":"2025-04-07T14:54:27.747567","indexId":"70265447","displayToPublicDate":"2025-04-07T07:50:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Estimating indicators of cyanobacterial harmful algal blooms in New York State","docAbstract":"Cyanobacteria harmful algal blooms (cyanoHABs) are a global concern for aquatic ecosystem and human health. Limited funding for monitoring programs and inconsistent determination of cyanoHAB occurrence present challenges for identifying commonly effective variables for characterizing cyanoHABs and the development of generalized models. We compiled a combination of water quality measurements, lake morphology, climatology, remote sensing data, and observations of cyanoHAB occurrence across New York State and used this dataset to develop two sets of predictive models. The first model predicted chlorophyll a, a common indicator of algal biomass, and assessed the importance of variables for modeled predictions. The most important variables were then used in a second set of models to classify cyanoHAB occurrence. The irradiance attenuation coefficient (Kd), which was estimated from Secchi depth measurements, and total phosphorus were the two most important variables for predicting chlorophyll a. The second model examined several variables for their ability to classify cyanoHAB occurrence. Predicted cyanoHAB occurrence based on thresholds of chlorophyll a, Kd, or total nitrogen all had moderate agreement and were able to correctly classify approximately 70% of observed cyanoHABs. Our analysis indicated that multiple data types were important for predicting chlorophyll a statewide and that simple widely available water quality parameters could classify cyanoHABs occurrence with reasonable accuracy. Identifying variables that can be monitored with increased frequency and decreased latency to detect cyanoHAB occurrence will better inform water managers and provide valuable additional data for further refining predictive models of the likelihood of cyanoHABs occurrence.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2025.113403","usgsCitation":"Savoy, P., Gorney, R.M., and Graham, J.L., 2025, Estimating indicators of cyanobacterial harmful algal blooms in New York State: Ecological Indicators, v. 173, 113403, 11 p., https://doi.org/10.1016/j.ecolind.2025.113403.","productDescription":"113403, 11 p.","ipdsId":"IP-171481","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":488558,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2025.113403","text":"Publisher Index Page"},{"id":484244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New 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York\",\"nation\":\"USA \"}}]}","volume":"173","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Savoy, Philip 0000-0002-6075-837X","orcid":"https://orcid.org/0000-0002-6075-837X","contributorId":300288,"corporation":false,"usgs":true,"family":"Savoy","given":"Philip","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":932740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gorney, Rebecca Michelle 0000-0003-4406-261X","orcid":"https://orcid.org/0000-0003-4406-261X","contributorId":317259,"corporation":false,"usgs":true,"family":"Gorney","given":"Rebecca","email":"","middleInitial":"Michelle","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":932742,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272682,"text":"70272682 - 2025 - Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data","interactions":[],"lastModifiedDate":"2025-12-04T16:46:03.167798","indexId":"70272682","displayToPublicDate":"2025-04-05T10:43:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":18010,"text":"JGR Machine Learning and Computation","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data","docAbstract":"Borehole nuclear magnetic resonance (bNMR) data are typically used to infer in situ hydrologic properties. Partial water content as a function of pore size is estimated by fitting the measured NMR response to a multi-exponential T2 distribution, and the sum of estimated T2 amplitudes equals the total volumetric water content. From these estimated parameters, several empirical relationships are commonly used to infer hydraulic conductivity from the NMR-estimated water content and T2 distribution. Often, parameters are estimated through deterministic inversion methods that produce a single best-fit estimate, but do not reflect uncertainties in model parameters. Here, a Bayesian Markov chain Monte Carlo (McMC) approach for analyzing bNMR data is developed that allows for comprehensive uncertainty quantification of NMR parameters and derived hydrologic properties. The underlying model that describes the T2 distribution is defined by a set of spline interpolation points. The number of interpolation points is allowed to vary in a trans-dimensional algorithm that naturally favors simple models with fewer interpolation points, allowing the data to inform the necessary level of model complexity. Additionally, data error is estimated as an unknown parameter. Analysis of the ensemble of models output from the McMC algorithm provides useful details on the range of plausible T2 distributions that can fit a measured bNMR decay curve, as well as uncertainty estimates of total water content. The ensemble of NMR parameters can also be propagated through commonly used relationships to produce uncertainty estimates on derived parameters such as bound/capillary/mobile water content or hydraulic conductivity.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JH000461","usgsCitation":"Minsley, B.J., Phillips, S.N., and James, S.R., 2025, Uncertainty quantification of geophysical and hydrologic parameters estimated from borehole nuclear magnetic resonance data: JGR Machine Learning and Computation, v. 2, no. 2, e2024JH000461, 15 p., https://doi.org/10.1029/2024JH000461.","productDescription":"e2024JH000461, 15 p.","ipdsId":"IP-171454","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024jh000461","text":"Publisher Index Page"},{"id":497066,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Stephanie N. 0000-0002-2022-7726","orcid":"https://orcid.org/0000-0002-2022-7726","contributorId":214857,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephanie","email":"","middleInitial":"N.","affiliations":[{"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":951327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"James, Stephanie R. 0000-0001-5715-253X","orcid":"https://orcid.org/0000-0001-5715-253X","contributorId":260620,"corporation":false,"usgs":true,"family":"James","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":951328,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70265808,"text":"70265808 - 2025 - Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California","interactions":[],"lastModifiedDate":"2025-04-16T14:10:07.800114","indexId":"70265808","displayToPublicDate":"2025-04-05T09:01:07","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":18346,"text":"EarthArXiv","active":true,"publicationSubtype":{"id":32}},"title":"Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California","docAbstract":"The area surrounding the Salinas Valley groundwater basin in Monterey and San Luis Obispo Counties of California is a highly productive agricultural area, contributes significantly to the local economy, and provides a substantial portion of vegetables and other agricultural commodities to the Nation. This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides significant volumes of agricultural products not just for California but the entire United States. Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface water and groundwater resources in the valley. This has resulted in water management challenges in the Salinas Valley that are predominantly related to distribution of water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. To deal with the distribution issue, historically water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface water supplies are insufficient. Availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand on groundwater and surface water resources throughout the Salinas Valley has resulted in undesirable effects of unsustainable water use, such as surface water depletion, groundwater level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface water and groundwater resources. To meet water demands and reduce undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and a variable climate. To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resource Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley Hydrogeologic system called the Salinas Valley System Model. The Salinas Valley Geologic Framework was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The Salinas Valley Watershed Model simulates the entire Salinas River watershed. Monthly surface water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.
","language":"English","publisher":"Eartharxiv","doi":"10.31223/X5ZD9N","usgsCitation":"Henson, W.R., Hanson, R., Boyce, S.E., Hevesi, J.A., and Jachens, E.R., 2025, Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California: EarthArXiv, https://doi.org/10.31223/X5ZD9N.","productDescription":"312 p.","ipdsId":"IP-172765","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":488263,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.31223/x5zd9n","text":"Publisher Index Page"},{"id":484636,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Henson, Wesley R. 0000-0003-4962-5565 whenson@usgs.gov","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":384,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley","email":"whenson@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, Randy 0000-0002-9819-7141","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":216356,"corporation":false,"usgs":false,"family":"Hanson","given":"Randy","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":933667,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyce, Scott E. 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933668,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hevesi, Joseph A. 0000-0003-2898-1800 jhevesi@usgs.gov","orcid":"https://orcid.org/0000-0003-2898-1800","contributorId":1507,"corporation":false,"usgs":true,"family":"Hevesi","given":"Joseph","email":"jhevesi@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jachens, Elizabeth Rae 0000-0001-5885-8892","orcid":"https://orcid.org/0000-0001-5885-8892","contributorId":294690,"corporation":false,"usgs":true,"family":"Jachens","given":"Elizabeth","email":"","middleInitial":"Rae","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933670,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267524,"text":"70267524 - 2025 - Streamflow response to glacier mass loss varies with basin precipitation across Alaska","interactions":[],"lastModifiedDate":"2025-05-28T14:28:22.882379","indexId":"70267524","displayToPublicDate":"2025-04-04T09:24:54","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Streamflow response to glacier mass loss varies with basin precipitation across Alaska","docAbstract":"Diminishing glaciers affect streamflow, and given the extent of glaciers in Alaska and adjacent Canada, continued glacier mass loss is likely to have profound effects on ecosystems sensitive to runoff. The effects of glacier mass loss on streamflow are likely to vary across the wide ranges of basin size, glacier cover, and precipitation in this region. In this study, we use U.S. Geological Survey (USGS) streamflow data with satellite-based glacier volume change estimates to quantify how glacier mass loss subsidized streamflow over the 2000–2019 period for 116 glacierized basins. We examine interannual variability in that subsidy at three USGS-monitored glaciers to explore the ability of the subsidy to buffer streamflow derived solely from precipitation. We found the relative importance of percent glacier cover on streamflow magnitude increases in drier basins. In the driest basins, glaciers produced 40 times greater percent glacier mass loss subsidies to streamflow for the percent glacier cover compared to the wettest basins. While the subsidy from glacier mass loss buffers interannual variability in streamflow to varying degrees, it can also increase streamflow variability. Smaller amounts of percent glacier cover are needed to produce summer-melt-dominated seasonal flow regimes in drier basins than in wetter basins. Decreasing glacier cover will eventually decrease summer streamflow, increasing spring streamflow in drier basins, and attenuating seasonality with increasing spring and autumnal streamflow in wetter basins. Quantifying the downstream effects of continued glacier mass loss without the computational expense of a hydrological model is broadly applicable in this changing climate.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024WR037859","usgsCitation":"Curran, J.H., Rick, B., Littell, J., and Sass, L., 2025, Streamflow response to glacier mass loss varies with basin precipitation across Alaska: Water Resources Research, v. 61, no. 4, e2024WR037859, 18 p., https://doi.org/10.1029/2024WR037859.","productDescription":"e2024WR037859, 18 p.","ipdsId":"IP-165191","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":490156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024wr037859","text":"Publisher Index Page"},{"id":486640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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space","interactions":[],"lastModifiedDate":"2025-05-23T15:49:02.287668","indexId":"70267440","displayToPublicDate":"2025-04-04T08:37:29","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing control of a freshwater invader in time and space","docAbstract":"The global spread of invasive species in aquatic ecosystems has prompted population control efforts to mitigate negative impacts on native species and ecosystem functions. Removal programs that optimally allocate removal effort across space and time offer promise for improving invader suppression or eradication, especially given the limited resources available to these programs. However, science-based guidance to inform such programs remains limited. This study leverages two intensive fish removal programs for nonnative green sunfish (Lepomis cyanellus) in intermittent streams of the Bill Williams River basin in Arizona, USA, to explore alternative management strategies involving variable allocation of removal effort in time and space and compare static versus dynamic decision rules. We used Bayesian hierarchical modeling to estimate demographic parameters using existing removal data, with evidence that both removal programs led to at least a 0.39 probability of eradication. Simulated alternative management strategies revealed that population suppression, but not eradication, could be achieved with reduced effort, and that dynamic management practices that respond to species abundance in real time can improve the efficiency of removal efforts. High removal frequency and program duration, including continued monitoring after zero fish were captured, contributed to successful population control. With management efforts struggling to keep pace with the rising spread and impacts of invasive species, this research demonstrates the utility of quantitative removal models to help improve invasive removal programs and robustly evaluate the success of population suppression and eradication.","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.70026","usgsCitation":"Diallo, J., Converse, S.J., Chmiel, M., Stites, A., and Olden, J., 2025, Optimizing control of a freshwater invader in time and space: Ecological Applications, v. 35, no. 3, e70026, 17 p., https://doi.org/10.1002/eap.70026.","productDescription":"e70026, 17 p.","ipdsId":"IP-151980","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":487965,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.70026","text":"Publisher Index Page"},{"id":486519,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Bill Williams River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.87855871265536,\n 34.69978264689745\n ],\n [\n -113.87855871265536,\n 34.0589425188774\n ],\n [\n -113.23223159100554,\n 34.0589425188774\n ],\n [\n -113.23223159100554,\n 34.69978264689745\n ],\n [\n -113.87855871265536,\n 34.69978264689745\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"35","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Diallo, Jessica O.","contributorId":355825,"corporation":false,"usgs":false,"family":"Diallo","given":"Jessica O.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":938203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":938204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chmiel, Matthew","contributorId":355827,"corporation":false,"usgs":false,"family":"Chmiel","given":"Matthew","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":938205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stites, Andy","contributorId":355829,"corporation":false,"usgs":false,"family":"Stites","given":"Andy","affiliations":[{"id":12922,"text":"Arizona Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":938206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olden, Julian D.","contributorId":338326,"corporation":false,"usgs":false,"family":"Olden","given":"Julian D.","affiliations":[],"preferred":false,"id":938207,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268269,"text":"70268269 - 2025 - Sprague’s Pipits (Anthus spragueii) occupying high-elevation intermontane valley habitat throughout the breeding season in southwest Montana","interactions":[],"lastModifiedDate":"2025-06-18T15:23:10.932977","indexId":"70268269","displayToPublicDate":"2025-04-04T08:16:12","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3746,"text":"Western North American Naturalist","onlineIssn":"1944-8341","printIssn":"1527-0904","active":true,"publicationSubtype":{"id":10}},"title":"Sprague’s Pipits (Anthus spragueii) occupying high-elevation intermontane valley habitat throughout the breeding season in southwest Montana","docAbstract":"Sprague's Pipit (Anthus spragueii) is an imperiled bird species that breeds in grasslands of the northern Great Plains of North America. While conducting avian surveys in the Centennial Valley, Beaverhead County, southwest Montana, during spring and summer 2023, we detected approximately 10 male Sprague's Pipits performing aerial displays. These represent the first detailed observations of Sprague's Pipits in Beaverhead County, Montana, and the first confirmed observations of territorial displays therein. Subsequent detections included multiple adults, one of which was seen flying with food in its bill. We hypothesize that these observations represent a small but previously undescribed breeding population occurring above 2000 m elevation, which is higher than elevations at which this species is generally thought to breed. Our discovery also expands the known breeding habitat of this species to include intermontane valley bottoms, raising questions of whether the historical range included this habitat prior to its large-scale modifications across western North America and contemporary global change. These additions to our understanding of Sprague's Pipit ecology may be important for both land managers in the region and conservation efforts for this species. The evidence described here, of a breeding population of Sprague's Pipits in the Centennial Valley, Montana, may warrant further investigations in intermontane valleys throughout the region to better understand the breeding extent and the management actions needed to conserve this species and its habitat.
Improved methods for identifying species at risk are needed to strengthen climate change vulnerability assessments, as current estimates indicate that up to one million species face extinction due to environmental changes. Integrating multiple sources of uncertainty enhances the robustness of Red List of Threatened Species assessments, providing a more comprehensive understanding of species’ risks. We present a comprehensive framework that incorporates uncertainties, including measurement error, structural uncertainty, natural variability, future climate emissions scenario, and extreme events of sea ice loss, to evaluate the extinction risk of the emperor penguin (Aptenodytes forsteri), currently classified as Near-Threatened. We apply three ecological models, one bioclimatic and two metapopulation models, combined with a multi-model large ensemble (MMLE) of climate projections from general circulation models, to conduct a Red List evaluation at both global, regional and colony levels. Our results show that emperor penguins could be classified under a range of Red List categories depending on the ecological model, Intergovernmental Panel on Climate Change (IPCC) climate emissions scenario, and extreme event frequency. Under Criterion A, global classifications vary from Vulnerable to Critically Endangered. Severe declines are projected in the Indian and East Pacific sectors, Dronning Maud Land and the Amundsen-Bellingshausen Sea, with Criterion E indicating that 24% to 100% of colonies meet Endangered status thresholds, depending on huddling thresholds and ecological models. This study represents the first application of an MMLE coupled with an ecological ensemble approach to project climate change impacts on a species, capturing a comprehensive range of uncertainties and offering a framework for improving forecasting and decision-making under climate change.
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