The U.S. Geological Survey (USGS) is using collaborative, interdisciplinary planning to develop data and tools needed to optimize the management of water resources and land use by resource management agencies during an ongoing, multidecadal drought in the Colorado River Basin. The USGS Actionable and Strategic Integrated Science and Technology team works to build relationships with resource management agencies and other stakeholders who can benefit from the use of USGS data and products. In 2023, the Actionable and Strategic Integrated Science and Technology team hosted a series of collaborative workshops to bring together representatives of resource management agencies and other stakeholders (any person or entity with interests in a resource or location) with USGS program managers, scientists, and multidisciplinary subject matter experts to codevelop concepts for interdisciplinary drought science and technology projects to address pressing needs related to drought in the Colorado River Basin. Workshop participants identified current and recent scientific data that could be shared through a centralized online data portal. Workshop participants also identified drought science and technology needs and developed project concepts to address those science needs. Participants categorized project concepts based on their potential to develop short-, mid-, and long-term drought science data and tools, provide for the spatial or temporal expansion of ongoing USGS science projects, and address high-priority science needs. Participants developed nine project concepts: (1) understanding shifting ecohydrologic baselines, (2) San Juan River Basin synthesis, (3) incorporating dynamic land cover into hydrologic models, (4) aridification compared to drought, (5) surface water-groundwater interactions, (6) cascading effects of drought on dust, (7) cascading effects of drought on water availability, (8) cascading effects of drought on socioeconomic factors, and (9) the value of water in the Colorado River Basin. This report provides an overview of the 2023 Codesign Workshop Series, synthesized outcomes from workshop materials and discussions, and science project concepts that emerged from the collaborative meetings that will continue to be refined into science project proposals through codevelopment processes. This report also highlights lessons learned and next steps needed to receive feedback and testing of the USGS Science Collaboration Portal, continue collaboration to develop detailed specifics and steps for short-term wins, develop interdisciplinary project proposals, and implement science planning and studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20251041","usgsCitation":"Anderson, P.J., Godaire, J.E., Jones, D.K., Andrews, W.J., Torregrosa, A.A., Bell, M.T., Holloway, J.M., Blakowski, M.A., Hevesi, J.A., and Qi, S.L., 2025, Collaborative drought science planning in the Colorado River Basin: U.S. Geological Survey Open-File Report 2025–1041, 32 p., https://doi.org/10.3133/ofr20251041.","productDescription":"vi, 32 p.","onlineOnly":"Y","ipdsId":"IP-165607","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":494357,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1041/ofr20251041.xml"},{"id":494378,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251041/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1041"},{"id":494325,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1041/ofr20251041.pdf","text":"Report","size":"9.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1041"},{"id":494356,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1041/images"},{"id":494324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1041/coverthb.jpg"}],"country":"Mexico, United States","state":"Arizona, California, Colorado, Nevada, New Mexico, Utah, Wyoming","otherGeospatial":"Colorado River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.23441985470737,\n 42.42360949558767\n ],\n [\n -110.0074572875208,\n 42.9273485741041\n ],\n [\n -110.88201818257588,\n 40.83215412591818\n ],\n [\n -112.09041488325958,\n 37.81270064609009\n ],\n [\n -113.86864235906498,\n 37.77076755792572\n ],\n [\n -113.94586057217214,\n 38.21912009189296\n ],\n [\n -115.10119317735365,\n 39.08121928179544\n ],\n [\n -115.47544949784407,\n 35.429353160164375\n ],\n [\n -115.29249888241867,\n 31.986896837542588\n ],\n [\n -110.42076682180414,\n 30.172954165166573\n ],\n [\n -108.95437388160886,\n 30.991312421045535\n ],\n [\n -108.56364522256465,\n 31.857948821439074\n ],\n [\n -107.84802514114666,\n 32.26017852956302\n ],\n [\n -107.22575341999277,\n 34.155285973008596\n ],\n [\n -107.68523996280838,\n 35.482296714195456\n ],\n [\n -106.46728549757393,\n 37.071939542790304\n ],\n [\n -105.6885671199549,\n 39.88037502712785\n ],\n [\n -106.23441985470737,\n 42.42360949558767\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
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Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland were carried out in July–August 1971 as part of a grant to the University of Oregon Center for Volcanology to refine the models of crystallization and differentiation of the intrusion, specifically to test whether the intrusion is underlain by dense rocks of a reservoir 20 kilometers (km) thick (referred to as a “hidden zone”). The Skaergaard intrusion is a source of platinum group elements that are critical mineral resources for many technologies, and because no new data have been collected these legacy datasets remain a valuable asset. The total-intensity aeromagnetic survey was flown in early July 1971 with a proton precession magnetometer at a constant barometric altitude of 1.5 km (5,000 feet) with a nominal line spacing of 1 km. Two gravimeters were used to acquire 168 stations of which 86 were at known altitudes (mainly sea level) and 82 had altitudes measured by altimetry in late July–August 1971. Finally, a north-south ground vertical-intensity magnetic traverse was completed across the intrusion together with collection of oriented hand specimens. The hand specimens were measured for remnant magnetization and density, along with density measurements of more specimens collected by expedition geologists for other purposes.
The intrusion is composed of layered gabbro with extensive crystal fractionation that is dense and strongly reversely polarized. After terrain correction and standard Bouguer gravity reduction, the gravity anomaly dataset was corrected for all rock above sea level using the density measurements of the various zones of the intrusion and the topographic and geologic maps (variable density Bouguer gravity reduction).
A large regional gradient in the gravity anomaly data was removed using orthogonal polynomial fitting to the gridded data. The zonal volumes of rock below sea level were calculated from the dipping polygonal layer gravity model of the intrusion below sea level and combined with elliptic cross–section cylinders for the various zones above sea level to approximate the original zonal volumes of the intrusion. The residual gravity anomaly of 18–20 milligals (mGal) was only about half of the expected anomaly if a large hidden zone proposed from petrologic considerations were present, and both two-dimensional and three-dimensional models imply that the exposed series of intrusion zones explain the gravity anomaly by their down-dip extension below sea level together with a small hidden-zone volume. A three-dimensional model of the exposed rocks and their down-dip extension below sea level also can account for the aeromagnetic anomaly with little or no requirement for hidden-zone rock. The middle and upper zone units of the intrusion contain the most magnetite and account for most of the aeromagnetic anomaly.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251030","programNote":"Mineral Resources Program","usgsCitation":"Gettings, M.E., 2025, Gravity and magnetic surveys of the Skaergaard intrusion, East Greenland: U.S. Geological Survey Open-File Report 2025–1030, 43 p., https://doi.org/10.3133/ofr20251030.","productDescription":"Report: ix, 43 p.; Data Release","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-126792","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":494352,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91OVG7G","text":"USGS data release","description":"Gettings, M.E., and Parks, H.L., 2025, Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland, 1971: U.S. Geological Survey data release, https://doi.org/10.5066/P91OVG7G.","linkHelpText":"Aeromagnetic and gravity surveys of the Skaergaard intrusion in East Greenland, 1971"},{"id":494347,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1030/coverthb.jpg"},{"id":494348,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1030/ofr20251030.pdf","text":"Report","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1030 PDF"},{"id":494349,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251030/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1030 HTML"},{"id":494350,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1030/ofr20251030.XML","description":"OFR 2025-1030 XML"},{"id":494351,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1030/images"}],"country":"Greenland","otherGeospatial":"Skaergaard intrusion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -32.1667,\n 68.3\n ],\n [\n -32.1677,\n 68\n ],\n [\n -31.1667,\n 68\n ],\n [\n -31.1667,\n 68.3\n ],\n [\n -32.1667,\n 68.3\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, and Geophysics Science Center
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Conventional dietary assessments are challenging in hematophagous species, particularly in sea lamprey (Petromyzon marinus). However, recent technological developments and molecular approaches have provided an attractive alternative through the use of DNA metabarcoding. While DNA metabarcoding has been used for dietary analyses in numerous species, including lampreys, applications of universal primers that detect a diverse set of prey items can be limited by the amplification of predator DNA. In this study, we designed and tested eight blocking primers designed to suppress the amplification of sea lamprey DNA with vertebrate-universal primers targeting the mitochondrial 12S rRNA gene. This approach allowed for the use of a single marker to amplify a taxonomically diverse suite of host species, in contrast to previous studies that used multiple taxon-specific primer pairs (e.g., Salmonidae, Cyprinidae, and Catostomidae). Candidate blocking primers evaluated in this study differed in base pair length, end sequence modification, and purification method. Samples with different sea lamprey-to-host DNA ratios were subjected to multiple detection methods including gel electrophoresis, quantitative PCR, and DNA metabarcoding to assess the ability of each blocking primer to selectively suppress amplification of the sea lamprey 12S gene region. All blocking primers tested performed well and demonstrated high effectiveness, suppressing sea lamprey reads by > 99.9% in mock communities and improving host DNA sequence recovery across various sample types, including wild-caught lamprey. Results show that the blocking primers evaluated can facilitate molecular diet analysis in sea lamprey, allowing the amplification of a taxonomically diverse range of host fish species with universal primers.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71999","usgsCitation":"O'Kane, C., Johnson, N.S., Scribner, K.T., Kanefsky, J., Li, W., and Robinson, J.D., 2025, Development of PCR blocking primers enabling DNA metabarcoding analysis of dietary composition in hematophagous sea lamprey: Ecology and Evolution, v. 15, no. 8, e71999, 17 p., https://doi.org/10.1002/ece3.71999.","productDescription":"e71999, 17 p.","ipdsId":"IP-180902","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":495047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71999","text":"Publisher Index Page"},{"id":494536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.42859751371756,\n 46.71487752181625\n ],\n [\n -88.36277690371458,\n 45.01774821823912\n ],\n [\n -88.31731481855903,\n 41.21678815653618\n ],\n [\n -82.47857075519083,\n 40.921825838317346\n ],\n [\n -76.56443794208697,\n 42.71597391873013\n ],\n [\n -75.95858087681425,\n 44.662611421640634\n ],\n [\n -78.61421032535229,\n 45.36119897624181\n ],\n [\n -83.48488030611055,\n 47.11030206757272\n ],\n [\n -83.94723014044203,\n 48.52355518474724\n ],\n [\n -89.06406805799038,\n 49.4614460474032\n ],\n [\n -93.42859751371756,\n 46.71487752181625\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-08-20","publicationStatus":"PW","contributors":{"authors":[{"text":"O'Kane, Conor","contributorId":360151,"corporation":false,"usgs":false,"family":"O'Kane","given":"Conor","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946858,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":597,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas","email":"njohnson@usgs.gov","middleInitial":"S.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":946859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scribner, Kim T.","contributorId":360153,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim","middleInitial":"T.","affiliations":[{"id":85977,"text":"Michigan State Univesity","active":true,"usgs":false}],"preferred":false,"id":946860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kanefsky, Jeannette","contributorId":243198,"corporation":false,"usgs":false,"family":"Kanefsky","given":"Jeannette","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946862,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Robinson, John D.","contributorId":360155,"corporation":false,"usgs":false,"family":"Robinson","given":"John","middleInitial":"D.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":946863,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70272186,"text":"70272186 - 2025 - Divergent trends in fluvial suspended-sediment concentrations following improved land-use practices, southwest Washington State","interactions":[],"lastModifiedDate":"2025-11-18T15:33:25.145266","indexId":"70272186","displayToPublicDate":"2025-08-20T09:20:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Divergent trends in fluvial suspended-sediment concentrations following improved land-use practices, southwest Washington State","docAbstract":"Improvements in logging practices since the mid-20th century are widely presumed to have reduced suspended sediment loads in streams across the Pacific Northwest. However, there have been few opportunities to directly assess this, particularly in larger rivers. We compare modern (2019–22) and historical (1960s) suspended sediment monitoring in three large, actively managed watersheds in western Washington with similar land-use histories. In the two watersheds draining the southern Olympic Mountains (Satsop and Wynoochee Rivers), modern sediment yields were around 300 t/km2/yr, two to three times lower than historical conditions. Most suspended sediment exiting these watersheds came from rolling terrain mantled by glacial deposits in the lower watersheds, not the steep headwaters. Modern sediment yields in the Chehalis River, draining the low-relief Willapa Hills, were lower (70 t/km2/yr), though this represented a 50 % increase relative to historical conditions. SSC-discharge relations in the Chehalis River were steady from 1961 to 1994, indicating this increase happened sometime after 1994. The Chehalis River headwaters were uniquely impacted by landsliding during a 2007 storm, though there is some evidence against that storm as the cause of the recent increase. Ultimately, improved land-use practices appear to have reduced suspended sediment loads in large rivers of the southern Olympic Mountains several-fold, consistent with prior findings in the western Olympic Mountains, primarily due to reduced sediment delivery from the lower watersheds. Countervailing SSC-discharge trends and lower yields in the Chehalis River underscore that background sediment delivery rates and sensitivity to land-use disturbance may vary substantially within a region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2025.109963","usgsCitation":"Anderson, S., Curran, C.A., Wilkerson, O., and Seguin, K., 2025, Divergent trends in fluvial suspended-sediment concentrations following improved land-use practices, southwest Washington State: Geomorphology, v. 488, 109963, 13 p., https://doi.org/10.1016/j.geomorph.2025.109963.","productDescription":"109963, 13 p.","ipdsId":"IP-159608","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":496732,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2025.109963","text":"Publisher Index Page"},{"id":496585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Chehalis River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124,\n 47.667\n ],\n [\n -124,\n 46.333\n ],\n [\n -122.333,\n 46.333\n ],\n [\n -122.333,\n 47.667\n ],\n [\n -124,\n 47.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"488","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W 0000-0002-6239-7352","orcid":"https://orcid.org/0000-0002-6239-7352","contributorId":344221,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott W","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":950367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilkerson, Oscar A. 0000-0003-1786-5329","orcid":"https://orcid.org/0000-0003-1786-5329","contributorId":344222,"corporation":false,"usgs":true,"family":"Wilkerson","given":"Oscar","middleInitial":"A.","affiliations":[{"id":80400,"text":"Washington Water Science Center","active":true,"usgs":false}],"preferred":true,"id":950369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seguin, Katie","contributorId":362358,"corporation":false,"usgs":false,"family":"Seguin","given":"Katie","affiliations":[{"id":86510,"text":"USGS, WA WSC","active":true,"usgs":false}],"preferred":false,"id":950368,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70270360,"text":"fs20253040 - 2025 - Assessment of undiscovered conventional oil and gas resources in Mexico, Belize, and Guatemala, 2024","interactions":[],"lastModifiedDate":"2026-02-03T15:09:56.734333","indexId":"fs20253040","displayToPublicDate":"2025-08-20T01:55:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-3040","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources in Mexico, Belize, and Guatemala, 2024","title":"Assessment of undiscovered conventional oil and gas resources in Mexico, Belize, and Guatemala, 2024","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional resources of 14.6 billion barrels of oil and 83.7 trillion cubic feet of gas in Mexico, Belize, and Guatemala.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20253040","programNote":"National and Global Petroleum Assessment","usgsCitation":"Schenk, C.J., Mercier, T.J., Le, P.A., Cicero, A.D., Drake, R.M., II, Gelman, S.E., Hearon, J.S., Johnson, B.G., Lagesse, J.H., Leathers-Miller, H.M., and Timm, K.K., 2025, Assessment of undiscovered conventional oil and gas resources in Mexico, Belize, and Guatemala, 2024: U.S. Geological Survey Fact Sheet 2025–3040, 6 p., https://doi.org/10.3133/fs20253040.","productDescription":"Report: 6 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-168543","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":494358,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20253040/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"FS 2025-3040"},{"id":494355,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2025/3040/fs20253040.xml"},{"id":494354,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2025/3040/images"},{"id":494238,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1ZDDFCV","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project—Provinces of Mexico, Belize, and Guatemala—Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":494236,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2025/3040/coverthb.jpg"},{"id":494237,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2025/3040/fs20253040.pdf","text":"Report","size":"5.30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2025-3040"}],"country":"Belize, Guatemala, Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -101.3086992481862,\n 25.996938636083627\n ],\n [\n -101.3086992481862,\n 14.653424847535774\n ],\n [\n -86.17860869264547,\n 14.653424847535774\n ],\n [\n -86.17860869264547,\n 25.996938636083627\n ],\n [\n -101.3086992481862,\n 25.996938636083627\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The aquarium trade is a global industry responsible for the movement of live plants and animals, but it also serves as a major pathway for the introduction and spread of aquatic invasive species. Invasive species contribute to biodiversity loss, disrupt ecosystems, and can have widespread economic and societal impacts. A significant but poorly understood invasion risk in the plant aquarium trade is the transport of hitchhiking species, which are organisms unintentionally transported along with a species of primary interest in trade. Aquatic hitchhikers can persist in aquaria and later be released into the wild, potentially establishing invasive populations. While some studies have identified hitchhiking as a pathway for aquatic species spread, it remains largely unrecognized in international regulations. Increased awareness, triggered by incidents such as zebra mussels found in aquarium plants, highlights the need for further investigation into this emerging pathway of concern. As a response, we reviewed the current state of knowledge regarding aquatic plants in the aquarium trade as vectors for transporting invasive hitchhiking species, with a particular focus on how morphological complexity of plants influences associated hitchhikers. We found that although awareness of hitchhiking species in the aquarium trade is increasing, few studies have empirically examined aquarium plants as vectors for invasive species. Understanding this pathway can help to inform invasive species management around the plant aquarium trade and to keep aquarium organisms in a sustainable manner.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2025.16.4.01","usgsCitation":"O'Shaughnessy, K.A., Daniel, W., Hendrickson, Z.C., Smith, S., McDonald, A.M., and Martin, C.W., 2025, Invasive hitchhiking organisms on aquarium plants: An emerging pathway of introduction: Management of Biological Invasions, v. 16, no. 4, p. 879-893, https://doi.org/10.3391/mbi.2025.16.4.01.","productDescription":"15 p.","startPage":"879","endPage":"893","ipdsId":"IP-180113","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497744,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2025.16.4.01","text":"Publisher Index Page"},{"id":497678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Shaughnessy, Kathryn A.","contributorId":364444,"corporation":false,"usgs":false,"family":"O'Shaughnessy","given":"Kathryn","middleInitial":"A.","affiliations":[{"id":48711,"text":"Dauphin Island Sea Lab","active":true,"usgs":false}],"preferred":false,"id":952648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daniel, Wesley M. 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":214505,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":952649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hendrickson, Zoey C.W.","contributorId":364447,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Zoey","middleInitial":"C.W.","affiliations":[{"id":48710,"text":"University of South Alabama","active":true,"usgs":false}],"preferred":false,"id":952650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Samantha N.","contributorId":349763,"corporation":false,"usgs":false,"family":"Smith","given":"Samantha N.","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":952651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McDonald, Ashley M.","contributorId":364450,"corporation":false,"usgs":false,"family":"McDonald","given":"Ashley","middleInitial":"M.","affiliations":[{"id":48711,"text":"Dauphin Island Sea Lab","active":true,"usgs":false}],"preferred":false,"id":952652,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martin, Charles W.","contributorId":364453,"corporation":false,"usgs":false,"family":"Martin","given":"Charles","middleInitial":"W.","affiliations":[{"id":48710,"text":"University of South Alabama","active":true,"usgs":false}],"preferred":false,"id":952653,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271501,"text":"70271501 - 2025 - A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices","interactions":[],"lastModifiedDate":"2025-09-18T15:27:18.163987","indexId":"70271501","displayToPublicDate":"2025-08-19T10:22:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1457,"text":"Ecological Informatics","active":true,"publicationSubtype":{"id":10}},"title":"A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices","docAbstract":"Wildlife conservation planning increasingly requires collaboration and integration of research from discrete studies spanning large geographic areas. Tracking datasets are essential for analyzing animal movements and species distributions in relation to environmental conditions and combining them can enable powerful analyses to further aid planning efforts. However, combining datasets necessitates addressing variation in study designs, tracking methodologies, location uncertainty, and data attributes. We outline a compilation pipeline to integrate ground-based and satellite-based telemetry tracking datasets, motivated from our work with greater sage-grouse (Centrocercus urophasianus), a highly imperiled species of western North America. Our objective was to create a database with a standardized set of attributes to facilitate filtering locations for spatial analyses. Our pipeline phases are: (1) dataset pre-processing, (2) formatting individual datasets to a common template, (3) dataset binding, (4) error checking, and (5) filtering. Our pipeline includes additional functionality to identify coordinates from recurrently visited locations (e.g., nest sites), which may be of special interest. The final compiled sage-grouse database included nearly 5 million locations collected from 53 datasets and over 19,000 birds tracked from 1980 to 2022, including over 11,000 nest locations. Our error checks flagged 3.9 % of locations as likely errors, predominantly collected from satellite-based telemetry transmissions. We demonstrate the ability of our pipeline to identify nest locations and flag erroneous locations by applying it to simulated tracking datasets. Overall, our workflow offers a transferable approach for researchers aiming to standardize wildlife telemetry datasets and conduct ecological analyses for both individual studies and large-scale collaborations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoinf.2025.103220","collaboration":"Bureau of Land Management","usgsCitation":"Wann, G.T., Whipple, A.L., O’Donnell, M.S., and Aldridge, C.L., 2025, A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices: Ecological Informatics, v. 90, 103220, 11 p., https://doi.org/10.1016/j.ecoinf.2025.103220.","productDescription":"103220, 11 p.","ipdsId":"IP-174162","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":495748,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoinf.2025.103220","text":"Publisher Index Page"},{"id":495714,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.33602266473824,\n 36.14719079486781\n ],\n [\n -110.55053462488866,\n 37.206242788039134\n ],\n [\n -105.89746256645961,\n 40.02501095984442\n ],\n [\n -102.5194136320973,\n 44.82182818739983\n ],\n [\n -106.52465821457994,\n 48.378668867318794\n ],\n [\n -106.59044740699102,\n 48.95429657658073\n ],\n [\n -121.6328973274124,\n 48.97073706473478\n ],\n [\n -122.65581494478303,\n 41.23928046174427\n ],\n [\n -118.33602266473824,\n 36.14719079486781\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"90","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whipple, Ashley L. 0000-0002-0304-7643","orcid":"https://orcid.org/0000-0002-0304-7643","contributorId":300552,"corporation":false,"usgs":true,"family":"Whipple","given":"Ashley","email":"","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":140876,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":948972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":948973,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272727,"text":"70272727 - 2025 - Assessing policy effectiveness trends in nonindigenous aquatic species introduction in the Ohio River basin","interactions":[],"lastModifiedDate":"2025-12-05T15:58:38.264512","indexId":"70272727","displayToPublicDate":"2025-08-19T09:52:20","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Assessing policy effectiveness trends in nonindigenous aquatic species introduction in the Ohio River basin","docAbstract":"Aquatic invasive species (AIS) create costly, detrimental effects when established. Recognition of this in the United States reached a threshold in 1990 with the federal passage of the Nonindigenous Aquatic Nuisance Prevention and Control Act. This act created six regional panels, the national Aquatic Nuisance Species Task Force, and incentivized state-level AIS planning. The management of the Ohio River basin fell under the Mississippi River Basin Panel and the state-led Mississippi Interstate Cooperative Resource Association, which developed a joint action plan in 2010 to prevent, contain, and manage AIS. All Ohio River basin states besides West Virginia created aquatic nuisance species plans between 1999 and 2021. This study aims to utilize the best available data, the USGS Nonindigenous Aquatic Species (NAS) database, to examine how legislative and planning milestones have influenced the rate of new AIS arrivals and the spread of existing and new AIS. Arrival and spread of AIS were assessed at the HUC-8 scale (8-digit hydrological unit code) along the Ohio, Wabash, Cumberland, Alleghany, Monongahela, and Tennessee rivers. A near-linear increase in new AIS across all rivers was determined. Most AIS species (35–55%) did not spread beyond the HUC they were first detected in, while less than 10% spread to all HUCs in a river. The findings indicate no clear correlation between legislative and planning milestones and changes in AIS spread. More work could help to fill data gaps in detecting and monitoring AIS through coordinated local and regional programs, as expanding the quality and quantity of data collection efforts can improve understanding of AIS dynamics, assessments of management effectiveness, and inform future policy. Future work could expand the analysis to evaluate the effectiveness of policy and planning programs in reducing AIS, considering the variability in on-the-ground approaches and spread prevention efforts across states.","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2025.16.4.04","usgsCitation":"Clasgens, A.N., Murry, B.A., Zipp, K., Arantes, C.C., and Neilson, M., 2025, Assessing policy effectiveness trends in nonindigenous aquatic species introduction in the Ohio River basin: Management of Biological Invasions, v. 16, no. 4, p. 943-959, https://doi.org/10.3391/mbi.2025.16.4.04.","productDescription":"17 p.","startPage":"943","endPage":"959","ipdsId":"IP-167017","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":497391,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2025.16.4.04","text":"Publisher Index Page"},{"id":497141,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, Illinois, Indiana, Kentucky, Mississippi, New York, Ohio, Pennsylvania, Tennessee, West Virginia","otherGeospatial":"Ohio River drainage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.86189828374268,\n 41.77677411774701\n ],\n [\n -78.63164005664989,\n 42.413236850225616\n ],\n [\n -80.3205619541407,\n 41.52394031593266\n ],\n [\n -81.68440343936543,\n 39.99520322262126\n ],\n [\n -83.73626351948025,\n 40.91179316865117\n ],\n [\n -85.75377241079076,\n 41.00045122078683\n ],\n [\n -87.29259028984461,\n 40.42166367952521\n ],\n [\n -88.54389544444282,\n 39.58671971059428\n ],\n [\n -89.34400773501363,\n 38.01283806367644\n ],\n [\n -89.61987832634247,\n 37.407427236343395\n ],\n [\n -89.33088690734974,\n 35.30445704462397\n ],\n [\n -88.08870098862076,\n 34.22161459059926\n ],\n [\n -86.40862152775846,\n 34.1696767386851\n ],\n [\n -82.7983151924422,\n 35.87757326220134\n ],\n [\n -81.42706279554102,\n 36.962278650385485\n ],\n [\n -79.30304403712026,\n 39.43812621588444\n ],\n [\n -77.86189828374268,\n 41.77677411774701\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Clasgens, Abigail N. 0009-0002-5133-1507","orcid":"https://orcid.org/0009-0002-5133-1507","contributorId":363326,"corporation":false,"usgs":false,"family":"Clasgens","given":"Abigail","middleInitial":"N.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":951454,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murry, Brent A. 0000-0003-3142-1628","orcid":"https://orcid.org/0000-0003-3142-1628","contributorId":363327,"corporation":false,"usgs":false,"family":"Murry","given":"Brent","middleInitial":"A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":951455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zipp, Kaylyn 0009-0008-0621-8285","orcid":"https://orcid.org/0009-0008-0621-8285","contributorId":363330,"corporation":false,"usgs":false,"family":"Zipp","given":"Kaylyn","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false}],"preferred":false,"id":951456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arantes, Caroline C. 0000-0002-9752-1499","orcid":"https://orcid.org/0000-0002-9752-1499","contributorId":363331,"corporation":false,"usgs":false,"family":"Arantes","given":"Caroline","middleInitial":"C.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":951457,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neilson, Matthew 0000-0002-5139-5677","orcid":"https://orcid.org/0000-0002-5139-5677","contributorId":214507,"corporation":false,"usgs":true,"family":"Neilson","given":"Matthew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":951458,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270458,"text":"70270458 - 2025 - Improved prediction of postfire debris flows through rainfall anomaly maps","interactions":[],"lastModifiedDate":"2025-08-20T14:53:20.297849","indexId":"70270458","displayToPublicDate":"2025-08-19T09:48:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Improved prediction of postfire debris flows through rainfall anomaly maps","docAbstract":"Predicting where runoff-generated debris flows might occur during rainfall on steep, recently burned terrain is challenging. Studies of mass-movement processes in unburned areas indicate that event locations are well-predicted by rainfall anomaly, R*, in which peak observed rainfall is normalized by local rainfall climatology. Here, we use remote and field methods to map debris flows triggered within the 2020 Dolan Fire burn area in coastal California, demonstrate that a short-duration R* metric predicts debris-flow occurrence more effectively than absolute peak intensity or longer-duration rainfall metrics, and show that incorporating an R* criterion into an existing debris-flow likelihood model can reduce false positive predictions and improve accuracy. We test R* at three other climatically distinct fires in California, demonstrating its utility for mapping likely debris-flow locations in different climates. We also consider how R* can benefit postfire debris-flow prediction given recent increases in climatological variability within individual burn perimeters.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025GL114791","usgsCitation":"Cavagnaro, D.B., McCoy, S.W., Thomas, M.A., Kostelnik, J., and Lindsay, D.N., 2025, Improved prediction of postfire debris flows through rainfall anomaly maps: Geophysical Research Letters, v. 52, no. 16, e2025GL114791, 12 p., https://doi.org/10.1029/2025GL114791.","productDescription":"e2025GL114791, 12 p.","ipdsId":"IP-170042","costCenters":[{"id":78941,"text":"Geologic Hazards Science Center - Landslides / Earthquake Geology","active":true,"usgs":true}],"links":[{"id":494967,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13ZGR6F","text":"USGS data release","linkHelpText":"Inventory of fluvial erosion and debris-flow activity following the 2020 Dolan Fire, California"},{"id":494458,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025gl114791","text":"Publisher Index Page"},{"id":494344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Callifornia","county":"Monterey County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.7,\n 36.2\n ],\n [\n -121.7,\n 35.9\n ],\n [\n -121.3,\n 35.9\n ],\n [\n -121.3,\n 36.2\n ],\n [\n -121.7,\n 36.2\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"16","noUsgsAuthors":false,"publicationDate":"2025-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Cavagnaro, David B.","contributorId":359920,"corporation":false,"usgs":false,"family":"Cavagnaro","given":"David","middleInitial":"B.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":946432,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Scott W.","contributorId":359922,"corporation":false,"usgs":false,"family":"McCoy","given":"Scott","middleInitial":"W.","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":946433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Matthew A. 0000-0002-9828-5539 matthewthomas@usgs.gov","orcid":"https://orcid.org/0000-0002-9828-5539","contributorId":200616,"corporation":false,"usgs":true,"family":"Thomas","given":"Matthew","email":"matthewthomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":946434,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kostelnik, Jaime 0000-0002-1817-5461","orcid":"https://orcid.org/0000-0002-1817-5461","contributorId":300717,"corporation":false,"usgs":true,"family":"Kostelnik","given":"Jaime","email":"","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":946435,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lindsay, Donald N.","contributorId":359924,"corporation":false,"usgs":false,"family":"Lindsay","given":"Donald","middleInitial":"N.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":946436,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270862,"text":"70270862 - 2025 - Estimating the hypothetical endowment of critical minerals and other commodities in porphyry copper mine waste in the Four Corners states, USA","interactions":[],"lastModifiedDate":"2025-08-26T14:17:35.326171","indexId":"70270862","displayToPublicDate":"2025-08-19T09:14:15","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Estimating the hypothetical endowment of critical minerals and other commodities in porphyry copper mine waste in the Four Corners states, USA","docAbstract":"Society is fundamentally dependent upon commodities that are used in end-use products for the aerospace, defense, energy, telecommunication, and transportation sectors, resulting in centuries of mining to supply these commodities and materials. Waste from these mining operations can remain on the landscape indefinitely, but there is a lack of national understanding of the distribution and scale of such waste features. The renewable energy transition will continue to increase demand for critical minerals and will result in increasing volumes of mine waste on the Earth’s surface. Reprocessing mine waste can reduce environmental risks and recover needed commodities to match growing demand for societal growth. Therefore, understanding the approximate abundance of commodities that may be available for recovery within mine waste features can be an important piece of domestic critical mineral supply.
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change over time for a suite of monitored tidal water quality parameters and associated potential drivers of those trends for the period of 1985 to 2022, and provides a brief description of the current state of knowledge explaining these observed changes. Water quality parameters described include surface (above pycnocline) total nitrogen (TN), surface total phosphorus (TP), surface water temperature (WTEMP), spring (March-May) and summer (July-September) surface chlorophyll a, summer bottom (below pycnocline) dissolved oxygen (DO) concentrations, and Secchi disk depth (a measure of water clarity). Results for annual bottom TP, bottom TN, surface ortho-phosphate (PO4), surface dissolved inorganic nitrogen (DIN), surface total suspended solids (TSS), and summer surface DO concentrations are provided in Appendix B. Drivers discussed include physiographic watershed characteristics, changes in TN, TP, and sediment loads from the watershed to tidal waters, expected effects of changing land use, and implementation of nutrient management and natural resource conservation practices. Factors internal to estuarine waters that also play a role as drivers are described including biogeochemical processes, physical forces such as wind driven mixing of the water column and increase in rainfall intensity and volume, and biological factors such as phytoplankton biomass and the presence of submerged aquatic vegetation. Continuing to track water quality response and investigating these influencing factors are important steps to understanding water quality patterns and changes in the Potomac River. The intended audiences for this report include, but are not limited to, 1) technical managers within jurisdictions who are looking at tidal water quality data and trying to understand why patterns are occurring, 2) local watershed organizations that are trying to understand these analyses and working to connect them to their local area(s), and 3) federal, state, and academic researchers. Figure 1 presents a conceptual model highlighting these intended audiences. Our goal is for the Tributary Summary documents to be sources of readily available background for change over time in tidal water quality observed with monitoring data. The intended purpose of the Tributary Summary documents is to help answer questions related to water quality, show how landscape factors drive water quality change over time, provide support for management decisions that may alter water quality trends and living resources conditions, and highlight where there may be information or knowledge gaps.","language":"English","publisher":"Chesapeake Bay Program","usgsCitation":"Sullivan, B.M., Gootman, K., Gunnerson, A., Betts, S., Duran, G., Johnson, C., Mason, C.A., Perry, E., Bhatt, G., Keisman, J.L., Webber, J.S., Harcum, J., Lane, M., Devereux, O., Zhang, Q., Murphy, R., Renee Karrh, Butler, T., and Wei, Z., 2025, Potomac Tributary Summary: A summary of trends in tidal water quality and associated factors, 1985 - 2022, 88 p.","productDescription":"88 p.","ipdsId":"IP-173187","costCenters":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science 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resources","interactions":[],"lastModifiedDate":"2025-08-26T15:40:42.066035","indexId":"70270880","displayToPublicDate":"2025-08-19T08:35:22","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22182,"text":"Forest Ecology & Management","active":true,"publicationSubtype":{"id":10}},"title":"Shifts in suitability of pinyon-juniper communities: A climate adaptation framework for range-wide management of arid woodland resources","docAbstract":"Pinyon-juniper (PJ) woodlands are a diverse ecosystem type providing a wealth of ecosystem services across western North America. Managing PJ woodlands in the 21st century entails balancing multiple conservation objectives, and resource managers and policy-makers working to sustain PJ woodlands need spatially explicit information about current PJ woodland conditions and how they may be impacted in coming decades in the context of wildfire risk and changing climate. Here, we address knowledge gaps and provide information that improves the long-term value of conservation and restoration actions in PJ woodlands. To this end, we merged projections of future environmental suitability for nine PJ species with wildfire risk and locations of mature and old-growth (MOG) woodlands to assess spatial variation in PJ woodlands with differing threats and management opportunities. We identified potential climate refugia with enduring high community suitability and low burn probability (3 % of study area) that may persist with relatively little management. We found promising locations of PJ-MOG forest type with high future suitability (12 % of areas) that could be prioritized for fire risk reduction to maintain high-value woodlands. Despite a 38 % mean community suitability decline under future climate conditions, some locations (7 % of areas) may act as climate refugia where future climate conditions can support current PJ woodland composition and structure. We conclude by demonstrating how this information can be integrated into a conceptual framework to help prioritize conservation and climate adaptation in PJ woodlands.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2025.123075","collaboration":"Bureau of Land Management","usgsCitation":"Noel, A.R., Schlaepfer, D.R., Barrett, I.P., Duniway, M.C., Norris, J.R., Domschke, C.T., Butterfield, B.J., Swan, M.C., Hartwig, K., Crist, M.R., and Bradford, J.B., 2025, Shifts in suitability of pinyon-juniper communities: A climate adaptation framework for range-wide management of arid woodland resources: Forest Ecology & Management, v. 596, 123075, 13 p., https://doi.org/10.1016/j.foreco.2025.123075.","productDescription":"123075, 13 p.","ipdsId":"IP-178751","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2025.123075","text":"Publisher Index 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The MTJ marks the nexus of the Mendocino and San Andreas faults with the Cascadia subduction zone (CSZ). Historically, most large earthquakes around the MTJ have been within the offshore Gorda plate and its subducted portion beneath the NA plate. North of the MTJ, active faults mapped in the NA plate are part of the CSZ fold‐and‐thrust belt. Although some events have been detected in the NA plate, no large historic events have been associated with mapped surface faults. The 21 December 1954 Mw 6.5 earthquake in Humboldt County is one possible exception. Using published data from catalogs and articles, unpublished data from Berkeley’s archives, and S‐P times interpreted from two U.S. Coast and Geodetic Survey (USCGS) accelerometers, we determine a probability cloud for the earthquake’s hypocenter using NonLinLoc. The highest probability location lies beneath Fickle Hill just east of the city of Arcata, California, at 40.87° N, 124.03° W, and ∼11 km depth. Using P‐wave polarities from Berkeley stations and the digitized waveforms from the accelerometers, we find that the focal mechanism most consistent with the data indicates thrust movement with strike, dip, and rake of 350°, 10°, and 90°, respectively, at a depth of 14 km. Given the depth uncertainties of both this event and the megathrust, this implies that the earthquake most likely took place on the subduction interface rather than on the mapped faults in the Mad River fault zone that trend 322° and dip to the northeast. The revisited intensity in the epicentral region also supports a location beneath Fickle Hill to the east of the city of Arcata, California.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120250080","usgsCitation":"Hellweg, M., Lee, T.A., Dreger, D.S., Lomax, A., Hagos, L., Haddabi, H., McPherson, R.C., Dengler, L., Hough, S.E., and Patton, J.R., 2025, Revisiting an enigma on California's north coast: The Mw6.5 Fickle Hill earthquake of 21 December 1954: Bulletin of the Seismological Society of America, v. 115, no. 6, p. 2623-2639, https://doi.org/10.1785/0120250080.","productDescription":"17 p.","startPage":"2623","endPage":"2639","ipdsId":"IP-177949","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":494901,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.23082743259238,\n 46.45369999658712\n ],\n [\n -124.94108692827174,\n 41.87317683684783\n ],\n [\n -124.0036946792876,\n 37.27396300370703\n ],\n [\n -120.72594459506794,\n 33.05110616586563\n ],\n [\n -116.56731665360127,\n 33.7291335831041\n ],\n [\n -116.56731665360127,\n 46.45369999658712\n ],\n [\n -124.23082743259238,\n 46.45369999658712\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"115","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Hellweg, Margaret","contributorId":360602,"corporation":false,"usgs":false,"family":"Hellweg","given":"Margaret","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":947294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Thomas A.","contributorId":360603,"corporation":false,"usgs":false,"family":"Lee","given":"Thomas","middleInitial":"A.","affiliations":[{"id":6644,"text":"Princeton University","active":true,"usgs":false}],"preferred":false,"id":947295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dreger, Douglas S.","contributorId":360605,"corporation":false,"usgs":false,"family":"Dreger","given":"Douglas","middleInitial":"S.","affiliations":[{"id":36629,"text":"University of California","active":true,"usgs":false}],"preferred":false,"id":947296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lomax, Anthony","contributorId":355480,"corporation":false,"usgs":false,"family":"Lomax","given":"Anthony","affiliations":[{"id":84757,"text":"ALomax Scientific, Mouans Sartoux, France","active":true,"usgs":false}],"preferred":false,"id":947297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hagos, Lijam","contributorId":300811,"corporation":false,"usgs":false,"family":"Hagos","given":"Lijam","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":947298,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haddabi, Hamid","contributorId":360611,"corporation":false,"usgs":false,"family":"Haddabi","given":"Hamid","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":947299,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McPherson, Robert C.","contributorId":350346,"corporation":false,"usgs":false,"family":"McPherson","given":"Robert","middleInitial":"C.","affiliations":[{"id":83721,"text":"Cal Poly Humboldt Univ.","active":true,"usgs":false}],"preferred":false,"id":947300,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dengler, Lori","contributorId":197374,"corporation":false,"usgs":false,"family":"Dengler","given":"Lori","affiliations":[],"preferred":false,"id":947301,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":947302,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Patton, Jason R.","contributorId":317714,"corporation":false,"usgs":false,"family":"Patton","given":"Jason","email":"","middleInitial":"R.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":947334,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70271353,"text":"70271353 - 2025 - Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm","interactions":[],"lastModifiedDate":"2025-09-10T14:57:19.895523","indexId":"70271353","displayToPublicDate":"2025-08-19T07:53:02","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7164,"text":"Environmental Modelling & Software","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm","docAbstract":"Stream temperature controls a variety of physical and biological processes that affect ecosystems, human health, and economic activities. We used 42 years (1979–2021) of data to predict daily summary statistics of stream temperature across >50,000 stream reaches in the contiguous United States using a recurrent graph convolution network. We comprehensively documented the performance – both across all reaches and by stream type (e.g., reservoir or groundwater influence) – as a baseline for future improvement. The model showed reach-level RMSE of <2 °C with 90 % prediction intervals that contain 90.7 % of observations. We also assessed how the model captured variability in ecologically relevant metrics (e.g., R2 for annual 7-day maximum = 0.76; R2 for days exceeding 25 °C = 0.75). This model does not outperform state-of-the-art machine learning efforts (e.g., RMSE ≤1.5 °C) due to a limited input set but does provide the most spatially complete modeling to date to support water availability assessments.
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Division","active":true,"usgs":true}],"preferred":true,"id":948190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorski, Galen 0000-0003-0083-4251","orcid":"https://orcid.org/0000-0003-0083-4251","contributorId":329714,"corporation":false,"usgs":true,"family":"Gorski","given":"Galen","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":948192,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271129,"text":"70271129 - 2025 - Avian influenza spillover into poultry: Environmental influences and biosecurity protections","interactions":[],"lastModifiedDate":"2025-08-28T14:54:17.55377","indexId":"70271129","displayToPublicDate":"2025-08-19T07:47:16","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22340,"text":"One Health","active":true,"publicationSubtype":{"id":10}},"title":"Avian influenza spillover into poultry: Environmental influences and biosecurity protections","docAbstract":"With the continued spread of highly pathogenic avian influenza (HPAI), understanding the complex dynamics of virus transfer at the wild – agriculture interface is paramount. Spillover events (i.e., virus transfer from wild birds into poultry) are related to proximity to infected wild bird populations and environmental conditions. By accounting for such dynamics, we can take a combined approach to assess the impacts of biosecurity measures implemented at poultry farms while simultaneously accounting for their local risk levels. We implemented a Bayesian joint-likelihood logistic regression for the Continental U.S. comparing models of spatiotemporal risk according to land use, weather, and predicted waterfowl distributions followed by integrating a farm-level case-control questionnaire dataset focused on identifying trends in HPAI spillover risk associated with a farm's biosecurity practices. We found that estimates of waterfowl abundance, along with mean precipitation and temperature during winter, were most correlated with spatiotemporal HPAI risk. Additionally, we identified multiple biosecurity practices associated with reduced risk to HPAI, where the strongest relationships were related to litter decontamination treatments, vehicle wash stations, and avoiding shared dead-bird disposal sites with other farms. This model broadly guides surveillance of HPAI in wild and domestic populations, identifying when and where we are most likely to see increased instances of the virus while also providing insights into how poultry farms can better protect themselves from risk.","language":"English","publisher":"Elsevier","doi":"10.1016/j.onehlt.2025.101172","usgsCitation":"Gonnerman, M.B., Mullinax, J., Fox, A., Patyk, K.A., Fields, V., McCool, M., Torchetti, M.K., Lantz, K., Sullivan, J.D., and Prosser, D.J., 2025, Avian influenza spillover into poultry: Environmental influences and biosecurity protections: One Health, v. 21, 101172, 9 p., https://doi.org/10.1016/j.onehlt.2025.101172.","productDescription":"101172, 9 p.","ipdsId":"IP-178496","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":495069,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.onehlt.2025.101172","text":"Publisher Index 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Resource managers need to understand stream and river condition and how these conditions are changing over time to determine whether regional long-term restoration and conservation goals are being met. The objective of this report was to document the spatial and temporal variability of conditions for seven indicators of river and stream health across the nontidal Chesapeake Bay watershed. The framework for the U.S. Geological Survey’s Nontidal Network (NTN), a network of more than 100 nutrient and suspended sediment monitoring locations, was extended to assess conditions for six additional indicators of stream health: temperature, salinity, toxic contaminants, streamflow, hydromorphology, and biological aquatic communities. For each indicator, the latest available data from multiple sources were compiled and harmonized, and key metrics were identified to describe indicator conditions across space and time. A status condition was defined for each indicator to describe overall spatial variability in recent condition, and trend analyses were used to describe changes in each indicator metric over time. The analysis revealed clear differences in spatial and temporal data coverage across the seven indicators, so individual indicator trend analyses were not constrained to a common time interval. However, a status snapshot was conducted across all indicators for the 2015–17 period to simultaneously explore spatial variability across all indicators. The status snapshot highlighted general degraded conditions across multiple indicators in large metropolitan regions, such as the Baltimore–Washington, D.C., metropolitan area. Regression analysis between indicator status metrics and major land cover for the sites suggest urbanization as a potential driver of degraded conditions for many of the indicator metrics, including total phosphorus, salinity, temperature, high-flow frequency, and metrics of habitat and biological assemblage quality. A final analysis exploring the spatial representation of each indicator network showed that some indicator monitoring networks did not cover certain settings, such as small watersheds. These results provided an initial assessment of stream health status and trends and will continue to be leveraged to describe conditions across the Chesapeake Bay watershed to help inform local and regional management decisions. These results also highlighted the need for improved coordination among monitoring organizations to support long-term multi-indicator monitoring and assessment.
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U.S. Geological Survey
1730 East Parham Road
Richmond, Virginia 23228
The ages and sizes at which organisms mature have significant implications for lifetime reproductive success. For species at risk of extinction, such as sea turtles, these attributes can ultimately impact probability of population persistence. Within the Northwest Atlantic Ocean, the broader loggerhead sea turtle (Caretta caretta) population comprises management units both along the US Gulf of America (formerly Gulf of Mexico) and Atlantic coasts. Although age, growth, and maturation have been more intensively studied along the US Atlantic, data specific to the Gulf of America have remained sparse. To address this data gap, we conducted skeletal growth mark analysis (skeletochronology) for 123 humerus bones collected from loggerheads found dead in the US Gulf of America from 1998 to 2021. We compared resulting age, growth, and maturation data with information from studies of US Atlantic coast loggerheads for similar size and year ranges, using the exact same skeletochronology methods, as well as with Gulf of America mark-recapture growth data. Results indicate that Gulf of America loggerheads exhibit significantly faster juvenile somatic growth. In addition, sizes at maturation were substantially smaller, corresponding with mean estimates of age at maturation 7.5 to 15 years earlier than US Atlantic counterparts. Finally, the maximum observed Gulf of America adult age estimate was 42.5 years, considerably less than the highest US Atlantic estimate of 77.0 years. These detailed data offer insights into regional variability in somatic growth dynamics and characteristics associated with maturation, which in turn can impact relative reproductive contributions and, ultimately, population trajectories.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00227-025-04684-7","usgsCitation":"Avens, L., Lamont, M., Foley, A.M., Higgins, B.M., Howell, L.N., Lovewell, G., Shaver, D.J., Stacy, B.A., Walker, J.S., Clark, J.M., Wallace, A.A., and Vander Zanden, H.B., 2025, Regional differentiation in somatic growth and maturation attributes for loggerhead sea turtles (Caretta caretta) in the Northwest Atlantic: Marine Biology, v. 172, 149, 18 p., https://doi.org/10.1007/s00227-025-04684-7.","productDescription":"149, 18 p.","ipdsId":"IP-174852","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":495125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -97.5836411781652,\n 28.517499803083524\n ],\n [\n -98.3287761682249,\n 25.88347550218039\n ],\n [\n -96.93640468182225,\n 26.147747319039482\n ],\n [\n -94.93117038891124,\n 28.91095771569899\n ],\n [\n -89.15507793558677,\n 29.00124525041998\n ],\n [\n -88.23789544109674,\n 29.769113103344438\n ],\n [\n -84.12290749690138,\n 29.588431042507242\n ],\n [\n -81.79016123453466,\n 24.92459095555828\n ],\n [\n -79.75533857769344,\n 25.074440813875754\n ],\n [\n -80.85660890636944,\n 31.409112363323715\n ],\n [\n -76.05282263235472,\n 34.77921941378759\n ],\n [\n -75.42015386931543,\n 36.82144397005821\n ],\n [\n -81.36725733335423,\n 33.0299954015619\n ],\n [\n -86.02046318984434,\n 31.178490607212467\n ],\n [\n -94.87030472277276,\n 29.898370916199873\n ],\n [\n -97.5836411781652,\n 28.517499803083524\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"172","noUsgsAuthors":false,"publicationDate":"2025-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Avens, Larisa","contributorId":204905,"corporation":false,"usgs":false,"family":"Avens","given":"Larisa","email":"","affiliations":[],"preferred":false,"id":947649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":206258,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":947650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foley, Allen M.","contributorId":360780,"corporation":false,"usgs":false,"family":"Foley","given":"Allen","middleInitial":"M.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":947651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Higgins, Benjamin M.","contributorId":360781,"corporation":false,"usgs":false,"family":"Higgins","given":"Benjamin","middleInitial":"M.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":947652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howell, Lyndsey N.","contributorId":360782,"corporation":false,"usgs":false,"family":"Howell","given":"Lyndsey","middleInitial":"N.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":947653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lovewell, Gretchen","contributorId":360783,"corporation":false,"usgs":false,"family":"Lovewell","given":"Gretchen","affiliations":[{"id":13147,"text":"Mote Marine Laboratory","active":true,"usgs":false}],"preferred":false,"id":947654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shaver, Donna J.","contributorId":360785,"corporation":false,"usgs":false,"family":"Shaver","given":"Donna","middleInitial":"J.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":947655,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stacy, Brian A.","contributorId":360787,"corporation":false,"usgs":false,"family":"Stacy","given":"Brian","middleInitial":"A.","affiliations":[{"id":36612,"text":"National Marine Fisheries Service","active":true,"usgs":false}],"preferred":false,"id":947656,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walker, J. 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The East Asian–Australasian Flyway plays a crucial role in HPAIV dynamics due to its large populations of migratory waterfowl and poultry. Over recent decades, this flyway has undergone substantial landscape changes, including both losses and gains of waterfowl habitats. These changes can affect waterfowl distributions, increase contact with poultry, and consequently alter ecological conditions that favor avian influenza virus (AIV) evolution. However, limited research has assessed these likely impacts. Here, we integrated empirical data and an individual-based model to simulate AIV transmission in migratory waterfowl and domestic poultry, including wild-to-poultry spillover and reassortment dynamics in poultry, across landscapes representing the years 2000 and 2015. We used the reassortment incidence as a proxy for ecological and transmission conditions that support viral diversification and the emergence of novel subtypes. Our simulations show that landscape change reshaped the waterfowl distribution, facilitated bird aggregation at improved habitats, increased coinfection, and raised reassortment rate by 1,593%, indicating a substantially higher potential for viral diversification and emergence. Model-generated risk maps show expanded and increased reassortment risk in southeastern China, the Yellow River Basin, and northeastern China. These findings suggest the importance of landscape change as a driver of potential AIV diversification and subtype emergence. This underscores the need for interdisciplinary approaches that integrate landscape dynamics, host movement, and viral evolution to better assess and mitigate future risk.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2503427122","usgsCitation":"Yin, S., Zhang, C., Teitelbaum, C.S., Si, Y., Zhang, G., Wang, X., Mao, D., Huangh, Z.Y., de Boer, W.F., Takekawa, J., Prosser, D.J., and Xiao, X., 2025, Landscape changes elevate the risk of avian influenza virus diversification and emergence in the East Asian–Australasian Flyway: Proceedings of the National Academy of Sciences, v. 122, no. 34, e2503427122, 9 p., https://doi.org/10.1073/pnas.2503427122.","productDescription":"e2503427122, 9 p.","ipdsId":"IP-176107","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":494467,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2503427122","text":"Publisher Index Page"},{"id":494397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Korea, Mongolia, Russia","otherGeospatial":"East Asian–Australasian Flyway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 75,\n 20\n ],\n [\n 175,\n 20\n ],\n [\n 175,\n 75\n ],\n [\n 75,\n 75\n ],\n [\n 75,\n 20\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"122","issue":"34","noUsgsAuthors":false,"publicationDate":"2025-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Yin, Shenglai","contributorId":223544,"corporation":false,"usgs":false,"family":"Yin","given":"Shenglai","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":946706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Chenchen","contributorId":360042,"corporation":false,"usgs":false,"family":"Zhang","given":"Chenchen","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":946707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teitelbaum, Claire Stewart 0000-0001-5646-3184","orcid":"https://orcid.org/0000-0001-5646-3184","contributorId":295336,"corporation":false,"usgs":true,"family":"Teitelbaum","given":"Claire","email":"","middleInitial":"Stewart","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Si, Yali","contributorId":223542,"corporation":false,"usgs":false,"family":"Si","given":"Yali","email":"","affiliations":[{"id":40738,"text":"Tsinghua University","active":true,"usgs":false}],"preferred":false,"id":946709,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Geli","contributorId":206235,"corporation":false,"usgs":false,"family":"Zhang","given":"Geli","email":"","affiliations":[],"preferred":false,"id":946710,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xinxin","contributorId":304701,"corporation":false,"usgs":false,"family":"Wang","given":"Xinxin","email":"","affiliations":[{"id":7062,"text":"University of Oklahoma","active":true,"usgs":false}],"preferred":false,"id":946711,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mao, Dehua","contributorId":360045,"corporation":false,"usgs":false,"family":"Mao","given":"Dehua","affiliations":[{"id":32415,"text":"Chinese Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":946712,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Huangh, Zheng Y.X.","contributorId":360047,"corporation":false,"usgs":false,"family":"Huangh","given":"Zheng","middleInitial":"Y.X.","affiliations":[{"id":79946,"text":"Nanjing Forestry University","active":true,"usgs":false}],"preferred":false,"id":946713,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"de Boer, Willem Frederik","contributorId":360049,"corporation":false,"usgs":false,"family":"de Boer","given":"Willem","middleInitial":"Frederik","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":946714,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Takekawa, John","contributorId":330942,"corporation":false,"usgs":false,"family":"Takekawa","given":"John","affiliations":[{"id":32931,"text":"USGS - Retired","active":true,"usgs":false}],"preferred":false,"id":946715,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Prosser, Diann J. 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":221167,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":946716,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Xiao, Xiangming","contributorId":150759,"corporation":false,"usgs":false,"family":"Xiao","given":"Xiangming","affiliations":[{"id":18095,"text":"Center for Spatial Analysis, U of OK, Norman, OK","active":true,"usgs":false}],"preferred":false,"id":946717,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70270422,"text":"70270422 - 2025 - Integrating hunter dynamics and waterfowl dynamics to inform harvest management","interactions":[],"lastModifiedDate":"2025-08-19T13:52:50.613209","indexId":"70270422","displayToPublicDate":"2025-08-17T08:50:39","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Integrating hunter dynamics and waterfowl dynamics to inform harvest management","docAbstract":"The successful conservation and management of North American waterfowl relies upon an adaptive harvest management framework that accounts for changes in the system state and critical uncertainties related to the dynamics of waterfowl populations and habitats. Increasing recognition of the importance of the human dimensions of the harvest process, particularly those related to hunters, has motivated calls for the integration of social objectives into waterfowl conservation programs and decision making. We introduce a framework for modeling the dynamics of hunter populations and behavior alongside those of waterfowl populations. Using Bayesian estimation, we fit a dynamic state space model to observational data from the Mid-Continent mallard (Anas platyrhynchos) system over a 20-year period and estimated parameter values for the relative effects of a set of hypothesized drivers of hunter recruitment, retention, reactivation, participation, and success rates. We then made projections across 3 future scenarios to examine the continuation of current trends, the potential effects of a shift to a moderate regulatory framework as informed by expert elicitation, and increased hunter recruitment to maintain a stable hunter population. We found that a theoretical stable state exists for Mid-Continent mallard and hunter populations but that the influence of broader sociocultural shifts and increasing hunter mortality from an aging base pose significant challenges for efforts to stabilize the ongoing decline of active hunter numbers, even under favorable regulatory conditions. This modeling framework and results from it can be used to inform decision processes in the management of game populations that seek to include social objectives and assess the potential trade-offs of prioritizing across social and ecological objectives. We emphasize the need for focused human dimensions expertise throughout the process of fully integrating goals for waterfowl populations, habitats, and people in waterfowl conservation.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70084","usgsCitation":"Berl, R.E., Devers, P.K., Boomer, G.S., and Runge, M., 2025, Integrating hunter dynamics and waterfowl dynamics to inform harvest management: Journal of Wildlife Management, no. Online First, https://doi.org/10.1002/jwmg.70084.","ipdsId":"IP-177503","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":498234,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.70084","text":"Publisher Index Page"},{"id":494296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"Online First","noUsgsAuthors":false,"publicationDate":"2025-08-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Berl, Richard Eugene Waggaman 0000-0002-4154-1319","orcid":"https://orcid.org/0000-0002-4154-1319","contributorId":336851,"corporation":false,"usgs":true,"family":"Berl","given":"Richard","email":"","middleInitial":"Eugene Waggaman","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Devers, Patrick K. 0000-0002-5281-6875","orcid":"https://orcid.org/0000-0002-5281-6875","contributorId":359900,"corporation":false,"usgs":false,"family":"Devers","given":"Patrick","middleInitial":"K.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":946389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boomer, G. Scott 0000-0001-5854-3604","orcid":"https://orcid.org/0000-0001-5854-3604","contributorId":261408,"corporation":false,"usgs":false,"family":"Boomer","given":"G.","email":"","middleInitial":"Scott","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":true,"id":946390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":214737,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":946391,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272650,"text":"70272650 - 2025 - Economic costs of invasive carps in the United States: Case study and management implications","interactions":[],"lastModifiedDate":"2025-12-03T15:39:53.981745","indexId":"70272650","displayToPublicDate":"2025-08-16T09:43:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Economic costs of invasive carps in the United States: Case study and management implications","docAbstract":"Biological invasions can have far-reaching impacts and incur enormous monetary costs. Economic considerations play an important role in management decision-making. We used the invasion of U.S. waterways by silver (Hypophthalmichthys molitrix) and bighead (H. nobilis) carp as a case study of the costs of aquatic invasive species. Although these carps are well-known invaders, published reports on their economic costs are lacking. Our study included market values for commercial fisheries, non-market values for recreational fisheries, and management costs. Our results showed that by 2020, U.S. federal and state agencies had spent nearly $592 million in cumulative management costs. A difference-in-difference model testing for the effect of invasive carp on commercial harvest in invaded versus uninvaded reaches of the Mississippi and Illinois Rivers showed no statistical significance. A benefit transfer analysis of invasion effects on total economic value of recreational fishing, an important ecosystem service, in a heavily invaded section of the Illinois River estimated a total loss of more than $10 million over 10 years. While there are other known impacts on ecosystem services, including alteration of aquatic food webs, plankton communities, and native fish communities, these could not be quantified in economic terms in our analysis.
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W.","contributorId":363146,"corporation":false,"usgs":false,"family":"Snapp","given":"Joseph","middleInitial":"W.","affiliations":[{"id":37487,"text":"formerly USGS","active":true,"usgs":false}],"preferred":false,"id":951169,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huber, Christopher","contributorId":363148,"corporation":false,"usgs":false,"family":"Huber","given":"Christopher","affiliations":[{"id":86628,"text":"NPS, formerly USGS","active":true,"usgs":false}],"preferred":false,"id":951170,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Caudill, James","contributorId":363149,"corporation":false,"usgs":false,"family":"Caudill","given":"James","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":951171,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grigelis, Peter E.","contributorId":363150,"corporation":false,"usgs":false,"family":"Grigelis","given":"Peter","middleInitial":"E.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":951172,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270821,"text":"70270821 - 2025 - Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan","interactions":[],"lastModifiedDate":"2025-08-25T15:21:07.451208","indexId":"70270821","displayToPublicDate":"2025-08-16T08:15:07","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3504,"text":"Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan","docAbstract":"The Ili River Basin is characterized by complex topography and diverse climatic zones with limited in situ observations. This study evaluates the performance of six widely used precipitation datasets, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), ERA5_Land (European Centre for Medium-Range Weather Forecasts—ECMWF Reanalysis 5_Land), GPCC (Global Precipitation Climatology Centre), IMERG (Integrated Multi-satellite Retrievals for GPM), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and TerraClimate, against ground-based data from 2001 to 2023. The evaluation is conducted across multiple spatial scales and temporal resolutions. At the basin scale, most datasets exhibit strong correlations with in situ observations across all temporal scales (r > 0.7), except for PERSIANN, which demonstrates a relatively weaker performance during summer and winter (r < 0.6). All datasets except ERA5_ Land show low annual and monthly bias (<5%), although larger errors are observed during summer, particularly for IMERG and PERSIANN. Dataset performance generally declines with increasing elevation. Basin-wide gridded evaluations reveal distinct spatial variations across all elevation zones, with CHIRPS showing the strongest ability to capture orographic precipitation gradients throughout the basin. All datasets correctly identified 2008 as a drought year and 2016 as a wet year, even though the magnitude and spatial resolution of the anomalies varied among them. These findings highlight the importance of selecting precipitation datasets that are suited to the complex topographic and climatic characteristics of transboundary basins. Our study provides valuable insights for improving hydrological modeling and can be used for water sustainability and flood–drought mitigation support activities in the Ili River Basin.
","language":"English","publisher":"MDPI","doi":"10.3390/su17167418","usgsCitation":"Duisebek, B., Senay, G., Ojima, D.S., Zhang, T., Sagin, J., and Wang, X., 2025, Evaluating the performance of multiple precipitation datasets over the transboundary Ili River Basin between China and Kazakhstan: Sustainability, v. 17, no. 16, 7418, 26 p., https://doi.org/10.3390/su17167418.","productDescription":"7418, 26 p.","ipdsId":"IP-181853","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":495056,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su17167418","text":"Publisher Index Page"},{"id":494743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China, Kazakhstan","otherGeospatial":"Ili River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 46.71910209135149,\n 50.09770097338648\n ],\n [\n 46.71910209135149,\n 44.15010644271524\n ],\n [\n 84.48446379774907,\n 44.15010644271524\n ],\n [\n 84.48446379774907,\n 50.09770097338648\n ],\n [\n 46.71910209135149,\n 50.09770097338648\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"16","noUsgsAuthors":false,"publicationDate":"2025-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Duisebek, Baktybek","contributorId":360498,"corporation":false,"usgs":false,"family":"Duisebek","given":"Baktybek","affiliations":[{"id":86016,"text":"Kazakh British Technical University","active":true,"usgs":false}],"preferred":false,"id":947122,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":947123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ojima, Dennis S.","contributorId":208511,"corporation":false,"usgs":false,"family":"Ojima","given":"Dennis","email":"","middleInitial":"S.","affiliations":[{"id":37812,"text":"Colorado State University; North Central Climate Science Center","active":true,"usgs":false}],"preferred":false,"id":947124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Tibin","contributorId":360499,"corporation":false,"usgs":false,"family":"Zhang","given":"Tibin","affiliations":[{"id":86019,"text":"State Key Laboratory of Soil and Water Conservation Science and Engineering, Northwest A&F University","active":true,"usgs":false}],"preferred":false,"id":947125,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sagin, Janay","contributorId":360500,"corporation":false,"usgs":false,"family":"Sagin","given":"Janay","affiliations":[{"id":86016,"text":"Kazakh British Technical University","active":true,"usgs":false}],"preferred":false,"id":947126,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Xuejiao","contributorId":271179,"corporation":false,"usgs":false,"family":"Wang","given":"Xuejiao","email":"","affiliations":[{"id":12433,"text":"China University of Geosciences","active":true,"usgs":false}],"preferred":false,"id":947127,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70270385,"text":"70270385 - 2025 - RAD (Resist-Accept-Direct) switch points and triggers for adaptation planning","interactions":[],"lastModifiedDate":"2025-08-18T14:13:27.087542","indexId":"70270385","displayToPublicDate":"2025-08-15T09:05:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"RAD (Resist-Accept-Direct) switch points and triggers for adaptation planning","docAbstract":"Climate change is transforming ecosystems globally. The Resist-Accept-Direct (RAD) framework has gained traction within many natural resource management institutions to help consider the decision space in response to this transformation. Because RAD helps manage for directional change, RAD choices entail considering which RAD pathway to implement and for how long. For example, one may accept a slowly changing ecosystem, but at a certain point, decide to begin resisting or directing the change an ecosystem is experiencing. Alternatively, one may begin resisting an ecosystem transformation, but ultimately realize resistance is no longer feasible based on cost or efficacy. These choices are challenging and encompass broad domains of cultural, ecological, financial, organizational, public, regulatory, and technological considerations to determine when to switch RAD pathways. We introduce the concepts of RAD switch points and triggers to help support these decision processes. We illustrate these concepts using case studies on walleye (Sander vitreus) stocking decisions in Wisconsin, wildfire response in the Greater Yellowstone Ecosystem, and bull trout (Salvelinus confluentus) management in Oregon, USA. Synthesizing across these examples, we delineate key points for decision makers as they (iteratively) reevaluate among the RAD pathways as conditions continue to change.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2025.126419","usgsCitation":"Lynch, A.J., Ashander, J., Ciocco, A., Cravens, A.E., Dassow, C.J., Dee, L.E., Dunham, J., Eaton, M.J., Embke, H., Hennessy, J., Latzka, A., Lawrence, D.J., Littell, J., Miller, B.W., Palasti, L., Runge, M., Sass, G., Shultz, A.D., Siegel, K., Svancara, L.K., Thompson, L., Thurman, L., Valler, J.B., Weiskopf, S.R., and Yocum, H.M., 2025, RAD (Resist-Accept-Direct) switch points and triggers for adaptation planning: Journal of Environmental Management, v. 392, 126419, 13 p., https://doi.org/10.1016/j.jenvman.2025.126419.","productDescription":"126419, 13 p.","ipdsId":"IP-165065","costCenters":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":494254,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"392","noUsgsAuthors":false,"publicationDate":"2025-08-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Lynch, Abigail J. 0000-0001-8449-8392","orcid":"https://orcid.org/0000-0001-8449-8392","contributorId":204271,"corporation":false,"usgs":true,"family":"Lynch","given":"Abigail","middleInitial":"J.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":946256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashander, Jaime 0000-0002-1841-4768","orcid":"https://orcid.org/0000-0002-1841-4768","contributorId":294949,"corporation":false,"usgs":true,"family":"Ashander","given":"Jaime","email":"","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":946257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ciocco, Anthony 0000-0002-5849-888X","orcid":"https://orcid.org/0000-0002-5849-888X","contributorId":356914,"corporation":false,"usgs":true,"family":"Ciocco","given":"Anthony","affiliations":[{"id":85276,"text":"NC CASC","active":true,"usgs":false}],"preferred":true,"id":946258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cravens, Amanda E. 0000-0002-0271-7967 aecravens@usgs.gov","orcid":"https://orcid.org/0000-0002-0271-7967","contributorId":196752,"corporation":false,"usgs":true,"family":"Cravens","given":"Amanda","email":"aecravens@usgs.gov","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":946259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dassow, Colin J.","contributorId":293206,"corporation":false,"usgs":false,"family":"Dassow","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":16117,"text":"Wisconsin DNR","active":true,"usgs":false}],"preferred":false,"id":946260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dee, Laura E. 0000-0003-0471-1371","orcid":"https://orcid.org/0000-0003-0471-1371","contributorId":213455,"corporation":false,"usgs":false,"family":"Dee","given":"Laura","email":"","middleInitial":"E.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":946261,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science 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M.","contributorId":199495,"corporation":false,"usgs":false,"family":"Hennessy","given":"Joseph M.","affiliations":[],"preferred":false,"id":946266,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Latzka, Alexander W.","contributorId":348855,"corporation":false,"usgs":false,"family":"Latzka","given":"Alexander W.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946267,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Lawrence, David J","contributorId":242819,"corporation":false,"usgs":false,"family":"Lawrence","given":"David","email":"","middleInitial":"J","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":946268,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Littell, Jeremy S. 0000-0002-5302-8280","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":205907,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","middleInitial":"S.","affiliations":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":946269,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Miller, Brian W. 0000-0003-1716-1161","orcid":"https://orcid.org/0000-0003-1716-1161","contributorId":196603,"corporation":false,"usgs":true,"family":"Miller","given":"Brian","email":"","middleInitial":"W.","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":946270,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Palasti, Luca","contributorId":359786,"corporation":false,"usgs":false,"family":"Palasti","given":"Luca","affiliations":[{"id":12502,"text":"University of Colorado - Boulder","active":true,"usgs":false}],"preferred":false,"id":946271,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":214737,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":946272,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Sass, Gregory","contributorId":359787,"corporation":false,"usgs":false,"family":"Sass","given":"Gregory","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":946273,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Shultz, Aaron D.","contributorId":303739,"corporation":false,"usgs":false,"family":"Shultz","given":"Aaron","email":"","middleInitial":"D.","affiliations":[{"id":16233,"text":"Great Lakes Indian Fish and Wildlife Commission","active":true,"usgs":false}],"preferred":false,"id":946274,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Siegel, Katherine","contributorId":359788,"corporation":false,"usgs":false,"family":"Siegel","given":"Katherine","affiliations":[{"id":7044,"text":"University of Toronto","active":true,"usgs":false}],"preferred":false,"id":946275,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Svancara, Leona Kay 0009-0007-1936-6079","orcid":"https://orcid.org/0009-0007-1936-6079","contributorId":359789,"corporation":false,"usgs":true,"family":"Svancara","given":"Leona","middleInitial":"Kay","affiliations":[{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":946276,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Thompson, Laura 0000-0002-7884-6001","orcid":"https://orcid.org/0000-0002-7884-6001","contributorId":207364,"corporation":false,"usgs":true,"family":"Thompson","given":"Laura","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":946277,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":946278,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Valler, Jackson Brear 0009-0006-0076-7481","orcid":"https://orcid.org/0009-0006-0076-7481","contributorId":359790,"corporation":false,"usgs":true,"family":"Valler","given":"Jackson","middleInitial":"Brear","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":946279,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Weiskopf, Sarah R. 0000-0002-5933-8191","orcid":"https://orcid.org/0000-0002-5933-8191","contributorId":207699,"corporation":false,"usgs":true,"family":"Weiskopf","given":"Sarah","email":"","middleInitial":"R.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":946280,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Yocum, Heather M. 0000-0002-3754-4330","orcid":"https://orcid.org/0000-0002-3754-4330","contributorId":265513,"corporation":false,"usgs":false,"family":"Yocum","given":"Heather","email":"","middleInitial":"M.","affiliations":[{"id":54706,"text":"Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":946281,"contributorType":{"id":1,"text":"Authors"},"rank":25}]}} ,{"id":70270388,"text":"70270388 - 2025 - Relationships between water quality, stream metabolism, and water stargrass growth in the lower Yakima River, 2018 to 2020","interactions":[],"lastModifiedDate":"2025-08-18T13:32:56.593268","indexId":"70270388","displayToPublicDate":"2025-08-15T08:30:05","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":"Relationships between water quality, stream metabolism, and water stargrass growth in the lower Yakima River, 2018 to 2020","docAbstract":"Since the early 2000s, water clarity on the lower Yakima River has improved. Changes in best management practices combined with a total maximum daily load for suspended sediment led to these improved conditions. As water clarity improved, so did conditions for aquatic plants; the clearer the water, the better the light penetration, and dramatic increases in plant biomass were observed. In the lower Yakima River, beds of native water stargrass (grass-leaf mud-plantain, Heteranthera dubia) are prolific and can extend bank to bank in some locations. Increased primary productivity can alter local water quality by increasing daily swings of dissolved oxygen (DO) and pH from photosynthesis. In this study, we collected continuous water quality data for 2.5 years at three sites on the lower Yakima River to provide a detailed examination of water quality conditions. These sites were located just below the Prosser Dam (Prosser site, USGS station 12509489), at a long-term USGS streamgage in Benton County (Kiona site, USGS station 12510500), and in West Richland, WA (Van Giesen site; USGS station 12511800). In addition to the continuous water quality data collected, estimates of water stargrass biomass were made through the growing season (June through September) during water years 2018–2020. The main objectives of this study were to document water quality conditions on the lower Yakima River and to analyze if there was a statistical relation between the amount of water stargrass biomass and the observed daily cycles of water quality.
During summer, frequent exceedances of established water quality criteria were documented each year during this study. Maximum daily temperatures exceeded 21o C, minimum DO concentrations were below 8 milligrams per liter (mg/L), and maximum pH surpassed 8.5 almost every day from June through August each water year across all three monitoring locations. Water stargrass biomass tended to increase from June through August and September but was ‘reset’ by the following summer likely from high winter and spring streamflows and natural die-off. Results from this study suggest that spring peak discharge and average spring discharge affects late-season water stargrass biomass. In 2018, the highest peak discharge of the study took place, and the August water stargrass biomass values were lower in 2018 than in 2019 and 2020.
Seven different water quality metrics were computed for a 7-day and 28-day period prior to each water stargrass sample to examine possible correlations between the plant biomass and water quality. We examined daily maximum temperature, DO minimum, DO range, pH maximum, pH range, mean nitrate, and nitrate range. While there were some statistically significant correlations among the seven water quality metrics and median water stargrass biomass, the correlations were not consistent across all three sites. At the Prosser site, the 7-day average daily maximum pH and average daily pH range showed significant correlations with median water stargrass biomass. At the Kiona site, both the 7-day and 28-day mean nitrate values showed a significant relationship to median water stargrass biomass. At the Van Giesen site, there were no significant correlations between the seven water quality metrics and median water stargrass biomass. However, whole-stream estimates of gross primary productivity at the Kiona site, which incorporate the entire river community, were related to temperature, DO, and pH indicating the whole river community is influencing surface water quality to some extent.
Additional data on water stargrass biomass and continuous water quality could help elucidate the complex interactions between growth and water quality. At a minimum, collection of water stargrass biomass data near the end of the growing season (mid to late August) could be added to locations where continuous water quality and streamflow discharge measurements are also being collected. In addition, experimental removal of water stargrass and its effects on local water quality could provide insight into the complex relationships between water stargrass growth and water quality. Finally, further investigations into streamflow and its effects on water stargrass could be improved. Our data showed a qualitative relationship between spring peak discharge, average spring discharge, and August water stargrass biomass, but more data are needed to confirm this. If spring high streamflows are important for late-season biomass, then targeted flow releases from reservoirs in the upper watershed could be used to slow down water stargrass growth during summer months.