Sustainable and just environmental management depends on meaningful consideration of the plural values of nature, as they arise in association with diverse worldviews and understandings of well-being. To achieve value pluralism in decision-making, we must also attend to knowledge pluralism, in terms of recognizing the validity and decision relevance of a broader suite of knowledge forms that convey diverse understandings of well-being and benefit. In this article, we outline a social learning tool – the Benefits Knowledges Learning Framework – that supports expanded thinking about decision-relevant, actionable knowledge, and the associated spectrum of available opportunities to learn from these diverse knowledge forms across phases of decision-making. It does so through: 1) cultivation of reflexivity and mutual learning about the knowledge systems of diverse actors involved in the decision process; 2) identification of diverse benefits knowledge forms that are available to inform decision-making; and 3) identification of opportunities to learn from these knowledge forms. Diverse forms of benefits knowledge include both knowledge products (documentation) and knowledge practices (lived and embodied). The framework can be applied to retrospective case analysis to understand and learn from constraints and enabling factors in past decision processes. It can also be applied to assess on-going decision-making and identify current opportunities for improvement. The framework begins with a start-up phase that encourages those applying the framework to address any concerns raised by stakeholders and rightsholders and determine whether framework application is appropriate in a particular context.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2025.101759","usgsCitation":"Hoelting, K.R., Martinez, D.E., Bair, L., Schuster, R., and Gavin, M.C., 2025, The Benefits Knowledges Learning Framework: A tool for learning across diverse knowledge systems in ecosystem valuation: Ecosystem Services, v. 75, 101759, 22 p., https://doi.org/10.1016/j.ecoser.2025.101759.","productDescription":"101759, 22 p.","ipdsId":"IP-159527","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":495380,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoser.2025.101759","text":"Publisher Index Page"},{"id":495218,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.57860063518241,\n 48.14959704491247\n ],\n [\n -123.56501105685818,\n 48.11843129821039\n ],\n [\n -123.5785436643449,\n 48.08332135398534\n ],\n [\n -123.62254984136398,\n 47.97943696162014\n ],\n [\n -123.59267384461675,\n 47.9768449053573\n ],\n [\n -123.5597999390546,\n 48.05669139870743\n ],\n [\n -123.54507441495804,\n 48.10618573356931\n ],\n [\n -123.54769205038426,\n 48.14959704491247\n ],\n [\n -123.57860063518241,\n 48.14959704491247\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"75","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hoelting, Kristin R. 0000-0003-3358-2257","orcid":"https://orcid.org/0000-0003-3358-2257","contributorId":361008,"corporation":false,"usgs":false,"family":"Hoelting","given":"Kristin","middleInitial":"R.","affiliations":[{"id":86144,"text":"Colorado State University, Human Dimensions of Natural Resources Department, Fort Collins, CO, United States","active":true,"usgs":false}],"preferred":false,"id":948102,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinez, Doreen E.","contributorId":361009,"corporation":false,"usgs":false,"family":"Martinez","given":"Doreen","middleInitial":"E.","affiliations":[{"id":86145,"text":"Colorado State University, Department of Ethnic Studies, Fort Collins, CO, United States","active":true,"usgs":false}],"preferred":false,"id":948103,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bair, Lucas 0000-0002-9911-3624","orcid":"https://orcid.org/0000-0002-9911-3624","contributorId":248714,"corporation":false,"usgs":true,"family":"Bair","given":"Lucas","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":948104,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schuster, Rudy 0000-0003-2353-8500 schusterr@usgs.gov","orcid":"https://orcid.org/0000-0003-2353-8500","contributorId":3119,"corporation":false,"usgs":true,"family":"Schuster","given":"Rudy","email":"schusterr@usgs.gov","affiliations":[],"preferred":true,"id":948105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gavin, Michael C. 0000-0002-2169-4668","orcid":"https://orcid.org/0000-0002-2169-4668","contributorId":361010,"corporation":false,"usgs":false,"family":"Gavin","given":"Michael","middleInitial":"C.","affiliations":[{"id":86144,"text":"Colorado State University, Human Dimensions of Natural Resources Department, Fort Collins, CO, United States","active":true,"usgs":false}],"preferred":false,"id":948106,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271296,"text":"70271296 - 2025 - Dispersal and survival of sea lamprey in Lake Erie and connected waterways","interactions":[],"lastModifiedDate":"2026-01-05T16:40:02.610528","indexId":"70271296","displayToPublicDate":"2025-08-29T07:47:50","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Dispersal and survival of sea lamprey in Lake Erie and connected waterways","docAbstract":"Invasive sea lamprey inhabiting the North American Laurentian Great Lakes are the target of the world’s longest running vertebrate invasive species control program. However, metapopulation dynamics comprising survival and dispersal during the sea lampreys’ lake-resident life stages are poorly understood. We applied acoustic telemetry and continuous-time multistate capture-recapture modeling to address this knowledge gap in Lake Erie. We acoustic-tagged sea lamprey (n = 619) and deployed acoustic receivers into all known connected waterways containing larval sea lamprey rearing habitat (n = 23), including the Detroit River (connecting Lake Erie to Lake Huron) and distributaries to Lake Ontario. Distribution of tagged sea lamprey to putative spawning waterways was shaped by heterogeneous stream attractiveness and distance-limited dispersal. Using parameter estimates from our capture-recapture model and simulation, we predicted survival and dispersal outcomes for a hypothetical sea lamprey population evenly distributed throughout Lake Erie at the beginning of January (34% pre-spawn mortality, 45% dispersal into Lake Erie tributaries, 19% dispersal into the Detroit River, and 2% dispersal into Lake Ontario). The methodology we applied may be widely useful for investigating dispersal and survival of aquatic organisms.","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2025-0103","usgsCitation":"Lewandoski, S.A., and Holbrook, C., 2025, Dispersal and survival of sea lamprey in Lake Erie and connected waterways: Canadian Journal of Fisheries and Aquatic Sciences, v. 82, p. 1-13, https://doi.org/10.1139/cjfas-2025-0103.","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-181833","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":495148,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496372,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2025-0103","text":"Publisher Index Page"}],"country":"Canada, United States","otherGeospatial":"Lake Erie, Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.70617488623432,\n 42.02384024551296\n ],\n [\n -83.62185164386733,\n 41.22531282546535\n ],\n [\n -80.95581262939565,\n 41.614162157533514\n ],\n [\n -78.44800562562105,\n 42.65436741270719\n ],\n [\n -78.07746378748234,\n 44.06396277336654\n ],\n [\n -79.76290535037472,\n 43.86046169412299\n ],\n [\n -83.70617488623432,\n 42.02384024551296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","noUsgsAuthors":false,"publicationDate":"2025-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Lewandoski, Sean Alois 0000-0002-6801-5861","orcid":"https://orcid.org/0000-0002-6801-5861","contributorId":340324,"corporation":false,"usgs":true,"family":"Lewandoski","given":"Sean","email":"","middleInitial":"Alois","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":947884,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":139681,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher","email":"cholbrook@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":947885,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271378,"text":"70271378 - 2025 - Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper","interactions":[],"lastModifiedDate":"2025-09-10T14:44:00.057371","indexId":"70271378","displayToPublicDate":"2025-08-29T07:38:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper","docAbstract":"The Palila (Loxioides bailleui), the last member of the once speciose finch-billed Hawaiian honeycreeper clade (Drepanidinae) in the main Hawaiian Islands, faces critical conservation challenges as an endangered species. Understanding the drivers of its decline is essential for effective management. We used additive decomposition models to examine temporal trends in climatic variables (temperature, precipitation, drought) and Normalized Difference Vegetation Index (NDVI), a vegetation health metric hypothesized to be associated with long-term trends in Palila abundance at landscape (250 m) scales on the Island of Hawai'i. A breakpoint analysis identified 2005–2009 as critical years of Palila decline. Vegetation health metrics at the 250 m scale lined up well both spatially and temporally with trends in Palila declines, with a significant browning from January 2004 to January 2014. Given the strong correlation between vegetation health and drought metrics at the landscape scale (r = 0.75, p < 0.001), NDVI changes appeared driven by drought. To enable the future projection of habitat quality in this area, we explored a stepwise linear regression to explain the variation in MODIS NDVI in recent years. We found that 87 % of the variability in NDVI can be explained by wet season precipitation and vapor pressure deficit from the previous dry season. The model is largely driven by a strong positive correlation between wet season precipitation and NDVI (r = 0.72, adjusted p < 0.001). Areas that maintained a low likelihood of NDVI decline throughout the time series and experienced increases in predicted Palila count represent potential drought microrefugia for the species. This higher elevation microrefugia is likely resilient against decreases in wet season precipitation through supplemental water retention from fog drip. While NDVI rebounded after 2014, Palila have not recovered. Our analysis highlights the importance of trend decomposition for monitoring endangered species with limited rebound potential due to small population dynamics and indicate continued warm, dry conditions may prevent Palila recovery without intervention.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03831","usgsCitation":"Gallerani, E.M., Camp, R.J., Banko, P.C., Madson, A., Dong, C., Fortini, L., Ma, Z., and Gillespie, T.W., 2025, Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian honeycreeper: Global Ecology and Conservation, v. 62, e03831, 14 p., https://doi.org/10.1016/j.gecco.2025.e03831.","productDescription":"e03831, 14 p.","ipdsId":"IP-166687","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":495392,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2025.e03831","text":"Publisher Index Page"},{"id":495277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.6511297931527,\n 19.916012794249554\n ],\n [\n -155.6511297931527,\n 19.716091807948942\n ],\n [\n -155.34902248798784,\n 19.716091807948942\n ],\n [\n -155.34902248798784,\n 19.916012794249554\n ],\n [\n -155.6511297931527,\n 19.916012794249554\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gallerani, Erica M.","contributorId":361171,"corporation":false,"usgs":false,"family":"Gallerani","given":"Erica","middleInitial":"M.","affiliations":[{"id":86232,"text":"University of California Los Angles","active":true,"usgs":false}],"preferred":false,"id":948318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":948319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":948320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madson, Austin","contributorId":304629,"corporation":false,"usgs":false,"family":"Madson","given":"Austin","email":"","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":948321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dong, Chunyu","contributorId":304633,"corporation":false,"usgs":false,"family":"Dong","given":"Chunyu","email":"","affiliations":[{"id":37968,"text":"Sun Yat-Sen University","active":true,"usgs":false}],"preferred":false,"id":948322,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fortini, Lucas Berio 0000-0002-5781-7295","orcid":"https://orcid.org/0000-0002-5781-7295","contributorId":236984,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas Berio","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":948323,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ma, Zhimin","contributorId":304634,"corporation":false,"usgs":false,"family":"Ma","given":"Zhimin","email":"","affiliations":[{"id":37968,"text":"Sun Yat-Sen University","active":true,"usgs":false}],"preferred":false,"id":948324,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gillespie, Thomas W.","contributorId":361172,"corporation":false,"usgs":false,"family":"Gillespie","given":"Thomas","middleInitial":"W.","affiliations":[{"id":86232,"text":"University of California Los Angles","active":true,"usgs":false}],"preferred":false,"id":948325,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271142,"text":"gip261 - 2025 - U.S. Geological Survey monitoring milestones—Chagrin River at Willoughby, OH (04209000)","interactions":[],"lastModifiedDate":"2026-02-03T15:17:16.867519","indexId":"gip261","displayToPublicDate":"2025-08-28T12:04:44","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"261","displayTitle":"U.S. Geological Survey Monitoring Milestones—Chagrin River at Willoughby, OH (04209000)","title":"U.S. Geological Survey monitoring milestones—Chagrin River at Willoughby, OH (04209000)","docAbstract":"The Chagrin River at Willoughby, OH (04209000), streamgage is the 1,000th U.S. Geological Survey (USGS) streamgage to reach Centennial status. Centennial Streamgages are USGS streamgages that have been in operation for 100 years or more. Collecting water data since 1925, it celebrated its 100th birthday on August 1, 2025.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip261","usgsCitation":"Bunch, C.E., 2025, U.S. Geological Survey monitoring milestones—Chagrin River at Willoughby, OH (04209000): U.S. Geological Survey General Information Product 261, https://doi.org/10.3133/gip261.","productDescription":"1 p.","onlineOnly":"Y","ipdsId":"IP-181201","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":495028,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/261/coverthb.jpg"},{"id":495029,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/261/gip261.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 261"}],"country":"United States","state":"Ohio","city":"Willoughby","otherGeospatial":"Chagrin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.40271134368446,\n 41.63183038434812\n ],\n [\n -81.40271134368446,\n 41.62829118594672\n ],\n [\n -81.39884786935615,\n 41.62829118594672\n ],\n [\n -81.39884786935615,\n 41.63183038434812\n ],\n [\n -81.40271134368446,\n 41.63183038434812\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"National Streamgage Networks Coordinator
Observing Systems Division
Water Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Smallmouth Bass (Micropterus dolomieu) has been widely introduced beyond its native distribution where interactions with other organisms are largely unknown. We examined the food habits of Smallmouth Bass in Coeur d'Alene Lake, Idaho. Smallmouth Bass were sampled monthly from March 2012 to May 2013 using short duration (1–2 hr sets) gill netting and electrofishing. In total, food habits were evaluated from 904 Smallmouth Bass varying in total length from 39 to 492 mm using gastric lavage. Diet composition varied by season and age. Smallmouth Bass less than 100 mm had diets dominated by invertebrates, particularly Ephemeroptera, Odonata, and Diptera. Fishes were increasingly important in the diet of Smallmouth Bass longer than 100 mm. Interestingly, crayfish (Decapoda) were virtually absent in Smallmouth Bass stomachs; only eight Smallmouth Bass had crayfish in their diet. Native vertebrates were also rare in Smallmouth Bass diets. Rather, kokanee (Oncorhynchus nerka), a nonnative species, was generally the most commonly consumed fish prey item (present in 5–15% of Smallmouth Bass across seasons). Kokanee contributed the highest percentage of total energy (approximately 45% of all energy) of any prey item. Results of this study suggest that native fishes of conservation concern are a minor component of Smallmouth Bass diets and that kokanee is important in meeting the energy demands of nonnative Smallmouth Bass. Further research on the distribution and abundance of crayfish in the system and on the population-level effects of Smallmouth Bass predation on kokanee would be insightful and help guide management actions in Coeur d'Alene Lake and similar systems in western North America.
","language":"English","publisher":"BioOne","doi":"10.3955/046.098.0202","usgsCitation":"Quist, M., Walrath, J.D., Firehammer, J.A., 2025, Food habits of nonnative Smallmouth Bass in Coeur d’Alene Lake, Idaho: Northwest Science, v. 98, no. 2, p. 99-115, https://doi.org/10.3955/046.098.0202.","productDescription":"17 p.","startPage":"99","endPage":"115","ipdsId":"IP-171065","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500350,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Coeur d'Alene Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.95399615968373,\n 47.7008848338825\n ],\n [\n -116.95399615968373,\n 47.313395369365765\n ],\n [\n -116.60623470246856,\n 47.313395369365765\n ],\n [\n -116.60623470246856,\n 47.7008848338825\n ],\n [\n -116.95399615968373,\n 47.7008848338825\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"98","issue":"2","noUsgsAuthors":false,"publicationDate":"2025-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Quist, Michael C. 0000-0001-8268-1839","orcid":"https://orcid.org/0000-0001-8268-1839","contributorId":272016,"corporation":false,"usgs":true,"family":"Quist","given":"Michael C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walrath, John D.","contributorId":204718,"corporation":false,"usgs":false,"family":"Walrath","given":"John","email":"","middleInitial":"D.","affiliations":[{"id":36596,"text":"Wyoming Game and Fish Department","active":true,"usgs":false}],"preferred":false,"id":956314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Firehammer, Jon A.","contributorId":171508,"corporation":false,"usgs":false,"family":"Firehammer","given":"Jon","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":956315,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271435,"text":"70271435 - 2025 - Wetland ecohydrology","interactions":[],"lastModifiedDate":"2025-09-15T13:53:29.901159","indexId":"70271435","displayToPublicDate":"2025-08-28T08:49:26","publicationYear":"2025","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Wetland ecohydrology","docAbstract":"Ecohydrology emphasizes the interactions between ecological and hydrological patterns and processes in wetlands. Given that wetlands are fundamentally defined by prolonged saturation or flooding of land, an ecohydrological perspective is implicit in wetland ecology. In this review, we provide examples of how variation in hydrologic processes in space and time influences wetland ecosystems in temperate riparian zones, inland temperate wetlands, and subtropical monsoonal wetlands. Because wetland ecosystems are highly impacted by anthropogenic change, an understanding of ecohydrological processes in wetlands will be critical for future conservation and restoration of wetlands in a changing world.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Routledge handbook of wetlands","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Routledge","doi":"10.4324/9781003219644-6","usgsCitation":"Dixon, M.D., Johnson, W.C., and Middleton, B., 2025, Wetland ecohydrology, chap. of Routledge handbook of wetlands, p. 38-53, https://doi.org/10.4324/9781003219644-6.","productDescription":"16 p.","startPage":"38","endPage":"53","ipdsId":"IP-149990","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":495485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Dixon, Alan","contributorId":361412,"corporation":false,"usgs":false,"family":"Dixon","given":"Alan","affiliations":[],"preferred":false,"id":948788,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Maddock, Ian","contributorId":361413,"corporation":false,"usgs":false,"family":"Maddock","given":"Ian","affiliations":[],"preferred":false,"id":948789,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Dixon, Mark D.","contributorId":361403,"corporation":false,"usgs":false,"family":"Dixon","given":"Mark","middleInitial":"D.","affiliations":[{"id":16684,"text":"University of South Dakota","active":true,"usgs":false}],"preferred":false,"id":948753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, W. Carter","contributorId":361404,"corporation":false,"usgs":false,"family":"Johnson","given":"W.","middleInitial":"Carter","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":948754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Beth A. 0000-0002-1220-2326","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":216869,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":948755,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272157,"text":"70272157 - 2025 - Sulfide stress tolerance as a controller of methane production in temperate wetlands","interactions":[],"lastModifiedDate":"2025-11-18T15:55:28.220002","indexId":"70272157","displayToPublicDate":"2025-08-28T08:47:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22709,"text":"International Society of Microbial Ecology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Sulfide stress tolerance as a controller of methane production in temperate wetlands","docAbstract":"Wetlands are a major source of methane emissions and contribute to the observed increase in atmospheric methane over the last 20 years. Methane production in wetlands is the final step of carbon decomposition performed by anaerobic archaea. Although hydrogen/carbon dioxide and acetate are the substrates most often attributed to methanogenesis, other substrates—such as methylated compounds—may additionally play important roles in driving methane production in wetland systems. Here we conducted mesocosm experiments combined with genome-resolved metatranscriptomics to investigate the impact of diverse methanogenic substrate amendment on methanogenesis in two high methane-emitting wetlands with distinct geochemistry, termed P7 and P8. Methanol amendment resulted in high methane production at both sites, whereas acetate and formate amendment only stimulated methanogenesis in P7 mesocosms, where aqueous sulfide concentrations were lower. In P7 sediments, formate amendment fueled acetogenic microbes that produced acetate, which was subsequently utilized by acetoclastic methanogens. In contrast to expression profiles in P7 mesocosms, active methylotrophic methanogen genomes from P8 showed increased expression of genes related to membrane remodeling and DNA damage repair, indicative of stress tolerance mechanisms to counter sulfide toxicity. Methylotrophic methanogenesis generates higher free energy yields than acetoclastic methanogenesis, which likely enables allocation of more energy toward stress responses. These findings contribute to the growing body of literature highlighting methylotrophic methanogenesis as an important methane production pathway in wetlands. By using less competitive substrates like methanol that provide greater energy yields, methylotrophic methanogens may invest in physiological strategies that provide competitive advantages across a range of environmental stresses.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ismejo/wraf196","usgsCitation":"Bechtold, E., Ellenbogen, J., Xin, D., Pacheco, M., Toner, B.M., Chin, Y., Arnold, W.A., Bansal, S., and Wilkins, M., 2025, Sulfide stress tolerance as a controller of methane production in temperate wetlands: International Society of Microbial Ecology Journal, v. 19, no. 1, wraf196, 15 p., https://doi.org/10.1093/ismejo/wraf196.","productDescription":"wraf196, 15 p.","ipdsId":"IP-178655","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":496736,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ismejo/wraf196","text":"Publisher Index Page"},{"id":496590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","city":"Jamestown","otherGeospatial":"Cottonwood Lakes Study Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -98.88244410419668,\n 47.01330601354951\n ],\n [\n -98.88244410419668,\n 46.93918875139511\n ],\n [\n -98.74201546634932,\n 46.93918875139511\n ],\n [\n -98.74201546634932,\n 47.01330601354951\n ],\n [\n -98.88244410419668,\n 47.01330601354951\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bechtold, Emily","contributorId":357031,"corporation":false,"usgs":false,"family":"Bechtold","given":"Emily","affiliations":[],"preferred":false,"id":950265,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellenbogen, Jared B.","contributorId":357034,"corporation":false,"usgs":false,"family":"Ellenbogen","given":"Jared B.","affiliations":[],"preferred":false,"id":950266,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xin, Danhui","contributorId":362279,"corporation":false,"usgs":false,"family":"Xin","given":"Danhui","affiliations":[],"preferred":false,"id":950267,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pacheco, Marcia","contributorId":362281,"corporation":false,"usgs":false,"family":"Pacheco","given":"Marcia","affiliations":[],"preferred":false,"id":950268,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toner, Brandy M.","contributorId":200816,"corporation":false,"usgs":false,"family":"Toner","given":"Brandy","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":950269,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chin, Yu-Ping","contributorId":195648,"corporation":false,"usgs":false,"family":"Chin","given":"Yu-Ping","affiliations":[],"preferred":false,"id":950270,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arnold, William A.","contributorId":362283,"corporation":false,"usgs":false,"family":"Arnold","given":"William","middleInitial":"A.","affiliations":[],"preferred":false,"id":950271,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bansal, Sheel 0000-0003-1233-1707 sbansal@usgs.gov","orcid":"https://orcid.org/0000-0003-1233-1707","contributorId":167295,"corporation":false,"usgs":true,"family":"Bansal","given":"Sheel","email":"sbansal@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":950272,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wilkins, Michael J.","contributorId":357049,"corporation":false,"usgs":false,"family":"Wilkins","given":"Michael J.","affiliations":[],"preferred":false,"id":950273,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70274048,"text":"70274048 - 2025 - Detection of deer at remote camera sites in relation to snow conditions","interactions":[],"lastModifiedDate":"2026-02-23T14:56:30.776203","indexId":"70274048","displayToPublicDate":"2025-08-28T07:42:50","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":"Detection of deer at remote camera sites in relation to snow conditions","docAbstract":"In the rain-snow transition zone of the Pacific Northwest, climate change is expected to alter the incidence of rain-on-snow and freeze-thaw events, which will change snow density and hardness dynamics. In winter, the ability of economically and ecologically important wildlife species, such as deer (Odocoileus spp.), to efficiently move through the landscape and access forage is mediated by snow conditions. Therefore, snow properties such as density and hardness can directly affect how energetically costly it is for these animals to survive. However, little is known about whether and how ungulates use habitats based on snow density and hardness. We deployed a stratified network of remote camera stations in complex forested terrain in Latah County, Idaho, USA, to remotely measure snow depth and detect deer. We also collected snow density and hardness measurements throughout the winter. We used these data to determine the degree to which the probability of deer presence at cameras could be explained by snow conditions and air temperature. Snow depth and density had negative relationships with the probability of deer presence, while ram resistance (a proxy for snow hardness) had a marginal positive effect. We were able to estimate snow conditions important to deer in winter 2020–2021 primarily using data obtained from cameras. This provides an important proof-of-concept that can be applied at different sites and climate conditions to gain a deeper understanding of how deer are affected by snowpack properties. These methods can be used by managers to determine how ungulates are affected by snow depth, density, and hardness collectively and subsequently inform ungulate management in a changing climate.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.70088","usgsCitation":"Vega, K.S., Marshall, A.M., Svancara, L.K., Ausband, D.E., Link, T., 2025, Detection of deer at remote camera sites in relation to snow conditions: Journal of Wildlife Management, v. 89, no. 8, e70088, 16 p., https://doi.org/10.1002/jwmg.70088.","productDescription":"e70088, 16 p.","ipdsId":"IP-170009","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","county":"Latah County","otherGeospatial":"Moscow Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.03253204629792,\n 46.77946691887465\n ],\n [\n -117.03253204629792,\n 46.67329333736248\n ],\n [\n -116.90649294818746,\n 46.67329333736248\n ],\n [\n -116.90649294818746,\n 46.77946691887465\n ],\n [\n -117.03253204629792,\n 46.77946691887465\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"89","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Vega, Kaitlyn S.","contributorId":366837,"corporation":false,"usgs":false,"family":"Vega","given":"Kaitlyn","middleInitial":"S.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":956291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Adrienne M.","contributorId":366838,"corporation":false,"usgs":false,"family":"Marshall","given":"Adrienne","middleInitial":"M.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":956292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":956293,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":956294,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Link, Timothy E","contributorId":223374,"corporation":false,"usgs":false,"family":"Link","given":"Timothy E","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":956295,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70271312,"text":"70271312 - 2025 - Hiding in plain sight: Genomic characterization of a novel nackednavirus and evidence of diverse adomaviruses in a hyperpigmented lesion of a largemouth bass (Micropterus salmoides)","interactions":[],"lastModifiedDate":"2025-09-04T14:39:15.900872","indexId":"70271312","displayToPublicDate":"2025-08-28T07:31:15","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3700,"text":"Viruses","active":true,"publicationSubtype":{"id":10}},"title":"Hiding in plain sight: Genomic characterization of a novel nackednavirus and evidence of diverse adomaviruses in a hyperpigmented lesion of a largemouth bass (Micropterus salmoides)","docAbstract":"Largemouth bass (LMB; Micropterus nigricans) are popular both as a sportfish and an aquaculture species. At present, six described viruses are associated with LMB, of which two are typically considered in cases of LMB mortality events. Advances in discovery and diagnostic capabilities using next-generation sequencing have augmented surveillance efforts and subsequently led to the discovery of novel cryptogenic viruses. Here, we present evidence of three novel viruses from a single skin sample collected from a hyperpigmented melanistic lesion of an LMB with blotchy bass syndrome associated with MnA-1 co-infection. These viruses represent recently described groups of viruses (adomaviruses and nackednaviruses) that infect fish. Both are markedly understudied and of unknown significance to fish health. This work highlights the diversity of viruses associated with LMB and further advances our understanding of the LMB virome. Application of de novo sequencing approaches presents an opportunity to explore a new frontier of host–pathogen relationships and microbes associated with changing environments.
","language":"English","publisher":"MDPI","doi":"10.3390/v17091173","usgsCitation":"Raines, C.D., Odenkirk, J., Isel, M., Mazik, P., Biggs, M., and Iwanowicz, L., 2025, Hiding in plain sight: Genomic characterization of a novel nackednavirus and evidence of diverse adomaviruses in a hyperpigmented lesion of a largemouth bass (Micropterus salmoides): Viruses, v. 17, no. 9, 1173, 22 p., https://doi.org/10.3390/v17091173.","productDescription":"1173, 22 p.","ipdsId":"IP-169535","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":495186,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/v17091173","text":"Publisher Index Page"},{"id":495164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Little Hunting Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.08426041188461,\n 38.738581446014194\n ],\n [\n -77.08426041188461,\n 38.73216586979461\n ],\n [\n -77.07199477688414,\n 38.73216586979461\n ],\n [\n -77.07199477688414,\n 38.738581446014194\n ],\n [\n -77.08426041188461,\n 38.738581446014194\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-08-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Raines, Clayton D. 0000-0002-0403-190X","orcid":"https://orcid.org/0000-0002-0403-190X","contributorId":296362,"corporation":false,"usgs":true,"family":"Raines","given":"Clayton","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":947946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Odenkirk, John","contributorId":219514,"corporation":false,"usgs":false,"family":"Odenkirk","given":"John","affiliations":[{"id":35592,"text":"Virginia Department of Game and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":947947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Isel, Michael","contributorId":360938,"corporation":false,"usgs":false,"family":"Isel","given":"Michael","affiliations":[{"id":81907,"text":"Virginia Department Wildlife Resources","active":true,"usgs":false}],"preferred":false,"id":947948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazik, Patricia 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":220979,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":947949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Biggs, Morgan Alexandra 0000-0002-5360-8613","orcid":"https://orcid.org/0000-0002-5360-8613","contributorId":345155,"corporation":false,"usgs":true,"family":"Biggs","given":"Morgan Alexandra","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":947950,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Iwanowicz, Luke 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":302048,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":947951,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70267466,"text":"dr1210 - 2025 - A synthesis engine for constructing geologic maps of the United States","interactions":[],"lastModifiedDate":"2026-02-03T15:16:36.738393","indexId":"dr1210","displayToPublicDate":"2025-08-27T13:20:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1210","displayTitle":"A Synthesis Engine for Constructing Geologic Maps of the United States","title":"A synthesis engine for constructing geologic maps of the United States","docAbstract":"The geologic history of the United States is cataloged in thousands of geologic maps produced during many decades. However, the disparate nature of these individual maps makes it challenging to assess resources, research geologic histories, or characterize natural hazards holistically across the Nation. The U.S. House of Representatives 2020 appropriations bill for the U.S. Department of the Interior (H.R. 116-100) requires the U.S. Geological Survey to “bring together detailed national and continental-resolution [two-dimensional] and [three-dimensional] information produced throughout the Survey and by [F]ederal and [S]tate partners.” In response to this directive, this report presents a compilation and synthesis of geologic maps across the United States in the form of a relational database. The synthesis database includes thematic maps that synthesize the Nation’s geology, and retains the original input maps as well as linkages to standardized vocabularies to aid the discoverability of geologic information. Specifically, the synthesis database is targeted toward producing four National-resolution maps for the conterminous United States: Quaternary geology, the geology at the Earth’s surface, pre-Quaternary geology, and Precambrian geology. In addition, the synthesis database includes the infrastructure necessary to expand to additional resolutions in the future.
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Box 25046, Mail Stop 980
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The former Stuart Ranch, now managed by the Bureau of Land Management, is transected by Meadow Valley Wash, where 4,600 feet of perennial stream and adjacent riparian vegetation provide critical habitat for several wildlife and aquatic species protected under the Endangered Species Act. The stream has been altered by prior construction of irrigation diversions, gravel mining, and removal of riparian vegetation, resulting in the loss of instream and riparian vegetation and disconnected floodplains. The stream alteration has also resulted in the loss of native species and increased non-native invasive species and changes in ecological cycles. With the goal of improving habitat extent and quality for native threatened and endangered species, the Bureau of Land Management (BLM) is considering establishing perennial streams through braided side channels by constructing beaver dam analogs, excavating side channel connectors, and grading an irrigation reservoir berm on the floodplain. The U.S. Geological Survey (USGS) provided hydraulic modeling to assist the BLM in evaluating how possible restoration modifications could affect the extent of aquatic, riparian, and other habitat types. Three two-dimensional (2-D) hydraulic models were developed to simulate 2021 conditions (when most of the topographic data were collected), minor restoration modifications (one excavated side channel and a beaver dam analog), and major restoration modifications (three excavated side channels, a beaver dam analog, and an excavated and graded area to remove the irrigation reservoir) to determine streamflow-inundation extents and hydraulic characteristics (depth and velocity) for base flow and various flood (50-, 20-, 10-, 4-, 2-, and 1-percent annual exceedance probability [AEP]) scenarios. An average summer base flow of 0.92 cubic feet per second was estimated based on data from a USGS streamgage in the study area. The 50-, 20-, 10-, 4-, 2-, and 1-percent AEP streamflows were estimated based on a flood-frequency analysis of data from the streamgage. The base flow and AEP floods were combined with surveyed topographic data to create a 2-D unsteady hydraulic model. The hydraulic model was used to simulate the base flow and flood-inundation extents and hydraulic characteristics under 2021 conditions and with two possible restoration modification scenarios. Under 2021 conditions, flow remains in a single channel until the most downstream end of the modeled reach, where flow then expands into slower velocity pools. During floods, streamflow begins to enter the side channels at the 50-percent flood, expands into the east floodplain at 20-percent flood, and flows in the irrigation reservoir at 4-percent flood. Compared to 2021 conditions with no terrain modification, base flow under the possible restoration modifications enters and remains in the side channels, thus increasing the likelihood of expanding riparian habitat. Additionally, during floods under the major restoration modifications, streamflow expands into the modified terrain surrounding the irrigation reservoir at 10-percent AEP, as opposed to 4-percent AEP under 2021 conditions. For all modeled streamflow scenarios, streamflow is deepest in the center of the main and side channels, as well as the downstream pooled areas. Streamflow is fastest in the narrow sections of the channels, especially in the upper 1,220 feet of the modeled reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255069","collaboration":"Prepared in cooperation with Bureau of Land Management","programNote":"Water Resources Mission Area","usgsCitation":"Dye, L.A., Morris, C.M., and Childres, H.K., 2025, Streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada: U.S. Geological Survey Scientific Investigations Report 2025–5069, 24 p., https://doi.org/10.3133/sir20255069.","productDescription":"Report: vi, 24 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-124818","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":494320,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5069/images"},{"id":494319,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HQ6F7","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data, flood-frequency analysis, and surface-water model archive for streamflow extents and hydraulic characteristics of Meadow Valley Wash at Stuart Ranch, near Rox, Nevada"},{"id":494317,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5069/sir20255069.pdf","text":"Report","size":"11.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5069"},{"id":494316,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5069/coverthb.jpg"},{"id":494318,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255069/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5069"},{"id":494321,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5069/sir20255069.XML"}],"country":"United States","state":"Nevada","city":"Rox","otherGeospatial":"Meadow Valley Wash at Stuart Ranch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.6611,\n 36.84\n ],\n [\n -114.6611,\n 36.8278\n ],\n [\n -114.65,\n 36.8278\n ],\n [\n -114.65,\n 36.84\n ],\n [\n -114.6611,\n 36.84\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
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Carson City, Nevada 89701
The development of environmental DNA (eDNA) methods for terrestrial arthropods could be transformative for the difficult task of assessing the status of species of conservation concern. The primary goal of this study was to investigate the efficacy of detecting the Dakota skipper (Hesperia dacotae) from its DNA left behind on inflorescences as a means of inferring species presence. We developed and tested a novel qPCR assay and validated the assay in both controlled and field contexts. Using captive animals at the Minnesota Zoo, we found that the number of skippers in an enclosure increased the probability of skipper DNA detection. In the field, Dakota skipper DNA was found on 14% (11 of 81) of inflorescences collected. All detections were from narrowleaf purple coneflower (Echinacea angustifolia). Known visitation of an inflorescence by Dakota skipper prior to sample collection was not a strong predictor of either skipper DNA presence or amount of DNA, but skipper eDNA was detected at 60% (3 of 5) of sites where skippers were observed and 33% (1 of 3) of sites where skippers were not observed. These findings demonstrate successful application of a targeted-species approach to eDNA sampling for butterflies in the field. Taken together, our findings indicate that this method could provide a novel and useful source of data for assessing occupancy trends of butterflies without capturing or even observing them in the wild.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03815","usgsCitation":"Pilliod, D.S., Grossklaus, M.R., Kageyama, S.A., Nordmeyer, C., Reinisch, J., Runquist, E., and Spear, S.F., 2025, A 21st Century butterfly net: Using eDNA to detect the imperiled Dakota skipper: Global Ecology and Conservation, v. 62, e03815, 12 p., https://doi.org/10.1016/j.gecco.2025.e03815.","productDescription":"e03815, 12 p.","ipdsId":"IP-180064","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":497023,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13JBGIU","text":"USGS data release","linkHelpText":"Detection of Dakota skipper eDNA from inflorescences in the Upper Midwest, June and July 2022 (ver. 1.1, November 2025)"},{"id":495733,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2025.e03815","text":"Publisher Index Page"},{"id":495517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United states","state":"Minnesota, North Dakota, South Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.4255937792456,\n 43.75282749088453\n ],\n [\n -95.82307671174901,\n 44.537984912524394\n ],\n [\n -95.85210368026306,\n 46.61850738417658\n ],\n [\n -102.74334512161774,\n 48.947800618009666\n ],\n [\n -103.87685016438193,\n 48.559342537992194\n ],\n [\n -103.84723638965521,\n 46.63167447613088\n ],\n [\n -101.82183750965085,\n 46.16543147358968\n ],\n [\n -99.3119300920362,\n 45.59635742673848\n ],\n [\n -96.4255937792456,\n 43.75282749088453\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":216342,"corporation":false,"usgs":true,"family":"Pilliod","given":"David","middleInitial":"S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":948761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grossklaus, Michaela Ray 0009-0002-0890-6520","orcid":"https://orcid.org/0009-0002-0890-6520","contributorId":342051,"corporation":false,"usgs":true,"family":"Grossklaus","given":"Michaela","email":"","middleInitial":"Ray","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":948762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kageyama, Stacie A. 0000-0003-4185-3627 skageyama@usgs.gov","orcid":"https://orcid.org/0000-0003-4185-3627","contributorId":195991,"corporation":false,"usgs":true,"family":"Kageyama","given":"Stacie","email":"skageyama@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":948763,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nordmeyer, Cale 0000-0002-8826-251X","orcid":"https://orcid.org/0000-0002-8826-251X","contributorId":361407,"corporation":false,"usgs":false,"family":"Nordmeyer","given":"Cale","affiliations":[{"id":79104,"text":"Minnesota Zoo","active":true,"usgs":false}],"preferred":false,"id":948764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reinisch, Jerry","contributorId":361408,"corporation":false,"usgs":false,"family":"Reinisch","given":"Jerry","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":948765,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Runquist, Erik","contributorId":335441,"corporation":false,"usgs":false,"family":"Runquist","given":"Erik","affiliations":[{"id":79104,"text":"Minnesota Zoo","active":true,"usgs":false}],"preferred":false,"id":948766,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Spear, Stephen Frank 0000-0001-8351-9382","orcid":"https://orcid.org/0000-0001-8351-9382","contributorId":293162,"corporation":false,"usgs":true,"family":"Spear","given":"Stephen","email":"","middleInitial":"Frank","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":948767,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271730,"text":"70271730 - 2025 - New constraints on location and timing of the Great Lakes tectonic zone, central Upper Peninsula, Michigan, USA","interactions":[],"lastModifiedDate":"2025-09-22T14:18:30.472971","indexId":"70271730","displayToPublicDate":"2025-08-27T09:14:46","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1168,"text":"Canadian Journal of Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"New constraints on location and timing of the Great Lakes tectonic zone, central Upper Peninsula, Michigan, USA","docAbstract":"The Great Lakes tectonic zone (GLTZ) forms the boundary between the Wawa–Abitibi and Minnesota River Valley subprovinces within the Archean Superior Province. The GLTZ is concealed for all of its 1100 km length, except for a segment in the central Upper Peninsula of Michigan. There, it is exposed as a northwest-striking mylonite zone along a 11 km segment, extending to the onlap of Paleozoic rocks to the east. Farther east, its location has been unknown. Here, we use aeromagnetic and gravity data to develop interpretations of the expression of the GLTZ and to define its extent under cover. Aeromagnetic gradients over the mylonite zone are interpreted to be produced by structurally juxtaposed rocks with varying magnetizations. Gravity data show a regional gradient along the GLTZ, produced by the juxtaposition of a dense greenstone belt on the north against lower-density gneisses and granites on the south. The GLTZ is interpreted to extend ∼55 km under cover to the east. The GLTZ is terminated on the east by the buried eastern arm of the ca. 1100 Ma Midcontinent Rift. An undeformed granitic dike that cuts the mylonitic foliation produces a U–Pb apatite age of 2523 ± 33 Ma, implying no major post-Archean shearing occurred, and is at odds with previous interpretations of major Proterozoic reactivation. A granite intrusion in the Minnesota River Valley subprovince produces a Pb–Pb zircon age of 2606.9 ± 3.6/7.4 Ma. This suggests that magmatism related to the Sacred Heart orogeny, previously known in Minnesota, extended to Michigan.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjes-2025-0021","usgsCitation":"Drenth, B.J., Souders, A., Cannon, W.F., and Thompson, J.M., 2025, New constraints on location and timing of the Great Lakes tectonic zone, central Upper Peninsula, Michigan, USA: Canadian Journal of Earth Sciences, v. 62, no. 9, p. 1459-1473, https://doi.org/10.1139/cjes-2025-0021.","productDescription":"15 p.","startPage":"1459","endPage":"1473","ipdsId":"IP-171166","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"central Upper Peninsula","volume":"62","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-07-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949212,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Souders, Amanda 0000-0002-1367-8924","orcid":"https://orcid.org/0000-0002-1367-8924","contributorId":296423,"corporation":false,"usgs":true,"family":"Souders","given":"Amanda","email":"","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949213,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannon, William F. 0000-0002-2699-8118","orcid":"https://orcid.org/0000-0002-2699-8118","contributorId":201972,"corporation":false,"usgs":true,"family":"Cannon","given":"William","email":"","middleInitial":"F.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":949214,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Jay M. 0000-0003-3322-0870","orcid":"https://orcid.org/0000-0003-3322-0870","contributorId":329664,"corporation":false,"usgs":true,"family":"Thompson","given":"Jay","middleInitial":"M.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":949215,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70273135,"text":"70273135 - 2025 - Desert ecosystems shape diversification in glossy snakes (genus Arizona) requiring a re-alignment of evolutionary and conservation units","interactions":[],"lastModifiedDate":"2025-12-16T15:09:11.907324","indexId":"70273135","displayToPublicDate":"2025-08-27T08:52:27","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2779,"text":"Molecular Phylogenetics and Evolution","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Desert ecosystems shape diversification in glossy snakes (genus Arizona) requiring a re-alignment of evolutionary and conservation units","title":"Desert ecosystems shape diversification in glossy snakes (genus Arizona) requiring a re-alignment of evolutionary and conservation units","docAbstract":"Subspecies are often targets for conservation, yet many lack the genetic data necessary to validate their status as distinctive evolutionary lineages. In 2016, conservationists faced this issue when designating the California glossy snake, Arizona elegans occidentalis, as a Species of Special Concern in California, a decision prompted by population declines and habitat loss but absent of genetic information about its evolutionary integrity. To address this knowledge gap, we collected genomic and mitochondrial data from a rangewide sample of the Arizona elegans complex (n = 257) and characterized genetic structure at varying spatial scales. We confirmed an east–west phyletic division within the A. elegans complex that correlates with an ecotone between the Sonoran and Chihuahuan Deserts and pinpoint the separation to a ∼20 km area in southeastern Arizona, USA. Individuals recognized as A. e. occidentalis do not form a genetically cohesive unit within a more inclusive western clade that is sister to the endemic Arizona pacata in Baja California, México. We synonymize four subspecies circumscribed by the western clade and recognize a new species Arizona occidentalis to re-align the taxonomy with the phylogeographic structure. Most of the diversity within A. occidentalis occurs in California, with three major lineages corresponding separate desert biomes. We revise the conservation units within A. occidentalis to mirror these lineages and address concerns regarding habitat loss in transitional environments along the western edge of its range. This work underscores the importance of aligning taxonomy, evolutionary identity, and management units to design the most effective conservation strategies.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ympev.2025.108441","usgsCitation":"Wood, D., Richmond, J.Q., Westphal, M.F., Hollingsworth, B.D., Fisher, R.D., and Vandergast, A.G., 2025, Desert ecosystems shape diversification in glossy snakes (genus Arizona) requiring a re-alignment of evolutionary and conservation units: Molecular Phylogenetics and Evolution, v. 213, 108441, 15 p., https://doi.org/10.1016/j.ympev.2025.108441.","productDescription":"108441, 15 p.","ipdsId":"IP-175218","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":498287,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ympev.2025.108441","text":"Publisher Index Page"},{"id":497565,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.28258728665597,\n 40.693035314631345\n ],\n [\n -119.78832300902783,\n 31.602553781844435\n ],\n [\n -111.36681184455207,\n 22.61258270236084\n ],\n [\n -97.05757848026627,\n 22.24916886918969\n ],\n [\n -94.40812045478627,\n 32.37973867254225\n ],\n [\n -95.39342062000813,\n 40.44807423817957\n ],\n [\n -125.28258728665597,\n 40.693035314631345\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"213","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wood, Dustin 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":195223,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","affiliations":[],"preferred":true,"id":952412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":952413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westphal, Michael F.","contributorId":364262,"corporation":false,"usgs":false,"family":"Westphal","given":"Michael","middleInitial":"F.","affiliations":[{"id":37086,"text":"U.S. Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":952414,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hollingsworth, Bradford D.","contributorId":364265,"corporation":false,"usgs":false,"family":"Hollingsworth","given":"Bradford","middleInitial":"D.","affiliations":[{"id":16175,"text":"San Diego Natural History Museum","active":true,"usgs":false}],"preferred":false,"id":952415,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fisher, Robert D. 0000-0002-2956-3240 rdfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":3913,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rdfisher@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":952416,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":952417,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271410,"text":"70271410 - 2025 - Contribution of traffic emissions to PM2.5 concentrations at bus stops in Denver, Colorado","interactions":[],"lastModifiedDate":"2025-09-12T15:19:51.803063","indexId":"70271410","displayToPublicDate":"2025-08-27T08:09:19","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":"Contribution of traffic emissions to PM2.5 concentrations at bus stops in Denver, Colorado","docAbstract":"Individuals are routinely exposed to traffic-related air pollution on their commutes, which has significant health impacts. Mitigating exposure to traffic-related pollution is a key urban sustainability concern. In Denver, Colorado, low-income Americans are more likely to rely on buses and spend time waiting at bus stops. Evaluating the contribution of traffic emissions at bus stops can provide important information on risks experienced by these populations. We measured PM2.5 constituents at eight bus stops and one background reference site in Denver, in the summer of 2023. Source profiles, including gasoline emissions from traffic, were estimated using Positive Matrix Factorization (PMF) analysis of PM2.5 constituents collected at a Chemical Speciation Network site in our study region. The contributions of the different sources at each bus stop were estimated by regressing the vector of species concentrations at each site (dependent variable) on the source-profile matrix from the PMF analysis (independent variables). Traffic-related emissions (~2.5–6.6 μg/m3) and secondary organics (~3–5 μg/m3) contributed to PM2.5 at the bus stops in our dataset. The highest traffic-related emissions-derived PM2.5 concentrations were observed at bus stops near local sources: a gas station and a car wash. The contribution of traffic-related emissions was lower at the background site (~1 μg/m3).
","language":"English","publisher":"MDPI","doi":"10.3390/su17177707","usgsCitation":"deSouza, P., Hopke, P., L'Orange, C., Ibsen, P.C., Green, C., Graeber, B., Cicione, B., Mekonnen, R., Purushothama, S., Kinney, P., and Volckens, J., 2025, Contribution of traffic emissions to PM2.5 concentrations at bus stops in Denver, Colorado: Sustainability, v. 17, no. 17, 7707, 14 p., https://doi.org/10.3390/su17177707.","productDescription":"7707, 14 p.","ipdsId":"IP-176935","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":495724,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/su17177707","text":"Publisher Index Page"},{"id":495442,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.32990609528034,\n 39.95761559533625\n ],\n [\n -105.32990609528034,\n 39.506686432213314\n ],\n [\n -104.5591800032328,\n 39.506686432213314\n ],\n [\n -104.5591800032328,\n 39.95761559533625\n ],\n [\n -105.32990609528034,\n 39.95761559533625\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"17","noUsgsAuthors":false,"publicationDate":"2025-08-27","publicationStatus":"PW","contributors":{"authors":[{"text":"deSouza, Priyanka","contributorId":353306,"corporation":false,"usgs":false,"family":"deSouza","given":"Priyanka","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948628,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hopke, Phillip","contributorId":361336,"corporation":false,"usgs":false,"family":"Hopke","given":"Phillip","affiliations":[{"id":12960,"text":"Clarkson University","active":true,"usgs":false}],"preferred":false,"id":948629,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"L'Orange, Christian","contributorId":361337,"corporation":false,"usgs":false,"family":"L'Orange","given":"Christian","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":948630,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ibsen, Peter Christian 0000-0002-3436-9100","orcid":"https://orcid.org/0000-0002-3436-9100","contributorId":260735,"corporation":false,"usgs":true,"family":"Ibsen","given":"Peter","email":"","middleInitial":"Christian","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":948631,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Green, Carl Jr.","contributorId":361338,"corporation":false,"usgs":false,"family":"Green","given":"Carl","suffix":"Jr.","affiliations":[{"id":86239,"text":"Denver Regional Transportation District","active":true,"usgs":false}],"preferred":false,"id":948632,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graeber, Brady","contributorId":361326,"corporation":false,"usgs":false,"family":"Graeber","given":"Brady","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948633,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cicione, Brendan","contributorId":361327,"corporation":false,"usgs":false,"family":"Cicione","given":"Brendan","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948634,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mekonnen, Ruth","contributorId":361328,"corporation":false,"usgs":false,"family":"Mekonnen","given":"Ruth","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948635,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Purushothama, Saadhana","contributorId":361329,"corporation":false,"usgs":false,"family":"Purushothama","given":"Saadhana","affiliations":[{"id":16824,"text":"University of Colorado Denver","active":true,"usgs":false}],"preferred":false,"id":948636,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kinney, Patrick","contributorId":353314,"corporation":false,"usgs":false,"family":"Kinney","given":"Patrick","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":948637,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Volckens, John","contributorId":361331,"corporation":false,"usgs":false,"family":"Volckens","given":"John","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":948638,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70271408,"text":"70271408 - 2025 - High-resolution multi-pollutant mapping in Denver, Colorado","interactions":[],"lastModifiedDate":"2025-09-12T15:00:52.282043","indexId":"70271408","displayToPublicDate":"2025-08-27T07:54:09","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":22349,"text":"Atmospheric Environment X","active":true,"publicationSubtype":{"id":10}},"title":"High-resolution multi-pollutant mapping in Denver, Colorado","docAbstract":"Characterizing traffic-related air pollutants (TRAPs), which significantly impact health, and greenhouse gases (GHGs) can be challenging in urban environments. Mobile monitoring has the potential to capture the spatial distribution of these pollutants. We present results from a campaign using the Denver Mobile Monitoring Laboratory (DMML) in the summer of 2023 when we measured ultrafine particles (UFPs), black carbon (BC), ozone (O3), methane (CH4), and carbon dioxide (CO2) concentrations in Denver, CO. Despite our campaign being brief, we obtained several interesting results. We observed elevated UFP and BC concentrations on major roads. In contrast, O3 concentrations were higher on neighborhood streets and roads and in the industrial neighborhood of Commerce City. We consistently observed elevated CH4 concentrations (>2.5 ppm) on highway I-70, suggesting the presence of a previously unknown major source of CH4. The CH4 concentrations measured in our campaign did not align with those from an overlapping aerial campaign, suggesting that mobile monitoring is crucial to capture important, potentially intermittent CH4 hotspots in cities. We evaluated if trees mitigated pollution concentrations, as planting trees is a key policy initiative of the city of Denver. We observed significant negative associations between tree canopy coverage and UFPs, BC, and CH4, and a positive association with O3 when using linear mixed-effects regression models. Our work highlights the importance of investigating the role of tree canopy coverage to mitigate TRAPs.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aeaoa.2025.100364","usgsCitation":"deSouza, P., Crawford, B., Durant, J.L., Hudda, N., Ibsen, P.C., L'Orange, C., Jimenez, J., Graeber, B., Cicione, B., Mekonnen, R., Purushothama, S., Kahn, R., Kinney, P.L., and Volckens, J., 2025, High-resolution multi-pollutant mapping in Denver, Colorado: Atmospheric Environment X, v. 27, 100364, 10 p., https://doi.org/10.1016/j.aeaoa.2025.100364.","productDescription":"100364, 10 p.","ipdsId":"IP-177506","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":495723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeaoa.2025.100364","text":"Publisher Index Page"},{"id":495408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","city":"Denver","geographicExtents":"{\n 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This process, known as “crosswalking,” enabled the development of a global map of GET level 3 Ecosystem Functional Groups (EFGs) at a 250-meter spatial resolution. Crosswalking involved manually assigning 1,781 biogeographically stratified WTEs to their most probable EFG based on similarities in climate, terrain, vegetation, and geographic distribution. We compared attributes of the WTE dataset with summary characteristics of the EFGs. The resulting crosswalked global map of International Union for Conservation of Nature GET ecosystems is intended to be useful for standardizing ecosystem classification and reporting under frameworks such as the Kunming-Montreal Global Biodiversity Framework and the United Nations System of Environmental-Economic Accounting. We discuss key challenges in reconciling non-identical classifications, such as many-to-one relationships and variation in data quality.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251043","programNote":"National Land Imaging Program","usgsCitation":"Sides, K.B., Naji, N., Kremer, A., Burton, D., and Sayre, R., 2025, A crosswalk of the 2015 World Terrestrial Ecosystems to the International Union for the Conservation of Nature Global Ecosystem Typology Framework: U.S. Geological Survey Open-File Report 2025–1043, 10 p., https://doi.org/10.3133/ofr20251043.","productDescription":"Report: iv, 10 p.; 2 Appendixes","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-174837","costCenters":[{"id":86069,"text":"National Land Imaging","active":true,"usgs":true}],"links":[{"id":494756,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2025/1043/ofr20251043_appendix.csv","text":"Appendix","size":"215 KB","linkFileType":{"id":7,"text":"csv"},"description":"OFR 2025-1043 Appendix CSV","linkHelpText":"- A Crosswalk of the U.S. Geological Survey/Esri/The Nature Conservancy World Terrestrial Ecosystems to the International Union for the Conservation of Nature Global Ecosystem Typology (GET) Ecosystem Functional Groups in a CSV file"},{"id":494750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1043/coverthb.jpg"},{"id":494755,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2025/1043/ofr20251043_appendix.xlsx","text":"Appendix","size":"70.4 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2025-1043 Appendix XLSX","linkHelpText":"- A Crosswalk of the U.S. Geological Survey/Esri/The Nature Conservancy World Terrestrial Ecosystems to the International Union for the Conservation of Nature Global Ecosystem Typology (GET) Ecosystem Functional Groups"},{"id":494754,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1043/images/"},{"id":494753,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1043/ofr20251043.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1043 XML"},{"id":494752,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251043/full","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1043 HTML"},{"id":494751,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1043/ofr20251043.pdf","text":"Report","size":"12.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1043 PDF"}],"contact":"Director, National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Objective:
Sediment has an important role in aquatic ecosystems, however, excess sediment can negatively impact fish and other aquatic life. Quantifying the response of aquatic life, particularly fish, to suspended sediment is important for natural resource managers tasked with developing sediment management guidelines to protect aquatic ecosystems. Our goal was to assess the ability of established, revised, and alternate severity of ill effect (SEV) dose-response models to predict the impact of suspended sediment on fish.
Methods: We synthesized existing literature to develop an expansive dataset that relates suspended sediment concentration and exposure duration to biological effects on fishes and assessed the predictive ability of established and revised SEV dose-response models. We investigated potential sources of variation in biological responses to suspended sediment dose and explored two alternative approaches for assessing the effects of suspended sediment on fish: 90th quantile SEV dose-response regression models and logistic SEV dose-response models.
Results: We found that both established and revised linear SEV dose-response models poorly quantify fish biological response to suspended sediment. Quantile SEV dose-response regressions also performed poorly. More promising are logistic dose-response models that identify sediment thresholds where major effects of sediment on fish can be expected to occur. We demonstrate that fish biological response to suspended sediment is modulated by sediment particle size, water temperature, and dissolved oxygen levels, suggesting additional environmental and biological variables to consider when evaluating the effects of suspended sediment on fish.
Conclusion: We contribute revised and novel empirically derived tools for predicting the effects of suspended sediment on fish and demonstrate how environmental variables and life stage may modulate fish biological response. Our work illustrates challenges associated with predictive modeling and some potential sources of variation. While empirical models integrating biological stress response to suspended sediment may help natural resource managers capture potential impacts of this stressor, a cautious approach that considers co-acting stressors may be most effective for sediment management that is protective of fish.
","language":"English","publisher":"American Fisheries Society","doi":"10.1093/najfmt/vqaf051","usgsCitation":"Pilkerton, A.M., McCullough, S.M., Patterson, L.S., Rahel, F., Walters, A.W., 2025, Suspended sediment and fisheries: An exploration of empirical relationships: North American Journal of Fisheries Management, v. 45, no. 5, p. 753-766, https://doi.org/10.1093/najfmt/vqaf051.","productDescription":"14 p.","startPage":"753","endPage":"766","ipdsId":"IP-174503","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-08-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Pilkerton, Ashleigh M.","contributorId":366479,"corporation":false,"usgs":false,"family":"Pilkerton","given":"Ashleigh","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":955978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCullough, Sara M.","contributorId":366480,"corporation":false,"usgs":false,"family":"McCullough","given":"Sara","middleInitial":"M.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":955979,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Patterson, Lindsay S.","contributorId":366481,"corporation":false,"usgs":false,"family":"Patterson","given":"Lindsay","middleInitial":"S.","affiliations":[{"id":84900,"text":"Wyoming Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":955980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rahel, Frank J.","contributorId":337685,"corporation":false,"usgs":false,"family":"Rahel","given":"Frank J.","affiliations":[{"id":36628,"text":"University of Wyoming","active":true,"usgs":false}],"preferred":false,"id":955981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":955982,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270851,"text":"70270851 - 2025 - Perceptions and management of chronic wasting disease in Washington State: A survey of cervid hunters","interactions":[],"lastModifiedDate":"2025-08-26T15:18:10.962517","indexId":"70270851","displayToPublicDate":"2025-08-26T10:16:45","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":22188,"text":"Cooperative Report","active":true,"publicationSubtype":{"id":2}},"title":"Perceptions and management of chronic wasting disease in Washington State: A survey of cervid hunters","docAbstract":"Chronic wasting disease (CWD) is a fatal neurological disease caused by a misfolded protein, or prion, and is found in cervids (e.g., deer, elk, moose). It represents a serious threat to cervid populations and is one of the most important ungulate management issues facing state wildlife management agencies. Issues associated with CWD can affect many groups including hunters, tribal groups, biologists, rehabilitators, and farmers among others, and many can play an essential role in CWD management (e.g., hunters can help with cervid population control methods). In 2021, the Washington Department of Fish and Wildlife (WDFW) adopted the CWD Management Plan for Washington State, which specifically called for incorporating human dimensions of disease management with the ecological and epidemiological elements in CWD management. It is essential to develop a strong human dimensions component as management actions in other states have shown that when the public is not appropriately engaged, the probability of success is diminished. The study presented here sought to understand public preferences and perceptions of CWD and CWD management. We conducted 15 key constituent interviews and deployed a survey instrument in summer of 2023. (CWD was detected in Washington in July 2024, but this survey was completed ahead of that detection). The survey was emailed to 165,700 resident hunters in Washington State who had purchased a big game license since 2015 and the results presented below are based on interviews and completed survey responses from 7,403 individuals.
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hyperspectral","interactions":[],"lastModifiedDate":"2025-09-10T15:04:42.257035","indexId":"70271368","displayToPublicDate":"2025-08-26T07:58:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5098,"text":"Remote Sensing Applications: Society and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring cyanobacteria temporal trends in a hypereutrophic lake using remote sensing: From multispectral to hyperspectral","docAbstract":"Cyanobacterial harmful algal blooms (cyanoHABs) and associated cyanotoxins are a concern for inland waters. Due to the extensive spatial coverage and frequent availability of satellite images, multispectral remote sensing tools demonstrate utility for monitoring these blooms. The next frontier for remote sensing of cyanoHABs in inland waters is hyperspectral data. Recent and upcoming hyperspectral satellite missions using narrow wavelength imaging spectrometers could have a major impact on advancing our ability to detect, quantify, and characterize cyanobacterial blooms. This study compares multispectral and hyperspectral remote sensing capabilities and processing tools for monitoring cyanoHAB dynamics. We evaluated the temporal trends of cyanoHABs in Clear Lake, California, a hypereutrophic lake with diverse cyanobacteria genera based on 38 sampling events over a five-year monitoring period (2019–2023). We validated the Sentinel-3 Ocean and Land Color Instrument (multispectral) Cyanobacteria Index algorithm for Clear Lake using in situ cyanobacteria measurements, which complemented our field-based evaluation of cyanobacteria trends in Clear Lake. We then demonstrate the advantages of hyperspectral data from both in situ spectroradiometer measurements and full-lake hyperspectral satellite images. We apply the Spectral Mixture Analysis for Surveillance of HABs (SMASH) workflow, a Multiple Endmember Spectral Mixture Analysis (MESMA) algorithm, to the hyperspectral images to assess the potential of satellite imaging spectrometer data to identify cyanobacteria genera – the first study to test this tool outside its original study sites. We developed a Clear Lake-specific cyanobacteria spectral library using our field spectroradiometer measurements to improve SMASH performance in Clear Lake, which supports the continued development of this tool.
","language":"English","publisher":"Elseiver","doi":"10.1016/j.rsase.2025.101704","usgsCitation":"Sharp, S.L., Cortes, A., Forrest, A.L., Legleiter, C.J., Guild, L.S., Jin, Y., and Schladow, S.G., 2025, Monitoring cyanobacteria temporal trends in a hypereutrophic lake using remote sensing: From multispectral to hyperspectral: Remote Sensing Applications: Society and Environment, v. 39, 101704, 17 p., https://doi.org/10.1016/j.rsase.2025.101704.","productDescription":"101704, 17 p.","ipdsId":"IP-174209","costCenters":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":500065,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/5t83t0rw","text":"External Repository"},{"id":495280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.96267888555795,\n 39.16571325270124\n ],\n [\n -122.96267888555795,\n 38.914533541208556\n ],\n [\n -122.60070817606311,\n 38.914533541208556\n ],\n [\n -122.60070817606311,\n 39.16571325270124\n ],\n [\n -122.96267888555795,\n 39.16571325270124\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"39","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sharp, Samantha L.","contributorId":361094,"corporation":false,"usgs":false,"family":"Sharp","given":"Samantha","middleInitial":"L.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":948227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cortes, Alicia","contributorId":293333,"corporation":false,"usgs":false,"family":"Cortes","given":"Alicia","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":true,"id":948228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Forrest, Alexander L.","contributorId":361096,"corporation":false,"usgs":false,"family":"Forrest","given":"Alexander","middleInitial":"L.","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":948229,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":948230,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guild, Liane S.","contributorId":361098,"corporation":false,"usgs":false,"family":"Guild","given":"Liane","middleInitial":"S.","affiliations":[{"id":24796,"text":"NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":948231,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jin, Yufang","contributorId":361101,"corporation":false,"usgs":false,"family":"Jin","given":"Yufang","affiliations":[{"id":16975,"text":"University of California Davis","active":true,"usgs":false}],"preferred":false,"id":948232,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schladow, S. 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As part of this work, the workflow for hydrothermal resource favorability maps is being modified to integrate modern data-driven machine learning (ML) methods. Improvements include: [1] using new and refined evidence layers (features); [2] using an order of magnitude more training sites (labeled examples); [3] utilizing simple but non-linear supervised ML algorithms; [4] representing positive training sites (wells with measured heat flow) with their ordinal value proportional to the magnitude of convective upflow (i.e., low, high, or very high convective signals instead of past strategies using positive-negative labels); [5] supplementing training sites with additional sites with low convective signals to represent diverse under-sampled areas where hydrothermal systems are unlikely to exist; [6] comparing with competing approaches; and [7] utilizing Monte Carlo cross-validation to estimate and evaluate prediction uncertainty.
For the new favorability map, over half of the power-producing systems (i.e., 15 of 28) are predicted in the 99th percentile of most favorable locations (i.e., the highest 1 % of favorability, corresponding to 1 % of the map area), exceeding the performance of past models that have explicitly used power plants as training sites. Previous favorability maps predicted approximately half of the power-producing hydrothermal systems above the 80th percentile (i.e., 20 % of the map area). For the new favorability map, 93 % of power-producing systems (i.e., 26 of 28) are above the 80th percentile. The power-producing systems for which the new model does not perform well are either comparatively small, low-temperature systems or systems also not predicted well by prior modeling approaches, suggesting that these few systems are unusual when compared with most power-producing systems. Focusing research on these known, seemingly different systems may yield new insights and subsequent discovery of new prospects.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geothermics.2025.103450","usgsCitation":"Mordensky, S.P., Burns, E., Lipor, J., and DeAngelo, J., 2025, Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA: Geothermics, v. 133, 103450, 24 p., https://doi.org/10.1016/j.geothermics.2025.103450.","productDescription":"103450, 24 p.","ipdsId":"IP-170174","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":495066,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geothermics.2025.103450","text":"Publisher Index Page"},{"id":494947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Idaho, Nevada, Oregon, Utah","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.0202610934917,\n 42.55970962212865\n ],\n [\n -119.8746500530377,\n 37.88790476539039\n ],\n [\n -116.94256843416173,\n 36.91537025154052\n ],\n [\n -113.73824592248651,\n 36.98857095813982\n ],\n [\n -111.99293303262,\n 42.55970962212865\n ],\n [\n -115.98687680320434,\n 42.23211305382921\n ],\n [\n -118.48297767228134,\n 42.58841357223409\n ],\n [\n -121.0202610934917,\n 42.55970962212865\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"133","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Mordensky, Stanley Paul 0000-0001-8607-303X","orcid":"https://orcid.org/0000-0001-8607-303X","contributorId":292014,"corporation":false,"usgs":true,"family":"Mordensky","given":"Stanley","email":"","middleInitial":"Paul","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":947427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Erick R. 0000-0002-1747-0506","orcid":"https://orcid.org/0000-0002-1747-0506","contributorId":225412,"corporation":false,"usgs":true,"family":"Burns","given":"Erick R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":947428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lipor, John 0000-0002-0990-5493","orcid":"https://orcid.org/0000-0002-0990-5493","contributorId":292015,"corporation":false,"usgs":false,"family":"Lipor","given":"John","email":"","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":947429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeAngelo, Jacob 0000-0002-7348-7839 jdeangelo@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-7839","contributorId":237879,"corporation":false,"usgs":true,"family":"DeAngelo","given":"Jacob","email":"jdeangelo@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":947430,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70271243,"text":"70271243 - 2025 - Ten lessons for controlling invasive species: Wisdom from the long-standing sea lamprey control program on the Laurentian Great Lakes","interactions":[],"lastModifiedDate":"2025-12-01T16:28:51.193336","indexId":"70271243","displayToPublicDate":"2025-08-26T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Ten lessons for controlling invasive species: Wisdom from the long-standing sea lamprey control program on the Laurentian Great Lakes","docAbstract":"Sea lamprey (Petromyzon marinus) control in the Laurentian Great Lakes of North America is among the largest and most successful control programs of an invasive species anywhere on the planet. The effort began more than 75 years ago; it unites multiple nations, states, and provinces with the common goal of controlling this invasive species and protecting a valuable fishery. The science-based control program is administered by the Great Lakes Fishery Commission (GLFC), a body arising from a treaty signed by the United States and Canada. In the present article, we share 10 lessons learned from decades of successful sea lamprey control with the hopes of informing ongoing and future control programs targeting biological invasions. The 10 lessons we identified are to act boldly in times of crisis, to maintain the social license, to invest in capacity building, to break down the silos, to support fundamental science, to diversify your portfolio of control measures, to strive for continuous improvement, to confront the trade-off between information and action, to keep your foot on the gas, and to keep your eyes on the prize. The GLFC has long fostered a framework that uses some military strategy and verbiage that extends across the lessons (e.g., know your enemy). Other lessons are more nascent as the GLFC reenvisions its relationship with Indigenous peoples and governments in a path to reconciliation where two-eyed seeing is being embraced. Through adaptive management, horizon scanning methods, and embracing implementation science, the lessons learned about sea lamprey control will continue to evolve, which is itself a lesson. We submit that the lessons shared in the present article will help guide invasive species control programs spanning taxa, ecosystems, and regions.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/biosci/biaf133","usgsCitation":"Cooke, S.J., Baker, C., Mida Hinderer, J.L., Siefkes, M., Barber, J., Steeves, T., Docker, M.F., Li, W., Wilkie, M., Jones, M.L., Robinson, K.F., Dunlop, E.S., Brant, C., Johnson, N.S., Mattes, W., Gaden, M., and Muir, A., 2025, Ten lessons for controlling invasive species: Wisdom from the long-standing sea lamprey control program on the Laurentian Great Lakes: BioScience, v. 75, no. 11, p. 985-996, https://doi.org/10.1093/biosci/biaf133.","productDescription":"12 p.","startPage":"985","endPage":"996","ipdsId":"IP-167789","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":495181,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biaf133","text":"Publisher Index 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S.","contributorId":146961,"corporation":false,"usgs":false,"family":"Dunlop","given":"Erin","email":"","middleInitial":"S.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":947781,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Brant, Cory 0000-0002-0919-1566","orcid":"https://orcid.org/0000-0002-0919-1566","contributorId":223422,"corporation":false,"usgs":true,"family":"Brant","given":"Cory","email":"","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":947782,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"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":947783,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Mattes, William","contributorId":306053,"corporation":false,"usgs":false,"family":"Mattes","given":"William","email":"","affiliations":[{"id":16233,"text":"Great Lakes Indian Fish and Wildlife Commission","active":true,"usgs":false}],"preferred":false,"id":947927,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Gaden, Marc","contributorId":346957,"corporation":false,"usgs":false,"family":"Gaden","given":"Marc","affiliations":[{"id":7019,"text":"Great Lakes Fishery Commission","active":true,"usgs":false}],"preferred":false,"id":947784,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Muir, Andrew M.","contributorId":103933,"corporation":false,"usgs":false,"family":"Muir","given":"Andrew M.","affiliations":[],"preferred":false,"id":947785,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70270258,"text":"ofr20251047 - 2025 - Methodology and technical input for the 2025 U.S. List of Critical Minerals—Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy","interactions":[],"lastModifiedDate":"2026-04-16T13:59:07.528586","indexId":"ofr20251047","displayToPublicDate":"2025-08-25T10:58:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1047","displayTitle":"Methodology and Technical Input for the 2025 U.S. List of Critical Minerals—Assessing the Potential Effects of Mineral Commodity Supply Chain Disruptions on the U.S. Economy","title":"Methodology and technical input for the 2025 U.S. List of Critical Minerals—Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy","docAbstract":"The Secretary of the Interior, acting through the Director of the U.S. Geological Survey, is tasked by section 7002 (“Mineral Security”) of title VII (“Critical Minerals”) of the Energy Act of 2020 (Public Law 116–260, December 27, 2020, 116th Congress) with reviewing and revising the methodology used to evaluate mineral commodity supply risk and the U.S. List of Critical Minerals (LCM) no less than every 3 years. Following two previous LCM assessments, this analysis represents the latest technical input for evaluating each mineral commodity’s supply risk and determining their recommended status on the LCM. We evaluated mineral commodity supply risk using two criteria: (1) an economic effects assessment that quantified the potential effects of various trade disruption scenarios on the U.S. economy, and (2) an examination of whether the mineral commodity’s U.S. supply chain relied on a sole domestic producer that represented a single point of failure. For the first criterion, postdisruption equilibrium quantities and prices for each mineral commodity were calculated based on their price elasticities of supply and demand and the availability of excess production capacity for each yearlong foreign trade disruption scenario. Subsequently, a nonlinear optimization routine was used with detailed economic input-output tables to estimate the potential economic effects on the U.S. economy of over 1,200 scenarios for 84 mineral commodities. After accounting for the probability of each scenario’s occurrence, the overall results are presented in terms of changes in U.S. gross domestic product (GDP) by individual industry and the economy overall. The results, which ranged from a net decrease in U.S. GDP of nearly $4.5 billion to a net increase of $33 million, largely reflect U.S. import dependency and world production concentration. Using the Jenks natural breaks optimization method, a statistical classification technique, we categorized the mineral commodities into several classes based on this overall risk quantification. Mineral commodities with annualized probability-weighted net decreases in U.S. GDP greater than $2 million were recommended for inclusion on the LCM. If a mineral commodity did not meet the threshold for inclusion on the LCM under the first criterion, its domestic supply chain was examined under the second criterion, which recommended a mineral commodity for inclusion on the LCM if there was only a single domestic producer. Ultimately, the two criteria resulted in the recommendation of the addition of six mineral commodities (in descending risk order, potash, silicon, copper, silver, rhenium, and lead) to and the removal of two mineral commodities (arsenic and tellurium) from the LCM. By using an economic effects assessment, the results of this analysis provide a prioritization that can also be compared directly against other risk analyses and the cost of various risk mitigation strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251047","usgsCitation":"Nassar, N.T., Pineault, D., Allen, S.M., McCaffrey, D.M., Padilla, A.J., Brainard, J.L., Bayani, M., Shojaeddini, E., Ryter, J.W., Lincoln, S., and Alonso, E., 2025, Methodology and technical input for the 2025 U.S. List of Critical Minerals— Assessing the potential effects of mineral commodity supply chain disruptions on the U.S. economy (ver. 2.0, 2026): U.S. Geological Survey Open-File Report 2025–1047, 215 p., https://doi.org/10.3133/ofr20251047.","productDescription":"Report: vi, 215 p.; Data Release","numberOfPages":"215","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-180772","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":494012,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1047/ofr20251047.pdf","text":"Report","size":"3.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1047 PDF"},{"id":494011,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1047/coverthb3.jpg"},{"id":494013,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251047/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1047 HTML"},{"id":494014,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1047/ofr20251047.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1047 XML"},{"id":494015,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1047/images/"},{"id":499034,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118752.htm","linkFileType":{"id":5,"text":"html"}},{"id":502425,"rank":8,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2025/1047/versionHist.txt","size":"3.01 KB","linkFileType":{"id":2,"text":"txt"}},{"id":494403,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14BRF29","text":"USGS data release","linkHelpText":"U.S. Geological Survey Minerals Yearbook data for select mineral commodities referenced in “U.S. Geological Survey Methodology and Technical Input for the 2025 U.S. List of Critical Minerals—Assessing the Potential Effects of Mineral Commodity Supply Chain Disruptions on the U.S. Economy”"}],"edition":"Version 1.0: August 2025; Version 2.0: April 2026","contact":"Director, National Minerals Information Center
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Email: nmicrecordsmgt@usgs.gov
","tableOfContents":"To quantify the risks associated with potential disruptions and to recommend mineral commodities for inclusion on the updated U.S. List of Critical Minerals, as required by the Energy Act of 2020, the U.S. Geological Survey developed an economic model to estimate the potential effects of foreign trade disruptions of mineral commodities on the U.S. economy. The results of the study recommend the addition of six mineral commodities (in descending risk order, potash, silicon, copper, silver, rhenium, and lead) to and the removal of two mineral commodities (arsenic and tellurium) from the List of Critical Minerals. The analysis also provides a prioritization based on the results. The economic model has several advantages over previous assessments including the ability to directly compare the results against other economic risks and the costs of initiatives aimed at reducing the risks.
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Of the 47 bat species native to the conterminous United States, Alaska, Hawaii, and Canada, 12 have been affected by WNS, including 3 endangered species and 1 proposed endangered species. WNS has also been detected in 40 States and 9 Canadian Provinces. U.S. Geological Survey (USGS) scientists have been critical in identifying the causal fungus for WNS (Pseudogymnoascus destructans [Pd]), characterizing the effects of WNS, and tracking the spread of Pd in many bat populations in North America.
The mission of the USGS WNS and Bat Health Science Team is to deliver integrated science in order to build resiliency into free-ranging bat populations through more effective WNS management, build capacity for bat health science, and enhance bat health information sharing across USGS science centers and cooperative research units as well as with stakeholders. The USGS can play an important role in supporting regional and national capacity building by providing resources and guidance to local, State, and Tribal management entities and by providing tools to enhance disease management. The USGS Ecosystems Mission Area’s Biological Threats and Invasive Species Research Program is the lead Federal program for free-ranging wildlife disease research and surveillance.
As of 2024, guided by the science priorities set by the WNS Steering Committee, USGS scientists are engaged in a nationwide response to WNS. This work is done in close coordination with our partners at the U.S. Fish and Wildlife Service, National Park Service, Bureau of Land Management, U.S. Forest Service of the U.S. Department of Agriculture, U.S. Department of Defense, as well as State and Tribal agencies. In addition to conducting WNS research, the USGS is mapping the spread of WNS and coordinating the North American Bat Monitoring Program (NABat) to understand how WNS and other stressors affect the status and trends of native bats across their range. The USGS is supporting the national WNS response through four science goals: (1) provide situational awareness on the health of bat populations; (2) conduct ecological studies of bats along the gradient of disease vulnerability; (3) contribute actionable science to enhance the resiliency of bat populations; and (4) implement an adaptive, holistic approach to bat health.
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