The potential for environmental DNA (eDNA) to disperse widely from source organisms enables high detection efficiency but raises questions about eDNA's ability to differentiate fine-scale spatial patterns relative to conventional fish capture data.
We evaluate these questions in the St. Louis River estuary—a hydrologically and spatially complex coastal system within Lake Superior that supports a diverse assemblage of resident and migratory fish species—via comparison of eDNA metabarcoding (12S and 16S loci) to multigear capture survey data from 2 years and two seasons.
The eDNA and capture surveys collectively yielded 68 fish species: 2 species detected only by capture, 27 detected only by eDNA, and 39 shared across both survey types but having generally higher occurrence frequencies with eDNA than capture. Six species detected only by eDNA were unexpected, having no prior records in the Lake Superior basin. Data from paired eDNA and capture stations showed little relationship between the two survey types, with capture yielding species at stations that eDNA did not, eDNA detecting species in different habitats and distant locations from any captures, and assemblage patterns homogenized in eDNA surveys relative to capture surveys.
Our study finds that eDNA is a sensitive tool for assessing species presence at the system scale but that capture surveys may better yield the fine-scale spatial distribution information of interest to fisheries and habitat managers, especially in spatially and hydrologically complex systems.
No abstract available.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"The 2024 annual report of the International Red River Watershed Board","largerWorkSubtype":{"id":3,"text":"Organization Series"},"language":"English","publisher":"International Joint Commission","usgsCitation":"Thomas, D., 2025, USGS water resource investigations and activities: Annual Report, v. 25, 15 p.","productDescription":"15 p.","startPage":"88","endPage":"102","ipdsId":"IP-179575","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":501179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":501178,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://ijc.org/en/rrb/irrwb-annual-report-2024"}],"volume":"25","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thomas, Daniel C 0009-0005-7051-9670","orcid":"https://orcid.org/0009-0005-7051-9670","contributorId":357351,"corporation":false,"usgs":true,"family":"Thomas","given":"Daniel C","affiliations":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":941274,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70272662,"text":"70272662 - 2025 - Critical mineral inventory of select IOA-IOCG deposits, southwestern USA","interactions":[],"lastModifiedDate":"2025-12-03T16:19:12.788724","indexId":"70272662","displayToPublicDate":"2025-09-01T10:11:28","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Critical mineral inventory of select IOA-IOCG deposits, southwestern USA","docAbstract":"Critical minerals are necessary for modern technology and strategic purposes. Their increasing importance requires finding new and nontraditional resources. Samples of ore, altered, and unaltered host rock were collected from 26 iron mines and prospects in California, Nevada, and Utah to assess the potential of these deposits to host economic quantities of different critical minerals. Geochemical analyses were conducted by 61 element ICP-OES-MS sodium peroxide fusion and major elements determined by WDXRF. These deposits concentrated many critical minerals beyond what is found in average upper crustal abundances, such as Sb, As, Bi, Co, Ga, Mg, Mn, Ni, Nb, Pd, REE, Sc, Te, Sn, Ti, W, V, and Zn. However, most of these are not concentrated enough in the ore to be considered as economic resources. Those critical minerals that are enriched enough in some of these deposits to possibly be considered as by-product commodities are Ni, REE, V, and potentially Co and Ga. These enrichments were not uniform, with REE more likely to be enriched in IOA deposits, whereas Co, Ga, Ni, and V could be found enriched in either IOA or IOCG deposits.","conferenceTitle":"18th SGA Biennial Meeting","conferenceDate":"August 3-7, 2025","conferenceLocation":"Golden, CO","language":"English","publisher":"Society for Geology Applied to Mineral Deposits","usgsCitation":"Taylor, R., Meighan, C.J., and Hofstra, A.H., 2025, Critical mineral inventory of select IOA-IOCG deposits, southwestern USA, 18th SGA Biennial Meeting, v. 3, Golden, CO, August 3-7, 2025, p. 963-966.","productDescription":"4 p.","startPage":"963","endPage":"966","ipdsId":"IP-176357","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":497013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":497012,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.e-sga.org/publications/conference-proceedings"}],"country":"United States","state":"California, Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.96837443642112,\n 32.704121200218324\n ],\n [\n -114.90627175927149,\n 35.276512718803005\n ],\n [\n -113.85778870259917,\n 36.75952704897722\n ],\n [\n -111.12601522383044,\n 37.041029453418844\n ],\n [\n -111.18086370424344,\n 38.21185945627386\n ],\n [\n -113.95734086339156,\n 38.55172394057118\n ],\n [\n -113.9625620365557,\n 41.846893445470926\n ],\n [\n -120.18862063281,\n 42.02269387816904\n ],\n [\n -121.46065541607419,\n 41.96050209334149\n ],\n [\n -121.80133036685531,\n 39.645958588292274\n ],\n [\n -114.96837443642112,\n 32.704121200218324\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Ryan D. 0000-0002-8845-5290","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":201948,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":951245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meighan, Corey J. 0000-0002-5668-1621 cmeighan@usgs.gov","orcid":"https://orcid.org/0000-0002-5668-1621","contributorId":5892,"corporation":false,"usgs":true,"family":"Meighan","given":"Corey","email":"cmeighan@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":951246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":951247,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272004,"text":"70272004 - 2025 - Assessing diet and genotyping success of goat pellet surveys from 2019 in Glacier National Park","interactions":[],"lastModifiedDate":"2025-09-30T15:06:54.506965","indexId":"70272004","displayToPublicDate":"2025-09-01T10:03:46","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"displayTitle":"Assessing Diet and Genotyping Success of Goat Pellet Surveys from 2019 in Glacier National Park","title":"Assessing diet and genotyping success of goat pellet surveys from 2019 in Glacier National Park","docAbstract":"Fecal pellets contain genetic information and can be used to identify individuals, their diet, and more. Individual identification can be useful in understanding movements of individuals, developing population estimates, assessing vital rates, genetic diversity and structure, and evaluating trends over time (e.g., Epps et al 2024). Successful genotyping depends on the quality of the sample, which can be influenced by many things including the initial state of the sample, environmental conditions that the pellets were exposed to, and the method of storage.
The diet of mountain goats (Oreamnos americanus) is hard to study as they are habitat specialists in some of the most remote and rugged alpine environments (Festa-Bianchet & Côté 2012). These iconic ungulates epitomize the renowned wilderness character of Glacier National Park (GNP), yet the population has declined by 45% since 2008 likely due at least in part to changing climate (Graves et al. 2025). This is well above the International Union for the Conservation of Nature’s population decline criterion used to designate a species as vulnerable (IUCN 2012).
Mountain goats are known as dietary generalists employing highly variable diets across systems, but diets have not been identified for GNP. Identifying goat diet composition in GNP can provide the information needed to determine whether this population decline could be related to climate-change induced shifts in forage phenology, diversity, productivity, and plant community structure. Other anthropogenic changes in GNP, such as increases in exotic and invasive plant species, will continue to affect plant community composition (Lesica et al. 1993). These alterations may reduce optimal forage availability and quality, which could have a deleterious effect on mountain goat survival. To examine these possibilities, we must first ask- What precisely are the mountain goats of Glacier National Park eating?
DNA metabarcoding of fecal pellets provides a cutting-edge, non-invasive method for assessing herbivore diet. Previous studies of mountain goat diet have used methods such as fecal crude protein analysis (Festa-Bianchet & Côté 2012), rumen analysis (Saunders 1955), fecal microhistology (Cobb et al. 2012), and bite-for-bite feeding observations (Daily et al. 1984). Many of these studies have only been able to identify diet components to functional plant type and the methods used are biased towards less digestible diet components such as grasses (McInnis et al. 1983). Metabarcoding of fecal pellets can provide a higher taxonomic resolution than previous methods (Scasta et al. 2019, Stapleton et al. 2022) and open the field for increased participation of volunteers, also called community or citizen scientists.
Here, we use mountain goat fecal pellets to conduct 1) an evaluation of which conditions might influence genotyping success and 2) a preliminary assessment of diet using metabarcoding. This pilot study allowed us to evaluate which pellets to focus on collecting, identify the best storage methods, explore approaches for analyzing metabarcoding data, examine the utility of metabarcoding for acquiring taxonomically specific diet information, and to identify genetic sequences that could not be resolved to genus or species levels using these methods. We examined the frequency of occurrence and relative diet composition of identified forbs, shrubs, graminoids, mosses, and trees in mountain goat diets.
","language":"English","publisher":"National Park Service","usgsCitation":"Scoresby, S., Dose, L.M., Belt, J., and Graves, T., 2025, Assessing diet and genotyping success of goat pellet surveys from 2019 in Glacier National Park, 23 p.","productDescription":"23 p.","ipdsId":"IP-174564","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":496262,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496254,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2311387"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.60109929508316,\n 49.00250961037867\n ],\n [\n -114.47247108032799,\n 49.00250961037867\n ],\n [\n -114.08980516405627,\n 48.48262143393191\n ],\n [\n -113.89155655683145,\n 48.4856773542281\n ],\n [\n -113.53655323691696,\n 48.22526656841134\n ],\n [\n -113.20921251335938,\n 48.41534459946189\n ],\n [\n -113.60109929508316,\n 49.00250961037867\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Scoresby, Salix","contributorId":352228,"corporation":false,"usgs":false,"family":"Scoresby","given":"Salix","affiliations":[{"id":84134,"text":"Contractor, USGS (Northern Arizona University)","active":true,"usgs":false}],"preferred":false,"id":949691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dose, Lindsay M","contributorId":361945,"corporation":false,"usgs":false,"family":"Dose","given":"Lindsay","middleInitial":"M","affiliations":[{"id":27609,"text":"Contractor to USGS","active":true,"usgs":false}],"preferred":false,"id":949692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belt, Jami","contributorId":177314,"corporation":false,"usgs":false,"family":"Belt","given":"Jami","affiliations":[],"preferred":false,"id":949693,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Tabitha A. 0000-0001-5145-2400","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":202084,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":949694,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70272285,"text":"70272285 - 2025 - Disturbance is the primary determinant of food chain length when the top predator is constant","interactions":[],"lastModifiedDate":"2025-11-20T16:30:30.424268","indexId":"70272285","displayToPublicDate":"2025-09-01T09:24:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2299,"text":"Journal of Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Disturbance is the primary determinant of food chain length when the top predator is constant","docAbstract":"Food chain length (FCL) is a primary determinant of food web structure and is hypothesized to be influenced by habitat size, productivity, and disturbance. Understanding the environmental characteristics that determine food chain length can assist in understanding how food webs may be impacted due to changes in habitats and environmental characteristics. This study examines the impact of hydrologic disturbance on stream food webs when the top predator is constant. We analyzed FCL in less disturbed groundwater flashy streams and more disturbed runoff flashy streams using stable isotopes. Despite no difference in species richness or fish density, food chains in more disturbed streams had a lower FCL compared to food chains in more stable streams. Assemblage analysis showed that flow regime and drainage area significantly impacted individual species abundances. The more disturbed runoff flashy streams had higher proportions of primary consumer fish, such as the algivorous Campostoma sp. (Stonerollers), which likely drives the reduced FCL. Drainage area and land cover had non-significant relationships with FCL. Shifting community structure due to hydrologic variability likely leads to differences in diet of Micropterus dolomieu (Smallmouth Bass), and thus a difference in FCL.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2025.2552789","usgsCitation":"Sorensen, S.F., and Magoulick, D.D., 2025, Disturbance is the primary determinant of food chain length when the top predator is constant: Journal of Freshwater Ecology, v. 40, no. 1, 2552789, 13 p., https://doi.org/10.1080/02705060.2025.2552789.","productDescription":"2552789, 13 p.","ipdsId":"IP-158669","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496764,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2025.2552789","text":"Publisher Index Page"},{"id":496698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","otherGeospatial":"Boston Mountains, Ozark Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.36140202738136,\n 36.86778775165942\n ],\n [\n -95.16750642659139,\n 35.284730700987836\n ],\n [\n -90.54968868524054,\n 35.4188870788884\n ],\n [\n -89.35998010774131,\n 36.86867805963976\n ],\n [\n -92.3624285247389,\n 37.51630205547987\n ],\n [\n -93.33606079252797,\n 37.097059236951665\n ],\n [\n -94.36140202738136,\n 36.86778775165942\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"40","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sorensen, Sarah F.","contributorId":362643,"corporation":false,"usgs":false,"family":"Sorensen","given":"Sarah","middleInitial":"F.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":950684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":950685,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273401,"text":"70273401 - 2025 - Newly released Grand Canyon flash flood incident report","interactions":[],"lastModifiedDate":"2026-01-12T16:09:12.732432","indexId":"70273401","displayToPublicDate":"2025-09-01T09:22:30","publicationYear":"2025","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":8569,"text":"Boatman's Quarterly Review","active":true,"publicationSubtype":{"id":30}},"title":"Newly released Grand Canyon flash flood incident report","docAbstract":"No abstract available.
","language":"English","publisher":"Grand Canyon River Guides","usgsCitation":"Byerley, E.P., 2025, Newly released Grand Canyon flash flood incident report: Boatman's Quarterly Review, v. 38, no. 3.","productDescription":"1 p.","startPage":"13","ipdsId":"IP-181804","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498535,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.gcrg.org/bqr"},{"id":498549,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.37659635793055,\n 36.92768493688186\n ],\n [\n -114.02194696398374,\n 36.92768493688186\n ],\n [\n -114.02194696398374,\n 35.784272392896824\n ],\n [\n -111.37659635793055,\n 35.784272392896824\n ],\n [\n -111.37659635793055,\n 36.92768493688186\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"38","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Byerley, Erica Paige 0009-0003-8483-7528","orcid":"https://orcid.org/0009-0003-8483-7528","contributorId":333657,"corporation":false,"usgs":true,"family":"Byerley","given":"Erica","email":"","middleInitial":"Paige","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":953587,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70272195,"text":"70272195 - 2025 - Living with wildfire in Estes Valley Fire Protection District, Larimer County, Colorado: 2023 Data report","interactions":[],"lastModifiedDate":"2025-11-19T14:57:49.939016","indexId":"70272195","displayToPublicDate":"2025-09-01T08:49:31","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":72,"text":"Research Note","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"RMRS-RN-108","title":"Living with wildfire in Estes Valley Fire Protection District, Larimer County, Colorado: 2023 Data report","docAbstract":"Homeowner wildfire risk mitigation and preparedness are critical components of community wildfire readiness. This report describes the data collected through two efforts conducted in the Estes Valley Fire Protection District of Larimer County, Colorado, study area: (1) parcel-level rapid wildfire risk assessments performed by trained assessors and (2) homeowner surveys in which respondents provided self-assessments of their parcel-level wildfire risk. This project was undertaken to support Estes Valley Fire Protection District’s desire to enhance resident wildfire risk mitigation and evacuation planning. The household surveys also explored the social dimensions of wildfire, including understanding of wildfire risk, outreach or communication preferences, mitigation and evacuation preparedness activities, and perceptions of community risk reduction strategies. The results provide evidence that despite high levels of wildfire awareness and experience, respondents underestimate the risk on their properties as compared to a trained professional and have not completed important steps in the evacuation preparedness process. However, respondents would like more information on wildfire risk reduction via newsletters (mailed or emailed), community meetings, and in-person interactions.
","language":"English","publisher":"U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station","doi":"10.2737/RMRS-RN-108","usgsCitation":"Donovan, C., Champ, P.A., Wittenbrink, S., Formeller, W., Taniguchi, C., Landkamer, J., Brenkert-Smith, H., Meldrum, J., Barth, C.M., and Wagner, C., 2025, Living with wildfire in Estes Valley Fire Protection District, Larimer County, Colorado: 2023 Data report: Research Note RMRS-RN-108, vi, 137 p., https://doi.org/10.2737/RMRS-RN-108.","productDescription":"vi, 137 p.","ipdsId":"IP-178025","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":496623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Estes Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -105.48606137456866,\n 40.39021611988062\n ],\n [\n -105.53633291099767,\n 40.39021611988062\n ],\n [\n -105.53633291099767,\n 40.31949882059695\n ],\n [\n -105.48606137456866,\n 40.31949882059695\n ],\n [\n -105.48606137456866,\n 40.39021611988062\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Donovan, Colleen","contributorId":240586,"corporation":false,"usgs":false,"family":"Donovan","given":"Colleen","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":950395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Champ, Patricia A. 0000-0003-1917-883X","orcid":"https://orcid.org/0000-0003-1917-883X","contributorId":360956,"corporation":false,"usgs":false,"family":"Champ","given":"Patricia","middleInitial":"A.","affiliations":[{"id":86128,"text":"U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station","active":true,"usgs":false}],"preferred":false,"id":950396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wittenbrink, Suzanne","contributorId":333353,"corporation":false,"usgs":false,"family":"Wittenbrink","given":"Suzanne","email":"","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":950397,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Formeller, Wilynn","contributorId":362386,"corporation":false,"usgs":false,"family":"Formeller","given":"Wilynn","affiliations":[{"id":86514,"text":"Estes Valley Watershed Coalition","active":true,"usgs":false}],"preferred":false,"id":950398,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taniguchi, Christine","contributorId":355605,"corporation":false,"usgs":false,"family":"Taniguchi","given":"Christine","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":950399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Landkamer, Jon","contributorId":362387,"corporation":false,"usgs":false,"family":"Landkamer","given":"Jon","affiliations":[{"id":86516,"text":"Estes Valley Fire Protection District","active":true,"usgs":false}],"preferred":false,"id":950400,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brenkert-Smith, Hannah 0000-0001-6117-8863","orcid":"https://orcid.org/0000-0001-6117-8863","contributorId":195485,"corporation":false,"usgs":false,"family":"Brenkert-Smith","given":"Hannah","email":"","affiliations":[],"preferred":false,"id":950401,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":950402,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Barth, Christopher M.","contributorId":362388,"corporation":false,"usgs":false,"family":"Barth","given":"Christopher","middleInitial":"M.","affiliations":[{"id":86132,"text":"U.S. Department of Agriculture, Forest Service, Washington Office","active":true,"usgs":false}],"preferred":false,"id":950403,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Wagner, Carolyn","contributorId":240587,"corporation":false,"usgs":false,"family":"Wagner","given":"Carolyn","affiliations":[{"id":48103,"text":"Wildfire Research (WiRē) Center","active":true,"usgs":false}],"preferred":false,"id":950404,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70271265,"text":"70271265 - 2025 - Comparison of creek and bay influences on salt marsh sediment budget and deposition patterns","interactions":[],"lastModifiedDate":"2025-09-03T15:37:29.40376","indexId":"70271265","displayToPublicDate":"2025-09-01T08:31:24","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of creek and bay influences on salt marsh sediment budget and deposition patterns","docAbstract":"The resilience of salt marshes with low organic production depends on their effective capture and retention of mineral sediment from adjacent waters. Little prior work has directly compared mechanisms of sediment import from wave-influenced marsh boundaries against those of tidal creeks. We used simultaneous deployment of net-deposition tiles and oceanographic sensors to identify the timing and magnitude of sediment import/export to, and redistribution within, a marsh in south San Francisco Bay. As the marsh has both an eroding bay-exposed scarp and a prominent tidal creek, we investigated the mechanisms and magnitudes of sediment import from the marsh-bay versus the marsh-creek interface. The strong daily sea breezes of the summer season produced most of the wave-driven erosion of the marsh scarp and controlled suspended sediment concentrations; the winter season had weaker winds punctuated by a few storms. A large seasonal difference in suspended sediment concentrations influenced both flood and ebb sediment fluxes to the marsh and led to much higher rates of import in the summer. Both bay-side and creek-side processes were important to total marsh sediment budget. Bay-side sediment contributions were more variable in time due to the bay-influenced environment, and creek-side contributions were overall larger, reflecting the large proportion of the marsh fed by creek water. Sediment was redistributed throughout the system, with erosion near the bay-edge, accretion near the creek-edge and slow import to the marsh interior. The marsh was net importing sediment in the summer and exporting in the winter from different rates of these processes; on an annual scale, the marsh was net importing despite rapid lateral marsh loss. These findings emphasize that a positive sediment budget does not imply a stable marsh and that both creek- and edge-side dynamics are important for marsh sedimentation and geomorphic trajectories. Further, we expand understandings of non-storm and seasonal controls on marsh sedimentation.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.70137","usgsCitation":"WinklerPrins, L.T., Lacy, J.R., Stacey, M.T., Thorne, K., Bristow, M.L., and Jones, S., 2025, Comparison of creek and bay influences on salt marsh sediment budget and deposition patterns: Earth Surface Processes and Landforms, v. 50, no. 11, e70137, 19 p., https://doi.org/10.1002/esp.70137.","productDescription":"e70137, 19 p.","ipdsId":"IP-167923","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":495183,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.70137","text":"Publisher Index Page"},{"id":495152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay, Whales Tail Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.1656695070773,\n 37.58939504635727\n ],\n [\n -122.1656695070773,\n 37.53784183376638\n ],\n [\n -122.10301033557374,\n 37.53784183376638\n ],\n [\n -122.10301033557374,\n 37.58939504635727\n ],\n [\n -122.1656695070773,\n 37.58939504635727\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"50","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"WinklerPrins, Lukas T. 0000-0003-0508-1455","orcid":"https://orcid.org/0000-0003-0508-1455","contributorId":304096,"corporation":false,"usgs":false,"family":"WinklerPrins","given":"Lukas","email":"","middleInitial":"T.","affiliations":[{"id":65968,"text":"UC Berkeley, contracted to USGS PCMSC","active":true,"usgs":false}],"preferred":false,"id":947814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lacy, Jessica R. 0000-0002-2797-6172","orcid":"https://orcid.org/0000-0002-2797-6172","contributorId":201703,"corporation":false,"usgs":true,"family":"Lacy","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":947815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stacey, Mark T.","contributorId":360868,"corporation":false,"usgs":false,"family":"Stacey","given":"Mark","middleInitial":"T.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":947816,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorne, Karen M. 0000-0002-1381-0657","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":204579,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":947817,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bristow, McKenna Leigh 0000-0003-2284-1380","orcid":"https://orcid.org/0000-0003-2284-1380","contributorId":330403,"corporation":false,"usgs":true,"family":"Bristow","given":"McKenna","middleInitial":"Leigh","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":947818,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jones, Scott 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":215602,"corporation":false,"usgs":true,"family":"Jones","given":"Scott","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":947819,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271308,"text":"70271308 - 2025 - Perfluorodecanoic acid (PFDA) disrupts immune regulation via the toll-like receptor signaling pathway in zebrafish","interactions":[],"lastModifiedDate":"2025-09-22T16:06:51.567934","indexId":"70271308","displayToPublicDate":"2025-09-01T08:14:47","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Perfluorodecanoic acid (PFDA) disrupts immune regulation via the toll-like receptor signaling pathway in zebrafish","docAbstract":"As there are a growing number of per- and polyfluoroalkyl substances (PFAS) alternative substitutes applied globally, it remains paramount to characterize their potential health risks. Perfluorodecanoic acid (PFDA) is the most common alternative PFAS detected in the environment; however, its toxic effects and underlying mechanism of action to aquatic biota remains unclear. In this study, we present in vitro evidence of PFDA-induced immunotoxicity and gain insight into underlying molecular mechanisms. PFDA induced immune dysfunction in zebrafish primarily through immunosuppression, apoptosis, and inflammatory response which further cascaded to suppress innate and adaptive immunities, ultimately weaking the ability of larvae to defend against pathogenic infection. PFDA-induced immunotoxicity was driven by a dysregulation in the toll-like receptor (TLR) signaling pathway, which was validated through a cotreatment of PFDA with either a morpholino knockdown or inhibitor of myeloid differentiation factor 88. Comparative toxicity studies were carried out with a subset of other alternative PFAS (PFBA, PFOA, PFNA) and it was found that PFDA posed a greater immunotoxic response than other commonly identified PFAS in the environment. This work identified a major target of PFDA, disrupting immune function through the TLR signaling pathway, while inducing a greater toxic response among other tested PFAS, which provides novel insights into understanding the potential environmental risks of PFAS substitutes.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.5c04320","usgsCitation":"Wang, J., Fang, D., Magnuson, J.T., Xu, B., Zheng, C., Tang, L., and Qiu, W., 2025, Perfluorodecanoic acid (PFDA) disrupts immune regulation via the toll-like receptor signaling pathway in zebrafish: Environmental Science & Technology, v. 59, no. 36, p. 19119-19130, https://doi.org/10.1021/acs.est.5c04320.","productDescription":"12 p.","startPage":"19119","endPage":"19130","ipdsId":"IP-177537","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":495167,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"59","issue":"36","noUsgsAuthors":false,"publicationDate":"2025-09-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Wang, Jiazhen","contributorId":329836,"corporation":false,"usgs":false,"family":"Wang","given":"Jiazhen","email":"","affiliations":[{"id":78727,"text":"Southern University of Science and Technology","active":true,"usgs":false}],"preferred":false,"id":947928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fang, Di","contributorId":348832,"corporation":false,"usgs":false,"family":"Fang","given":"Di","affiliations":[{"id":80251,"text":"Southern University of Science and Technology, China","active":true,"usgs":false}],"preferred":false,"id":947929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magnuson, Jason Tyler 0000-0001-6841-8014","orcid":"https://orcid.org/0000-0001-6841-8014","contributorId":329838,"corporation":false,"usgs":true,"family":"Magnuson","given":"Jason","email":"","middleInitial":"Tyler","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":947930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xu, Bentuo","contributorId":329839,"corporation":false,"usgs":false,"family":"Xu","given":"Bentuo","email":"","affiliations":[{"id":78729,"text":"Wenzhou University","active":true,"usgs":false}],"preferred":false,"id":947931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zheng, Chunmiao","contributorId":214041,"corporation":false,"usgs":false,"family":"Zheng","given":"Chunmiao","email":"","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":947932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tang, Liang","contributorId":360925,"corporation":false,"usgs":false,"family":"Tang","given":"Liang","affiliations":[{"id":84014,"text":"Shanghai University, China","active":true,"usgs":false}],"preferred":false,"id":947933,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Qiu, Wenhui","contributorId":334797,"corporation":false,"usgs":false,"family":"Qiu","given":"Wenhui","email":"","affiliations":[{"id":80251,"text":"Southern University of Science and Technology, China","active":true,"usgs":false}],"preferred":false,"id":947934,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70272596,"text":"70272596 - 2025 - Long‐term regime shifts in xeric ecoregion freshwater fish assemblages due to Anthropogenic and climate stressors","interactions":[],"lastModifiedDate":"2025-11-24T15:08:54.65527","indexId":"70272596","displayToPublicDate":"2025-09-01T08:04:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Long‐term regime shifts in xeric ecoregion freshwater fish assemblages due to Anthropogenic and climate stressors","docAbstract":"Shifting climate regimes are projected to increase the area of xeric regions and result in more pronounced intermittency across river networks. Given these projected changes, we aim to understand the factors contributing to species persistence under increasing aridity. To investigate how changing flow regimes are related to changes in fish richness and assemblage composition, we compiled data from 1473 xeric stream sites in the United States and Australia. The temporal coverage of this dataset is more than 40 years, from 1980 to 2021. Our focus was on fishes occurring in xeric streams and included 191 species. We compiled climate, hydrologic, and fish species trait data to identify relationships between environmental drivers of species persistence and corresponding characteristics common to species in these systems and traits eliciting the strongest responses to environmental change. Our data show declines in overall precipitation in concert with increasing temperatures over the last several decades. Climatic shifts were accompanied by declines in discharge, increased zero-flow days, and longer durations of no-flow periods. In these same systems, an overall linear decline in fish species richness was observed, but it was not directly correlated with any hydrologic predictors. However, xeric species of conservation concern were small-bodied and occupied lower trophic levels than those not of concern. Listed species were primarily affected by multiple stressors, including habitat degradation and invasive species, compounded by a small geographic range. We thus propose a multiple stressors argument for the declines in xeric fish assemblages, something that may be exacerbated by climate alterations in the future. This work highlights a critical conservation need for xeric fishes and identifies taxa that are especially vulnerable to a combination of anthropogenic stressors and changing climates.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.72067","usgsCitation":"Krabbenhoft, C.A., Rogosch, J.S., and Rowland, F.E., 2025, Long‐term regime shifts in xeric ecoregion freshwater fish assemblages due to Anthropogenic and climate stressors: Ecology and Evolution, v. 15, no. 9, e72067, 15 p., https://doi.org/10.1002/ece3.72067.","productDescription":"e72067, 15 p.","ipdsId":"IP-167908","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":496929,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.72067","text":"Publisher Index Page"},{"id":496822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -126.68838705734726,\n 42.46729142856819\n ],\n [\n -126.68838705734726,\n 31.274100073517374\n ],\n [\n -101.81329639705922,\n 31.274100073517374\n ],\n [\n -101.81329639705922,\n 42.46729142856819\n ],\n [\n -126.68838705734726,\n 42.46729142856819\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 112.14586345695147,\n -18.081847635268318\n ],\n [\n 112.14586345695147,\n -33.43692331548075\n ],\n [\n 144.94300096233883,\n -33.43692331548075\n ],\n [\n 144.94300096233883,\n -18.081847635268318\n ],\n [\n 112.14586345695147,\n -18.081847635268318\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Krabbenhoft, Corey A. 0000-0002-1041-5301","orcid":"https://orcid.org/0000-0002-1041-5301","contributorId":362965,"corporation":false,"usgs":false,"family":"Krabbenhoft","given":"Corey","middleInitial":"A.","affiliations":[{"id":37334,"text":"University at Buffalo","active":true,"usgs":false}],"preferred":false,"id":950883,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rogosch, Jane S. 0000-0002-1748-4991","orcid":"https://orcid.org/0000-0002-1748-4991","contributorId":317717,"corporation":false,"usgs":true,"family":"Rogosch","given":"Jane","middleInitial":"S.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":950884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rowland, Freya Elizabeth 0000-0002-1041-5301","orcid":"https://orcid.org/0000-0002-1041-5301","contributorId":302395,"corporation":false,"usgs":true,"family":"Rowland","given":"Freya","email":"","middleInitial":"Elizabeth","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":950885,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272187,"text":"70272187 - 2025 - Melt generation sources and conditions in the wake of a migrating slab window: Geochemistry and petrology of the million-year history of primitive volcanism at Clear Lake volcanic field, California","interactions":[],"lastModifiedDate":"2025-11-18T15:07:29.134486","indexId":"70272187","displayToPublicDate":"2025-09-01T07:59:45","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2420,"text":"Journal of Petrology","active":true,"publicationSubtype":{"id":10}},"title":"Melt generation sources and conditions in the wake of a migrating slab window: Geochemistry and petrology of the million-year history of primitive volcanism at Clear Lake volcanic field, California","docAbstract":"Clear Lake volcanic field (CLVF) is the northernmost and youngest (~2.2 Ma to 8 ka) of the volcanic centers distributed along the San Andreas transform fault in western California. The initial phase of CLVF volcanism (interval one) occurred between ~2.2 and 1.3 Ma and extends ~35 km southeast of Clear Lake, forming a semi-continuous upland plateau capped by lava flows, with isolated volcanic remnants on the periphery. This volcanism is broadly characterized by geochemically primitive compositions that reflect three source compositions and conditions of melt generation. (1) Partial melting of upwelling asthenospheric mantle lherzolite at moderate pressures (1.2–1.4 GPa) and temperatures (1297–1329 °C) produced high-CaO (9.8–11.3 wt %) basalts with high Al2O3 (16.8–17.6 wt %), Mg#s (66–70), MgO (8–10 wt %), Ni (103–262 μg/g), and Cr (284–609 μg/g). These high-CaO basalts contain olivine (Fo87–91) phenocrysts with Cr-spinel inclusions ± subordinate plagioclase and crop out only in the southern part of the CLVF. (2) Partial melting of depleted sub-continental lithospheric mantle harzburgite at variable pressures (0.7–1.5 GPa) and temperatures (1097–1299 °C) produced a compositional continuum of med-K2O, calc-alkaline, high-MgO basalts through high-MgO andesites with high Mg#s (67–77), MgO (8–14 wt %) and high Ni and Cr abundances (154–439 and 340–1124 μg/g, respectively). Mineral assemblages are olivine (Fo88–93) with Cr-spinel inclusions ± subordinate clinopyroxene, orthopyroxene and plagioclase. Small (<2.5 cm) mantle harzburgite xenoliths and mantle olivine xenocrysts are also found in several of these samples. These high-MgO basalts through andesites represent the largest volume of primitive compositions and have erupted predominantly along the main, fault-controlled northwest-southeast trending axis of volcanism with peripheral outcrops to the north, west, and east. (3) Partial melting of the Gorda eclogite slab edge produced adakitic silicic slab melts with strong depletion in the heavy rare earth elements (Yb = 0.6 μg/g). Subsequent reaction of those melts with depleted ultramafic rocks during ascent imprinted the adakitic dacites with high Mg#s (65–78) and elevated Ni (117–210 μg/g) and Cr (191–283 μg/g). Phenocrysts of orthopyroxene (En87–94) with spinel inclusions (Cr# = 80–88) and extremely Ni-rich (9483 μg/g) olivine cores (Fo84–93) record those reactions. Small-volume outcrops of the adakites on the eastern periphery of the CLVF track the passing slab edge. The trio of melting sources recorded by early CLVF magmatism reflect the tectonically complex environment and the hot (1097–1329 °C), shallow (0.7–1.5 GPa) melting conditions for these primitive compositions and provide estimates of the heat delivered to the crust. Over time, this flux led to maturation of the CLVF magmatic system toward the more voluminous and silicic volcanism that characterizes the balance of its subsequent volcanic history and maintains the present-day anomalously high heat flow in the region. The current interval (interval four) of volcanic activity at CLVF is characterized by low-volume, fault-controlled eruptions of basaltic andesite and andesite suggestive of mantle magma and heat delivery to the crust, similar to interval one. This analogous activity provides motivation for the current study and begs the question of whether the system is undergoing thermal priming for renewed silicic volcanism.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/petrology/egaf077","usgsCitation":"Blatter, D.L., and Burgess, S.D., 2025, Melt generation sources and conditions in the wake of a migrating slab window: Geochemistry and petrology of the million-year history of primitive volcanism at Clear Lake volcanic field, California: Journal of Petrology, v. 66, no. 9, egaf077, 43 p., https://doi.org/10.1093/petrology/egaf077.","productDescription":"egaf077, 43 p.","ipdsId":"IP-173749","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496579,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Clear Lake volcanic field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.9635380144356,\n 39.14844575495471\n ],\n [\n -122.9635380144356,\n 38.917438489493804\n ],\n [\n -122.5731123436415,\n 38.917438489493804\n ],\n [\n -122.5731123436415,\n 39.14844575495471\n ],\n [\n -122.9635380144356,\n 39.14844575495471\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"66","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-09-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Blatter, Dawnika L. 0000-0002-7161-6844 dblatter@usgs.gov","orcid":"https://orcid.org/0000-0002-7161-6844","contributorId":4899,"corporation":false,"usgs":true,"family":"Blatter","given":"Dawnika","email":"dblatter@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":950370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgess, Seth D. 0000-0002-2128-9144","orcid":"https://orcid.org/0000-0002-2128-9144","contributorId":362359,"corporation":false,"usgs":true,"family":"Burgess","given":"Seth","middleInitial":"D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":950371,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70271905,"text":"70271905 - 2025 - A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed","interactions":[],"lastModifiedDate":"2025-09-24T15:03:35.249606","indexId":"70271905","displayToPublicDate":"2025-09-01T07:53:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed","docAbstract":"Tsunami hazards are substantial threats to coastal communities across the United States (U.S.) and its territories. U.S. states and territories collaborate through the National Tsunami Hazard Mitigation Program (NTHMP) to develop their own tsunami-hazard information for outreach and evacuation planning. An effort to curate this tsunami-hazard information to support comprehensive risk analysis at the national level has not yet been completed. In support of this effort, the Federal Emergency Management Agency (FEMA) collaborated with the NTHMP, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) starting in 2023. This collaboration included the collection and analysis of existing tsunami hazard data and methods in the U.S. Tsunami subject matter experts identified and selected scientifically defensible methods for estimating the risks to buildings and populations in coastal communities. These efforts may support decision making regarding resilience policies, priorities, strategies and funding levels.
Tsunamis can be triggered by earthquakes, subaerial or submarine landslides, volcanic eruptions, glacial calving, near-earth objects, weather or other events. These events can cause severe destruction, injuries, and loss of life due to powerful currents and flooding. Tsunamis pose a substantial threat to the western United States and all U.S. territories, as described below.
■ Hawaii is threatened by distant tsunamis due to its central location in the Pacific Ocean basin and has a history of local events.
■ Alaska, particularly the Aleutian Islands, faces local tsunami threats due to proximity to the Alaska-Aleutian Subduction Zone, as well as distant tsunamis from around the Pacific Ocean basin.
■ The western coast of the U.S. is threatened by distant tsunamis from around the Pacific Ocean basin and local source tsunamis from earthquakes generated within the Cascadia Subduction Zone in the Pacific Northwest.
■ American Samoa faces local tsunami threats from earthquakes generated in the nearby Tonga Trench, as well as distant tsunami threats.
■ Guam and the Commonwealth of the Northern Mariana Islands are threatened by local tsunamis from the nearby Mariana Subduction Zone, as well as distant sources from around the Pacific Ocean Basin.
■ Puerto Rico and the United States Virgin Islands are threatened by multiple local and distant tsunami sources, such as the Puerto Rico Trench (PRT), given their location in the complex seismic region of the Caribbean Sea.
Several historical events stand out because of their catastrophic impacts.
■ In the Pacific Northwest, the 1700 Cascadia earthquake caused a tsunami that affected coastal Native American communities, though the extent of the damage is not fully documented (Ludwin, et al., 2005).
■ In Puerto Rico, the 1918 earthquake triggered a tsunami that caused $77 million in damage in 2022 dollars and 116 fatalities, primarily along the western coast (Coffman et al., 1982).
■ The 1946 Aleutian Islands earthquake triggered a massive tsunami that devastated Hilo, Hawaii, killing 158 people and resulting in approximately $375 million in damage (adjusted to 2022 dollars) (Fisher et al., 2023).
■ The 1964 Alaska earthquake (M 9.2) generated tsunamis that caused severe destruction in some communities across Alaska, Oregon, and California. This disaster led to a total of 124 fatalities and approximately $2.9 billion in property damage (adjusted to 2022 dollars) (Brocher et al., 2014) (Alaska Science Center, 2024).
■ In American Samoa, a tsunami generated by the 2009 Samoa earthquake (Mw 8.1) caused widespread devastation, resulting in 34 confirmed fatalities (Apatu et al., 2013) and economic losses exceeding $160 million (adjusted to 2022 dollars) (DHS, 2011).
More recent events, including the 2010 Chile earthquake, the 2011 Japan earthquake, and the 2022 Tonga volcanic eruption, resulted in millions of dollars in damage to numerous ports and harbors in the U.S. South Pacific territories, Hawaii, and along the west coast of the U.S. (Lynett, et al., 2022) (Wilson, et al., 2013). Since these events, the expansion of the built environment in lowlying areas along the coast has increased the exposure of buildings and people, thereby further escalating community risk from tsunamis.
This report provides a comprehensive national assessment of earthquake-generated tsunami risk. It does not include impacts from tsunamis generated by landslides, volcanic eruptions, glacial calving, near-earth objects, weather, or other events. This study is based on the best available hazard data from the U.S. Pacific Coast (California, Oregon and Washington), Alaska, Hawaii, U.S. Pacific Territories (American Samoa, Guam and Commonwealth of the Northern Mariana Islands) and Caribbean Territories (Puerto Rico and United States Virgin Islands). Tsunami risks associated with states along the East Coast, Gulf Coast, and Great Lakes are not included in this study because Hazus 6.1 software (FEMA 2024a) does not currently include the ability to analyze tsunami risk in those states. Once modeling capabilities and tsunami hazard data become available for additional states, FEMA may incorporate these data into future editions of this study.
","language":"English","publisher":"FEMA","collaboration":"NOAA","usgsCitation":"Sheehan, A., Zuzak, C., Wood, N.J., Bausch, D., Yeager, C.G., and McDougall, A., 2025, Estimated average annualized tsunami losses for the United States, xiv, 158 p.","productDescription":"xiv, 158 p.","startPage":"158","ipdsId":"IP-178510","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":496895,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":496887,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fema.gov/sites/default/files/documents/fema_hazus_p-2426_estimated-average-annualized-tsunami-losses-united-states_092025.pdf"}],"country":"Commonwealth of the Northern Marianas Islands, United States","state":"Alaska, California, Hawaii Oregon, Washington","otherGeospatial":"American Samoa, Guam, Puerto Rico, U.S. West Coast, U.S. Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.6062294093663,\n 32.458500190297286\n ],\n [\n -116.21011015789321,\n 32.61698973791238\n ],\n [\n -120.88127417845152,\n 38.097464026104745\n ],\n [\n -121.68897114430274,\n 43.641049483331926\n ],\n [\n -120.34804469609418,\n 49.018589200520125\n ],\n [\n -123.12851993389381,\n 49.04770425376117\n ],\n [\n -123.58278288935202,\n 48.27176292059826\n ],\n [\n -124.95203781557444,\n 48.578276829289365\n ],\n [\n -124.70518072910363,\n 43.308256616227965\n ],\n [\n -124.76507745528673,\n 39.923570535757506\n ],\n [\n -122.37534605972587,\n 35.72406424053497\n ],\n [\n -119.44385408995873,\n 31.666408612606844\n ],\n [\n -117.6062294093663,\n 32.458500190297286\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -133.81830784107177,\n 54.43040660167367\n ],\n [\n -129.76495508589912,\n 54.95815271579741\n ],\n [\n -135.6583468478097,\n 59.80163756858815\n ],\n [\n -137.38717762509742,\n 59.14898446525993\n ],\n [\n -139.0212948291892,\n 60.264215429201585\n ],\n [\n -140.67745731463765,\n 60.40250770133565\n ],\n [\n -147.12836656435022,\n 63.83618995053891\n ],\n [\n -157.02008942678643,\n 60.85939892145646\n ],\n [\n -164.76539100027318,\n 60.5605869360071\n ],\n [\n -168.5622481995147,\n 60.48553755022252\n ],\n [\n -165.12347779691626,\n 58.42730886399775\n ],\n [\n -161.493786069723,\n 56.49260594277732\n ],\n [\n -175.42839689288203,\n 52.956535311511544\n ],\n [\n -179.9,\n 54.52382870093885\n ],\n [\n -179.9,\n 51.22773800011237\n ],\n [\n -172.6433514154191,\n 50.29861431159446\n ],\n [\n -151.87796136149032,\n 56.06405816776248\n ],\n [\n -144.79039533251827,\n 59.13811166015611\n ],\n [\n -138.74393964928734,\n 58.34696508033625\n ],\n [\n -133.81830784107177,\n 54.43040660167367\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 172.37049936297774,\n 54.268426823808824\n ],\n [\n 171.61788874531328,\n 52.630288408231536\n ],\n [\n 179.9,\n 50.868515155629694\n ],\n [\n 179.9,\n 52.677061761263815\n ],\n [\n 172.37049936297774,\n 54.268426823808824\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.58899597170847,\n 18.80780695678041\n ],\n [\n -154.62217606792944,\n 19.488067095861567\n ],\n [\n -156.5059490410102,\n 21.394871757964566\n ],\n [\n -159.4581955185556,\n 22.524641133352787\n ],\n [\n -160.53360458138968,\n 21.818256668769024\n ],\n [\n -160.10943449390106,\n 21.42891078182835\n ],\n [\n -159.34137919171857,\n 21.619327559524734\n ],\n [\n -157.4512265578657,\n 20.569605349731987\n ],\n [\n -156.29713248900438,\n 20.077543633655395\n ],\n [\n -155.9389788104159,\n 18.749301821932846\n ],\n [\n -155.58899597170847,\n 18.80780695678041\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -68.01302817465651,\n 18.76757835197182\n ],\n [\n -68.01302817465651,\n 17.821804600078025\n ],\n [\n -65.54801115314501,\n 17.821804600078025\n ],\n [\n -65.54801115314501,\n 18.76757835197182\n ],\n [\n -68.01302817465651,\n 18.76757835197182\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -64.65003052717975,\n 18.34728286609773\n ],\n [\n -64.74208222509347,\n 18.380884344303098\n ],\n [\n -64.91025359628094,\n 18.421197475640327\n ],\n [\n -65.09435699210782,\n 18.359044127510117\n ],\n [\n -64.89609179660236,\n 17.672207739051927\n ],\n [\n -64.71375862573525,\n 17.67389441714137\n ],\n [\n -64.52788500494862,\n 17.74977853644579\n ],\n [\n -64.65888165197907,\n 18.108525019700863\n ],\n [\n -64.65003052717975,\n 18.34728286609773\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -170.94576625447908,\n -14.099410688761111\n ],\n [\n -170.94576625447908,\n -14.459783544967976\n ],\n [\n -169.30826542787432,\n -14.459783544967976\n ],\n [\n -169.30826542787432,\n -14.099410688761111\n ],\n [\n -170.94576625447908,\n -14.099410688761111\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 145.92690626103928,\n 15.34521806192096\n ],\n [\n 145.62414052912254,\n 15.333692541624018\n ],\n [\n 144.43299639961504,\n 13.287941208980982\n ],\n [\n 144.83535612229275,\n 13.163842264822051\n ],\n [\n 145.94284129955997,\n 15.276055412396587\n ],\n [\n 145.92690626103928,\n 15.34521806192096\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sheehan, Anne","contributorId":330480,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":951001,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zuzak, Casey","contributorId":287432,"corporation":false,"usgs":false,"family":"Zuzak","given":"Casey","affiliations":[{"id":61582,"text":"FEMA Risk Mgmt Directorate","active":true,"usgs":false}],"preferred":false,"id":951002,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Nathan J. 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":3347,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","middleInitial":"J.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":951003,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bausch, Doug","contributorId":195191,"corporation":false,"usgs":false,"family":"Bausch","given":"Doug","email":"","affiliations":[{"id":34169,"text":"Pacific Disaster Center","active":true,"usgs":false}],"preferred":false,"id":951004,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yeager, Cadie Goulette 0009-0002-6966-1811","orcid":"https://orcid.org/0009-0002-6966-1811","contributorId":361919,"corporation":false,"usgs":false,"family":"Yeager","given":"Cadie","middleInitial":"Goulette","affiliations":[{"id":86387,"text":"Niyam IT","active":true,"usgs":false}],"preferred":false,"id":951005,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McDougall, Alice","contributorId":363052,"corporation":false,"usgs":false,"family":"McDougall","given":"Alice","affiliations":[{"id":86600,"text":"FACTOR","active":true,"usgs":false}],"preferred":false,"id":951006,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70273980,"text":"70273980 - 2025 - 3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park","interactions":[],"lastModifiedDate":"2026-02-24T14:58:17.527534","indexId":"70273980","displayToPublicDate":"2025-09-01T00:00:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park","docAbstract":"The ongoing degradation of coral reef habitats is widely acknowledged to have adverse effects on the abundance and diversity of reef fish populations, yet the direct effects on ecosystem functions remain uncertain. This study used a quantitative approach to determine the mechanistic links between fish assemblages and ecological function. We investigated the effects of 3D habitat structure and coral morphology on the ecological, behavioral, and morphological functional traits of reef fish within a protected marine national park. Fish traits such as Gregariousness, Water Column Position, and Body Shape were identified to be highly influential in shaping the multidimensional fish functional space, which was categorized into 10 Fish Functional Groups (FFG). Furthermore, habitat complexity and coral morphology significantly explained the abundances of eight out of 10 FFG. Notably, the habitat complexity metrics of Slope and Surface Complexity, along with coral morphologies of Branching and Mounding types, emerged as the most influential habitat features across FFG. Pairing Compressiform species and Schooling Short/Deep species, for example, significantly increased in abundance on substrate with higher Slopes and increased percentages of branching coral cover. Additionally, Cryptic and Nocturnal species exhibited statistically significant associations with all coral morphologies and substrates with high trait values of Slope and Curvature. Elucidating ecological drivers of specific functional groups of reef fish is critical for determining how changes in reef composition and structure will alter fish assemblages. Broad scale patterns were also detected, suggesting that although structural complexity is important, live coral morphologies have a greater positive impact on reef fish functional groups. These findings have direct implications for conservation and monitoring efforts, offering valuable insights for predicting the impacts of environmental change on community dynamics and ecosystem functioning.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71992","usgsCitation":"Ferreira, S.B., Burns, J.H., Fukunaga, A., Raz, L., McKenna, S.A., Annandale, K., Monello, R.J., 2025, 3D habitat complexity and coral morphology modulate reef fish functional structure in a marine national park: Ecology and Evolution, v. 15, no. 9, e71992, 16 p., https://doi.org/10.1002/ece3.71992.","productDescription":"e71992, 16 p.","ipdsId":"IP-174520","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500601,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71992","text":"Publisher Index Page"},{"id":500436,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","city":"Kailua-Kona","otherGeospatial":"Kaloko-Honokohau National Historical Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.0727322749224,\n 19.716285054970754\n ],\n [\n -156.0727322749224,\n 19.58261325737645\n ],\n [\n -155.92066431233505,\n 19.58261325737645\n ],\n [\n -155.92066431233505,\n 19.716285054970754\n ],\n [\n -156.0727322749224,\n 19.716285054970754\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ferreira, Sofia B.","contributorId":366488,"corporation":false,"usgs":false,"family":"Ferreira","given":"Sofia","middleInitial":"B.","affiliations":[],"preferred":false,"id":955983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, John H.R.","contributorId":366489,"corporation":false,"usgs":false,"family":"Burns","given":"John","middleInitial":"H.R.","affiliations":[],"preferred":false,"id":955984,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fukunaga, Atsuko","contributorId":366490,"corporation":false,"usgs":false,"family":"Fukunaga","given":"Atsuko","affiliations":[],"preferred":false,"id":955985,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raz, Lillian Joy Tuttle 0000-0002-5009-8080","orcid":"https://orcid.org/0000-0002-5009-8080","contributorId":354940,"corporation":false,"usgs":true,"family":"Raz","given":"Lillian Joy Tuttle","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":955986,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKenna, Sheila A.","contributorId":366491,"corporation":false,"usgs":false,"family":"McKenna","given":"Sheila","middleInitial":"A.","affiliations":[],"preferred":false,"id":955987,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Annandale, Kailea","contributorId":366492,"corporation":false,"usgs":false,"family":"Annandale","given":"Kailea","affiliations":[],"preferred":false,"id":955988,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Monello, Ryan J.","contributorId":366493,"corporation":false,"usgs":false,"family":"Monello","given":"Ryan","middleInitial":"J.","affiliations":[],"preferred":false,"id":955989,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271342,"text":"70271342 - 2025 - Refining PAH and PCB bioavailability predictions in industrial sediments using source-fingerprinting, particle size, and bulk carbon, Puget Sound, Washington","interactions":[],"lastModifiedDate":"2025-09-08T15:39:35.751285","indexId":"70271342","displayToPublicDate":"2025-08-30T08:34:23","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Refining PAH and PCB bioavailability predictions in industrial sediments using source-fingerprinting, particle size, and bulk carbon, Puget Sound, Washington","docAbstract":"Nearshore marine sediments in a Puget Sound, Washington industrial embayment had elevated levels of PAHs, PCBs and DDTs. Chemical fingerprints implicated nearshore sources including creosote, industrial oil and tar waste, and a landfill. Elevated concentrations were confined to an approximate 300-m shoreline buffer in the industrial waterfront, suggesting high site fidelity and limited along-shore or off-shore transport. Total PAH concentrations approximately doubled when including alkylated compounds. The industrial sediments often exceeded toxicity criteria; however, chemicals were likely less bioavailable than predicted, in part, due to assumed strong sorption to anthropogenic carbon like coal tar. Analyses of separated particle-size fractions showed that approximately half of PAHs were associated with particles greater than 500 μm, suggesting that a wide range of particle sizes are relevant to occurrence and transport. Predicted freely dissolved chemical concentrations in sediment pore water were unrealistically high using a bulk organic carbon sorption coefficient. When reduced to environmentally reasonable levels by applying a high-sorption partition coefficient applicable to contaminated sediments, predicted freely dissolved concentrations in some industrial sediments exceeded sublethal effect levels or surface water quality standards. Chemical assemblages predicted in the freely dissolved aqueous fraction, which is relevant for biotic uptake from water, shifted to predominantly low molecular weight as compared to sediment, highlighting the role of exposure pathways in bioavailability. Insights from chemical fingerprinting coupled with co-analysis of bulk carbon and grain size allowed refinement of bioavailability assessments of complex chemical mixtures in contaminated nearshore environments that are relevant for ecosystem health and restoration.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2025.118634","usgsCitation":"Conn, K., Spanjer, A.R., and Takesue, R., 2025, Refining PAH and PCB bioavailability predictions in industrial sediments using source-fingerprinting, particle size, and bulk carbon, Puget Sound, Washington: Marine Pollution Bulletin, v. 222, no. 1, 118634, 13 p., https://doi.org/10.1016/j.marpolbul.2025.118634.","productDescription":"118634, 13 p.","ipdsId":"IP-179381","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":495383,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpolbul.2025.118634","text":"Publisher Index Page"},{"id":495222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.5803557715652,\n 48.71546982579352\n ],\n [\n -122.5803557715652,\n 48.62987350152983\n ],\n [\n -122.45585962195041,\n 48.62987350152983\n ],\n [\n -122.45585962195041,\n 48.71546982579352\n ],\n [\n -122.5803557715652,\n 48.71546982579352\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"222","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Conn, Kathleen 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":214913,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spanjer, Andrew R. 0000-0002-7288-2722 aspanjer@usgs.gov","orcid":"https://orcid.org/0000-0002-7288-2722","contributorId":150395,"corporation":false,"usgs":true,"family":"Spanjer","given":"Andrew","email":"aspanjer@usgs.gov","middleInitial":"R.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":948115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Takesue, Renee K. 0000-0003-1205-0825 rtakesue@usgs.gov","orcid":"https://orcid.org/0000-0003-1205-0825","contributorId":214915,"corporation":false,"usgs":true,"family":"Takesue","given":"Renee","email":"rtakesue@usgs.gov","middleInitial":"K.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":948116,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70272751,"text":"70272751 - 2025 - Induced earthquakes are generally not tidally triggered in Oklahoma and Kansas","interactions":[],"lastModifiedDate":"2025-12-08T15:25:54.972708","indexId":"70272751","displayToPublicDate":"2025-08-30T08:19:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Induced earthquakes are generally not tidally triggered in Oklahoma and Kansas","docAbstract":"Human-induced earthquakes occur along critically stressed faults as injected wastewater simultaneously heightens fluid pressure and pushes faults to failure. We investigate the possibility that small stresses imposed by Earth tides could trigger earthquakes in the induced seismicity region of Oklahoma and Kansas from 2011 to 2018. We decluster a catalog consisting of ∼110,000 earthquakes using three methods (Reasenberg, nearest-neighbor distance, and phase-bin). We find no significant tidal earthquake triggering using Schuster's p-value test for the declustered catalogs as a whole. We search for localized triggering using discretized space-time cells and find ∼0–6% of cells have significant tidal triggering which is close to what is randomly expected (5%) and indicates there is an insignificant amount of tidal triggering for the full study region. One area that has significant p-values across multiple time windows, ∼2014–2016 is ∼15 km from a region of large wastewater injection volume. It is possible that localized tidal triggering occurs for this time and area because faults remain critically stressed and are particularly susceptible to slip under the small stress load from the semidiurnal tide. Possible explanations for the lack of tidal triggering in our broader study are that the pre-seismic stressing rate in the earthquake nucleation area is faster than the tidal stressing rate (∼3 kPa/day), faults are not close enough to critically stressed to be affected by tidal forcing, and that nucleation occurs over longer periods than the tides considered in this study (∼1, ∼14 days). Fluid injection could be the source of a higher pre-seismic stress rate.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JB030254","usgsCitation":"Glasgow, M.E., Rubinstein, J., and Hardebeck, J.L., 2025, Induced earthquakes are generally not tidally triggered in Oklahoma and Kansas: JGR Solid Earth, v. 130, no. 9, e2024JB030254, 14 p., https://doi.org/10.1029/2024JB030254.","productDescription":"e2024JB030254, 14 p.","ipdsId":"IP-170440","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":497187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.51048622346829,\n 37.582532311249224\n ],\n [\n -99.51048622346829,\n 35.29053847687989\n ],\n [\n -96.58737926620248,\n 35.29053847687989\n ],\n [\n -96.58737926620248,\n 37.582532311249224\n ],\n [\n -99.51048622346829,\n 37.582532311249224\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"130","issue":"9","noUsgsAuthors":false,"publicationDate":"2025-08-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Glasgow, Margaret Elizabeth 0000-0001-5637-5918","orcid":"https://orcid.org/0000-0001-5637-5918","contributorId":340268,"corporation":false,"usgs":true,"family":"Glasgow","given":"Margaret","email":"","middleInitial":"Elizabeth","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rubinstein, Justin 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":215341,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hardebeck, Jeanne L. 0000-0002-6737-7780","orcid":"https://orcid.org/0000-0002-6737-7780","contributorId":254964,"corporation":false,"usgs":true,"family":"Hardebeck","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":951603,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70270765,"text":"sir20255077 - 2025 - Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming","interactions":[],"lastModifiedDate":"2026-02-03T15:17:46.175988","indexId":"sir20255077","displayToPublicDate":"2025-08-29T11:03:01","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-5077","displayTitle":"Fluvial Sediment Dynamics in the Shoshone River and Tributaries Around Willwood Dam, Park County, Wyoming","title":"Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming","docAbstract":"Sedimentation affects many of the aging reservoirs in the United States. Dams and water diversions from rivers have been central elements of infrastructure supporting agricultural irrigation in the arid and semiarid regions of the Western United States for more than a century. The Willwood Irrigation District diversion dam (hereafter referred to as “Willwood Dam”) in Park County, Wyoming, is approximately 12 miles northeast of Cody, Wyo.; has a structural height of 70 feet; and impounds the Shoshone River for diversion into the Willwood Canal. Willwood Dam is part of a larger irrigation scheme supported by water storage in the much larger Buffalo Bill Dam, which is approximately 20 miles upstream. In October 2016, renovation construction activities at Willwood Dam and the Willwood Canal caused an unplanned evacuation of nearly 96,000 cubic yards of fine sediment.
The fine sediment release in 2016 raised concerns that ongoing sediment management at Willwood Dam could impose limits on the long-term health of the aquatic ecosystem and fish populations. The U.S. Geological Survey, in cooperation with Wyoming Department of Environmental Quality and Willwood Work Groups 2 and 3, initiated an investigation of the dynamics of sediment transport in the Shoshone River and selected tributaries between Buffalo Bill Dam and Willwood Dam. The goal of the study was to quantify sediment transport into and out of Willwood Dam on an annual, seasonal, and event basis to better understand the relative quantities of sediment coming from natural sources and human activities on the landscape. The study ran from March 2019 through October 2021 and used observations of streamflow, turbidity, and acoustic backscatter collected at streamgages upstream and downstream from Willwood Dam to quantify suspended-sediment loads into and out of the dam during irrigation and fallow seasons, precipitation-runoff events, and deliberate sediment releases. Each tributary’s relative contribution to the sediment load upstream from Willwood Dam was examined using discrete measurements of suspended-sediment concentration and bedload during irrigation and fallow seasons, precipitation events, and stable conditions.
Analysis of daily precipitation and temperature data indicated that conditions in the study area during the 2019 agricultural year were wetter and colder than period of record normal, and drier and near normal temperatures for the 2020 and 2021 agricultural years. Not all sediment load records between 2019 and 2021 are complete because of rejected observations (outliers), instrument failures or fouling, and instrument removal for calibrations.
Statistical modeling of suspended-sediment concentration using paired values of turbidity and acoustic backscatter produced four models that, after refinement, had coefficients of determination indicating that more than 84 percent of the variance was explained by either turbidity or acoustic backscatter. A system of rules was developed to select the model predictions based on the seasonal operations of Willwood Dam, assumptions about the grain sizes mobilized during these operations, and assumed accuracy of the models at the downstream streamgage (Shoshone River below Willwood Dam, near Ralston, Wyo. [streamgage 06284010]) under different operational conditions. The sediment budget between upstream and downstream estimates of loads was interpreted using the mean predicted values bound by their respective model prediction intervals. When mean predicted loads of one streamgage were contained in the prediction intervals of the other streamgage, and vice-versa, difference in the sediment budget were interpreted as “indeterminate.”
Modeled sediment load balances demonstrated the depositional and erosional behaviors expected from the conceptual model of dam operations whereby sediment tends to accumulate during irrigation seasons when the dam is spilling over the top, and sediment tends to evacuate during the fallow seasons when it is flowing through the sluice gates at the base of the dam. The sediment load calculations using the rules-based model criteria indicated that between 14,200 and 380,000 tons of suspended sediment moved through the Shoshone River around Willwood Dam during the irrigation seasons of 2019, 2020, and 2021; 380,000 tons of suspended sediment were transported during the cool, wet year of 2019, and 14,200 tons of suspended sediment were transported in 2020, which was relatively dry. During fallow seasons 2019, 2020, and 2021, which had fewer complete records, between 1,140 and 106,000 tons of suspended sediment was estimated to have moved through the river.
For all seasons except fallow season 2022, the models estimated that more sediment was released from the dam than entered the dam, but the modeled mean loads at each streamgage were nearly always within the prediction intervals of each other, making the sediment balance indeterminant. Examination of suspended-sediment loads during irrigation seasons indicated that between 65 and 85 percent of fine sediment was transported during annual high flows and storm events, with the remainder transported during steady, lower streamflows. Examination of suspended loads during fallow seasons indicated that deliberate sediment releases through Willwood Dam accounted for between 39 and 67 percent of the total sediment moved during the fallow seasons. Deliberate sediment releases from Willwood Dam had estimated net exports of between 1,360 and 22,400 tons.
Between August 2017 and July 2023, suspended-sediment concentration and bedload sediment samples were collected from 9 tributaries to the Shoshone River during 137 sampling events, including stable and precipitation-runoff conditions. During irrigation season precipitation events, the mean total sediment yields ranged from 0.33 to 9.51 tons per day per square mile; during fallow season precipitation events, the mean total yields ranged from 0.04 to 0.95 ton per day per square mile. The mean total sediment yield per unit area across all samples at each tributary site ranged from 0.26 to 3.08 tons per day per square mile. Bedload was a minor fraction of the total load, constituting a mean of 4 percent across all samples; 3 and 6 percent for events and nonevents, respectively, during irrigation season; and 3 and 1 percent for events and nonevents, respectively, during the fallow season. With the exception of one tributary, Dry Creek, these mean yield values were within the range of watershed-scale background sediment yield values estimated from reservoir surveys and previous suspended-sediment studies.
Imagery from irrigation seasons 2012, 2015, 2017, 2019, and 2022 was used to determine the planimetric backwater extent of the pool area in the Shoshone River behind Willwood Dam to identify any changes in sediment storage. Active river channel widths in the Shoshone River upstream from Willwood Dam were all similar between years except 2015, which was determined to be statistically different from all other years. Bathymetric data taken in the pool behind Willwood Dam during three different surveys between November 2017 and April 2022 indicated no statistically significant differences in bed elevations between the years. Results from the planimetric and bathymetric survey data provide multiple lines of evidence indicating that sediment did not accumulate behind the dam within the error of the methods used.
Examination of how precipitation affects sediment transport in the Shoshone River upstream from Willwood Dam indicated that accumulated rainfall from the natural runoff events captured during the study period varied from a trace to as much as 4.26 inches, with associated predicted suspended-sediment loads varying from 112 to 232,000 tons of suspended sediment. The behavior of the sediment loads relative to accumulated precipitation did not appear to change depending on irrigation or fallow season. A model of suspended-sediment concentrations relative to the 2-day accumulated precipitation indicated that suspended-sediment concentrations in the Shoshone River upstream from Willwood Dam increased exponentially for accumulations of 0.3 inch or more; such storms accounted for 10 percent or less of precipitation events observed during the 1981 to 2018 period of record.
The gaps in records, precision of the instrumentation, and large variation in grain sizes in suspended-sediment mixtures downstream from the dam made closing the sediment budgets for most seasons unattainable. The biggest recent change in sediment storage measured using the planimetric area of deposits behind Willwood Dam took place between 2015 and 2017. The main event between these two measurements was the installation of new Willwood Canal gates in October 2016, which resulted in the large unplanned sediment release. Because the sediment budgets were nearly always indeterminate and the planimetric and bathymetric data indicated little change in the bed and bank material, it is likely that the change in sediment storage behind the dam during the study period was small relative to the precision of the statistical models and other uncertainties.
This body of evidence suggests that, averaged during the 3-year study period, no major changes in storage took place, and that the current operations may be keeping storage at near-equilibrium. This condition could have been initiated because the middle sluice gate has now been operational since 2014, and the sediment release in October 2016 evacuated a large amount of legacy sediment from storage. Although the uncertainties are large, sluicing events allow for controlled releases of sediment that contributed to the near equilibrium conditions observed over an annual basis during this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20255077","collaboration":"Prepared in cooperation with the Wyoming Department of Environmental Quality","usgsCitation":"Alexander, J.S., Brown, H., Eddy-Miller, C.A., Burckhardt, J., Burckhardt, L., Ellison, C., McIntyre, C., Moger, T., Patterson, L., Tavelli, C., Waterstreet, D., and Williams, M., 2025, Fluvial sediment dynamics in the Shoshone River and tributaries around Willwood Dam, Park County, Wyoming: U.S. Geological Survey Scientific Investigations Report 2025–5077, 70 p., https://doi.org/10.3133/sir20255077.","productDescription":"Report: x, 70 p.; Data Release; Dataset","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-164415","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":494651,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20255077/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2025-5077"},{"id":494674,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":494673,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13VHDRG","text":"USGS data release","linkHelpText":"Shapefiles of digitized backwater extent behind Willwood Dam on the Shoshone River, near Cody, Wyoming, derived from 2012, 2015, 2017, 2019, and 2022 National Agriculture Imagery Program imagery"},{"id":494652,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2025/5077/images"},{"id":494654,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2025/5077/sir20255077.XML","linkFileType":{"id":8,"text":"xml"}},{"id":494650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2025/5077/sir20255077.pdf","text":"Report","size":"9.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2025-5077"},{"id":494649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2025/5077/coverthb.jpg"}],"country":"United States","state":"Wyoming","county":"Park County","otherGeospatial":"Shoshone River and tributaries around Willwood Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.66170194279013,\n 44.80967182289373\n ],\n [\n -109.31267227648169,\n 44.80967182289373\n ],\n [\n -109.31267227648169,\n 44.39309612019585\n ],\n [\n -108.66170194279013,\n 44.39309612019585\n ],\n [\n -108.66170194279013,\n 44.80967182289373\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
The world in which birds evolved to migrate has been drastically altered in the Anthropocene by artificial light. Sources of light such as urban centers or bright upward-facing lights attract migrants, altering their behavior, especially during inclement weather, often leading to mortality. Seemingly less extreme sources, such as pole-mounted floodlighting, ubiquitous throughout much of the world, have received comparatively less study, and migrant responses to such sources are poorly understood. We studied migrant behavior in relation to light at White Sands Missile Range (New Mexico, USA) by recording nocturnal flight calls at sites with and without lights during non-inclement weather. We collected 103,424 h of recordings and detected 2,851,863 calls over three fall migration seasons. We assessed how temporal, weather, and lighting variables explain variability in call rates between light and dark sites, and examined how different taxonomic groups behave in relation to light. Contrary to predictions, call rates were higher at dark sites than at light sites, and this difference was strongest early in the migration season. We found illuminated sites with a greater proportion of shielded lights, or with lights of higher dominant wavelengths (warmer color temperatures), had higher call rates (closely resembling dark sites) than other light sites, indicating that these factors may reduce impact to migrants. Our taxonomic analyses revealed consistent differences in call rate between light and dark sites for warblers, but no difference for most sparrows. Our findings indicate that lights alter behavior, but the use of “bird-friendly” lighting strategies may reduce this impact.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2025.111441","usgsCitation":"Osterhaus, D.M., Boland, K.C., Lawson, A.J., Horton, K.G., Van Doren, B.M., Cutler, P.L., Wright, T.F., Desmond, M.J., 2025, Nocturnal flight call monitoring reveals in-flight behavioral alteration by avian migrants in response to artificial light at night: Biological Conservation, v. 311, 111441, 12 p., https://doi.org/10.1016/j.biocon.2025.111441.","productDescription":"111441, 12 p.","ipdsId":"IP-176948","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":500585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.biocon.2025.111441","text":"Publisher Index Page"},{"id":500418,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Chihuahuan Desert, Tularosa Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.55080543536515,\n 33.44865539823519\n ],\n [\n -106.55080543536515,\n 32.58929786516667\n ],\n [\n -106.0131364575159,\n 32.58929786516667\n ],\n [\n -106.0131364575159,\n 33.44865539823519\n ],\n [\n -106.55080543536515,\n 33.44865539823519\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"311","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Osterhaus, Dylan M.","contributorId":366575,"corporation":false,"usgs":false,"family":"Osterhaus","given":"Dylan","middleInitial":"M.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":956060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boland, Kelley C.","contributorId":366576,"corporation":false,"usgs":false,"family":"Boland","given":"Kelley","middleInitial":"C.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":956061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawson, Abigail Jean 0000-0002-2799-8750","orcid":"https://orcid.org/0000-0002-2799-8750","contributorId":276319,"corporation":false,"usgs":true,"family":"Lawson","given":"Abigail","email":"","middleInitial":"Jean","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":956062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horton, Kyle G.","contributorId":366577,"corporation":false,"usgs":false,"family":"Horton","given":"Kyle","middleInitial":"G.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":956063,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Doren, Benjamin M.","contributorId":366578,"corporation":false,"usgs":false,"family":"Van Doren","given":"Benjamin","middleInitial":"M.","affiliations":[{"id":38021,"text":"University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":956064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cutler, Patricia L.","contributorId":366579,"corporation":false,"usgs":false,"family":"Cutler","given":"Patricia","middleInitial":"L.","affiliations":[{"id":87496,"text":"U.S. Army Garrison, White Sands Missile Range","active":true,"usgs":false}],"preferred":false,"id":956065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wright, Timothy F.","contributorId":366580,"corporation":false,"usgs":false,"family":"Wright","given":"Timothy","middleInitial":"F.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":956066,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Desmond, Martha J.","contributorId":366581,"corporation":false,"usgs":false,"family":"Desmond","given":"Martha","middleInitial":"J.","affiliations":[{"id":12628,"text":"New Mexico State University","active":true,"usgs":false}],"preferred":false,"id":956067,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271694,"text":"70271694 - 2025 - Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin","interactions":[],"lastModifiedDate":"2025-09-19T14:08:41.362545","indexId":"70271694","displayToPublicDate":"2025-08-29T09:04:03","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin","docAbstract":"Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally efficient method that enables the projection of daily stream water quality under varying hydrologic conditions using commonly available discrete monitoring data. WRTDS-P model performance was validated using 39 sites in the Delaware River Basin (DRB) and four key constituents: specific conductance (SC), nitrate (NO3−), magnesium (Mg2+) and calcium (Ca2+). Projections were tested against holdout data from the final 1 to 5 years of each time series, demonstrating robust predictive capability, with median Nash-Sutcliffe efficiencies of 0.67 for SC, 0.56 for NO3−, 0.65 for Ca2+, and 0.79 for Mg2+. Model uncertainty was correlated with indicators of hydrologic or geochemical mass-sinks, such as groundwater storage and adsorption in wetland soils. Drought scenario analyses for SC used ranges of reduced discharge including flows from the 1965 drought of record. Scenarios predicted widespread increases of SC, especially in southern DRB streams where baseline SC levels are already elevated. Fractional increases of SC were more uniformly distributed, indicating potential risk to sensitive ecosystems. Notably, drought-induced SC increases were positively correlated with interannual SC trends, indicating that hydrologic extremes could exacerbate ongoing salinization. This work provides a transferable and interpretable framework for projecting future water quality and assessing hydrologic risk to water resources and aquatic ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2025.180286","usgsCitation":"Green, C., Hirsch, R.M., Essaid, H., and Sanford, W.E., 2025, Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin: Science of the Total Environment, v. 999, 180286, 14 p., https://doi.org/10.1016/j.scitotenv.2025.180286.","productDescription":"180286, 14 p.","ipdsId":"IP-159069","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":496136,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.180286","text":"Publisher Index Page"},{"id":495782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.79788517502844,\n 39.713218235332164\n ],\n [\n -75.44918608740714,\n 38.663983307614814\n ],\n [\n -74.82016028228699,\n 38.99952921670035\n ],\n [\n -74.61504317192174,\n 39.81307746348011\n ],\n [\n -74.15695069541222,\n 41.998596289750736\n ],\n [\n -74.9227212407762,\n 42.30779251171998\n ],\n [\n -75.65430560107949,\n 41.9782683665571\n ],\n [\n -76.07821429583441,\n 41.159834427011475\n ],\n [\n -76.03035363674925,\n 40.632678412780365\n ],\n [\n -75.79788517502844,\n 39.713218235332164\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"999","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Green, Christopher 0000-0002-6480-8194","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":201642,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":949040,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":949041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Essaid, Hedeff 0000-0003-0154-8628","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":361587,"corporation":false,"usgs":false,"family":"Essaid","given":"Hedeff","affiliations":[{"id":37814,"text":"Former USGS","active":true,"usgs":false}],"preferred":false,"id":949042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":337084,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":949043,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70274281,"text":"70274281 - 2025 - Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees","interactions":[{"subject":{"id":70274281,"text":"70274281 - 2025 - Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees","indexId":"70274281","publicationYear":"2025","noYear":false,"title":"Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees"},"predicate":"SUPERSEDED_BY","object":{"id":70272087,"text":"70272087 - 2025 - Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees","indexId":"70272087","publicationYear":"2025","noYear":false,"title":"Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees"},"id":1}],"supersededBy":{"id":70272087,"text":"70272087 - 2025 - Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees","indexId":"70272087","publicationYear":"2025","noYear":false,"title":"Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees"},"lastModifiedDate":"2026-03-24T13:28:19.016054","indexId":"70274281","displayToPublicDate":"2025-08-29T08:25:12","publicationYear":"2025","noYear":false,"publicationType":{"id":27,"text":"Preprint"},"publicationSubtype":{"id":32,"text":"Preprint"},"seriesTitle":{"id":19846,"text":"BioRxiv","active":true,"publicationSubtype":{"id":32}},"title":"Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees","docAbstract":"Terrestrial environmental DNA (eDNA) techniques have been proposed as a means of sensitive, non-lethal pollinator monitoring. To date, however, no studies have provided evidence that eDNA methods can achieve detection densities on par with traditional pollinator surveys. Using a large-scale dataset of eDNA and corresponding net surveys, we show that eDNA methods enable sensitive, species-level characterization of whole bumble bee communities, including rare and critically endangered species such as the rusty pathed bumble bee (RPBB; Bombus affinis). All species present in netting surveys were detected within eDNA surveys, apart from two rare species in the socially parasitic subgenus Psithyrus (cuckoo bumble bees). Further, for rare non-parasitic species, eDNA methods exhibited similar sensitivity relative to traditional netting. Relative to flower eDNA samples, sequenced field negative controls resulted in significantly lower rates of Bombus detection, and these detections were likely attributable to high rates of background eDNA on environmental surfaces. Lastly, we found that eDNA-based frequency of detection across replicate surveys was strongly associated with net-based measures of abundance across site visits. We conclude that the method is cost-effective and highly scalable for semi-quantitative characterization of at-risk bumble bee communities, providing a new approach for improving our understanding of species habitat associations.
","language":"English","publisher":"BioRxiv","doi":"10.1101/2025.05.13.649340","usgsCitation":"Richardson, R.T., Avalos, G., Garland, C.J., Trott, R., Hager, O., Hepner, M.J., Raines, C.D., and Goodell, K., 2025, Sensitive environmental DNA methods for low-risk surveillance of at-risk bumble bees: BioRxiv, https://doi.org/10.1101/2025.05.13.649340.","productDescription":"20 p.","ipdsId":"IP-179467","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501666,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1101/2025.05.13.649340","text":"External Repository"},{"id":501438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Richardson, Rodney T.","contributorId":332908,"corporation":false,"usgs":false,"family":"Richardson","given":"Rodney","middleInitial":"T.","affiliations":[{"id":38802,"text":"University of Maryland Center for Environmental Studies","active":true,"usgs":false}],"preferred":false,"id":957564,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Avalos, Grace","contributorId":332902,"corporation":false,"usgs":false,"family":"Avalos","given":"Grace","email":"","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":957565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garland, Cameron J.","contributorId":360431,"corporation":false,"usgs":false,"family":"Garland","given":"Cameron","middleInitial":"J.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":957566,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Trott, Regina","contributorId":332903,"corporation":false,"usgs":false,"family":"Trott","given":"Regina","email":"","affiliations":[{"id":37215,"text":"University of Maryland Center for Environmental Science","active":true,"usgs":false}],"preferred":false,"id":957567,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hager, Olivia","contributorId":360433,"corporation":false,"usgs":false,"family":"Hager","given":"Olivia","affiliations":[{"id":86002,"text":"University of Maryland Center for Environmental Science; MD Western EcoSystems Technology, Inc","active":true,"usgs":false}],"preferred":false,"id":957568,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hepner, Mark J.","contributorId":335438,"corporation":false,"usgs":false,"family":"Hepner","given":"Mark","middleInitial":"J.","affiliations":[{"id":80404,"text":"Metamophecology","active":true,"usgs":false}],"preferred":false,"id":957569,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":957570,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goodell, Karen","contributorId":332906,"corporation":false,"usgs":false,"family":"Goodell","given":"Karen","email":"","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":957571,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70271173,"text":"70271173 - 2025 - National Park Service staff perspectives on how climate change affects visitor use","interactions":[],"lastModifiedDate":"2025-11-20T16:59:00.614048","indexId":"70271173","displayToPublicDate":"2025-08-29T08:24:53","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5936,"text":"People and Nature","active":true,"publicationSubtype":{"id":10}},"title":"National Park Service staff perspectives on how climate change affects visitor use","docAbstract":"1. Many public lands, including those managed by the U.S. National Park Service(NPS), have the purpose of conserving natural and cultural resources and providing opportunities for visitors to recreate in and enjoy these areas. Achieving this mission becomes more challenging as drought, flooding, increasing temperatures and other climatic change effects are impacting NPS lands and visitors and affecting factors such as visitation, recreation access and health and safety among other aspects of park operations.
2. However, the literature lacks insights from staff dealing with on-the-ground climate impacts to visitor use. To address this gap, we held semi-structured interviews with 63 staff from 31 NPS units across the United States (U.S.) to better understand the effects of climate change on visitor use. We qualitatively analysed the interviews using both deductive and inductive methods to identify key themes.
3. Interview participants consistently noted that climate change is already affecting visitor use at their parks. For instance, increasing temperatures are negatively affecting both staff and visitor safety at parks nationwide, whereas all coastal parks within our sample are already experiencing impacts from sea-level rise or more frequent and severe coastal storms and hurricanes. Other impacts include reduced recreational access, damaged infrastructure and cultural resources and diminished visitor experiences due to fire and smoke.
4. Similarly, concerns about future impacts often revolved around the health and safety of visitors and staff—particularly related to wildfire and smoke, water quality and availability, and increased heat—and climate change forever altering parks.
5. Our research shows staff in parks and protected areas are noticing effects of climate change on visitor use; some of these impacts have not been previously documented in the scientific literature. Study results highlight future visitor use management research needs and key topics to consider for visitor use planning processes.
","language":"English","publisher":"Wiley","doi":"10.1002/pan3.70107","usgsCitation":"Rappaport Keener, S., Wilkins, E.J., Carr, W., Winder, S.G., Reas, J., Daniele, D.B., and Wood, S.A., 2025, National Park Service staff perspectives on how climate change affects visitor use: People and Nature, v. 7, no. 10, p. 2346-2360, https://doi.org/10.1002/pan3.70107.","productDescription":"15 p.","startPage":"2346","endPage":"2360","ipdsId":"IP-178271","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":495179,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/pan3.70107","text":"Publisher Index Page"},{"id":495122,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -130.67138671875,\n 54.686534234529695\n ],\n [\n -129.9462890625,\n 55.36662484928637\n ],\n [\n -130.1220703125,\n 56.145549500679074\n ],\n [\n -131.9677734375,\n 56.9449741808516\n ],\n [\n -135.3076171875,\n 59.833775202184206\n ],\n [\n -136.38427734375,\n 59.65664225341022\n ],\n [\n -136.6259765625,\n 59.23217626921806\n ],\n [\n -137.52685546875,\n 58.938673187948304\n ],\n [\n -137.65869140625,\n 59.33318942659219\n ],\n [\n -138.8232421875,\n 60.009970961180386\n ],\n [\n -139.21874999999997,\n 60.108670463036\n ],\n [\n -139.04296875,\n 60.403001945865476\n ],\n [\n -139.85595703125,\n 60.337823495982015\n ],\n [\n -140.99853515625,\n 60.337823495982015\n ],\n [\n -141.15234374999997,\n 69.71810669906763\n ],\n [\n -143.4375,\n 70.17020068549206\n ],\n [\n -145.1953125,\n 70.08056215839737\n ],\n [\n -149.765625,\n 70.58341752317065\n ],\n [\n -152.40234375,\n 70.61261423801925\n ],\n [\n -152.314453125,\n 70.95969716686398\n ],\n [\n -157.1484375,\n 71.35706654962706\n ],\n [\n -159.9609375,\n 70.8734913192635\n ],\n [\n -162.0703125,\n 70.31873847853124\n ],\n [\n -163.916015625,\n 69.06856318696033\n ],\n [\n -166.376953125,\n 68.942606818121\n ],\n [\n -166.376953125,\n 68.26938680456564\n ],\n [\n -163.30078125,\n 66.86108230224609\n ],\n [\n -161.982421875,\n 66.47820814385636\n ],\n [\n -163.564453125,\n 66.08936427047088\n ],\n [\n -163.564453125,\n 66.6181218846659\n ],\n [\n -165.76171875,\n 66.40795547978848\n ],\n [\n -168.0908203125,\n 65.69447579373418\n ],\n [\n -166.55273437499997,\n 65.14611484756372\n ],\n [\n -166.904296875,\n 65.05360170595502\n ],\n [\n -166.3330078125,\n 64.41592147626879\n ],\n [\n -162.861328125,\n 64.39693778132846\n ],\n [\n -160.927734375,\n 64.90491004905083\n ],\n [\n -161.0595703125,\n 64.47279382008166\n ],\n [\n -161.4990234375,\n 64.49172504435471\n ],\n [\n -160.8837890625,\n 63.87939001720202\n ],\n [\n -161.1474609375,\n 63.470144746565424\n ],\n [\n -162.6416015625,\n 63.64625919492172\n ],\n [\n -163.212890625,\n 63.05495931065107\n ],\n [\n -164.2236328125,\n 63.37183226679281\n ],\n [\n -166.1572265625,\n 61.75233128411639\n ],\n [\n -165.3662109375,\n 60.54377524118842\n ],\n [\n -167.431640625,\n 60.326947742998414\n ],\n [\n -167.255859375,\n 59.866883195210214\n ],\n [\n -165.8935546875,\n 59.7563950493563\n ],\n [\n -162.68554687499997,\n 59.734253447591364\n ],\n [\n -162.3779296875,\n 60.174306261926034\n ],\n [\n -161.806640625,\n 59.46740794183739\n ],\n [\n -162.0263671875,\n 59.108308258604964\n ],\n [\n -161.806640625,\n 58.768200159239576\n ],\n [\n -162.20214843749997,\n 58.65408464530598\n ],\n [\n -160.83984375,\n 58.44773280389084\n ],\n [\n -159.9609375,\n 58.6769376725869\n ],\n [\n -159.08203125,\n 58.309488840677645\n ],\n [\n -156.88476562499997,\n 58.92733441827545\n ],\n [\n -157.5,\n 58.516651799363785\n ],\n [\n -157.8076171875,\n 57.61010702068388\n ],\n [\n -161.54296875,\n 56.022948079627454\n ],\n [\n -168.6181640625,\n 53.4357192066942\n ],\n [\n -174.9462890625,\n 52.26815737376817\n ],\n [\n -178.2421875,\n 51.83577752045248\n ],\n [\n -173.1884765625,\n 51.590722643120145\n ],\n [\n -162.5537109375,\n 54.23955053156177\n ],\n [\n -155.302734375,\n 55.52863052257191\n ],\n [\n -151.4794921875,\n 57.51582286553883\n ],\n [\n -146.9970703125,\n 60.08676274626006\n ],\n [\n -145.546875,\n 60.21799073323445\n ],\n [\n -144.228515625,\n 59.689926220143356\n ],\n [\n -142.3828125,\n 59.93300042374631\n ],\n [\n -138.3837890625,\n 58.83649009392136\n ],\n [\n -135.6591796875,\n 56.31653672211301\n ],\n [\n -133.2421875,\n 54.521081495443596\n ],\n [\n -130.67138671875,\n 54.686534234529695\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.796875,\n 44.902577996288876\n ],\n [\n -67.67578124999999,\n 45.583289756006316\n ],\n [\n -67.939453125,\n 47.57652571374621\n ],\n [\n -69.2578125,\n 47.338822694822\n ],\n [\n -71.19140625,\n 45.27488643704891\n ],\n [\n -75.146484375,\n 44.96479793033101\n ],\n [\n -78.046875,\n 43.644025847699496\n ],\n [\n -79.1015625,\n 43.51668853502906\n ],\n [\n -79.1015625,\n 42.87596410238256\n ],\n [\n -82.68310546875,\n 41.65649719441145\n ],\n [\n -83.14453125,\n 42.049292638686836\n ],\n [\n -83.07861328125,\n 42.374778361114195\n ],\n [\n -82.529296875,\n 42.601619944327965\n ],\n [\n -82.24365234375,\n 43.6599240747891\n ],\n [\n -82.41943359375,\n 45.058001435398275\n ],\n [\n -83.60595703125,\n 45.85941212790755\n ],\n [\n -83.49609375,\n 46.027481852486645\n ],\n [\n -83.7158203125,\n 46.164614496897094\n ],\n [\n -83.95751953125,\n 46.07323062540835\n ],\n [\n -84.24316406249999,\n 46.558860303117164\n ],\n [\n -84.72656249999999,\n 46.558860303117164\n ],\n [\n -84.90234375,\n 46.92025531537451\n ],\n [\n -88.41796875,\n 48.3416461723746\n ],\n [\n -89.3408203125,\n 47.96050238891509\n ],\n [\n -90.76904296874999,\n 48.122101028190805\n ],\n [\n -90.87890625,\n 48.22467264956519\n ],\n [\n -91.51611328125,\n 48.10743118848039\n ],\n [\n -92.2412109375,\n 48.37084770238366\n ],\n [\n -92.39501953125,\n 48.23930899024907\n ],\n [\n -92.94433593749999,\n 48.61838518688487\n ],\n [\n -93.44970703125,\n 48.63290858589535\n ],\n [\n -94.7021484375,\n 48.748945343432936\n ],\n [\n -94.833984375,\n 49.23912083246698\n ],\n [\n -95.1416015625,\n 49.396675075193976\n ],\n [\n -95.20751953125,\n 49.009050809382046\n ],\n [\n -123.22265625000001,\n 48.99463598353405\n ],\n [\n -123.0908203125,\n 48.80686346108517\n ],\n [\n -123.24462890625,\n 48.66194284607006\n ],\n [\n -123.1787109375,\n 48.32703913063476\n ],\n [\n -124.78271484375,\n 48.472921272487824\n ],\n [\n -124.93652343749999,\n 48.16608541901253\n ],\n [\n -124.365234375,\n 46.58906908309182\n ],\n [\n -124.541015625,\n 44.15068115978094\n ],\n [\n -124.93652343749999,\n 42.69858589169842\n ],\n [\n -124.541015625,\n 41.22824901518529\n ],\n [\n -124.73876953125,\n 40.43022363450862\n ],\n [\n -124.03564453125,\n 39.35129035526705\n ],\n [\n -124.01367187499999,\n 38.8225909761771\n ],\n [\n -122.05810546875,\n 36.12012758978146\n ],\n [\n -120.95947265624999,\n 34.88593094075317\n ],\n [\n -120.80566406250001,\n 34.08906131584994\n ],\n [\n -118.21289062499999,\n 32.2313896627376\n ],\n [\n -117.22412109375,\n 32.54681317351514\n ],\n [\n -114.78515624999999,\n 32.713355353177555\n ],\n [\n -114.78515624999999,\n 32.491230287947594\n ],\n [\n -110.98388671874999,\n 31.3348710339506\n ],\n [\n -108.21533203125,\n 31.297327991404266\n ],\n [\n -108.2373046875,\n 31.765537409484374\n ],\n [\n -106.435546875,\n 31.765537409484374\n ],\n [\n -104.9853515625,\n 30.600093873550072\n ],\n [\n -104.47998046875,\n 29.592565403314087\n ],\n [\n -103.20556640625,\n 28.94086176940557\n ],\n [\n -102.65625,\n 29.76437737516313\n ],\n [\n -102.3486328125,\n 29.84064389983441\n ],\n [\n -101.49169921875,\n 29.7453016622136\n ],\n [\n -100.83251953125,\n 29.267232865200878\n ],\n [\n -100.30517578125,\n 28.246327971048842\n ],\n [\n -99.60205078124999,\n 27.586197857692664\n ],\n [\n -99.47021484375,\n 27.31321389856826\n ],\n [\n -99.228515625,\n 26.52956523826758\n ],\n [\n -98.2177734375,\n 26.05678288577881\n ],\n [\n -97.75634765625,\n 26.03704188651584\n ],\n [\n -97.44873046875,\n 25.839449402063185\n ],\n [\n -97.20703125,\n 25.93828707492375\n ],\n [\n -96.8994140625,\n 26.194876675795218\n ],\n [\n -96.78955078125,\n 27.858503954841247\n ],\n [\n -93.75732421875,\n 29.420460341013133\n ],\n [\n -90.2197265625,\n 28.998531814051795\n ],\n [\n -88.22021484375,\n 29.05616970274342\n ],\n [\n -87.91259765625,\n 30.14512718337613\n ],\n [\n -86.5283203125,\n 30.183121842195515\n ],\n [\n -85.2978515625,\n 29.49698759653577\n ],\n [\n -84.13330078125,\n 29.80251790576445\n ],\n [\n -82.81494140625,\n 28.555576049185973\n ],\n [\n -83.21044921875,\n 27.800209937418252\n ],\n [\n -82.77099609375,\n 26.941659545381516\n ],\n [\n -82.08984375,\n 25.878994400196202\n ],\n [\n -81.5625,\n 25.264568475331583\n ],\n [\n -82.28759765625,\n 24.467150664739002\n ],\n [\n -82.0458984375,\n 24.046463999666567\n ],\n [\n -80.6396484375,\n 24.56710835257599\n ],\n [\n -79.78271484375,\n 25.34402602913433\n ],\n [\n -79.60693359375,\n 27.27416111737468\n ],\n [\n -80.68359375,\n 30.713503990354965\n ],\n [\n -80.66162109375,\n 31.50362930577303\n ],\n [\n -76.81640625,\n 34.07086232376631\n ],\n [\n -75.16845703124999,\n 35.263561862152095\n ],\n [\n -75.498046875,\n 37.055177106660814\n ],\n [\n -73.58642578125,\n 39.90973623453719\n ],\n [\n -71.3671875,\n 40.84706035607122\n ],\n [\n -69.63134765625,\n 40.9964840143779\n ],\n [\n -70.0048828125,\n 42.342305278572816\n ],\n [\n -70.3564453125,\n 42.89206418807337\n ],\n [\n -67.2802734375,\n 44.37098696297173\n ],\n [\n -67.0166015625,\n 44.69989765840318\n ],\n [\n -66.796875,\n 44.902577996288876\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.56640625,\n 18.771115062337024\n ],\n [\n -154.68749999999997,\n 19.642587534013032\n ],\n [\n -156.9287109375,\n 21.453068633086783\n ],\n [\n -159.521484375,\n 22.43134015636061\n ],\n [\n -160.5322265625,\n 21.983801417384697\n ],\n [\n -159.9609375,\n 21.207458730482642\n ],\n [\n -158.291015625,\n 20.92039691397189\n ],\n [\n -156.97265625,\n 19.932041306115536\n ],\n [\n -155.9619140625,\n 18.8543103618898\n ],\n [\n -155.56640625,\n 18.771115062337024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Rappaport Keener, Sarah Lynn 0009-0005-5299-147X","orcid":"https://orcid.org/0009-0005-5299-147X","contributorId":348911,"corporation":false,"usgs":true,"family":"Rappaport Keener","given":"Sarah Lynn","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":947642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilkins, Emily J. 0000-0003-3055-4808","orcid":"https://orcid.org/0000-0003-3055-4808","contributorId":328409,"corporation":false,"usgs":true,"family":"Wilkins","given":"Emily","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":947643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Wylie","contributorId":273040,"corporation":false,"usgs":false,"family":"Carr","given":"Wylie","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":947644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winder, Samantha G.","contributorId":360777,"corporation":false,"usgs":false,"family":"Winder","given":"Samantha","middleInitial":"G.","affiliations":[{"id":86104,"text":"University of Washington Outdoor Recreation and Data Lab","active":true,"usgs":false}],"preferred":false,"id":947645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reas, Julianne","contributorId":348912,"corporation":false,"usgs":false,"family":"Reas","given":"Julianne","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":947646,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Daniele, Daniela B.","contributorId":360778,"corporation":false,"usgs":false,"family":"Daniele","given":"Daniela","middleInitial":"B.","affiliations":[{"id":52985,"text":"National Park Service Climate Change Response Program","active":true,"usgs":false}],"preferred":false,"id":947647,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wood, Spencer A.","contributorId":360779,"corporation":false,"usgs":false,"family":"Wood","given":"Spencer","middleInitial":"A.","affiliations":[{"id":86104,"text":"University of Washington Outdoor Recreation and Data Lab","active":true,"usgs":false}],"preferred":false,"id":947648,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70271299,"text":"70271299 - 2025 - Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA","interactions":[],"lastModifiedDate":"2025-09-03T15:29:49.125047","indexId":"70271299","displayToPublicDate":"2025-08-29T08:20:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA","docAbstract":"Rising chloride concentrations pose critical risks to freshwater stream ecosystems in temperate regions like the Delaware River Basin (DRB), USA, where winter deicer applications (i.e., road salt) are common. Increasing chloride concentrations have been documented in the region, but the extent to which chloride exceeds regulatory benchmarks remains unclear because detection of exceedances requires continuous monitoring of chloride (i.e., hourly or daily). A network of 82 non-tidal continuous specific conductance (SC) monitoring sites, spanning varied land use and geological settings, was established across the DRB to address this research need. First, a cluster analysis was conducted to group sites based on their watershed characteristics. Next, regression models for sites and clusters were developed to predict chloride using SC as a proxy. Finally, daily mean and hourly mean chloride concentration predictions were made for a three-year period (2020–2022) at the 82 study sites and analyzed to determine where and when chloride exceeded federal regulatory benchmarks. Chloride exceedance events occurred at 35% of the sites, all of which had 5% impervious cover or greater. Seasonally elevated chloride also was predicted at sites with less than 5% impervious cover. Variability in chloride patterns likely was influenced by deicer material types, winter weather patterns, geological settings, and gaps in data coverage. This study demonstrated the value of SC as a proxy for predicting chloride concentrations and showed how SC-chloride regression relationships vary across settings. More broadly, this study highlighted the value of continuous water quality monitoring to assess effects of freshwater salinization at a regional scale.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s10661-025-14485-6","usgsCitation":"Fanelli, R.M., Morency, M., Fleming, B.J., Moore, J., Hardesty, D., and Shoda, M.E., 2025, Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA: Environmental Monitoring and Assessment, no. 197, 1056, 25 p., https://doi.org/10.1007/s10661-025-14485-6.","productDescription":"1056, 25 p.","ipdsId":"IP-175501","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":495182,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-025-14485-6","text":"Publisher Index Page"},{"id":495151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.79184558063025,\n 41.902372822441464\n ],\n [\n -75.79184558063025,\n 38.41313507684677\n ],\n [\n -74.54201398019202,\n 38.41313507684677\n ],\n [\n -74.54201398019202,\n 41.902372822441464\n ],\n [\n -75.79184558063025,\n 41.902372822441464\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","issue":"197","noUsgsAuthors":false,"publicationDate":"2025-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Fanelli, Rosemary M. 0000-0002-0874-1925","orcid":"https://orcid.org/0000-0002-0874-1925","contributorId":341844,"corporation":false,"usgs":true,"family":"Fanelli","given":"Rosemary","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morency, Michelle 0009-0000-9027-7561","orcid":"https://orcid.org/0009-0000-9027-7561","contributorId":345367,"corporation":false,"usgs":false,"family":"Morency","given":"Michelle","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":947887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fleming, Brandon J. 0000-0001-9649-7485 bjflemin@usgs.gov","orcid":"https://orcid.org/0000-0001-9649-7485","contributorId":4115,"corporation":false,"usgs":true,"family":"Fleming","given":"Brandon","email":"bjflemin@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Joel","contributorId":49034,"corporation":false,"usgs":false,"family":"Moore","given":"Joel","affiliations":[],"preferred":false,"id":947889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hardesty, Deanna 0000-0002-4924-2233","orcid":"https://orcid.org/0000-0002-4924-2233","contributorId":341845,"corporation":false,"usgs":true,"family":"Hardesty","given":"Deanna","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":947890,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":947891,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70271340,"text":"70271340 - 2025 - The Benefits Knowledges Learning Framework: A tool for learning across diverse knowledge systems in ecosystem valuation","interactions":[],"lastModifiedDate":"2025-09-08T15:07:48.838449","indexId":"70271340","displayToPublicDate":"2025-08-29T08:00:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"The Benefits Knowledges Learning Framework: A tool for learning across diverse knowledge systems in ecosystem valuation","docAbstract":"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":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"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}]}} ]}