Human expansion is a major driver of both declining wildlife abundance and the contraction of species’ distributions, increasing the risk of genetic erosion and the need for genetic monitoring. Rapidly advancing technology has expanded the types of genetic data that are available for wildlife conservation. However, inferences from different genetic markers could result in different management decisions and, thus, must be considered carefully. Rebounding from near extinction in the early 1900s, the majority of North American plains bison (Bison bison bison) are managed as small and isolated herds. Microsatellite-based analyses have been used to inform management of the US Federal bison conservation herds since the early 2000s. Transitioning from monitoring with tens of multiallelic loci (e.g., microsatellite loci) to thousands of biallelic loci (e.g., single nucleotide polymorphisms [SNPs]) could increase genotyping efficiency and improve the precision of population genetic inference but would require an understanding of the inferential differences between genetic marker types. We compared microsatellite-based measures of genetic diversity, differentiation, and population structure for 20 bison conservation herds (17 Federal, 1 Tribal, 2 Canadian) to inference from SNP-based analyses for the Tribal herd and 15 of the Federal herds. Data from both genetic marker types found that all herds have remarkably high genetic diversity given the severity of the bottleneck from which these populations recovered, and that population structure was consistent with founding histories. Importantly, SNPs had greater power to describe differences in genetic diversity and groups of related herds, but only if analyses are based on 250 or more loci. Overall, we found that microsatellite and SNP data can provide comparable conservation insight, but SNPs must be carefully selected to ensure continuity in genetic monitoring and to achieve the increased precision in genetic diversity and differentiation among herds that we observed in this study.
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0000-0003-4183-3546","orcid":"https://orcid.org/0000-0003-4183-3546","contributorId":359173,"corporation":false,"usgs":false,"family":"Giglio","given":"Rachael","middleInitial":"Marie","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":945013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geremia, Chris","contributorId":167003,"corporation":false,"usgs":false,"family":"Geremia","given":"Chris","email":"","affiliations":[],"preferred":false,"id":945014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Lee C.","contributorId":149998,"corporation":false,"usgs":false,"family":"Jones","given":"Lee","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":945015,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCann, 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terrain data to model wildlife walking functions","docAbstract":"Context
The relationship between slope and terrestrial animal locomotion is key to landscape ecology but underexplored across species. This is partly due to a lack of scalable methodology that applies to a diversity of wildlife.
Objectives
This study investigates the slope-speed relationship for two species, Texas tortoise (Gopherus berlandieri) and pronghorn (Antilocapra americana), through the combined application of remote sensing, GPS tracking, behavior models, and parametric distribution. While using readily available Digital Elevation Models (DEM) for pronghorn, we explore the use of very high-resolution lidar Digital Terrain Models (DTM) from Unoccupied Aerial Systems (UAS) to characterize tortoise movements at micro-scales.
Methods
After classifying animal behavior with GPS tracking data and Hidden Markov Models (HMMs), we analyzed the relationship between the speed of the animals and the slope of the terrain using a 30-m DEM for pronghorn, and a fine-scale UAS DTM for Texas tortoise, and three nonlinear models: Laplace, Gauss, and Lorentz.
Results
High-resolution DTM, coupled with GPS tracking, accurately models the relationship of speed and slope at a micro-scale, while a DEM is suitable for a larger scale. Laplace models best predicted the speed of both the Texas tortoise and pronghorn. Models showed tortoises, which are not known for rapid and agile movement like the pronghorn, have a broader tolerance for varying slopes at a fine scale.
Conclusions
These findings enhance understanding of species-specific movement offering valuable insights for habitat management and conservation tailored to species’ behaviors and capabilities.
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A.","contributorId":354033,"corporation":false,"usgs":false,"family":"Guerra","given":"Daniel A.","affiliations":[{"id":36331,"text":"Texas Tech University","active":true,"usgs":false}],"preferred":false,"id":934986,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":934981,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266188,"text":"ofr20211030V - 2025 - System characterization report on Resourcesat-2A Advanced Wide Field Sensor","interactions":[{"subject":{"id":70266188,"text":"ofr20211030V - 2025 - System characterization report on Resourcesat-2A Advanced Wide Field Sensor","indexId":"ofr20211030V","publicationYear":"2025","noYear":false,"chapter":"V","displayTitle":"System Characterization Report on Resourcesat-2A Advanced Wide Field Sensor","title":"System characterization report on Resourcesat-2A Advanced Wide Field Sensor"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation 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These reports describe the methodology and procedures used for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Resourcesat-2A was launched in 2016 on the Polar Satellite Launch Vehicle-C36; it is identical to Resourcesat-2, and together, they decrease imaging revisit time from 5 days to 2–3 days, providing data continuity and improved temporal resolution. Resourcesat-2 and -2A carry the AWiFS, Linear Imaging Self Scanning-3, and Linear Imaging Self Scanning-4 medium-resolution imaging sensors, continuing the legacy of the Indian Space Research Organisation’s Indian Remote Sensing-1C/1D/P3 satellite programs. More information about Indian Space Research Organisation satellites and sensors is available through the Joint Agency Commercial Imagery Evaluation Earth Observing Satellites Online Compendium and from the Indian Space Research Organisation at https://www.isro.gov.in/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team assessed the geometric, radiometric, and spatial performance of the Resourcesat-2A AWiFS sensor. Geometric performance is divided into the interior geometric performance of band-to-band registration and the exterior geometric performance of geolocation accuracy. The interior geometric performance had offsets in the range of −1.10 meters (m; −0.020 pixel) to 3.67 m (0.066 pixel) in easting and −5.68 m (−0.101 pixel) to 10.38 m (0.185 pixel) in northing with root mean square error values from 5.60 m (0.100 pixel) to 11.31 m (0.202 pixel) in easting and from 3.00 m (0.054 pixel) to 13.52 m (0.241 pixel) in northing.
The exterior geometric performance had mean offsets of −25.29 m in easting and 16.22 m northing with root mean square error values of 26.07 m in easting and 17.60 m in northing compared to the Landsat 8 Operational Land Imager sensor. The radiometric performance had offsets from −0.002 to 0.029 and slopes from 0.733 to 1.012. Spatial performance was in the range of 1.354 to 1.639 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.108 to 0.174.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030V","usgsCitation":"Shrestha, M., Kim, M., Sampath, A., and Clausen, J., 2025, System characterization report on Resourcesat-2A Advanced Wide Field Sensor, chap. V of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 18 p., https://doi.org/10.3133/ofr20211030V.","productDescription":"v, 18 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-170096","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":485174,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211030V/full"},{"id":485170,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/v/coverthb.jpg"},{"id":485171,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/v/ofr20211030v.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-V"},{"id":485172,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/v/ofr20211030v.XML"},{"id":485173,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/v/images/"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The overarching issue we address here is how to extract clear and actionable ecological and management insights from real-world field data that often do not satisfy traditional statistical assumptions. Toward this goal, we developed a general 12+6 step adaptive management framework tool. We applied this framework tool to existing biodiversity monitoring data to create a proof-of-concept result that addresses the overarching question of “why might a specific native stream fish taxon be present or absent at specific locations?” Our multi-step framework tool links established steps and steps that are unique to our framework through weight-of evidence (WOE) integration, an approach that combines quantitative results from multiple visualization and statistical procedures. The systematic use of all steps in our framework can provide improved conservation outcomes compared to a single analysis. Advantages accrue from our approach because our framework tool refines the overarching goal into related sub-questions, applies a specific quantitative procedure to each sub-step, combines results from all sub-questions using a WOE integration, identifies testable questions that elucidate ambiguities and gaps revealed through WOE integration, and proposes practical field methods for obtaining this clarifying information through future research and data collections. The process of considering multiple visualizations and analyses as individual pieces of a shared puzzle offers a new way to approach the use of existing data. Our team-based approach transforms the collection and analysis of existing data into a series of field tests that can guide future actions (e.g., data collection-analysis events, restoration initiatives, research). Habitat and impact regressors will vary with taxa and system, but our structured process tool has broad generality for a range of conservation issues in which freshwater systems are threatened by human impacts.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/ffwsc.2025.1520312","usgsCitation":"Rode, O., Mather, M.E., Oliver, D., Nelson, K., Reed, V., Moore, T., and Pratap, S., 2025, A framework tool that applies weight-of-evidence integration to the analysis of existing datasets to guide freshwater conservation: Frontiers in Freshwater Science, v. 3, 1520312, 22 p., https://doi.org/10.3389/ffwsc.2025.1520312.","productDescription":"1520312, 22 p.","ipdsId":"IP-162976","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":497411,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/ffwsc.2025.1520312","text":"Publisher Index Page"},{"id":497280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.02756449525691,\n 39.99175254524536\n ],\n [\n -102.02756449525691,\n 37.01810081729228\n ],\n [\n -94.52122428405349,\n 37.01810081729228\n ],\n [\n -94.52122428405349,\n 39.99175254524536\n ],\n [\n -102.02756449525691,\n 39.99175254524536\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2025-04-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Rode, Olivia","contributorId":363581,"corporation":false,"usgs":false,"family":"Rode","given":"Olivia","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":951801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":951802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oliver, Devon","contributorId":195899,"corporation":false,"usgs":false,"family":"Oliver","given":"Devon","affiliations":[],"preferred":false,"id":951803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Katherine","contributorId":363584,"corporation":false,"usgs":false,"family":"Nelson","given":"Katherine","affiliations":[{"id":86724,"text":"Department of Geography & Geospatial Sciences","active":true,"usgs":false}],"preferred":false,"id":951804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reed, Victoria","contributorId":363585,"corporation":false,"usgs":false,"family":"Reed","given":"Victoria","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":951805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moore, Trisha","contributorId":353634,"corporation":false,"usgs":false,"family":"Moore","given":"Trisha","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":951806,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pratap, Suyash","contributorId":363586,"corporation":false,"usgs":false,"family":"Pratap","given":"Suyash","affiliations":[{"id":12661,"text":"Kansas State University","active":true,"usgs":false}],"preferred":false,"id":951807,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70266216,"text":"70266216 - 2025 - Bridging social and ecological science to create spatially-explicit models of human-caused mortality of carnivores","interactions":[],"lastModifiedDate":"2025-08-04T15:39:56.471945","indexId":"70266216","displayToPublicDate":"2025-04-29T08:08:26","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":698,"text":"Ambio","active":true,"publicationSubtype":{"id":10}},"title":"Bridging social and ecological science to create spatially-explicit models of human-caused mortality of carnivores","docAbstract":"Research indicates that human-caused mortality (HCM) is a key factor limiting numerous large carnivore populations. However, efforts to represent HCM in spatially explicit models have generally been limited in scope—often relying on proxies, such as road or human density. Yet such efforts fail to distinguish different sources of HCM, which can arise from different antecedent processes. We offer a systems-based conceptual framework for understanding the antecedents of HCMs that is grounded in theory from the social and behavioral sciences. Specifically, we first explain how HCMs are usefully distinguished into four types (e.g., accidental, harvest, illicit, control actions), then discuss how these different types tend to be driven by different sets of psychological and sociopolitical processes. We contend that improvements in understanding the spatial variation in HCMs would rise from more explicit attention to the various antecedent processes that precede each mortality type.","language":"English","publisher":"Springer Nature","doi":"10.1007/s13280-025-02165-1","usgsCitation":"Bruskotter, J.T., Carter, N.H., Berl, R.E., Hinton, J.W., Murphy, J., Elbroch, L.M., and Vucetich, J.A., 2025, Bridging social and ecological science to create spatially-explicit models of human-caused mortality of carnivores: Ambio, v. 54, p. 1479-1490, https://doi.org/10.1007/s13280-025-02165-1.","productDescription":"12 p.","startPage":"1479","endPage":"1490","ipdsId":"IP-170006","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":485205,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":487885,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s13280-025-02165-1","text":"Publisher Index Page"}],"volume":"54","noUsgsAuthors":false,"publicationDate":"2025-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Bruskotter, Jeremy T.","contributorId":171472,"corporation":false,"usgs":false,"family":"Bruskotter","given":"Jeremy","email":"","middleInitial":"T.","affiliations":[{"id":16172,"text":"Ohio State University, Columbus, OH","active":true,"usgs":false}],"preferred":false,"id":934964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Neil H.","contributorId":338283,"corporation":false,"usgs":false,"family":"Carter","given":"Neil","email":"","middleInitial":"H.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":934965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berl, Richard Eugene Waggaman 0000-0002-4154-1319","orcid":"https://orcid.org/0000-0002-4154-1319","contributorId":336851,"corporation":false,"usgs":true,"family":"Berl","given":"Richard","email":"","middleInitial":"Eugene Waggaman","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":934966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinton, Joseph W.","contributorId":179346,"corporation":false,"usgs":false,"family":"Hinton","given":"Joseph","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":934967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murphy, Jazmin","contributorId":354020,"corporation":false,"usgs":false,"family":"Murphy","given":"Jazmin","affiliations":[{"id":84538,"text":"Wolf Conservation Center","active":true,"usgs":false}],"preferred":false,"id":934968,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elbroch, L. Mark","contributorId":337813,"corporation":false,"usgs":false,"family":"Elbroch","given":"L.","email":"","middleInitial":"Mark","affiliations":[{"id":81049,"text":"Panthera","active":true,"usgs":false}],"preferred":false,"id":934969,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vucetich, John A.","contributorId":219329,"corporation":false,"usgs":false,"family":"Vucetich","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":39990,"text":"School of Forest Resources and Environmental Science, Michigan Tech, Houghton","active":true,"usgs":false}],"preferred":false,"id":934970,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70268437,"text":"70268437 - 2025 - Integrating marine historical ecology into management of Alaska’s Pacific cod fishery for climate readiness","interactions":[],"lastModifiedDate":"2025-06-25T14:47:04.627818","indexId":"70268437","displayToPublicDate":"2025-04-29T07:41:32","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1936,"text":"ICES Journal of Marine Science","active":true,"publicationSubtype":{"id":10}},"title":"Integrating marine historical ecology into management of Alaska’s Pacific cod fishery for climate readiness","docAbstract":"The Pacific cod (Gadus macrocephalus) fishery was closed in 2020 after a rapid decline in biomass caused by the marine heat waves of 2014–2019. Pacific cod are exceptionally thermally sensitive and management of this fishery is now challenged by increasingly unpredictable climate conditions. Fisheries monitoring is critical for climate readiness, but short-term monitoring data may be inadequate for recognizing and anticipating change under rapid climate changes. We propose an interdisciplinary, marine historical ecology framework that looks to long-term records (local and traditional knowledge, history, archaeology, and paleoclimatology) to capture a long range of ecological variability and provide historical context for management. In order to connect to contemporary fisheries management, this framework must be built on a common vocabulary and an understanding of the key metrics used in fisheries stock assessments. Here, we propose metrics derived from Pacific cod stock assessment and synthesize information relevant to understanding the effects of past warming periods on cod populations across the Gulf of Alaska and Bering Sea. This case study provides a framework for thinking about how to use these historical records in the context of fisheries management under rapidly changing climate conditions.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/icesjms/fsaf056","usgsCitation":"West, C., McClenachan, L., Barbeaux, S.J., Spies, I.B., Addison, J.A., Anderson, B., Hofman, C.A., Reedy, K., Smith, E., Etnier, M., Helser, T.E., and Finney, B., 2025, Integrating marine historical ecology into management of Alaska’s Pacific cod fishery for climate readiness: ICES Journal of Marine Science, v. 82, no. 4, fsaf056, 17 p., https://doi.org/10.1093/icesjms/fsaf056.","productDescription":"fsaf056, 17 p.","ipdsId":"IP-170032","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":491443,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/icesjms/fsaf056","text":"Publisher Index Page"},{"id":491279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -203.937437508192,\n 54.954559063654074\n ],\n [\n -203.937437508192,\n 50.326282088235786\n ],\n [\n -148.52655859208141,\n 50.326282088235786\n ],\n [\n -148.52655859208141,\n 54.954559063654074\n ],\n [\n -203.937437508192,\n 54.954559063654074\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"82","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"West, Catherine F. 0000-0001-5177-9235","orcid":"https://orcid.org/0000-0001-5177-9235","contributorId":345839,"corporation":false,"usgs":false,"family":"West","given":"Catherine F.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":941291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McClenachan, Loren","contributorId":260606,"corporation":false,"usgs":false,"family":"McClenachan","given":"Loren","email":"","affiliations":[{"id":51887,"text":"Colby College","active":true,"usgs":false}],"preferred":false,"id":941292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barbeaux, Steven J.","contributorId":256680,"corporation":false,"usgs":false,"family":"Barbeaux","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":34572,"text":"NOAA, National Marine Fisheries Service, Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":941293,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spies, Ingrid B.","contributorId":256688,"corporation":false,"usgs":false,"family":"Spies","given":"Ingrid","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":941294,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Addison, Jason A. 0000-0003-2416-9743 jaddison@usgs.gov","orcid":"https://orcid.org/0000-0003-2416-9743","contributorId":4192,"corporation":false,"usgs":true,"family":"Addison","given":"Jason","email":"jaddison@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":941295,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Bruce T. 0000-0001-7006-5967","orcid":"https://orcid.org/0000-0001-7006-5967","contributorId":345835,"corporation":false,"usgs":false,"family":"Anderson","given":"Bruce T.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":941296,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hofman, Courtney A.","contributorId":127441,"corporation":false,"usgs":false,"family":"Hofman","given":"Courtney","email":"","middleInitial":"A.","affiliations":[{"id":6997,"text":"Department of Anthropology, Smithsonian Institution National Museum of Natural History (NMNH)","active":true,"usgs":false}],"preferred":false,"id":941297,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reedy, Katherine L.","contributorId":345838,"corporation":false,"usgs":false,"family":"Reedy","given":"Katherine L.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":941298,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smith, Emma A. Elliott 0000-0002-3221-0737","orcid":"https://orcid.org/0000-0002-3221-0737","contributorId":357366,"corporation":false,"usgs":false,"family":"Smith","given":"Emma A. Elliott","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":941299,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Etnier, Michael A. 0000-0002-6546-7854","orcid":"https://orcid.org/0000-0002-6546-7854","contributorId":357369,"corporation":false,"usgs":false,"family":"Etnier","given":"Michael A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":941300,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Helser, Thomas E.","contributorId":203203,"corporation":false,"usgs":false,"family":"Helser","given":"Thomas","email":"","middleInitial":"E.","affiliations":[{"id":36580,"text":"Alaska Fisheries Science Center, National Oceanic and Atmospheric Administration, Seattle, Washington","active":true,"usgs":false}],"preferred":false,"id":941301,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Finney, Bruce P.","contributorId":267775,"corporation":false,"usgs":false,"family":"Finney","given":"Bruce P.","affiliations":[{"id":38154,"text":"Idaho State University","active":true,"usgs":false}],"preferred":false,"id":941302,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70270724,"text":"70270724 - 2025 - Comparison of two benthic assemblage sampling gears for use on intertidal oyster reefs in Louisiana","interactions":[],"lastModifiedDate":"2025-09-22T16:05:13.473914","indexId":"70270724","displayToPublicDate":"2025-04-28T11:03:19","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":860,"text":"Aquatic Biology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of two benthic assemblage sampling gears for use on intertidal oyster reefs in Louisiana","docAbstract":"Background
Estuarine biodiversity plays a vital role in supporting ecosystem functions yet remains threatened by climate change and anthropogenic activity. Tracking and identifying estuarine biodiversity trends helps management ensure long-term provisions of human and environmental benefits by contributing to the estimation of habitat loss and the monitoring of restoration and conservation progress. However, the sampling gear and biodiversity metric used may indicate different conclusions, which can lead to uncertainty in the actual state of the ecosystem-level biodiversity. Sampling benthic biodiversity in complex estuarine habitats, such as oyster reefs, is particularly challenging because no one gear type captures entire target assemblages, and differences in gear efficiency on these complex habitats make comparisons across gear types challenging.
Methods
We investigated how estimates of oyster reef-associated benthic taxa abundance, richness, Pielou’s evenness, and Shannon-Wiener diversity differed across three Crassostrea virginica reefs in Louisiana between suction sampler and substrate tray sampling gears (n = 6), and how gear influenced comparisons across reefs (3 reefs × 6 replicates × 2 gears).
Results
Abundance and richness were higher, and Pielou’s evenness was lower, in trays compared to suction samples at all reefs. Shannon-Wiener diversity was similar in suction samples and trays at two out of three reefs. Amphipod taxa were numerically dominant in trays, skewing the distribution of abundances and driving the reef assemblage differences between gears. Abundance and Shannon-Wiener diversity were similar across reefs within each gear. However, there were significant differences in richness across reefs in tray samples only, while evenness differed across reefs only in suction samples. Our results highlight that gear choices, along with biodiversity metrics tracked, can result in different conclusions in biodiversity trends, ultimately affecting conservation decisions and management.
","language":"English","publisher":"Peer J","doi":"10.7717/peerj.19346","usgsCitation":"Campanino, F.M., Archer, S.K., Tuptiza, J.C., Glaspie, C.N., and La Peyre, M., 2025, Comparison of two benthic assemblage sampling gears for use on intertidal oyster reefs in Louisiana: Aquatic Biology, v. 13, e19346, 13 p., https://doi.org/10.7717/peerj.19346.","productDescription":"e19346, 13 p.","ipdsId":"IP-159581","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":495051,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.19346","text":"Publisher Index Page"},{"id":494566,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.18844430172265,\n 33.05933747886088\n ],\n [\n -93.93839548881195,\n 29.657698500033632\n ],\n [\n -91.47053061521939,\n 28.941858732825423\n ],\n [\n -89.65507085191668,\n 29.110391374618672\n ],\n [\n -89.27077210572385,\n 29.664235014130195\n ],\n [\n -91.45664556469545,\n 31.116558532764905\n ],\n [\n -90.9367332746039,\n 32.812492651944765\n ],\n [\n -94.18844430172265,\n 33.05933747886088\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Campanino, Finella M.","contributorId":360220,"corporation":false,"usgs":false,"family":"Campanino","given":"Finella","middleInitial":"M.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":946900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archer, Stephanie K.","contributorId":360222,"corporation":false,"usgs":false,"family":"Archer","given":"Stephanie","middleInitial":"K.","affiliations":[{"id":12699,"text":"Louisiana Universities Marine Consortium","active":true,"usgs":false}],"preferred":false,"id":946901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tuptiza, Jillian C.","contributorId":360224,"corporation":false,"usgs":false,"family":"Tuptiza","given":"Jillian","middleInitial":"C.","affiliations":[{"id":85986,"text":"Louisiana State University and Agricultural and Mechanical College","active":true,"usgs":false}],"preferred":false,"id":946902,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glaspie, Cassandra N.","contributorId":360225,"corporation":false,"usgs":false,"family":"Glaspie","given":"Cassandra","middleInitial":"N.","affiliations":[{"id":85986,"text":"Louisiana State University and Agricultural and Mechanical College","active":true,"usgs":false}],"preferred":false,"id":946903,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"La Peyre, Megan 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":79375,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan","email":"mlapeyre@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":946904,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266856,"text":"70266856 - 2025 - Three decades of World Recreational Fishing Conferences: What have we learned about the dynamics of recreational fisheries?","interactions":[],"lastModifiedDate":"2025-07-21T15:30:37.382955","indexId":"70266856","displayToPublicDate":"2025-04-28T09:55:40","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Three decades of World Recreational Fishing Conferences: What have we learned about the dynamics of recreational fisheries?","docAbstract":"Recreational fishing extends beyond catching fish, connecting individuals with nature, generating environmental stewards and contributing significantly to both local, regional and national economies. Assessing potential impacts on ecosystems and social-ecological systems requires dedicated multi- and interdisciplinary research and integrative management and policy approaches. Managing recreational fisheries effectively also necessitates transdisciplinary thinking, yet this poses continued challenges, as researchers and managers balance specialized expertise with innovative, boundary-crossing perspectives in light of limited funding in a rapidly changing social-ecological environment. The World Recreational Fishing Conference (WRFC) serves as the leading global scientific forum for addressing these challenges, fostering interdisciplinary exchange among scientists, managers, policy makers and stakeholders. The papers in this special issue represent the output of the last WRFC in Melbourne, Australia in 2023. By reviewing the content of the papers published in the present special issue, we illustrate the critical role of collaborative spaces, such as the WRFC, in bridging different expertise and approaches and fostering innovation, thereby securing adaptive management and conservation of recreational fisheries in response to global changes. Evaluating the development of the WRFC over three decades highlights how this conference series represents a leading think tank serving the entire network of recreational fisheries professionals globally.","language":"English","publisher":"Wiley","doi":"10.1111/fme.12815","usgsCitation":"Sbragaglia, V., Arlinghaus, R., Ochwada-Doyle, F., Embke, H.S., Griffin, L., and Hunt, T., 2025, Three decades of World Recreational Fishing Conferences: What have we learned about the dynamics of recreational fisheries?: Fisheries Management and Ecology, v. 32, no. 4, p. 2-10, https://doi.org/10.1111/fme.12815.","productDescription":"9 p.","startPage":"2","endPage":"10","ipdsId":"IP-174479","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":485811,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":488175,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/fme.12815","text":"Publisher Index Page"}],"volume":"32","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Sbragaglia, Valerio","contributorId":355146,"corporation":false,"usgs":false,"family":"Sbragaglia","given":"Valerio","affiliations":[],"preferred":false,"id":936931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arlinghaus, Robert","contributorId":32425,"corporation":false,"usgs":false,"family":"Arlinghaus","given":"Robert","email":"","affiliations":[{"id":17980,"text":"Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany","active":true,"usgs":false}],"preferred":false,"id":936932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ochwada-Doyle, Faith","contributorId":355147,"corporation":false,"usgs":false,"family":"Ochwada-Doyle","given":"Faith","affiliations":[],"preferred":false,"id":936933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Embke, Holly Susan 0000-0002-9897-7068","orcid":"https://orcid.org/0000-0002-9897-7068","contributorId":270754,"corporation":false,"usgs":true,"family":"Embke","given":"Holly","email":"","middleInitial":"Susan","affiliations":[{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":936934,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Griffin, Lucas P","contributorId":228796,"corporation":false,"usgs":false,"family":"Griffin","given":"Lucas P","affiliations":[{"id":41510,"text":"Department of Environmental Conservation, University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":936935,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hunt, Taylor","contributorId":355148,"corporation":false,"usgs":false,"family":"Hunt","given":"Taylor","affiliations":[],"preferred":false,"id":936936,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266796,"text":"70266796 - 2025 - International gas hydrate research and development","interactions":[],"lastModifiedDate":"2025-05-13T14:46:34.567905","indexId":"70266796","displayToPublicDate":"2025-04-28T09:42:36","publicationYear":"2025","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"International gas hydrate research and development","docAbstract":"Gas hydrates are increasingly acknowledged as a potential future natural gas resource, sparking extensive global research into their geological characteristics and the technology needed for production. This paper offers a comprehensive review of gas hydrate-related research initiatives and production testing activities, including those in the Alaska North Slope (USA), Mackenzie Delta (Canada), Gulf of America (USA), South China Sea (PRC), Nankai Trough (Japan), Bay of Bengal (India), and Black Sea (Turkey).
Recent studies have demonstrated successful gas production from hydrates found in sand-rich sediments using existing conventional technologies, particularly depressurization techniques. This review highlights the production trials conducted in Alaska, Canada, China, and Japan, providing insight into gas hydrate production feasibility. In addition, the implications of the completed production trials are reviewed relative to their energy planning considerations. This review also emphasizes research opportunities for technological advancements to effectively utilize the substantial volumes of gas stored in gas hydrates across various global geological settings. This compilation underscores the critical role that gas hydrates could play in meeting future energy demands.
","conferenceTitle":"Offshore Technology Conference","conferenceDate":"May 5-8, 2025","conferenceLocation":"Houston, TX","language":"English","publisher":"OnePetro","doi":"10.4043/35912-MS","usgsCitation":"Collett, T., 2025, International gas hydrate research and development, Offshore Technology Conference, Houston, TX, May 5-8, 2025, 25 p., https://doi.org/10.4043/35912-MS.","productDescription":"25 p.","ipdsId":"IP-174405","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":485808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2025-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Collett, Timothy 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":220812,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":936801,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70266408,"text":"70266408 - 2025 - Increased flood exposure in the Pacific Northwest following earthquake-driven subsidence and sea-level rise","interactions":[],"lastModifiedDate":"2025-05-06T14:24:28.816171","indexId":"70266408","displayToPublicDate":"2025-04-28T09:18:21","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Increased flood exposure in the Pacific Northwest following earthquake-driven subsidence and sea-level rise","docAbstract":"Climate-driven sea-level rise is increasing the frequency of coastal flooding worldwide, exacerbated locally by factors like land subsidence from groundwater and resource extraction. However, a process rarely considered in future sea-level rise scenarios is sudden (over minutes) land subsidence associated with great (>M8) earthquakes, which can exceed 1 m. Along the Washington, Oregon, and northern California coasts, the next great Cascadia subduction zone earthquake could cause up to 2 m of sudden coastal subsidence, dramatically raising sea level, expanding floodplains, and increasing the flood risk to local communities. Here, we quantify the potential expansion of the 1% floodplain (i.e., the area with an annual flood risk of 1%) under low (~0.5 m), medium (~1 m), and high (~2 m) earthquake-driven subsidence scenarios at 24 Cascadia estuaries. If a great earthquake occurred today, floodplains could expand by 90 km2 (low), 160 km2 (medium), or 300 km2 (high subsidence), more than doubling the flooding exposure of residents, structures, and roads under the high subsidence scenario. By 2100, when climate-driven sea-level rise will compound the hazard, a great earthquake could expand floodplains by 170 km2 (low), 240 km2 (medium), or 370 km2 (high subsidence), more than tripling the flooding exposure of residents, structures, and roads under the high subsidence scenario compared to the 2023 floodplain. Our findings can support decision-makers and coastal communities along the Cascadia subduction zone as they prepare for compound hazards from the earthquake cycle and climate-driven sea-level rise and provide critical insights for tectonically active coastlines globally.
","language":"English","publisher":"National Academy of Sciences of the United States","doi":"10.1073/pnas.2424659122","usgsCitation":"Dura, T., Chilton, W., Small, D., Garner, A., Hawkes, A.D., Melgar, D., Engelhart, S.E., Staisch, L.M., Witter, R., Nelson, A., Kelsey, H., Allan, J., Bruce, D.S., DePaolis, J., Priddy, M., Briggs, R.W., Weiss, R., La Selle, S., Willis, M.J., and Horton, B.P., 2025, Increased flood exposure in the Pacific Northwest following earthquake-driven subsidence and sea-level rise: PNAS, v. 122, no. 18, e2424659122, 9 p., https://doi.org/10.1073/pnas.2424659122.","productDescription":"e2424659122, 9 p.","ipdsId":"IP-176650","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":488123,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2424659122","text":"Publisher Index Page"},{"id":485446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -127.97536588577248,\n 47.44031706213207\n ],\n [\n -127.97536588577248,\n 40.23117017976111\n ],\n [\n -121.9496452484936,\n 40.23117017976111\n ],\n [\n -121.9496452484936,\n 47.44031706213207\n ],\n [\n -127.97536588577248,\n 47.44031706213207\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"122","issue":"18","noUsgsAuthors":false,"publicationDate":"2025-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Dura, Tina","contributorId":195530,"corporation":false,"usgs":false,"family":"Dura","given":"Tina","email":"","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":935842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chilton, William 0009-0001-9186-4167","orcid":"https://orcid.org/0009-0001-9186-4167","contributorId":354553,"corporation":false,"usgs":false,"family":"Chilton","given":"William","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":935843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Small, David 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Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":935849,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Witter, Robert C. 0000-0002-1721-254X rwitter@usgs.gov","orcid":"https://orcid.org/0000-0002-1721-254X","contributorId":4528,"corporation":false,"usgs":true,"family":"Witter","given":"Robert C.","email":"rwitter@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":935850,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nelson, Alan 0000-0001-7117-7098","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":216700,"corporation":false,"usgs":true,"family":"Nelson","given":"Alan","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":935851,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kelsey, Harvey","contributorId":254376,"corporation":false,"usgs":false,"family":"Kelsey","given":"Harvey","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":935852,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Allan, Jonathan","contributorId":46847,"corporation":false,"usgs":false,"family":"Allan","given":"Jonathan","affiliations":[{"id":7198,"text":"Oregon Department Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":935853,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bruce, David S.","contributorId":188228,"corporation":false,"usgs":false,"family":"Bruce","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":935854,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"DePaolis, Jessica","contributorId":334364,"corporation":false,"usgs":false,"family":"DePaolis","given":"Jessica","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":935855,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Priddy, Mike","contributorId":354556,"corporation":false,"usgs":false,"family":"Priddy","given":"Mike","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":935856,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":4136,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":935857,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Weiss, Robert","contributorId":306163,"corporation":false,"usgs":false,"family":"Weiss","given":"Robert","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":935858,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"La Selle, SeanPaul 0000-0002-4500-7885 slaselle@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-7885","contributorId":181565,"corporation":false,"usgs":true,"family":"La Selle","given":"SeanPaul","email":"slaselle@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":935859,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Willis, Michael J. 0000-0003-1308-2888","orcid":"https://orcid.org/0000-0003-1308-2888","contributorId":242617,"corporation":false,"usgs":false,"family":"Willis","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":13693,"text":"University of Colorado Boulder","active":true,"usgs":false}],"preferred":false,"id":935860,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Horton, Benjamin P.","contributorId":192807,"corporation":false,"usgs":false,"family":"Horton","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false},{"id":5110,"text":"Earth Observatory of Singapore, Nanyang Technological University","active":true,"usgs":false}],"preferred":false,"id":935861,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70271909,"text":"70271909 - 2025 - Mapping predicted ecological states at landscape scales using remote sensing data and machine learning","interactions":[],"lastModifiedDate":"2025-09-24T15:44:17.513747","indexId":"70271909","displayToPublicDate":"2025-04-28T08:37:41","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Mapping predicted ecological states at landscape scales using remote sensing data and machine learning","docAbstract":"Dryland ecosystems, covering 45% of the Earth's land and supporting over one-third of the global population, face significant threats from land degradation and ecological state change. Managing these ecosystems is complex, and science-based frameworks like Ecological Site Descriptions and state-and-transition models are essential tools for guiding decisions to support ecological health while maintaining stakeholder values such as grazing, wildlife, and recreation. However, alignment of these frameworks with smaller scale soil survey maps limits their applicability to broader ecological processes. Here, we extend these frameworks to larger landscapes with a machine learning approach that integrates large-scale, high-resolution vegetation data with identified ecological states from a data-driven state-and-transition model developed for a landscape-scale Ecological Site Group. A “global” model, which used combined inputs from multiple remotely sensed datasets, outperformed individual dataset models based on evaluation with independent data. Ecological state maps generated through this approach broaden the utility of state-and-transition models across Ecological Site Groups, providing a more spatially robust tool for land management at watershed and larger landscape scales. These methods, and the associated ecological state maps, can help meet critical needs for improved land condition assessments that support development of resource management plans and help identify priority areas for restoration and conservation.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70243","usgsCitation":"Kleist, N.J., Domschke, C.T., Knight, A.C., Nauman, T.W., Duniway, M.C., and Carter, S.K., 2025, Mapping predicted ecological states at landscape scales using remote sensing data and machine learning: Ecosphere, v. 16, no. 4, e70243, 16 p., https://doi.org/10.1002/ecs2.70243.","productDescription":"e70243, 16 p.","ipdsId":"IP-157413","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":496158,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70243","text":"Publisher Index Page"},{"id":496018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah, Wyoming","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.0509637142687,\n 42.64630716588371\n ],\n [\n -111.8266792759012,\n 39.96910670756075\n ],\n [\n -114.76249387460862,\n 35.930067724930424\n ],\n [\n -108.04708953433448,\n 35.58278337785393\n ],\n [\n -107.09257565522607,\n 37.663677272255455\n ],\n [\n -107.38346712125988,\n 40.56490356337224\n ],\n [\n -108.74500520215983,\n 41.22226787777939\n ],\n [\n -111.0509637142687,\n 42.64630716588371\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2025-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Kleist, Nathan J. 0000-0002-2468-4318","orcid":"https://orcid.org/0000-0002-2468-4318","contributorId":260598,"corporation":false,"usgs":true,"family":"Kleist","given":"Nathan","email":"","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":949335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Domschke, Christopher T.","contributorId":361734,"corporation":false,"usgs":false,"family":"Domschke","given":"Christopher","middleInitial":"T.","affiliations":[{"id":86338,"text":"Bureau of Land Management, Colorado State Office, 2850 Youngfield St., Lakewood, CO 80215","active":true,"usgs":false}],"preferred":false,"id":949336,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nauman, Travis W.","contributorId":360619,"corporation":false,"usgs":false,"family":"Nauman","given":"Travis","middleInitial":"W.","affiliations":[{"id":86060,"text":"USDA Natural Resources Conservation Service, Soil and Plant Science Division, Moab, UT, USA","active":true,"usgs":false}],"preferred":false,"id":949338,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":219284,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":949339,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carter, Sarah K. 0000-0003-3778-8615","orcid":"https://orcid.org/0000-0003-3778-8615","contributorId":192418,"corporation":false,"usgs":true,"family":"Carter","given":"Sarah","email":"","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":949340,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266300,"text":"70266300 - 2025 - Slow rupture, long rise times, and multi-fault geometry: The 2020 M6.4 southwestern Puerto Rico mainshock","interactions":[],"lastModifiedDate":"2025-05-02T15:13:47.284869","indexId":"70266300","displayToPublicDate":"2025-04-28T08:08:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Slow rupture, long rise times, and multi-fault geometry: The 2020 M6.4 southwestern Puerto Rico mainshock","docAbstract":"The M6.4 mainshock of the southwestern Puerto Rico seismic sequence on 7 January 2020, was one of the most impactful modern earthquakes in the northeastern Caribbean. Due to its offshore location and complex aftershock distribution, its source kinematics remain poorly constrained. This active sequence illuminated a complex set of previously unrecognized structures that indicate multiple causative faults may have slipped during its rupture. Here, we utilize seismic and geodetic observations to enhance model resolution, estimate the finite slip of the mainshock, and test a multi-segment, geologically realistic fault geometry. Our refined model finds a lower rupture velocity and longer rise times than typical for an event of this magnitude. This indicates a slow-evolving rupture process that resembles characteristics of a tsunami earthquake. Although this normal/strike-slip faulting event was not tsunamigenic, these qualities, if pervasive for this region, have important implications for future seismic monitoring and hazards in southwestern Puerto Rico.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GL109740","usgsCitation":"Solares-Colón, M., Goldberg, D.E., Melgar, D., Vanacore, E.A., Sahakian, V., Yeck, W.L., Hernández, F., and Lopez-Venegas, A., 2025, Slow rupture, long rise times, and multi-fault geometry: The 2020 M6.4 southwestern Puerto Rico mainshock: Geophysical Research Letters, v. 52, no. 8, e2024GL109740, 12 p., https://doi.org/10.1029/2024GL109740.","productDescription":"e2024GL109740, 12 p.","ipdsId":"IP-170544","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":487926,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gl109740","text":"Publisher Index Page"},{"id":485330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -67.39442494689831,\n 18.578883979264447\n ],\n [\n -67.39442494689831,\n 17.849447857579676\n ],\n [\n -65.47820852132409,\n 17.849447857579676\n ],\n [\n -65.47820852132409,\n 18.578883979264447\n ],\n [\n -67.39442494689831,\n 18.578883979264447\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","issue":"8","noUsgsAuthors":false,"publicationDate":"2025-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Solares-Colón, Margarita M. 0000-0002-9387-7551","orcid":"https://orcid.org/0000-0002-9387-7551","contributorId":353919,"corporation":false,"usgs":false,"family":"Solares-Colón","given":"Margarita M.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":935442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goldberg, Dara Elyse 0000-0002-0923-3180","orcid":"https://orcid.org/0000-0002-0923-3180","contributorId":289891,"corporation":false,"usgs":true,"family":"Goldberg","given":"Dara","email":"","middleInitial":"Elyse","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":935443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Melgar, Diego","contributorId":341315,"corporation":false,"usgs":false,"family":"Melgar","given":"Diego","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":935444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanacore, Elizabeth A.","contributorId":316311,"corporation":false,"usgs":false,"family":"Vanacore","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[{"id":62735,"text":"University of Puerto Rico Mayagüez","active":true,"usgs":false}],"preferred":false,"id":935445,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sahakian, Valerie J.","contributorId":208097,"corporation":false,"usgs":false,"family":"Sahakian","given":"Valerie J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":935446,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yeck, William L. 0000-0002-2801-8873 wyeck@usgs.gov","orcid":"https://orcid.org/0000-0002-2801-8873","contributorId":147558,"corporation":false,"usgs":true,"family":"Yeck","given":"William","email":"wyeck@usgs.gov","middleInitial":"L.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":935447,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hernández, Francisco","contributorId":353921,"corporation":false,"usgs":false,"family":"Hernández","given":"Francisco","affiliations":[{"id":62735,"text":"University of Puerto Rico Mayagüez","active":true,"usgs":false}],"preferred":false,"id":935448,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lopez-Venegas, Alberto 0000-0002-3413-0546","orcid":"https://orcid.org/0000-0002-3413-0546","contributorId":350939,"corporation":false,"usgs":false,"family":"Lopez-Venegas","given":"Alberto","affiliations":[{"id":34129,"text":"University of Puerto Rico Mayaguez","active":true,"usgs":false}],"preferred":false,"id":935449,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70269031,"text":"70269031 - 2025 - Advancing broadscale spatial evapotranspiration modelling by incorporating sun-induced chlorophyll fluorescence measurements","interactions":[],"lastModifiedDate":"2025-07-14T14:48:30.146948","indexId":"70269031","displayToPublicDate":"2025-04-28T07:43:40","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":"Advancing broadscale spatial evapotranspiration modelling by incorporating sun-induced chlorophyll fluorescence measurements","docAbstract":"Evapotranspiration (ET) describes the sum of water transfer from the ground surface through soil evaporation and water loss from leaf stomata into the atmosphere − critical factors linking the global water and carbon cycles. Myriad ET models based on remote sensing data provide spatially continuous estimates of ET; however, leaf photosynthetic information is critical to ensure accurate ET estimates, which are difficult to measure from space. Remotely sensed sun-induced chlorophyll fluorescence (SIF) provides a proxy of stomatal conductance activity with high performance in predicting plant transpiration, which can account for a large proportion of terrestrial and riverine ET. This study aims to improve estimates of tree water use in semi-arid to arid environments. In this study, a fixed stomatal conductance model and three SIF-driven canopy conductance (gsc) models were applied to model potential ET (PET). The models estimated PET using the Penman-Monteith equation with: (1) a constant leaf stomatal conductance; (2) a transpiration-driven gsc model; (3) a gsc model based on electron-transfer rate and vapor pressure deficit, and a (4) Ball-Berry stomatal conductance model. A machine learning model was then applied to scale PET to actual ET (AET) using remote sensing and climate data. Accordingly, four AET models were cross-validated with in-situ measured AET at 52 sites, including 21 eddy covariance flux tower sites, and 31 sap-flow measurement sites (semi-arid and plantation area), for various plant functional types in Australia. This study demonstrated that SIF effectively captured seasonal variations of gsc, finding that AET models with SIF-driven gsc models correlated well with in-situ measured AET (R2 = 0.64). Modelled AET with dynamic variations of gsc generated lower prediction error (0.85 mm day−1), while the AET model with fixed stomatal conductance tended to overestimate AET in floodplains and underestimate it in evergreen broadleaf forests, indicating using fixed stomatal conductance results in unstable performance when modelling AET. This study demonstrated that SIF-driven AET models improved broadscale estimation of ET. Our findings provide vital broadscale hydrological data to assist catchment and regional water management, particularly over unmonitored areas at risk of future climate-driven reductions in rainfall.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2025.133404","usgsCitation":"Gao, S., Nagler, P.L., Woodgate, W., Huete, A., and Doody, T.M., 2025, Advancing broadscale spatial evapotranspiration modelling by incorporating sun-induced chlorophyll fluorescence measurements: Journal of Hydrology, v. 660, no. Part B, 133404, 16 p., https://doi.org/10.1016/j.jhydrol.2025.133404.","productDescription":"133404, 16 p.","ipdsId":"IP-172126","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":499843,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2025.133404","text":"Publisher Index Page"},{"id":492203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 123.28690979572599,\n -14.507783026538078\n ],\n [\n 113.28039887008524,\n -21.66065633263682\n ],\n [\n 112.17079996753354,\n -24.994521175001637\n ],\n [\n 115.10354300417447,\n -36.486501164702105\n ],\n [\n 122.24168422144697,\n -35.62034073401294\n ],\n [\n 131.93124828895753,\n -32.58906983701101\n ],\n [\n 141.10544225154464,\n -40.23302031896691\n ],\n [\n 152.81278701443853,\n -40.33448456027517\n ],\n [\n 155.92719705356842,\n -24.451431761649573\n ],\n [\n 144.11359477726128,\n -8.385497835754798\n ],\n [\n 130.88500806969773,\n -10.415819254694402\n ],\n [\n 123.28690979572599,\n -14.507783026538078\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"660","issue":"Part B","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gao, Sicong","contributorId":303040,"corporation":false,"usgs":false,"family":"Gao","given":"Sicong","email":"","affiliations":[{"id":65623,"text":"CSIRO, Land and Water, Waite Campus, Adelaide, South Australia, Australia; University of Canberra, Canberra, Australian Capital Territory, Australia","active":true,"usgs":false}],"preferred":false,"id":942957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":942958,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodgate, William","contributorId":357983,"corporation":false,"usgs":false,"family":"Woodgate","given":"William","affiliations":[{"id":85572,"text":"Earth Observation Research Centre, School of the Environment, The University of Queensland, Brisbane, QLD 4072, Australia; CSIRO, Space and Astronomy, Kensington, 6151, WA, Australia","active":true,"usgs":false}],"preferred":false,"id":942959,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huete, Alfredo 0000-0003-2809-2376","orcid":"https://orcid.org/0000-0003-2809-2376","contributorId":208294,"corporation":false,"usgs":false,"family":"Huete","given":"Alfredo","email":"","affiliations":[],"preferred":false,"id":942960,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doody, Tanya M.","contributorId":138691,"corporation":false,"usgs":false,"family":"Doody","given":"Tanya","email":"","middleInitial":"M.","affiliations":[{"id":12494,"text":"CSIRO Land and Water, Australia","active":true,"usgs":false}],"preferred":false,"id":942961,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268941,"text":"70268941 - 2025 - A psychologically wise intervention to inform relational organizing in the face of climate and ocean change","interactions":[],"lastModifiedDate":"2025-07-11T15:04:56.510852","indexId":"70268941","displayToPublicDate":"2025-04-27T09:56:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21993,"text":"npj Ocean Sustainability","active":true,"publicationSubtype":{"id":10}},"title":"A psychologically wise intervention to inform relational organizing in the face of climate and ocean change","docAbstract":"Widespread climate action is broadly recognized as necessary to reduce climate change impacts on oceans (“ocean change”), but threats to ocean ecosystems are commonly perceived as distant, irrelevant, and unchangeable. Communicating about ocean change, therefore, requires message framing strategies targeting evidence-based psychological precursors to behavior. In a pre-registered case study of coastal visitors in Oregon, United States (n = 2414), we tested the influence of psychologically wise message about ocean change on climate action intentions. We primarily focused on influencing relational organizing: people’s willingness to encourage others to act. A behavior-specific message targeting relational organizing efficacy beliefs significantly but weakly increased intentions for relational organizing regarding ocean change compared to a control. Neither a connectedness to coast (place-based) message nor an ocean acidification (proximate threat-based) message had detectable effects on intentions. Our results suggest that targeting relational organizing efficacy may increase climate action intentions for the protection of coastal ecosystems.
","language":"English","publisher":"Nature","doi":"10.1038/s44183-025-00115-8","usgsCitation":"Waldo, J., Swearingen, T., and Jones, M.S., 2025, A psychologically wise intervention to inform relational organizing in the face of climate and ocean change: npj Ocean Sustainability, v. 4, 17, 10 p., https://doi.org/10.1038/s44183-025-00115-8.","productDescription":"17, 10 p.","ipdsId":"IP-171105","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":492474,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s44183-025-00115-8","text":"Publisher Index Page"},{"id":492132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","noUsgsAuthors":false,"publicationDate":"2025-04-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Waldo, Jennifer L.","contributorId":357840,"corporation":false,"usgs":false,"family":"Waldo","given":"Jennifer L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":942681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swearingen, Thomas C.","contributorId":357842,"corporation":false,"usgs":false,"family":"Swearingen","given":"Thomas C.","affiliations":[{"id":85558,"text":"Oregon Department of Fish & Wildlife","active":true,"usgs":false}],"preferred":false,"id":942682,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Megan Siobhan 0000-0002-4284-3650","orcid":"https://orcid.org/0000-0002-4284-3650","contributorId":294651,"corporation":false,"usgs":true,"family":"Jones","given":"Megan","email":"","middleInitial":"Siobhan","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":942683,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266138,"text":"70266138 - 2025 - Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs","interactions":[],"lastModifiedDate":"2025-04-29T15:23:06.190421","indexId":"70266138","displayToPublicDate":"2025-04-27T08:15:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":16456,"text":"Frontiers in Enviornmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs","docAbstract":"Oil and gas reservoirs represent suitable containers to sequester carbon dioxide (CO2) in a supercritical state because they are accessible, reservoir properties are known, and they previously contained stored buoyant fluids. However, planners must quantify the relative magnitude of the CO2 storage resource in these reservoirs to formulate a comprehensive strategy for CO2 mitigation. Even reconnaissance-type estimates of CO2 storage resources of known oil and gas reservoirs may require complicated calculations involving 1) estimates of recoverable oil and gas, 2) reservoir properties (depth, temperature, pressure, etc.), and 3) the physical qualities of the retained fluids. We demonstrate the application of machine learning (ML) algorithms to bypass these computations to yield more rapid estimates of CO2 storage resources in reservoirs capable of hosting CO2 in a supercritical state. ML algorithms are computationally efficient because they do not impose the strong assumptions on the data-generating process that standard statistical or engineering procedures require. Further, ML algorithms can capture highly complex, particularly nonlinear, relationships among predictor variables. We demonstrate the application of four different ML algorithms using data from onshore and offshore oil and gas reservoirs in Europe, and show they perform well when predictions are compared to engineering estimates. The proposed methods and models provide an effective and novel way to more rapidly and directly determine the subsurface CO2 storage capacity of oil and gas reservoirs around the world, information that operators, researchers, and policymakers alike require to meet energy transition and decarbonization goals.
","language":"English","publisher":"frontiers","doi":"10.3389/fenvs.2025.1562087","usgsCitation":"Attanasi, E., Freeman, P., and Coburn, T.C., 2025, Machine learning provides reconnaissance-type estimates of carbon dioxide storage resources in oil and gas reservoirs: Frontiers in Enviornmental Science, v. 13, 1562087, 14 p., https://doi.org/10.3389/fenvs.2025.1562087.","productDescription":"1562087, 14 p.","ipdsId":"IP-166626","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":487848,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2025.1562087","text":"Publisher Index Page"},{"id":485138,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"western Europe","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -13.428924366035233,\n 54.504852491541925\n ],\n [\n -13.428924366035233,\n 41.74320075493446\n ],\n [\n 28.707525813502826,\n 41.74320075493446\n ],\n [\n 28.707525813502826,\n 54.504852491541925\n ],\n [\n -13.428924366035233,\n 54.504852491541925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2025-04-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":1809,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":934732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Philip A. 0000-0002-0863-7431 pfreeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":193093,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","email":"pfreeman@usgs.gov","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":934733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coburn, Timothy C.","contributorId":26011,"corporation":false,"usgs":true,"family":"Coburn","given":"Timothy","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":934734,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266322,"text":"70266322 - 2025 - Bølling-Allerød productivity in the subarctic Pacific driven by seasonal upwelling","interactions":[],"lastModifiedDate":"2025-05-02T15:09:54.928503","indexId":"70266322","displayToPublicDate":"2025-04-26T10:03:48","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Bølling-Allerød productivity in the subarctic Pacific driven by seasonal upwelling","docAbstract":"The Bølling-Allerød deglacial event is marked by high diatom productivity and opal deposition throughout the subarctic Pacific. This opal could either constitute a strengthened biological pump and thus carbon sequestration, or a weakened biological pump and release of marine-sequestered CO2 to the atmosphere. We quantify silicic acid supply at IODP Site U1340 in the Bering Sea using biogenic opal and δ30Si of Coscinodiscus, a diatom genus. These records, along with diatom environmental indicators, suggest the Bølling-Allerød had high silicic acid availability related to a shift from stratification to seasonal upwelling dynamics. We thus propose the primary cause of the high productivity event was increased macronutrient supply from vertical exchange that injected old, nutrient-rich, CO2-rich waters into the surface. Enhanced CO2 release from the subarctic Pacific may help explain critical intervals of CO2 rise that occur at the onsets of the Bølling-Allerød and PreBoreal.
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2025 - Evaluation of SARS-CoV-2 antibody detection methods for wild Cervidae","interactions":[],"lastModifiedDate":"2025-07-28T14:33:54.915552","indexId":"70269591","displayToPublicDate":"2025-04-26T09:18:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3117,"text":"Preventive Veterinary Medicine","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of SARS-CoV-2 antibody detection methods for wild Cervidae","docAbstract":"Wildlife surveillance programs often use serological data to monitor exposure to pathogens. 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We studied the influence of sample collection method using paired blood samples collected in serum separator tubes and on Nobuto strips from the same animal. Mean estimates of sampling sensitivity and specificity ranged from 0.21–0.95 and 0.94–1.00, respectively, varying by sample collection method, host species, and SARS-CoV-2 variant targeted by the assay. Broadly, sampling sensitivity was estimated to be higher for 1) sera collected in tubes, 2) detecting pre-Omicron SARS-CoV-2 variants, and 3) sVNT relative to cVNT assays. Sampling specificity tended to be high for all tests. We augmented our study with SARS-CoV-2 spike protein sequences derived from sampling locations and times coincident with white-tailed deer captures, finding common amino acid mutations relative to the sVNT Omicron antigen variant. The mutations may indicate that the SARS-CoV-2 variants circulating in cervids from 2021 through 2024 may be better adapted to cervid hosts and more closely related to variants that circulated in humans prior to Omicron variants. We conclude our study with an inter-test comparison of sVNT results, revealing that 40 % inhibition is an optimal threshold for test positivity when testing deer sera for responses to Omicron variant B.1.1.529, compared to the 30 % inhibition recommended for ancestral variants.
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These input data are maps of topography, surface slope, surface aspect, surface curvature, maximum temperature, depth to ice stability, permanently shadowed regions (PSRs), distance to PSRs, and PSR density. This model predicts where water ice is most likely within the top meter of regolith, assuming plausible relationships between ice concentration and the various inputs. The model is designed to be adjusted in near-real time as data are collected during the VIPER mission. As such, it is a tool for both analyzing data from the mission as well as planning operations. Since the current model, at this point, relies only on orbital remote sensing, the final version will also be a tool to extrapolate the VIPER mission results across the lunar poles.
","language":"English","publisher":"American Astronomical Society","doi":"10.3847/PSJ/adbc6c","usgsCitation":"Coyan, J.A., Siegler, M., Martinez-Comacho, J., Beyer, R.A., and Shirley, M., 2025, Prospectivity modeling of the NASA VIPER landing site at Mons Mouton near the Lunar South Pole: Planetary Science Journal, v. 6, no. 5, 105, 9 p., https://doi.org/10.3847/PSJ/adbc6c.","productDescription":"105, 9 p.","ipdsId":"IP-168617","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":487929,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3847/psj/adbc6c","text":"Publisher Index Page"},{"id":485333,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mons Mouton, Moon","volume":"6","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Coyan, Joshua Aaron 0000-0002-8450-7364","orcid":"https://orcid.org/0000-0002-8450-7364","contributorId":247291,"corporation":false,"usgs":true,"family":"Coyan","given":"Joshua","email":"","middleInitial":"Aaron","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":935581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siegler, Matthew A.","contributorId":237898,"corporation":false,"usgs":false,"family":"Siegler","given":"Matthew","middleInitial":"A.","affiliations":[{"id":24584,"text":"PSI","active":true,"usgs":false}],"preferred":false,"id":935582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martinez-Comacho, José 0000-0003-0542-7866","orcid":"https://orcid.org/0000-0003-0542-7866","contributorId":354404,"corporation":false,"usgs":false,"family":"Martinez-Comacho","given":"José","affiliations":[{"id":84624,"text":"University of Hawai’i at Manoa, Hawaii Institute for Geophysics and Planetology, 1680 East-West Road, POST Building, Honolulu, HI 96822","active":true,"usgs":false}],"preferred":false,"id":935583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beyer, Ross A.","contributorId":204235,"corporation":false,"usgs":false,"family":"Beyer","given":"Ross","email":"","middleInitial":"A.","affiliations":[{"id":36890,"text":"Sagan Center at the SETI Institute and NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":935584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shirley, Mark 0000-0001-8767-1760","orcid":"https://orcid.org/0000-0001-8767-1760","contributorId":354405,"corporation":false,"usgs":false,"family":"Shirley","given":"Mark","affiliations":[{"id":84625,"text":"SETI Institute/NASA Ames Research Center","active":true,"usgs":false}],"preferred":false,"id":935585,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70270067,"text":"70270067 - 2025 - Broadband stochastic simulation of earthquake ground motions with multiple strong phases with an application to the 2023 Kahramanmaraş, Turkey (Türkiye), earthquake","interactions":[],"lastModifiedDate":"2025-08-08T14:30:32.119094","indexId":"70270067","displayToPublicDate":"2025-04-25T09:26:17","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Broadband stochastic simulation of earthquake ground motions with multiple strong phases with an application to the 2023 Kahramanmaraş, Turkey (Türkiye), earthquake","docAbstract":"Stochastic ground motion simulation models are often less accurate at lower frequencies than at higher frequencies when fitting recorded data unless supplemented by a deterministic forward directivity velocity pulse model. Moreover, time-modulated stochastic models, which adjust ground motion amplitudes over time, typically use functions that fail to capture multiple strong-motion phases. The February 2023 Turkey (Türkiye) earthquake exhibited diverse recordings, including near-fault and far-field motions with pulse-like and non-pulse-like characteristics, along with single and multiple strong-motion phases. To better represent such a diverse set of recordings, this study enhances a fully non-stationary site-based stochastic model without combining it with a deterministic model. Improvements include a new band-pass filter with upper- and lower-frequency limits, which refines the representation of the low-frequency content. Moreover, a time-modulating function that can represent energy arrival in multiple strong phases is introduced. The reference model’s parameters are identified by fitting to the energy content, zero-level crossings, and cumulative counts of positive-minima and negative-maxima of a target accelerogram. This fitting procedure is modified to address the increased number of parameters. These improvements broaden the reference model’s applicability while preserving its simplicity, a key aspect appealing to engineering practitioners. The improved model’s applicability is demonstrated by simulating a dataset from the February 2023 Türkiye earthquake, and the accuracy is tested using a pulse-like Next Generation Attenuation Relationships for Western United States dataset. Validations are performed based on total energy, zero-level crossings, Fourier amplitude spectrum, elastic response spectra, and peak ground motion parameters. Validations are performed schematically in the time and frequency domains and quantitatively using goodness-of-fit scores, various validation-metrics errors, and inter-period correlations. Overall, the improved stochastic model can effectively simulate a set of diverse ground motion recordings, including near-fault pulse-like records, records with multiple strong phases, and far-field motions across a broad frequency range.
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We hypothesized that, in addition to these abiotic influences, mismatch of hosts from their reproductive habitat heightens infection risk via exposure and/or susceptibility mechanisms. We evaluated this “reproductive habitat mismatch hypothesis” by quantifying the interplay of host breeding mode, habitat, and rainfall on Bd infection dynamics using two years of frog survey data—including swab data for 3427 captures representing 44 species—from Brazil’s Atlantic Forest. We modeled infection prevalence, infection intensity, and the number of frogs captured as a function of rainfall, reproductive mode (aquatic or terrestrial), and habitat (aquatic or terrestrial) using hierarchical models. High rainfall was associated with increases in infection prevalence and infection intensity; however, these increases were particularly apparent for species in habitats that were mismatched from the species’ reproductive habitat. Tropical regions experiencing increases in precipitation will likely see higher Bd risk, and our results indicate that such increases in rainfall will be particularly problematic for species that are forced to move from their reproductive habitats by factors such as habitat loss or thermal stress.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2025.e03599","usgsCitation":"Gilbert, N.A., Bell, R.C., Catenazzi, A., Martins, R.A., Buttimer, S., Neely, W.J., Lambertini, C., Saenz Calderon, V., Haddad, C.F., Becker, C.G., and DiRenzo, G.V., 2025, Reproductive habitat mismatch influences chytrid infection dynamics in a tropical amphibian community: Global Ecology and Conservation, v. 60, e03599, 12 p., https://doi.org/10.1016/j.gecco.2025.e03599.","productDescription":"e03599, 12 p.","ipdsId":"IP-171930","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":494048,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13TRTVG","text":"USGS data release","linkHelpText":"Code for reproductive habitat mismatch influences chytrid infection dynamics in a tropical amphibian community"},{"id":493796,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gecco.2025.e03599","text":"Publisher Index Page"},{"id":493706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","otherGeospatial":"Parque Estadual da Serra do Mar–Núcleo Santa Virgínia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -45.079106081456246,\n -23.236053619691134\n ],\n [\n -45.236468001362624,\n -23.236053619691134\n ],\n [\n -45.236468001362624,\n -23.443275890477395\n ],\n [\n -45.079106081456246,\n -23.443275890477395\n ],\n [\n -45.079106081456246,\n -23.236053619691134\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"60","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gilbert, Neil A.","contributorId":359068,"corporation":false,"usgs":false,"family":"Gilbert","given":"Neil","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":944942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bell, Rayna C.","contributorId":359069,"corporation":false,"usgs":false,"family":"Bell","given":"Rayna","middleInitial":"C.","affiliations":[{"id":12937,"text":"California Academy of Sciences","active":true,"usgs":false}],"preferred":false,"id":944943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Catenazzi, Alessandro","contributorId":359070,"corporation":false,"usgs":false,"family":"Catenazzi","given":"Alessandro","affiliations":[{"id":7017,"text":"Florida International University","active":true,"usgs":false}],"preferred":false,"id":944944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martins, Renato A.","contributorId":359071,"corporation":false,"usgs":false,"family":"Martins","given":"Renato","middleInitial":"A.","affiliations":[{"id":85744,"text":"Universidade Federal de São Carlo","active":true,"usgs":false}],"preferred":false,"id":944945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Buttimer, Shannon","contributorId":359073,"corporation":false,"usgs":false,"family":"Buttimer","given":"Shannon","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":944946,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neely, Wesley J.","contributorId":359075,"corporation":false,"usgs":false,"family":"Neely","given":"Wesley","middleInitial":"J.","affiliations":[{"id":6677,"text":"Texas State University","active":true,"usgs":false}],"preferred":false,"id":944947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lambertini, Carolina","contributorId":359077,"corporation":false,"usgs":false,"family":"Lambertini","given":"Carolina","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":944948,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Saenz Calderon, Veronica","contributorId":359079,"corporation":false,"usgs":false,"family":"Saenz Calderon","given":"Veronica","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":944949,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Haddad, Célio F.B.","contributorId":359081,"corporation":false,"usgs":false,"family":"Haddad","given":"Célio","middleInitial":"F.B.","affiliations":[{"id":48854,"text":"Universidade Estadual Paulista","active":true,"usgs":false}],"preferred":false,"id":944950,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Becker, C. 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","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024GL112472","usgsCitation":"Manaster, A., Sheehan, A.F., Goldberg, D.E., Barnhart, K.R., and Roth, E., 2025, Detection of landslide-generated tsunami by shipborne GNSS precise point positioning: Geophysical Research Letters, v. 52, e2024GL112472, 9 p., https://doi.org/10.1029/2024GL112472.","productDescription":"e2024GL112472, 9 p.","ipdsId":"IP-169782","costCenters":[{"id":78686,"text":"Geologic Hazards Science Center - Seismology / Geomagnetism","active":true,"usgs":true}],"links":[{"id":487831,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024gl112472","text":"Publisher Index Page"},{"id":485128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Seward","otherGeospatial":"Resurrection Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.60008399844827,\n 60.18626730817803\n ],\n [\n -149.60008399844827,\n 59.864306105004715\n ],\n [\n -149.1691851387203,\n 59.864306105004715\n ],\n [\n -149.1691851387203,\n 60.18626730817803\n ],\n [\n -149.60008399844827,\n 60.18626730817803\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"52","noUsgsAuthors":false,"publicationDate":"2025-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Manaster, Adam E. 0000-0001-8183-4274","orcid":"https://orcid.org/0000-0001-8183-4274","contributorId":215663,"corporation":false,"usgs":true,"family":"Manaster","given":"Adam E.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":934768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheehan, Anne F 0000-0002-9629-1687","orcid":"https://orcid.org/0000-0002-9629-1687","contributorId":224234,"corporation":false,"usgs":false,"family":"Sheehan","given":"Anne","email":"","middleInitial":"F","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":934769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldberg, Dara Elyse 0000-0002-0923-3180","orcid":"https://orcid.org/0000-0002-0923-3180","contributorId":289891,"corporation":false,"usgs":true,"family":"Goldberg","given":"Dara","email":"","middleInitial":"Elyse","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934770,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Katherine R. 0000-0001-5682-455X","orcid":"https://orcid.org/0000-0001-5682-455X","contributorId":257870,"corporation":false,"usgs":true,"family":"Barnhart","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":934771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, Ethan F.","contributorId":353914,"corporation":false,"usgs":false,"family":"Roth","given":"Ethan F.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":934772,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70268068,"text":"70268068 - 2025 - Destruction and transformation: Lessons learned from the 2015 Gorkha, Nepal, earthquake","interactions":[],"lastModifiedDate":"2025-12-01T16:08:57.389863","indexId":"70268068","displayToPublicDate":"2025-04-25T09:07:06","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":21821,"text":"Temblor","active":true,"publicationSubtype":{"id":10}},"title":"Destruction and transformation: Lessons learned from the 2015 Gorkha, Nepal, earthquake","docAbstract":"No abstract available.
","language":"English","publisher":"Temblor, Inc.","doi":"10.32858/temblor.363","usgsCitation":"Shrestha, S., and Hough, S., 2025, Destruction and transformation: Lessons learned from the 2015 Gorkha, Nepal, earthquake: Temblor, HTML Document, https://doi.org/10.32858/temblor.363.","productDescription":"HTML Document","ipdsId":"IP-176968","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":490507,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Nepal","otherGeospatial":"Gorkha district west of Kathmandu Valley","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[88.12044,27.87654],[88.04313,27.44582],[88.1748,26.81041],[88.06024,26.41462],[87.22747,26.3979],[86.02439,26.63098],[85.25178,26.7262],[84.67502,27.2349],[83.30425,27.36451],[81.99999,27.92548],[81.0572,28.4161],[80.08842,28.79447],[80.47672,29.72987],[81.11126,30.18348],[81.5258,30.42272],[82.32751,30.11527],[83.33712,29.46373],[83.89899,29.32023],[84.23458,28.83989],[85.01164,28.64277],[85.82332,28.20358],[86.95452,27.97426],[88.12044,27.87654]]]},\"properties\":{\"name\":\"Nepal\"}}]}","noUsgsAuthors":false,"publicationDate":"2025-04-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Shrestha, Surya Narayan","contributorId":356806,"corporation":false,"usgs":false,"family":"Shrestha","given":"Surya Narayan","affiliations":[{"id":37310,"text":"National Society for Earthquake Technology, Nepal","active":true,"usgs":false}],"preferred":false,"id":940115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":350979,"corporation":false,"usgs":true,"family":"Hough","given":"Susan E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":940116,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70273501,"text":"70273501 - 2025 - Footprints of past mining in Alaska (USA) derived from high-resolution satellite imagery","interactions":[],"lastModifiedDate":"2026-01-20T15:43:08.696041","indexId":"70273501","displayToPublicDate":"2025-04-25T08:38:13","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3907,"text":"Scientific Data","active":true,"publicationSubtype":{"id":10}},"title":"Footprints of past mining in Alaska (USA) derived from high-resolution satellite imagery","docAbstract":"Mapping the land area used for mining in the past is essential for guiding the remediation of affected landscapes and assessing the resource potential of related waste products. Despite significant recent progress delineating footprints of active and inactive mining globally, the known inventory of such mine lands remains incomplete. Here, I describe a new map dataset of footprints of land surface disturbance and waste at sites of past mining in Alaska (USA) based on visual interpretation of satellite imagery. This dataset maps 6–14 times the area of previous regional and global mine footprint maps in Alaska and is the first in the region to explicitly delineate mine waste landforms (e.g., tailings piles). The data are publicly available from the U.S. Geological Survey under a “no rights reserved” Creative Commons (CC0) license agreement.
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Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1011","displayTitle":"Genetic Structure and Diversity in Wild Populations of the Light-Footed Ridgway’s Rail Reflect 20 Years of Augmentation Through Captive Breeding and Release","title":"Genetic structure and diversity in wild populations of the Light-footed Ridgway’s Rail reflect 20 years of augmentation through captive breeding and release","docAbstract":"Captive breeding and release programs aimed at recovery of rare species can be informed by genetic data to help select high-diversity source populations, make pairing decisions to minimize inbreeding, and manage release strategies. We developed a set of 54 microsatellite loci to assess genetic structure and diversity across the United States range of the Light-footed Ridgway’s Rail (Rallus obsoletus levipes), a federally endangered marsh bird for which populations have been augmented by a captive breeding program annually since 2001. We identified three regional genetic clusters, with the highest genetic diversity reported in the central cluster, which included all sampled wetlands in north San Diego County. Recent (2019–24) captive-breeding adults all clustered within the northernmost cluster (Orange and Ventura Counties), which was expected given that this cluster included the source wetland for the captive breeding program. Gene flow rates, which approximate the proportions of individuals in a population originating from other populations, were relatively high among clusters (4–24 percent) and may have been enhanced through the release of captive-bred rails. Based on the genetic data analyzed in a genetic rescue decision framework, sourcing new breeding birds from the north San Diego County cluster could provide the greatest genetic diversity benefits. The northernmost cluster, which included Mugu Lagoon and all sampled Orange County wetlands, was considered the most in need of genetic rescue. Recent breeding pairs in the captive breeding program have comparatively low diversity and high interrelatedness. Sourcing birds from wetlands with high genetic diversity and population sizes, assessing genetic relatedness before pairing, and focusing releases in areas that have low estimates of genetic diversity could improve the distribution of genetic diversity across wild populations in the future.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251011","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service, Carlsbad Fish and Wildlife Office","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Vandergast, A.G., Smith, J.G., Mitelberg, A., Wood, D.A., Sawyer, K.A., and Conway, C.J., 2025, Genetic structure and diversity in wild populations of the Light-footed Ridgway’s Rail reflect 20 years of augmentation through captive breeding and release: U.S. Geological Survey Open-File Report 2025–1011, 24 p., https://doi.org/10.3133/ofr20251011.","productDescription":"Report: viii, 24 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-169671","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":485012,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1011/coverthb.jpg"},{"id":485013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1011/ofr20251011.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1011"},{"id":485015,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P14CYDJC","text":"USGS data release","description":"USGS data release","linkHelpText":"Microsatellite genotypes for light-footed Ridgway's rail (Rallus obsoletus levipes) sampled in southern California"},{"id":485017,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1011/ofr20251011.XML"},{"id":485014,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251011/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1011"},{"id":485016,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1011/images"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.10331263380175,\n 34.10687099022617\n ],\n [\n -118.03807861620402,\n 33.46101273577156\n ],\n [\n -117.15926055168606,\n 32.54485080859107\n ],\n [\n -116.83812382579282,\n 32.56519890177364\n ],\n [\n -117.45219990652568,\n 33.65951802680661\n ],\n [\n -118.60202603728568,\n 34.09630540323134\n ],\n [\n -119.10331263380175,\n 34.10687099022617\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819