Infragravity waves are key components of the hydro-sedimentary processes in coastal areas, especially during extreme storms. Accurate modeling of coastal erosion and breaching requires consideration of the effects of infragravity waves. Here, we present InWave, a new infragravity wave driver of the Coupled Ocean-Atmopshere-Waves-Sediment Transport (COAWST) modeling system. InWave computes the spatial and temporal variation of wave energy at the wave group scale and the associated incoming bound infragravity wave. Wave group-varying forces drive free infragravity wave growth and propagation within the hydrodynamic model of the coupled modeling system, which is the Regional Ocean Modeling System (ROMS) in this work. Since ROMS is a three-dimensional model, this coupling allows for the combined formation of undertow currents and infragravity waves. We verified the coupled InWave-ROMS with one idealized test case, one laboratory experiment, and one field experiment. The coupled modeling system correctly reproduced the propagation of gravity wave energy with acceptable numerical dissipation. It also captured the transfer of energy from the gravity band to the infragravity band, and within the different infragravity bands in the surf zone, the measured three-dimensional flow structure, and dune morphological evolution satisfactorily. The idealized case demonstrated that the infragravity wave variance depends on the directional resolution and horizontal grid resolution, which are known challenges with the approach taken here. The addition of InWave to COAWST enables novel investigation of nearshore hydro-sedimentary dynamics driven by infragravity waves using the strengths of the other modeling components, namely the three-dimensional nature of ROMS and the sediment transport routines.
A three-dimensional petroleum systems model was built to support U.S. Geological Survey assessments of undiscovered oil and gas resources in the Williston Basin of North Dakota, Montana, and South Dakota. Numerous Paleozoic source rocks have been proven or postulated in the basin, of which five were the focus of maturation and migration modeling: the Ordovician Icebox Formation, the kukersite beds of the Ordovician Red River Formation, the shales of the Devonian–Mississippian Bakken Formation, the Mississippian Madison Group, and the Pennsylvanian Tyler Formation. Calibration of the three-dimensional model to present-day temperature data indicates the existence of a north-south trend of high heat flow in western North Dakota, along with a region of high heat flow in eastern Montana. These high heat flow trends strongly control the maturity of all studied source intervals. A Bakken-specific hydrocarbon generation kinetic model was developed to match the calibrated time-temperature history of the basin to spatial trends in hydrogen index from programmed pyrolysis data. Generation of hydrocarbons occurred in the Cretaceous through Paleogene due to increased burial. Subsequent uplift and erosion in the Neogene cooled the basin, ending hydrocarbon generation for all source rocks. The cumulative volume of hydrocarbons generated by each of the source rocks was calculated and used to compare their relative robustness. The shales of the Bakken Formation are estimated to have generated approximately 460 billion barrels of oil equivalent (BBOE), while the Red River Formation generated approximately 130 BBOE, the Tyler Formation 94 BBOE, the Madison Group 44 BBOE, and the Icebox Formation 28 BBOE. Gross migration trends were analyzed with respect to historical oil and gas production in the basin and generally indicate segregation of petroleum systems throughout the stratigraphic column. However, most modeled scenarios indicated significant loss of Bakken oil to the Madison Group, suggesting that mixing of Madison and Bakken oils may be more prevalent than has recently been recognized in the U.S. portion of the Williston Basin and is particularly likely in fractured regions of the basin.
Wildland fire in arid and semi-arid (dryland) regions can intensify when climatic, biophysical, and land-use factors increase fuel load and continuity. To inform wildland fire management under these conditions, we developed high-resolution (10-m) estimates of fine fuel across the Altar Valley in southern Arizona, USA, which spans dryland, grass-dominated ecosystems that are administered by multiple land managers and owners. We coupled field measurements at the end of the 2021 growing season with Sentinel-2 satellite imagery and vegetation indices acquired during and after the growing season to develop predictions of fine fuel across the entire valley. We then assessed how climate, soil, vegetation, and land-use factors influenced the amount and distribution of fine fuels. We connected fine fuels to fire management points, past ignition history, and socio-economic vulnerability to evaluate wildfire exposure and assessed how fuel related to habitat of the endangered masked bobwhite quail (Colinus virginianus ridgwayi).
The high amount of fine fuel (400–3600 kg/ha; mean = 1392 kg/ha) predicted by our remote sensing model (R2 = 0.63) for 2021 compared to previous years in the valley was stimulated by near-record high growing season precipitation that was 177% of the 1990–2020 mean. Fine fuel increased across the valley if it was contained within the wildlife refuge boundary and had lower temperature and vapor pressure deficit, higher soil organic content, and abundant annual plants and an invasive perennial grass (R2 = 0.24). The index of potential exposure to wildfire showed a clustering of high exposure centered around roads and low-density housing development distant from fire management points and extending into the upper elevations flanking the valley. Within the Buenos Aires National Wildlife Refuge, fine fuel increased with habitat suitability for the masked bobwhite quail within and adjacent to core habitat areas, representing a natural resource value at risk, accompanied with higher overall mean fine fuel (1672 kg/ha) in relation to 2015 (1347 kg/ha) and 2020 (1363 kg/ha) means.
By connecting high-resolution estimates of fine fuel to climatic, biophysical and land-use factors, wildfire exposure, and a natural resource value at risk, we provide a pro-active and adaptive framework for fire risk management within highly variable and rapidly changing dryland landscapes.
","language":"English","publisher":"Springer","doi":"10.1186/s42408-023-00196-1","usgsCitation":"Wells, A.G., Munson, S.M., Villarreal, M.L., Sesnie, S., and Laushman, K., 2023, Connecting dryland fine-fuel assessments to wildfire exposure and natural resource values at risk: Fire Ecology, v. 19, 37, 20 p., https://doi.org/10.1186/s42408-023-00196-1.","productDescription":"37, 20 p.","ipdsId":"IP-146903","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":442947,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-023-00196-1","text":"Publisher Index Page"},{"id":418583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Altar Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.68342763370987,\n 31.524152730957113\n ],\n [\n -111.07689163856048,\n 31.33347646138226\n ],\n [\n -110.93146487948965,\n 31.49996137458362\n ],\n [\n -110.95629383835528,\n 32.06679730274084\n ],\n [\n -110.97757580309751,\n 32.114877905907576\n ],\n [\n -111.07334464443704,\n 32.27096495459102\n ],\n [\n -111.10526759154996,\n 32.3728769856678\n ],\n [\n -111.4209500685577,\n 32.39084955148782\n ],\n [\n -111.68342763370987,\n 31.524152730957113\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2023-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Wells, Adam Gerhard 0000-0001-9675-4963","orcid":"https://orcid.org/0000-0001-9675-4963","contributorId":270137,"corporation":false,"usgs":true,"family":"Wells","given":"Adam","email":"","middleInitial":"Gerhard","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":876400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":876401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":876402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sesnie, Steven E.","contributorId":315379,"corporation":false,"usgs":false,"family":"Sesnie","given":"Steven E.","affiliations":[{"id":68297,"text":"U.S. Fish and Wildlife Service, Division of Biological Sciences, Albuquerque, NM 87102, USA","active":true,"usgs":false}],"preferred":false,"id":876403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laushman, Katherine M.","contributorId":315380,"corporation":false,"usgs":false,"family":"Laushman","given":"Katherine M.","affiliations":[{"id":68299,"text":"Washington Department of Fish and Wildlife, 7801 Phillips Road SW, Lakewood, WA 98498, USA","active":true,"usgs":false}],"preferred":false,"id":876404,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245114,"text":"sim3507 - 2023 - Percent-slope map showing historical anthracite coal-mining infrastructure at the northern end of the Lackawanna syncline, Wayne, Susquehanna, and Lackawanna Counties, Pennsylvania","interactions":[],"lastModifiedDate":"2026-02-19T18:09:02.7011","indexId":"sim3507","displayToPublicDate":"2023-06-23T20:35:00","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3507","displayTitle":"Percent-Slope Map Showing Historical Anthracite Coal-Mining Infrastructure at the Northern End of the Lackawanna Syncline, Wayne, Susquehanna, and Lackawanna Counties, Pennsylvania","title":"Percent-slope map showing historical anthracite coal-mining infrastructure at the northern end of the Lackawanna syncline, Wayne, Susquehanna, and Lackawanna Counties, Pennsylvania","docAbstract":"Abandoned railroads and infrastructure from the anthracite coal-mining industry are significant features in abandoned mine lands and are an important part of history; however, these features are often lost and masked by the passage of time and the regrowth of forests. The application of modern light detection and ranging (lidar) topographic analysis, combined with field verification, enabled the mapping of these historical features. Waste rock piles and abandoned mine lands from historical mining locally appear as distinct features on the landscape depicted on the percent-slope base map. Abandoned, and in many places demolished, infrastructure such as breakers, turntables, rail beds, water tanks, tram piers, and bridge abutments, for example, were identified in the field and located with a Global Positioning System (GPS) receiver. This percent-slope map shows the locations of many of the abandoned features from the coal-mining industry near Forest City, Pennsylvania, and preserves a time that was an important part of the industrial revolution and a way of life that has been quiet for over half a century.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3507","programNote":"National Cooperative Geologic Mapping Program","usgsCitation":"Walsh, G.J., and Walsh, M.C., 2023, Percent-slope map showing historical anthracite coal-mining infrastructure at the northern end of the Lackawanna syncline, Wayne, Susquehanna, and Lackawanna Counties, Pennsylvania: U.S. Geological Survey Scientific Investigations Map 3507, 1 sheet, scale 1:40,000, https://doi.org/10.3133/sim3507.","productDescription":"Sheet: 22.40 x 18.34 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-137242","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":500213,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114936.htm","linkFileType":{"id":5,"text":"html"}},{"id":418135,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P992K6GB","text":"USGS data release","linkHelpText":"Database of historical anthracite coal-mining infrastructure at the northern end of the Lackawanna syncline, Wayne, Susquehanna, and Lackawanna counties, Pennsylvania"},{"id":418134,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3507/sim3507.pdf","text":"Report","size":"41.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3507"},{"id":418133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3507/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Lackawanna County, Susquehanna County, Wayne County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.5,\n 41.667\n ],\n [\n -75.5,\n 41.6\n ],\n [\n -75.4417,\n 41.6\n ],\n [\n -75.4417,\n 41.667\n ],\n [\n -75.5,\n 41.667\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Deep learning (DL) models are increasingly used to forecast water quality variables for use in decision making. Ingesting recent observations of the forecasted variable has been shown to greatly increase model performance at monitored locations; however, observations are not collected at all locations, and methods are not yet well developed for DL models for optimally ingesting recent observations from other sites to inform focal sites. In this paper, we evaluate two different DL model structures, a long short-term memory neural network (LSTM) and a recurrent graph convolutional neural network (RGCN), both with and without data assimilation for forecasting daily maximum stream temperature 7 days into the future at monitored and unmonitored locations in a 70-segment stream network. All our DL models performed well when forecasting stream temperature as the root mean squared error (RMSE) across all models ranged from 2.03 to 2.11°C for 1-day lead times in the validation period, with substantially better performance at gaged locations (RMSE = 1.45–1.52°C) compared to ungaged locations (RMSE = 3.18–3.27°C). Forecast uncertainty characterization was near-perfect for gaged locations but all DL models were overconfident (i.e., uncertainty bounds too narrow) for ungaged locations. Our results show that the RGCN with data assimilation performed best for ungaged locations and especially at higher temperatures (>18°C) which is important for management decisions in our study location. This indicates that the networked model structure and data assimilation techniques may help borrow information from nearby monitored sites to improve forecasts at unmonitored locations. Results from this study can help guide DL modeling decisions when forecasting other important environmental variables.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/frwa.2023.1184992","usgsCitation":"Zwart, J.A., Diaz, J.A., Hamshaw, S.D., Oliver, S.K., Ross, J.C., Sleckman, M.J., Appling, A.P., Corson-Dosch, H.R., Jia, X., Read, J.S., Sadler, J., Thompson, T.P., Watkins, D., and White, E., 2023, Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations: Frontiers in Water, v. 5, 1184992, 18 p., https://doi.org/10.3389/frwa.2023.1184992.","productDescription":"1184992, 18 p.","ipdsId":"IP-151646","costCenters":[{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"links":[{"id":442963,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2023.1184992","text":"Publisher Index Page"},{"id":419304,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","noUsgsAuthors":false,"publicationDate":"2023-06-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Zwart, Jacob Aaron 0000-0002-3870-405X","orcid":"https://orcid.org/0000-0002-3870-405X","contributorId":237809,"corporation":false,"usgs":true,"family":"Zwart","given":"Jacob","email":"","middleInitial":"Aaron","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Diaz, Jeremy Alejandro 0000-0001-7087-7949","orcid":"https://orcid.org/0000-0001-7087-7949","contributorId":302986,"corporation":false,"usgs":true,"family":"Diaz","given":"Jeremy","email":"","middleInitial":"Alejandro","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879015,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hamshaw, Scott Douglas 0000-0002-0583-4237","orcid":"https://orcid.org/0000-0002-0583-4237","contributorId":305601,"corporation":false,"usgs":true,"family":"Hamshaw","given":"Scott","email":"","middleInitial":"Douglas","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":879016,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliver, Samantha K. 0000-0001-5668-1165","orcid":"https://orcid.org/0000-0001-5668-1165","contributorId":211886,"corporation":false,"usgs":true,"family":"Oliver","given":"Samantha","email":"","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879017,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ross, Jesse Cleveland 0000-0002-5422-8284","orcid":"https://orcid.org/0000-0002-5422-8284","contributorId":304193,"corporation":false,"usgs":true,"family":"Ross","given":"Jesse","email":"","middleInitial":"Cleveland","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879018,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sleckman, Margaux Jeanne 0000-0002-1843-6932","orcid":"https://orcid.org/0000-0002-1843-6932","contributorId":295257,"corporation":false,"usgs":true,"family":"Sleckman","given":"Margaux","email":"","middleInitial":"Jeanne","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879019,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Appling, Alison P. 0000-0003-3638-8572 aappling@usgs.gov","orcid":"https://orcid.org/0000-0003-3638-8572","contributorId":150595,"corporation":false,"usgs":true,"family":"Appling","given":"Alison","email":"aappling@usgs.gov","middleInitial":"P.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":879020,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Corson-Dosch, Hayley R. 0000-0001-8695-1584","orcid":"https://orcid.org/0000-0001-8695-1584","contributorId":244707,"corporation":false,"usgs":true,"family":"Corson-Dosch","given":"Hayley","middleInitial":"R.","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879021,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jia, Xiaowei 0000-0001-8544-5233","orcid":"https://orcid.org/0000-0001-8544-5233","contributorId":237807,"corporation":false,"usgs":false,"family":"Jia","given":"Xiaowei","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":879022,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Read, Jordan S 0000-0002-3888-6631","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":305964,"corporation":false,"usgs":false,"family":"Read","given":"Jordan","email":"","middleInitial":"S","affiliations":[{"id":12701,"text":"US Geological Survey","active":true,"usgs":false}],"preferred":false,"id":879023,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sadler, Jeffrey M 0000-0001-8776-4844","orcid":"https://orcid.org/0000-0001-8776-4844","contributorId":302989,"corporation":false,"usgs":false,"family":"Sadler","given":"Jeffrey M","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":879024,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Thompson, Theodore Paul 0000-0001-7373-314X","orcid":"https://orcid.org/0000-0001-7373-314X","contributorId":295258,"corporation":false,"usgs":true,"family":"Thompson","given":"Theodore","email":"","middleInitial":"Paul","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":879025,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Watkins, David 0000-0002-7544-0700","orcid":"https://orcid.org/0000-0002-7544-0700","contributorId":317375,"corporation":false,"usgs":true,"family":"Watkins","given":"David","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":879026,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"White, Elaheh 0000-0003-1248-5247","orcid":"https://orcid.org/0000-0003-1248-5247","contributorId":295260,"corporation":false,"usgs":true,"family":"White","given":"Elaheh","email":"","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":879027,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70251488,"text":"70251488 - 2023 - Efficient modeling of wave generation and propagation in a semi-enclosed estuary","interactions":[],"lastModifiedDate":"2024-02-13T14:32:29.361948","indexId":"70251488","displayToPublicDate":"2023-06-23T08:26:36","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5979,"text":"Ocean Modeling","active":true,"publicationSubtype":{"id":10}},"title":"Efficient modeling of wave generation and propagation in a semi-enclosed estuary","docAbstract":"Accurate, and high-resolution wave statistics are critical for regional hazard mapping and planning. However, long-term simulations at high spatial resolution are often computationally prohibitive. Here, multiple rapid frameworks including fetch-limited, look-up-table (LUT), and linear propagation are combined and tested in a large estuary exposed to both remotely (swell) and locally generated waves. Predictions are compared with observations and a traditional SWAN implementation coupled to a regional hydrodynamic model. Fetch-limited and LUT approaches both perform well where local winds dominate with errors about 10%–20% larger than traditional SWAN predictions. Combinations of these rapid approaches with linear propagation methods where remotely generated energy is present also perform well with errors 0%–20% larger than traditional SWAN predictions. Model–model comparisons exhibit lower variance than comparisons to observations suggesting that, while model implementation impacts prediction skill, model boundary conditions (winds, offshore waves) may be a dominant source of error. Overall results suggest that with a relatively small loss in prediction accuracy, simulations computation cost can be significantly reduced (by 2–4 orders of magnitude) allowing for high resolution and long-term predictions to adequately define regional wave statistics.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ocemod.2023.102231","usgsCitation":"Crosby, S.C., Nederhoff, C.M., VanArendonk, N.R., and Grossman, E.E., 2023, Efficient modeling of wave generation and propagation in a semi-enclosed estuary: Ocean Modeling, v. 184, 102231, 19 p., https://doi.org/10.1016/j.ocemod.2023.102231.","productDescription":"102231, 19 p.","ipdsId":"IP-142651","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442971,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ocemod.2023.102231","text":"Publisher Index Page"},{"id":425603,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, Washington","otherGeospatial":"Salish Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -125.72815512978502,\n 50.26605838403208\n ],\n [\n -124.94281020369127,\n 48.47577177154896\n ],\n [\n -123.03815382483049,\n 46.93731974931259\n ],\n [\n -121.69673890568171,\n 47.07660747940366\n ],\n [\n -122.56896464164149,\n 49.86949743396718\n ],\n [\n -125.72815512978502,\n 50.26605838403208\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Crosby, Sean C. 0000-0002-1499-6836","orcid":"https://orcid.org/0000-0002-1499-6836","contributorId":219466,"corporation":false,"usgs":false,"family":"Crosby","given":"Sean","email":"","middleInitial":"C.","affiliations":[{"id":40000,"text":"Contractor, USGS","active":true,"usgs":false}],"preferred":false,"id":894707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nederhoff, Cornelis M. 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":265889,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Cornelis","email":"","middleInitial":"M.","affiliations":[{"id":33886,"text":"Deltares USA","active":true,"usgs":false}],"preferred":true,"id":894708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"VanArendonk, Nathan R.","contributorId":334097,"corporation":false,"usgs":false,"family":"VanArendonk","given":"Nathan","email":"","middleInitial":"R.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":894709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grossman, Eric E. 0000-0003-0269-6307 egrossman@usgs.gov","orcid":"https://orcid.org/0000-0003-0269-6307","contributorId":196610,"corporation":false,"usgs":true,"family":"Grossman","given":"Eric","email":"egrossman@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":894710,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70246651,"text":"70246651 - 2023 - Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience","interactions":[],"lastModifiedDate":"2023-09-06T16:26:43.276047","indexId":"70246651","displayToPublicDate":"2023-06-23T07:16:08","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1466,"text":"Ecology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience","docAbstract":"Directly observing autotrophic biomass at ecologically relevant frequencies is difficult in many ecosystems, hampering our ability to predict productivity through time. Since disturbances can impart distinct reductions in river productivity through time by modifying underlying standing stocks of biomass, mechanistic models fit to productivity time series can infer underlying biomass dynamics. We incorporated biomass dynamics into a river ecosystem productivity model for six rivers to identify disturbance flow thresholds and understand the resilience of primary producers. The magnitude of flood necessary to disturb biomass and thereby reduce ecosystem productivity was consistently lower than the more commonly used disturbance flow threshold of the flood magnitude necessary to mobilize river bed sediment. The estimated daily maximum percent increase in biomass (a proxy for resilience) ranged from 5% to 42% across rivers. Our latent biomass model improves understanding of disturbance thresholds and recovery patterns of autotrophic biomass within river ecosystems.
The Proterozoic tectonic evolution of the south-western USA remains incompletely understood due to limited constraints on the timing and conditions of the tectono-metamorphic phases and depositional age of metasedimentary successions. We integrated multi-scale compositional mapping, petrologic modeling, and in situ geochronology to constrain pressure-temperature-time paths from samples of Paleoproterozoic basement gneisses and overlying quartzites in southwestern Colorado, USA. Basement gneiss from the western Needle Mountains records metamorphic conditions of 600 °C at 0.75 GPa at 1764 ± 9 Ma and ~575 °C at 1741 ± 10 Ma. Gneiss sampled from drill core near Pagosa Springs, Colorado, records conditions of 700 °C at 1748 ± 9 Ma, 800 °C at 1.1 GPa at 1650 ± 40 Ma, 540 °C at 1570 ± 36 Ma, and 440 °C at 1424 ± 12 Ma. The Uncompahgre Formation was deposited at ca. 1705 Ma, as constrained by detrital monazite (1707 ± 8 Ma) and xenotime (1692 ± 40, 1725 ± 50 Ma), metamorphic xenotime (1650 ± 10 Ma), and published 40Ar/39Ar and detrital zircon data. Compositions of ca. 1705 Ma detrital monazite and xenotime are consistent with derivation from a garnet-bearing source in the Yavapai orogenic hinterland. The Vallecito Conglomerate and Uncompahgre Formation record macroscopic folding and greenschist-facies metamorphism at 1650 ± 10 Ma and temperatures of 270 °C to >570 °C at 1470–1400 Ma. Laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) zircon geochronology yielded dates of 1775 ± 18 Ma from the Twilight Gneiss and 1696 ± 7 Ma from the Bakers Bridge Granite, supporting previous isotope dilution–thermal ionization mass spectrometry (ID-TIMS) dates. The Eolus Granite yielded a date of 1463 ± 6 Ma, which is older than previous 1.44–1.43 Ga ID-TIMS dates. The newly dated granite of Cataract Gulch is 1421 ± 12 Ma. In situ analysis of detrital and metamorphic monazite and xenotime, igneous zircon, and quantitative thermobarometry, integrated with previously published constraints, indicate multiple tectonic episodes after the emplacement of 1800–1760 Ma arc-related rocks. The region experienced greenschist- to amphibolite-facies metamorphism (M1) from 1760 Ma to 1740 Ma, which was followed by the intrusion of granites at 1730–1695 Ma and deposition of the Uncompahgre Formation at ca. 1705 Ma, contemporaneous with the Yavapai orogeny. Metamorphism at 1680–1600 Ma was characterized by greenschist-facies conditions near Ouray, Colorado, and granulite-facies conditions near Pagosa Springs (M2) during the Mazatzal orogeny. From 1470 Ma to 1400 Ma, greenschist- to amphibolite-facies metamorphism (M3) and largely granitic plutonism occurred during the protracted Picuris orogeny. These results demonstrate the power of monazite and xenotime analyses to constrain depositional ages, provenance, and pressure-temperature-time (P-T-t) paths to resolve the compound orogenic history that is characteristic of most mountain belts.
The environments of Arctic Ocean nearshore areas experience high intra- and inter-annual variability, making it difficult to evaluate the impact of anthropogenic warming. However, a sediment record from the southern Canadian Beaufort Sea allowed us to reconstruct the impacts of climate and environmental changes over the last 1300 years along the northern Yukon coast, Canada. The coring site (PG2303; 69.513°N, 138.895°W; water depth 32 m) is located in the Herschel Basin, where high sedimentation rates (0.1–0.5 cm a−1) allowed analyses at sub-centennial to decadal resolutions. Benthic foraminiferal, ostracod, and tintinnid assemblages, as well as the stable isotope composition of the foraminifera Elphidium clavatum and Cassidulina reniforme were used as paleoclimatic and ecological indicators, while the age model was based on the combined radiometric data of 14C, 210Pb and 137Cs. From ca 700 to 1050 CE, our data suggest penetration of offshore shelf-break waters inferred by the dominance of C. reniforme followed by the relatively abundant Triloculina trihedra in the foraminiferal assemblages as both species are associated with stable saline conditions. Afterwards, the occurrence of ostracods Kotoracythere arctoborealis and Normanicythere leioderma suggests influx of Pacific-sourced waters until ca. 1150 CE. From ∼1150–1650 CE, persistent frigid waters, limited sediment supply, and low abundances of microfossils suggest cold conditions with pervasive annual sea-ice cover that may have restricted upwelling of oceanic waters. After ∼1800 CE, the co-occurrence of Tintinnopsis fimbriata and bacterial/complex organic carbon feeder foraminifera (Quinqueloculina stalkeri, Textularia earlandi and Stetsonia horvathi), suggest an increased influence of freshwater rich in particulate organic matter, which may be related to the spreading of the Mackenzie River plume and/or increased coastal permafrost erosion during longer ice-free seasons. Based on these proxy data, the shift at ∼1800 CE marks the onset of regional warming, which further intensified after ∼1955 CE, likely in response to the anthropogenic forcing.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2023.111670","usgsCitation":"Falardeau, J., de Vernal, A., Seidenkrantz, M., Fritz, M., Cronin, T.M., Gemery, L., Rochon, A., Carnero-Bravo, V., Hillaire-Marcel, C., Pearce, C., and Archambault, P., 2023, A 1300-year microfaunal record from the Beaufort Sea shelf indicates exceptional climate-related environmental changes over the last two centuries: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 625, 111670, 18 p., https://doi.org/10.1016/j.palaeo.2023.111670.","productDescription":"111670, 18 p.","ipdsId":"IP-146909","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":442984,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://orcid.org/0000-0003-4591-7325","text":"External Repository"},{"id":419154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Beaufort Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -145.2665658621064,\n 71.13218589622568\n ],\n [\n -145.2665658621064,\n 68.83512392360717\n ],\n [\n -136.49812630673208,\n 68.83512392360717\n ],\n [\n -136.49812630673208,\n 71.13218589622568\n ],\n [\n -145.2665658621064,\n 71.13218589622568\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"625","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Falardeau, Jade","contributorId":304651,"corporation":false,"usgs":false,"family":"Falardeau","given":"Jade","affiliations":[{"id":66141,"text":"1. Geotop and Département des sciences de la Terre et de l’atmosphère, Université du Québec à Montréal, Montréal, Canada","active":true,"usgs":false}],"preferred":false,"id":871236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Vernal, Anne","contributorId":304652,"corporation":false,"usgs":false,"family":"de Vernal","given":"Anne","affiliations":[{"id":66142,"text":"Geotop","active":true,"usgs":false}],"preferred":false,"id":871237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seidenkrantz, Marit-Solveig","contributorId":304650,"corporation":false,"usgs":false,"family":"Seidenkrantz","given":"Marit-Solveig","affiliations":[{"id":49183,"text":"Department of Geoscience, Aarhus University, Aarhus, Denmark","active":true,"usgs":false}],"preferred":false,"id":871238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fritz, Michael","contributorId":176701,"corporation":false,"usgs":false,"family":"Fritz","given":"Michael","email":"","affiliations":[],"preferred":false,"id":871239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cronin, Thomas M. 0000-0001-9522-3992 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0001-9522-3992","contributorId":304640,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":871240,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gemery, Laura 0000-0003-1966-8732","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":245413,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":871241,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rochon, Andre","contributorId":316792,"corporation":false,"usgs":false,"family":"Rochon","given":"Andre","email":"","affiliations":[],"preferred":false,"id":878327,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Carnero-Bravo, Vladislav","contributorId":304655,"corporation":false,"usgs":false,"family":"Carnero-Bravo","given":"Vladislav","email":"","affiliations":[],"preferred":false,"id":878328,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hillaire-Marcel, Claude","contributorId":304656,"corporation":false,"usgs":false,"family":"Hillaire-Marcel","given":"Claude","email":"","affiliations":[],"preferred":false,"id":878329,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pearce, Christof","contributorId":197126,"corporation":false,"usgs":false,"family":"Pearce","given":"Christof","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":878330,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Archambault, Philippe","contributorId":304657,"corporation":false,"usgs":false,"family":"Archambault","given":"Philippe","email":"","affiliations":[],"preferred":false,"id":878331,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70247338,"text":"70247338 - 2023 - The March 1940 superstorm: Geoelectromagnetic hazards and impacts on American communication and power systems","interactions":[],"lastModifiedDate":"2023-07-27T15:39:00.979793","indexId":"70247338","displayToPublicDate":"2023-06-22T10:35:37","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3456,"text":"Space Weather","active":true,"publicationSubtype":{"id":10}},"title":"The March 1940 superstorm: Geoelectromagnetic hazards and impacts on American communication and power systems","docAbstract":"An analysis is made of geophysical records of the 24 March 1940, magnetic storm and related reports of interference on long-line communication and power systems across the contiguous United States and, to a lesser extent, Canada. Most long-line system interference occurred during local daytime, after the second of two storm sudden commencements and during the early part of the storm's main phase. The high degree of system interference experienced during this storm is inferred to have been due to unusually large-amplitude and unusually rapid geomagnetic field variation, possibly driven by interacting interplanetary coronal-mass ejections. Geomagnetic field variation, in turn, induced geoelectric fields in the electrically conducting solid Earth, establishing large potential differences (voltages) between grounding points at communication depots and transformer substations connected by long transmission lines. It is shown that March 1940 storm-time communication- and power-system interference was primarily experienced over regions of high electromagnetic surface impedance, mainly in the upper Midwest and eastern United States. Potential differences measured on several grounded long lines during the storm exceeded 1-min resolution voltages that would have been induced by the March 1989 storm. In some places, voltages exceeded American electric-power-industry benchmarks. It is concluded that the March 1940 magnetic storm was unusually effective at inducing geoelectric fields. Although modern communication systems are now much less dependent on long electrically conducting transmission lines, modern electric-power-transmission systems are more dependent on such lines, and they, thus, might experience interference with the future occurrence of a storm as effective as that of March 1940.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022SW003379","usgsCitation":"Love, J.J., Rigler, E.J., Hartinger, M.D., Lucas, G., Kelbert, A., and Bedrosian, P.A., 2023, The March 1940 superstorm: Geoelectromagnetic hazards and impacts on American communication and power systems: Space Weather, v. 21, no. 6, e2022SW003379, 22 p., https://doi.org/10.1029/2022SW003379.","productDescription":"e2022SW003379, 22 p.","ipdsId":"IP-152212","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":442987,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022sw003379","text":"Publisher Index Page"},{"id":419393,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879260,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hartinger, Michael D 0000-0002-2643-2202","orcid":"https://orcid.org/0000-0002-2643-2202","contributorId":296645,"corporation":false,"usgs":false,"family":"Hartinger","given":"Michael","email":"","middleInitial":"D","affiliations":[{"id":48422,"text":"Space Science Institute","active":true,"usgs":false}],"preferred":false,"id":879261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lucas, Greg M. 0000-0003-1331-1863","orcid":"https://orcid.org/0000-0003-1331-1863","contributorId":223556,"corporation":false,"usgs":false,"family":"Lucas","given":"Greg M.","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":879262,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kelbert, Anna 0000-0003-4395-398X akelbert@usgs.gov","orcid":"https://orcid.org/0000-0003-4395-398X","contributorId":184053,"corporation":false,"usgs":true,"family":"Kelbert","given":"Anna","email":"akelbert@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879263,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":879264,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263629,"text":"70263629 - 2023 - Uncertainties in intensity-based earthquake magnitude estimates","interactions":[],"lastModifiedDate":"2025-02-18T15:46:50.341945","indexId":"70263629","displayToPublicDate":"2023-06-22T09:43:58","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainties in intensity-based earthquake magnitude estimates","docAbstract":"Estimating the magnitude of historical earthquakes is crucial for assessing seismic hazard. Magnitudes of early‐instrumental earthquakes can be inferred using a combination of instrumental records, field observations, and the observed distribution of shaking intensity determined from macroseismic observations. For earthquakes before 1900, shaking intensity distributions often provide the only information to constrain earthquake magnitude. Considerable effort has been made to develop methods to estimate the magnitude of moderate‐to‐large historical earthquakes using shaking intensities derived from macroseismic data. In this study, we consider earthquakes in California with known instrumental magnitudes to explore uncertainties in estimating the magnitude of historical earthquakes from intensity information alone. We use three California‐specific intensity prediction equations (IPEs) and an IPE based on a global ground‐motion model (GMM) to determine optimum intensity‐based magnitudes for 33 moderate‐to‐large California earthquakes between 1979 and 2021. Intensity‐based magnitudes are close to instrumental magnitudes on average. However, intensity‐based magnitudes for individual events differ by as much as 2.2 magnitude units from instrumental magnitudes. This result reflects the weak dependence of ground motions and shaking intensities on moment magnitude and their strong dependence on stress drop. Considering the intensity distributions of the 1906 San Francisco and 1989 Loma Prieta earthquakes, we show that information that could constrain rupture length is discarded when considering only the 2D decay of intensity with distance. We also show that ground‐motion intensity conversion equations used in a GMM‐based approach may cause a systematic overestimation of large historical earthquake magnitudes. This study underscores both the reducible and potentially irreducible uncertainties associated with using intensity data to estimate magnitudes of historical earthquakes using IPEs and highlights the value of using additional information to constrain rupture dimensions. Using intensity observations alone, moment magnitude uncertainties are typically on the order of a full unit.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220230030","usgsCitation":"Lucas, M.C., Hough, S.E., Stein, S., Salditch, L.M., Gallahue, M.M., Neely, J.S., and Abrahamson, N., 2023, Uncertainties in intensity-based earthquake magnitude estimates: Seismological Research Letters, v. 94, no. 5, p. 2202-2214, https://doi.org/10.1785/0220230030.","productDescription":"13 p.","startPage":"2202","endPage":"2214","ipdsId":"IP-153047","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-122.421439,37.869969],[-122.41847,37.852721],[-122.434403,37.852434],[-122.446316,37.861046],[-122.430958,37.872242],[-122.421439,37.869969]]],[[[-122.3785,37.826505],[-122.377879,37.830648],[-122.369941,37.832137],[-122.358779,37.814278],[-122.362661,37.807577],[-122.372422,37.811301],[-122.3785,37.826505]]],[[[-120.248484,33.999329],[-120.230001,34.010136],[-120.19578,34.004284],[-120.167306,34.008219],[-120.147647,34.024831],[-120.140362,34.025974],[-120.115058,34.019866],[-120.090182,34.019806],[-120.073609,34.024477],[-120.057637,34.03734],[-120.043259,34.035806],[-120.050382,34.013331],[-120.046575,34.000002],[-120.011123,33.979894],[-119.978876,33.983081],[-119.979913,33.969623],[-119.97026,33.944359],[-120.017715,33.936366],[-120.048611,33.915775],[-120.098601,33.907853],[-120.121817,33.895712],[-120.168974,33.91909],[-120.224461,33.989059],[-120.248484,33.999329]]],[[[-119.789798,34.05726],[-119.755521,34.056716],[-119.712576,34.043265],[-119.686507,34.019805],[-119.637742,34.013178],[-119.612226,34.021256],[-119.604287,34.031561],[-119.608798,34.035245],[-119.59324,34.049625],[-119.5667,34.053452],[-119.52064,34.034262],[-119.542449,34.021082],[-119.547072,34.005469],[-119.560464,33.99553],[-119.575636,33.996009],[-119.596877,33.988611],[-119.662825,33.985889],[-119.721206,33.959583],[-119.742966,33.963877],[-119.758141,33.959212],[-119.842748,33.97034],[-119.873358,33.980375],[-119.884896,34.008814],[-119.876329,34.032087],[-119.916216,34.058351],[-119.923337,34.069361],[-119.919155,34.07728],[-119.912857,34.077508],[-119.857304,34.071298],[-119.825865,34.059794],[-119.818742,34.052997],[-119.789798,34.05726]]],[[[-120.46258,34.042627],[-120.440248,34.036918],[-120.415287,34.05496],[-120.403613,34.050442],[-120.390906,34.051994],[-120.368813,34.06778],[-120.370176,34.074907],[-120.362251,34.073056],[-120.354982,34.059256],[-120.36029,34.05582],[-120.358608,34.050235],[-120.346946,34.046576],[-120.331161,34.049097],[-120.302122,34.023574],[-120.317052,34.018837],[-120.347706,34.020114],[-120.35793,34.015029],[-120.409368,34.032198],[-120.427408,34.025425],[-120.454134,34.028081],[-120.465329,34.038448],[-120.46258,34.042627]]],[[[-118.524531,32.895488],[-118.535823,32.90628],[-118.551134,32.945155],[-118.573522,32.969183],[-118.586928,33.008281],[-118.596037,33.015357],[-118.606559,33.01469],[-118.605534,33.030999],[-118.594033,33.035951],[-118.57516,33.033961],[-118.569013,33.029151],[-118.559171,33.006291],[-118.540069,32.980933],[-118.496811,32.933847],[-118.369984,32.839273],[-118.353504,32.821962],[-118.356541,32.817311],[-118.379968,32.824545],[-118.394565,32.823978],[-118.425634,32.800595],[-118.44492,32.820593],[-118.496298,32.851572],[-118.507193,32.876264],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.477646,33.448392],[-118.445812,33.428907],[-118.423576,33.427258],[-118.382037,33.409883],[-118.370323,33.409285],[-118.365094,33.388374],[-118.310213,33.335795],[-118.303174,33.320264],[-118.305084,33.310323],[-118.325244,33.299075],[-118.374768,33.320065],[-118.440047,33.318638],[-118.465368,33.326056],[-118.48877,33.356649],[-118.478465,33.38632],[-118.48875,33.419826],[-118.515914,33.422417],[-118.52323,33.430733],[-118.53738,33.434608],[-118.563442,33.434381],[-118.60403,33.47654],[-118.54453,33.474119],[-118.500212,33.449592]]],[[[-119.543842,33.280329],[-119.528141,33.284929],[-119.465717,33.259239],[-119.429559,33.228167],[-119.444269,33.21919],[-119.476029,33.21552],[-119.545872,33.233406],[-119.564971,33.24744],[-119.578942,33.278628],[-119.562042,33.271129],[-119.543842,33.280329]]],[[[-122.289533,42.007764],[-121.035195,41.993323],[-120.001058,41.995139],[-119.995926,40.499901],[-120.005743,39.228664],[-120.001014,38.999574],[-119.333423,38.538328],[-118.714312,38.102185],[-117.875927,37.497267],[-117.244917,37.030244],[-116.488233,36.459097],[-115.852908,35.96966],[-115.102881,35.379371],[-114.633013,35.002085],[-114.629015,34.986148],[-114.634953,34.958918],[-114.629753,34.938684],[-114.635176,34.875003],[-114.623939,34.859738],[-114.586842,34.835672],[-114.57101,34.794294],[-114.552682,34.766871],[-114.516619,34.736745],[-114.470477,34.711368],[-114.452628,34.668546],[-114.451753,34.654321],[-114.441465,34.64253],[-114.438739,34.621455],[-114.424202,34.610453],[-114.429747,34.591734],[-114.422382,34.580711],[-114.405228,34.569637],[-114.380838,34.529724],[-114.378124,34.507288],[-114.386699,34.457911],[-114.375789,34.447798],[-114.335372,34.450038],[-114.32613,34.437251],[-114.294836,34.421389],[-114.286802,34.40534],[-114.264317,34.401329],[-114.226107,34.365916],[-114.199482,34.361373],[-114.176909,34.349306],[-114.157206,34.317862],[-114.138282,34.30323],[-114.134768,34.268965],[-114.139055,34.259538],[-114.159697,34.258242],[-114.223384,34.205136],[-114.229715,34.186928],[-114.254141,34.173831],[-114.287294,34.170529],[-114.320777,34.138635],[-114.353031,34.133121],[-114.366521,34.118575],[-114.390565,34.110084],[-114.411681,34.110031],[-114.43338,34.088413],[-114.43934,34.057893],[-114.434949,34.037784],[-114.438266,34.022609],[-114.46283,34.008421],[-114.46117,33.994687],[-114.499883,33.961789],[-114.522002,33.955623],[-114.535478,33.934651],[-114.533679,33.926072],[-114.508558,33.906098],[-114.518555,33.889847],[-114.50434,33.876882],[-114.503017,33.867998],[-114.514673,33.858638],[-114.52453,33.858477],[-114.529597,33.848063],[-114.520465,33.827778],[-114.527161,33.816191],[-114.504863,33.760465],[-114.504483,33.750998],[-114.512348,33.734214],[-114.496565,33.719155],[-114.494197,33.707922],[-114.495719,33.698454],[-114.523959,33.685879],[-114.531523,33.675108],[-114.525201,33.661583],[-114.530244,33.65014],[-114.526947,33.637534],[-114.529662,33.622794],[-114.524813,33.611351],[-114.540617,33.591412],[-114.5403,33.580615],[-114.524391,33.553683],[-114.558898,33.531819],[-114.560552,33.518272],[-114.569533,33.509219],[-114.591554,33.499443],[-114.622918,33.456561],[-114.627125,33.433554],[-114.635183,33.422726],[-114.652828,33.412922],[-114.687953,33.417944],[-114.701732,33.408388],[-114.725535,33.404056],[-114.708408,33.384147],[-114.698035,33.352442],[-114.707962,33.323421],[-114.731223,33.302434],[-114.723259,33.288079],[-114.684363,33.276025],[-114.672401,33.26047],[-114.689421,33.24525],[-114.674479,33.225504],[-114.678749,33.203448],[-114.675831,33.18152],[-114.679359,33.159519],[-114.703682,33.113769],[-114.706488,33.08816],[-114.68902,33.084036],[-114.686991,33.070969],[-114.674296,33.057171],[-114.673659,33.041897],[-114.662317,33.032671],[-114.64598,33.048903],[-114.618788,33.027202],[-114.589778,33.026228],[-114.575161,33.036542],[-114.52013,33.029984],[-114.502871,33.011153],[-114.492938,32.971781],[-114.476156,32.975168],[-114.467664,32.966861],[-114.469113,32.952673],[-114.48074,32.937027],[-114.47664,32.923628],[-114.462929,32.907944],[-114.468971,32.845155],[-114.494116,32.823288],[-114.510217,32.816417],[-114.530755,32.793485],[-114.532432,32.776923],[-114.526856,32.757094],[-114.539093,32.756949],[-114.539224,32.749812],[-114.564447,32.749554],[-114.564508,32.742298],[-114.581736,32.742321],[-114.581784,32.734946],[-114.612697,32.734516],[-114.618373,32.728245],[-114.688779,32.737675],[-114.701918,32.745548],[-114.719633,32.718763],[-116.04662,32.623353],[-117.124862,32.534156],[-117.136664,32.618754],[-117.168866,32.671952],[-117.196767,32.688851],[-117.213068,32.687751],[-117.236239,32.671353],[-117.246069,32.669352],[-117.25757,32.72605],[-117.25257,32.752949],[-117.25497,32.786948],[-117.26107,32.803148],[-117.280971,32.822247],[-117.28217,32.839547],[-117.27387,32.851447],[-117.26497,32.848947],[-117.25617,32.859447],[-117.25167,32.874346],[-117.25447,32.900146],[-117.28077,33.012343],[-117.315278,33.093504],[-117.328359,33.121842],[-117.362572,33.168437],[-117.469794,33.296417],[-117.50565,33.334063],[-117.547693,33.365491],[-117.59588,33.386629],[-117.607905,33.406317],[-117.645582,33.440728],[-117.684584,33.461927],[-117.691984,33.456627],[-117.715349,33.460556],[-117.726486,33.483427],[-117.784888,33.541525],[-117.814188,33.552224],[-117.840289,33.573523],[-117.87679,33.592322],[-117.927091,33.605521],[-117.940591,33.620021],[-118.000593,33.654319],[-118.029694,33.676418],[-118.088896,33.729817],[-118.132698,33.753217],[-118.180831,33.763072],[-118.187701,33.749218],[-118.181367,33.717367],[-118.207476,33.716905],[-118.258687,33.703741],[-118.317205,33.712818],[-118.360505,33.736817],[-118.385006,33.741417],[-118.396606,33.735917],[-118.411211,33.741985],[-118.428407,33.774715],[-118.405007,33.800215],[-118.394376,33.804289],[-118.392107,33.840915],[-118.460611,33.969111],[-118.482729,33.995912],[-118.519514,34.027509],[-118.543115,34.038508],[-118.569235,34.04164],[-118.609652,34.036424],[-118.668358,34.038887],[-118.706215,34.029383],[-118.744952,34.032103],[-118.783433,34.021543],[-118.805114,34.001239],[-118.854653,34.034215],[-118.928048,34.045847],[-118.938081,34.043383],[-119.004644,34.066231],[-119.037494,34.083111],[-119.088536,34.09831],[-119.109784,34.094566],[-119.130169,34.100102],[-119.18864,34.139005],[-119.216441,34.146105],[-119.257043,34.213304],[-119.278644,34.266902],[-119.290945,34.274902],[-119.313034,34.275689],[-119.337475,34.290576],[-119.370356,34.319486],[-119.388249,34.317398],[-119.42777,34.353016],[-119.461036,34.374064],[-119.536957,34.395495],[-119.559459,34.413395],[-119.616862,34.420995],[-119.638864,34.415696],[-119.671866,34.416096],[-119.688167,34.412497],[-119.684666,34.408297],[-119.709067,34.395397],[-119.729369,34.395897],[-119.794771,34.417597],[-119.835771,34.415796],[-119.853771,34.407996],[-119.873971,34.408795],[-119.925227,34.433931],[-119.956433,34.435288],[-120.008077,34.460447],[-120.038828,34.463434],[-120.088591,34.460208],[-120.141165,34.473405],[-120.25777,34.467451],[-120.295051,34.470623],[-120.341369,34.458789],[-120.471376,34.447846],[-120.47661,34.475131],[-120.511421,34.522953],[-120.581293,34.556959],[-120.622575,34.554017],[-120.637805,34.56622],[-120.645739,34.581035],[-120.640244,34.604406],[-120.60197,34.692095],[-120.60045,34.70464],[-120.614852,34.730709],[-120.62632,34.738072],[-120.637415,34.755895],[-120.616296,34.816308],[-120.610266,34.85818],[-120.616325,34.866739],[-120.639283,34.880413],[-120.647328,34.901133],[-120.670835,34.904115],[-120.63999,35.002963],[-120.629931,35.061515],[-120.630957,35.101941],[-120.644311,35.139616],[-120.651134,35.147768],[-120.662475,35.153357],[-120.675074,35.153061],[-120.698906,35.171192],[-120.714185,35.175998],[-120.74887,35.177795],[-120.754823,35.174701],[-120.756086,35.160459],[-120.760492,35.15971],[-120.778998,35.168897],[-120.786076,35.177666],[-120.856047,35.206487],[-120.89679,35.247877],[-120.862684,35.346776],[-120.866099,35.393045],[-120.884757,35.430196],[-120.907937,35.449069],[-120.946546,35.446715],[-120.969436,35.460197],[-121.003359,35.46071],[-121.101595,35.548814],[-121.126027,35.593058],[-121.143561,35.606046],[-121.166712,35.635399],[-121.251034,35.656641],[-121.284973,35.674109],[-121.289794,35.689428],[-121.314632,35.71331],[-121.315786,35.75252],[-121.332449,35.783106],[-121.388053,35.823483],[-121.413146,35.855316],[-121.439584,35.86695],[-121.462264,35.885618],[-121.461227,35.896906],[-121.472435,35.91989],[-121.4862,35.970348],[-121.503112,36.000299],[-121.531876,36.014368],[-121.574602,36.025156],[-121.590395,36.050363],[-121.592853,36.065062],[-121.606845,36.072065],[-121.618672,36.087767],[-121.629634,36.114452],[-121.680145,36.165818],[-121.717176,36.195146],[-121.779851,36.227407],[-121.797059,36.234211],[-121.813734,36.234235],[-121.826425,36.24186],[-121.851967,36.277831],[-121.874797,36.289064],[-121.888491,36.30281],[-121.894714,36.317806],[-121.892917,36.340428],[-121.905446,36.358269],[-121.903195,36.393603],[-121.914378,36.404344],[-121.91474,36.42589],[-121.9416,36.485602],[-121.938763,36.506423],[-121.944666,36.521861],[-121.925937,36.525173],[-121.932508,36.559935],[-121.942533,36.566435],[-121.957335,36.564482],[-121.978592,36.580488],[-121.970427,36.582754],[-121.941666,36.618059],[-121.93643,36.636746],[-121.923866,36.634559],[-121.890164,36.609259],[-121.889064,36.601759],[-121.860604,36.611136],[-121.831995,36.644856],[-121.814462,36.682858],[-121.807062,36.714157],[-121.805643,36.750239],[-121.788278,36.803994],[-121.809363,36.848654],[-121.862266,36.931552],[-121.894667,36.961851],[-121.930069,36.97815],[-121.95167,36.97145],[-121.972771,36.954151],[-122.012373,36.96455],[-122.023373,36.96215],[-122.027174,36.95115],[-122.050122,36.948523],[-122.105976,36.955951],[-122.155078,36.98085],[-122.20618,37.013949],[-122.252181,37.059448],[-122.284882,37.101747],[-122.306139,37.116383],[-122.337071,37.117382],[-122.337833,37.135936],[-122.359791,37.155574],[-122.367085,37.172817],[-122.390599,37.182988],[-122.405073,37.195791],[-122.407181,37.219465],[-122.419113,37.24147],[-122.411686,37.265844],[-122.40085,37.359225],[-122.423286,37.392542],[-122.443687,37.435941],[-122.452087,37.48054],[-122.472388,37.50054],[-122.493789,37.492341],[-122.499289,37.495341],[-122.516689,37.52134],[-122.519533,37.537302],[-122.513688,37.552239],[-122.517187,37.590637],[-122.501386,37.599637],[-122.494085,37.644035],[-122.496784,37.686433],[-122.514483,37.780829],[-122.50531,37.788312],[-122.485783,37.790629],[-122.478083,37.810828],[-122.463793,37.804653],[-122.407452,37.811441],[-122.398139,37.80563],[-122.385323,37.790724],[-122.375854,37.734979],[-122.356784,37.729505],[-122.361749,37.71501],[-122.370411,37.717572],[-122.391374,37.708331],[-122.387626,37.67906],[-122.374291,37.662206],[-122.3756,37.652389],[-122.387381,37.648462],[-122.386072,37.637662],[-122.35531,37.615736],[-122.358583,37.611155],[-122.373309,37.613773],[-122.378545,37.605592],[-122.360219,37.592501],[-122.317676,37.590865],[-122.305895,37.575484],[-122.262698,37.572866],[-122.214264,37.538505],[-122.196593,37.537196],[-122.194957,37.522469],[-122.168449,37.504143],[-122.155686,37.501198],[-122.140142,37.507907],[-122.127706,37.500053],[-122.111344,37.50758],[-122.111998,37.528851],[-122.147014,37.588411],[-122.145378,37.600846],[-122.152905,37.640771],[-122.163049,37.667933],[-122.246826,37.72193],[-122.257953,37.739601],[-122.257134,37.745001],[-122.242638,37.753744],[-122.253753,37.761218],[-122.293996,37.770416],[-122.330963,37.786035],[-122.33555,37.799538],[-122.333711,37.809797],[-122.323567,37.823214],[-122.303931,37.830087],[-122.301313,37.847758],[-122.310477,37.873938],[-122.309986,37.892755],[-122.32373,37.905845],[-122.33453,37.908791],[-122.35711,37.908791],[-122.367582,37.903882],[-122.385908,37.908136],[-122.39049,37.922535],[-122.413725,37.937262],[-122.430087,37.963115],[-122.415361,37.963115],[-122.399832,37.956009],[-122.367582,37.978168],[-122.361905,37.989991],[-122.367909,38.01253],[-122.340093,38.003694],[-122.321112,38.012857],[-122.300823,38.010893],[-122.283478,38.022674],[-122.262861,38.0446],[-122.273006,38.07438],[-122.314567,38.115287],[-122.366273,38.141467],[-122.39638,38.149976],[-122.403514,38.150624],[-122.409798,38.136231],[-122.439577,38.116923],[-122.454958,38.118887],[-122.489974,38.112014],[-122.483757,38.071762],[-122.499465,38.032165],[-122.497828,38.019402],[-122.481466,38.007621],[-122.462812,38.003367],[-122.452995,37.996167],[-122.448413,37.984713],[-122.456595,37.978823],[-122.471975,37.981768],[-122.488665,37.966714],[-122.487684,37.948716],[-122.479175,37.941516],[-122.48572,37.937589],[-122.499465,37.939225],[-122.503064,37.928753],[-122.478193,37.918608],[-122.471975,37.910427],[-122.472303,37.902573],[-122.458558,37.894064],[-122.448413,37.89341],[-122.438268,37.880974],[-122.45005,37.871157],[-122.462158,37.868866],[-122.480811,37.873448],[-122.479151,37.825428],[-122.505383,37.822128],[-122.548986,37.836227],[-122.561487,37.851827],[-122.584289,37.859227],[-122.60129,37.875126],[-122.656519,37.904519],[-122.682171,37.90645],[-122.70264,37.89382],[-122.727297,37.904626],[-122.736898,37.925825],[-122.766138,37.938004],[-122.783244,37.951334],[-122.797405,37.976657],[-122.821383,37.996735],[-122.856573,38.016717],[-122.882114,38.025273],[-122.939711,38.031908],[-122.956811,38.02872],[-122.981776,38.009119],[-122.97439,37.992429],[-123.024066,37.994878],[-123.011533,38.003438],[-122.99242,38.041758],[-122.960889,38.112962],[-122.949074,38.15406],[-122.953629,38.17567],[-122.965408,38.187113],[-122.968112,38.202428],[-122.993959,38.237602],[-122.968569,38.242879],[-122.967203,38.250691],[-122.977082,38.267902],[-122.986319,38.273164],[-123.002911,38.295708],[-123.024333,38.310573],[-123.038742,38.313576],[-123.051061,38.310693],[-123.053504,38.299385],[-123.063671,38.302178],[-123.074684,38.322574],[-123.068437,38.33521],[-123.068265,38.359865],[-123.128825,38.450418],[-123.202277,38.494314],[-123.249797,38.511045],[-123.287156,38.540223],[-123.331899,38.565542],[-123.343338,38.590008],[-123.371876,38.607235],[-123.398166,38.647044],[-123.441774,38.699744],[-123.461291,38.717001],[-123.514784,38.741966],[-123.541837,38.776764],[-123.579856,38.802835],[-123.58638,38.802857],[-123.605317,38.822765],[-123.647387,38.845472],[-123.659846,38.872529],[-123.71054,38.91323],[-123.725367,38.917438],[-123.726315,38.936367],[-123.738886,38.95412],[-123.729053,38.956667],[-123.711149,38.977316],[-123.6969,39.004401],[-123.690095,39.031157],[-123.693969,39.057363],[-123.713392,39.108422],[-123.721505,39.125327],[-123.737913,39.143442],[-123.742221,39.164885],[-123.765891,39.193657],[-123.774998,39.212083],[-123.777368,39.237214],[-123.787893,39.264327],[-123.803848,39.278771],[-123.803081,39.291747],[-123.811387,39.312825],[-123.808772,39.324368],[-123.822085,39.343857],[-123.826306,39.36871],[-123.81469,39.446538],[-123.766475,39.552803],[-123.787417,39.604552],[-123.782322,39.621486],[-123.792659,39.684122],[-123.808208,39.710715],[-123.829545,39.723071],[-123.838089,39.752409],[-123.839797,39.795637],[-123.851714,39.832041],[-123.907664,39.863028],[-123.930047,39.909697],[-123.954952,39.922373],[-123.980031,39.962458],[-124.035904,40.013319],[-124.056408,40.024305],[-124.068908,40.021307],[-124.079983,40.029773],[-124.080709,40.06611],[-124.110549,40.103765],[-124.187874,40.130542],[-124.214895,40.160902],[-124.296497,40.208816],[-124.320912,40.226617],[-124.327691,40.23737],[-124.34307,40.243979],[-124.363414,40.260974],[-124.363634,40.276212],[-124.347853,40.314634],[-124.362796,40.350046],[-124.365357,40.374855],[-124.373599,40.392923],[-124.391496,40.407047],[-124.409591,40.438076],[-124.38494,40.48982],[-124.383224,40.499852],[-124.387023,40.504954],[-124.382816,40.519],[-124.329404,40.61643],[-124.158322,40.876069],[-124.137066,40.925732],[-124.118147,40.989263],[-124.112165,41.028173],[-124.125448,41.048504],[-124.138217,41.054342],[-124.153622,41.05355],[-124.154513,41.087159],[-124.160556,41.099011],[-124.159065,41.121957],[-124.165414,41.129822],[-124.158539,41.143021],[-124.149674,41.140845],[-124.1438,41.144686],[-124.106986,41.229678],[-124.072294,41.374844],[-124.063076,41.439579],[-124.066057,41.470258],[-124.081427,41.511228],[-124.081987,41.547761],[-124.092404,41.553615],[-124.101123,41.569192],[-124.097385,41.585251],[-124.100961,41.602499],[-124.114413,41.616768],[-124.120225,41.640354],[-124.135552,41.657307],[-124.147412,41.717955],[-124.164716,41.740126],[-124.17739,41.745756],[-124.194953,41.736778],[-124.23972,41.7708],[-124.248704,41.771459],[-124.255994,41.783014],[-124.245027,41.7923],[-124.230678,41.818681],[-124.208439,41.888192],[-124.203402,41.940964],[-124.204948,41.983441],[-124.211605,41.99846],[-123.656998,41.995137],[-123.624554,41.999837],[-123.347562,41.999108],[-123.145959,42.009247],[-123.045254,42.003049],[-122.893961,42.002605],[-122.289533,42.007764]]]]},\"properties\":{\"name\":\"California\",\"nation\":\"USA \"}}]}","volume":"94","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Lucas, Madeleine C.","contributorId":263451,"corporation":false,"usgs":false,"family":"Lucas","given":"Madeleine","email":"","middleInitial":"C.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hough, Susan E. 0000-0002-5980-2986","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":263442,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927608,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stein, Seth","contributorId":263457,"corporation":false,"usgs":false,"family":"Stein","given":"Seth","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927609,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Salditch, Leah Marschall 0000-0002-4478-1836","orcid":"https://orcid.org/0000-0002-4478-1836","contributorId":297144,"corporation":false,"usgs":true,"family":"Salditch","given":"Leah","email":"","middleInitial":"Marschall","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":927610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gallahue, Molly M.","contributorId":263448,"corporation":false,"usgs":false,"family":"Gallahue","given":"Molly","email":"","middleInitial":"M.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927611,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neely, James S.","contributorId":263454,"corporation":false,"usgs":false,"family":"Neely","given":"James","email":"","middleInitial":"S.","affiliations":[{"id":25254,"text":"Northwestern University","active":true,"usgs":false}],"preferred":false,"id":927612,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Abrahamson, Norman A.","contributorId":45202,"corporation":false,"usgs":false,"family":"Abrahamson","given":"Norman A.","affiliations":[{"id":13174,"text":"Pacific Gas & Electric","active":true,"usgs":false}],"preferred":false,"id":927613,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70244155,"text":"sir20235036 - 2023 - Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","interactions":[],"lastModifiedDate":"2026-03-06T21:18:08.428516","indexId":"sir20235036","displayToPublicDate":"2023-06-21T07:56:13","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5036","displayTitle":"Simulation of Future Streamflow and Irrigation Demand Based on Climate and Urban Growth Projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","title":"Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65","docAbstract":"Water resources in the coastal region of North Carolina and South Carolina (Coastal Carolinas) are currently under stress from competing ecological and societal needs. Projected changes in climate and population are expected to place even more stress on water resources in the region. The Coastal Carolinas Focus Area Study was initiated by the U.S. Geological Survey Water Availability and Use Science Program’s National Water Census to investigate these stressors and their effects on water resources for the Coastal Carolinas. As part of that study, the Soil and Water Assessment Tool (SWAT) model was used to investigate future streamflow and irrigation demand under six scenarios for the Cape Fear and Pee Dee River Basins, which flow through the Coastal Carolinas and into the Atlantic Ocean.
For each river basin, historical (2000 through 2014) Soil and Water Assessment Tool models were minimally calibrated, and future (2055 through 2065) scenario models were developed based on three alternative global climate models, two alternative urban growth projections, and water-use projections that correspond to each global climate model and urban growth projection pair. The river basins were delineated into 2,928 and 5,678 subbasins for the Cape Fear and Pee Dee, respectively, each approximately 2.6 square miles (mi2) in size. The best available water-use and wastewater discharge data were used for historical model calibration. The models simulated monthly mean streamflow with median Nash-Sutcliffe efficiency values of 0.53 (n = 36) and 0.61 (n = 33) in the Cape Fear and Pee Dee River Basins, respectively. Average percent bias was −4.8 percent for the Cape Fear River Basin and −1.2 percent for the Pee Dee River Basin. Catchments for streamgages chosen for model calibration that were small (less than 100 mi2) to medium (100–1,000 mi2) in area tended to perform better than larger catchments (greater than 1,000 mi2).
Historical models were used to develop future model scenarios by replacing historical weather, land-use, and water-use input datasets with projected datasets. One small, gaged catchment was selected to illustrate how the models can be used to evaluate the relative differences in simulated streamflow resulting from alternative global climate models and urban growth projections. For the selected catchment, future climate projections had a much greater influence on simulated streamflow than urban growth projections. Simulated cumulative monthly mean streamflow results for this catchment differed by 26 percent under alternative global climate models and differed by 2.4 percent under alternative urban growth projections.
Irrigation demand was modeled for subbasins with cropland. Simulated differences in irrigation demand were more pronounced and widespread across the model domain under the alternative future climate scenarios compared to alternative urban growth scenarios.
The calibrated and future scenario models have the capability to run on a daily time step and simulate streamflow and irrigation demand for thousands of small subbasins in the Cape Fear and Pee Dee River Basins. The models and underlying datasets enable future analyses for large and small areas within the basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235036","issn":"2328-0328","programNote":"Water Availability and Use Science Program","usgsCitation":"Gurley, L.N., García, A.M., Pfeifle, C.A., and Sanchez, G.M., 2023, Simulation of future streamflow and irrigation demand based on climate and urban growth projections in the Cape Fear and Pee Dee River Basins, North Carolina and South Carolina, 2055–65: U.S. Geological Survey Scientific Investigations Report 2023–5036, 23 p., https://doi.org/10.3133/sir20235036.","productDescription":"Report: viii, 23 p.; 2 Data Releases","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-118241","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":417754,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P951VE5P","text":"USGS Data Release—Soil and Water Assessment Tool (SWAT) models for the Pee Dee River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections"},{"id":417749,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5036/sir20235036.pdf","size":"12.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5036"},{"id":500906,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114934.htm","linkFileType":{"id":5,"text":"html"}},{"id":417753,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98PVDBW","text":"USGS Data Release—Soil and Water Assessment Tool (SWAT) models for the Cape Fear River Basin used to simulate future streamflow and irrigation demand based on climate and urban growth projections"},{"id":417752,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5036/images/"},{"id":417751,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235036/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5036 HTML"},{"id":417750,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5036/sir20235036.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5036 XML"},{"id":417748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5036/coverthb.jpg"}],"country":"United States","state":"North Carolina, South Carolina","otherGeospatial":"Cape Fear and Pee Dee River Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.57121892850378,\n 32.91032390352079\n ],\n [\n -79.1296411830063,\n 33.177656538712625\n ],\n [\n -78.78619182539771,\n 33.72348311575605\n ],\n [\n -77.91939106571822,\n 33.920494939888584\n ],\n [\n -77.52687751416516,\n 34.40766001221573\n ],\n [\n -76.77455987368852,\n 35.02604160967191\n ],\n [\n -78.54904822133423,\n 36.169665661169745\n ],\n [\n -79.23594693655193,\n 36.51875607367013\n ],\n [\n -80.06186086794473,\n 36.51218395574713\n ],\n [\n -81.09220894077154,\n 36.66976065554749\n ],\n [\n -81.87723604387764,\n 35.792485806453826\n ],\n [\n -80.6996953892185,\n 34.985853498019594\n ],\n [\n -80.79782377710687,\n 34.42115219807647\n ],\n [\n -80.72422748619073,\n 33.5123831107352\n ],\n [\n -79.57121892850378,\n 32.91032390352079\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"For more information about this publication, contact
Program Coordinator
U.S. Geological Survey
Water Availability and Use Science Program
National Water Quality Program
Email: wausp-info@usgs.gov
For additional information, visit
https://www.usgs.gov/programs/national-water-quality-program
How to identify the drivers of population connectivity remains a fundamental question in ecology and evolution. Answering this question can be challenging in aquatic environments where dynamic lake and ocean currents coupled with high levels of dispersal and gene flow can decrease the utility of modern population genetic tools. To address this challenge, we used RAD-Seq to genotype 959 yellow perch (Perca flavescens), a species with an ~40-day pelagic larval duration (PLD), collected from 20 sites circumscribing Lake Michigan. We also developed a novel, integrative approach that couples detailed biophysical models with eco-genetic agent-based models to generate “predictive” values of genetic differentiation. By comparing predictive and empirical values of genetic differentiation, we estimated the relative contributions for known drivers of population connectivity (e.g., currents, behavior, PLD). For the main basin populations (i.e., the largest contiguous portion of the lake), we found that high gene flow led to low overall levels of genetic differentiation among populations (FST = 0.003). By far the best predictors of genetic differentiation were connectivity matrices that were derived from periods of time when there were strong and highly dispersive currents. Thus, these highly dispersive currents are driving the patterns of population connectivity in the main basin. We also found that populations from the northern and southern main basin are slightly divergent from one another, while those from Green Bay and the main basin are highly divergent (FST = 0.11). By integrating biophysical and eco-genetic models with genome-wide data, we illustrate that the drivers of population connectivity can be identified in high gene flow systems.
Introduction: Animal movements are influenced by landscape features; disturbances to the landscape can alter movements, dispersal, and ultimately connectivity among populations. Faster or longer movements adjacent to a localized disturbance or within disturbed areas could indicate reduced habitat quality whereas slower or shorter movements and reduced movements may indicate greater availability of resources. The Mojave desert tortoise (Gopherus agassizii) is a threatened species that is challenged by anthropogenic disturbances.
Methods: We studied tortoise movements using Global Positioning System (GPS) loggers at multiple sites in the Mojave Desert of Nevada and California. Tortoises at our sites encountered localized, linear human infrastructure, including paved roads, dirt roads, and fences, as well as landscape-scale disturbances [wildfire, off highway vehicle use (OHV), livestock grazing area]. We fit two-state (moving and encamped) Hidden Markov models to GPS logger data to infer how tortoise movement behavior relates to anthropogenic and natural features.
Results: We found that temporal covariates, individual-level random effects (intercepts), and sex best explained state transition probability in all sites. We compared relationships between tortoise movement and linear disturbances, which varied depending on site and context. Tortoises made longer movements within the OHV recreation area, near most dirt roads, and near a low-traffic paved road, indicating that tortoises avoid these habitat disturbances. Conversely, tortoises made shorter movements in areas of higher slope and near highways, suggesting that these features may restrict movement or provide resources that result in prolonged use (e.g., forage or drinking locations). Tortoises that encountered fences around utility-scale solar installations were more active and made longer movements near fences, indicative of pacing behavior.
Discussion: These results provide insight into how different disturbances alter tortoise movement behavior and modify tortoise habitat use, providing information that can be used to manage tortoise habitat.
","language":"English","publisher":"Frontiers","doi":"10.3389/fevo.2023.971337","usgsCitation":"Hromada, S.J., Esque, T., Vandergast, A.G., Drake, K.K., Chen, F., Gottsacker, B.O., Swart, J.A., and Nussear, K., 2023, Linear and landscape disturbances alter Mojave desert tortoise movement behavior: Frontiers in Ecology and Evolution, v. 11, 971337, 14 p., https://doi.org/10.3389/fevo.2023.971337.","productDescription":"971337, 14 p.","ipdsId":"IP-144743","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442999,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2023.971337","text":"Publisher Index Page"},{"id":418620,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.85708110970195,\n 36.70940504207991\n ],\n [\n -116.85708110970195,\n 34.67613588087687\n ],\n [\n -114.55094165903384,\n 34.67613588087687\n ],\n [\n -114.55094165903384,\n 36.70940504207991\n ],\n [\n -116.85708110970195,\n 36.70940504207991\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-06-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hromada, Steven J.","contributorId":245147,"corporation":false,"usgs":false,"family":"Hromada","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":876504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Esque, Todd 0000-0002-4166-6234 tesque@usgs.gov","orcid":"https://orcid.org/0000-0002-4166-6234","contributorId":195896,"corporation":false,"usgs":true,"family":"Esque","given":"Todd","email":"tesque@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vandergast, Amy G. 0000-0002-7835-6571","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":57201,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876506,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, K. Kristina 0000-0003-0711-7634 kdrake@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-7634","contributorId":3799,"corporation":false,"usgs":true,"family":"Drake","given":"K.","email":"kdrake@usgs.gov","middleInitial":"Kristina","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876507,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chen, Felicia 0000-0002-7408-5946","orcid":"https://orcid.org/0000-0002-7408-5946","contributorId":210469,"corporation":false,"usgs":true,"family":"Chen","given":"Felicia","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876508,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gottsacker, Benjamin O 0000-0002-9481-6267","orcid":"https://orcid.org/0000-0002-9481-6267","contributorId":315424,"corporation":false,"usgs":true,"family":"Gottsacker","given":"Benjamin","email":"","middleInitial":"O","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876509,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Swart, Jordan Andrew 0000-0002-3348-4721","orcid":"https://orcid.org/0000-0002-3348-4721","contributorId":315425,"corporation":false,"usgs":true,"family":"Swart","given":"Jordan","email":"","middleInitial":"Andrew","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":876510,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nussear, Ken E","contributorId":221816,"corporation":false,"usgs":false,"family":"Nussear","given":"Ken E","affiliations":[{"id":16686,"text":"University of Nevada, Reno","active":true,"usgs":false}],"preferred":false,"id":876511,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70246266,"text":"70246266 - 2023 - Putting down roots: Afforestation and bank cohesion of Icelandic Rivers","interactions":[],"lastModifiedDate":"2023-11-07T15:07:54.763698","indexId":"70246266","displayToPublicDate":"2023-06-21T07:04:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Putting down roots: Afforestation and bank cohesion of Icelandic Rivers","docAbstract":"Riparian vegetation is widely recognized as a critical component of functioning fluvial systems. Human pressures on woody vegetation including riparian areas have had lasting effects, especially at high latitude. In Iceland, prior to human settlement, native downy birch woodlands covered approximately 15%–40% of the land area compared to 1%–2% today. Afforestation efforts include planting seedlings, protecting native forest remnants, and acquiring land areas as national forests. The planted and protected nature of vegetation along rivers within forests provides a unique opportunity to evaluate the various taxa within riparian zones and the channel stabilizing characteristics of the vegetation used in afforestation. We investigated bank properties, sediment textures, and root characteristics within riparian zones along four rivers in forests in Iceland. Bank sediment textures are dominantly sandy loam overlying coarser textures. Undercut banks are common because of erosion of the less cohesive subsurface layer. Quantitative root data indicate that the woody taxa have greater root densities, rooting depths, and more complex root structures than forbs or graminoids. The native downy birch has the highest root densities, with <1 mm roots most abundant. Modeling of added bank cohesion indicates that willow provides up to six times and birch up to four times more added cohesion to the coarse sediment textures comprising stream banks compared to no vegetation. We conclude that planting and protecting the native birch and willow helps to reduce bank erosion, especially where long-term grazing exclusion can be maintained.
A central focus of modern fisheries management is eradicating invaders that threaten imperiled native fishes. However, vast landscapes and limited funding and personnel resources demand a prioritized approach to management. Brook Stickleback Culaea inconstans (Kirtland, 1840) is an aquatic invasive species in Wyoming, USA, that may pose a risk to native biodiversity. Our aim was to evaluate Brook Stickleback’s invasive potential in the North Platte River drainage. We updated the current distribution of Brook Stickleback, evaluated for possible range expansion, and determined landscape-level habitat drivers and occurrence potential for streams across the North Platte River drainage. Additionally, we examined Brook Stickleback’s spatial overlap with native nongame fishes. At the landscape scale, Brook Stickleback preferred low-gradient streams with moderate disturbance risk. Though we did not find evidence of current Brook Stickleback range expansion 61% of streams in the drainage have landscape-level environmental characteristics that are likely suitable for Brook Stickleback, creating potential for future expansion. Brook Stickleback overlapped spatially with 13 native nongame species, though spatial overlap was less common than expected for species with similar habitat preferences. Our work serves as a case study of the factors to consider when assessing a species’ invasive potential in a previously unstudied region.
Management regimes on publicly owned freshwater wetlands in the Mississippi Flyway of North America (i.e., Flyway) have historically emphasized waterfowl, but there is limited information on how waterfowl-focused wetland management affects other wetland-dependent wildlife. Secretive marsh birds (SMBs) depend on wetlands with emergent vegetation throughout their migratory life cycle and often encounter vegetation and water conditions resulting from waterfowl-focused management regimes. Thus, there is a need for better understanding of how SMBs are affected by wetland management and the extent to which waterfowl-focused management regimes provide habitat for SMBs. In this review, we identify the vegetation and water conditions resulting from typical management objectives on freshwater emergent wetlands in the Flyway, review and qualitatively synthesize results from studies that directly evaluate how wetland management practices affect SMBs or their habitat, and assess how the vegetation and water conditions being produced for target species (mainly waterfowl) align with SMB habitat requirements. We searched online databases and used Google Scholar to locate peer-reviewed literature, technical reports, and graduate theses that pertained to responses of SMBs or their habitat to water-level manipulation, herbicide application, prescribed fire, disking, mowing, and planting crops. There are several management strategies that complement SMBs and waterfowl, such as reducing cover of woody species and providing flooded emergent vegetation. We also highlight management strategies that may not currently align with SMB life-cycle needs and suggest adjustments that might promote habitat for SMBs while still achieving waterfowl population objectives. For example, adjusting the dates and duration of spring water-level drawdowns on a portion of wetlands within a larger complex can provide for spring migrating waterfowl and ensure habitat for migrating and nesting SMBs. Ideally, future studies would address how modifications to management practices affect SMBs and monitor potential effects on waterfowl, resulting in a more holistic approach to wetland management.
The demography of, and factors that influence these metrics, are largely unknown for most vultures in the Americas. Survivorship of Turkey Vultures (Cathartes aura) may be influenced by landscape heterogeneity and human disturbance. We quantified the effects of landscape composition (Shannon’s diversity index) and configuration (contagion, edge density, and largest patch index), and human disturbance (road density) on the annual and seasonal survival probabilities of the three North American breeding populations (western, central, and eastern) of Turkey Vultures that spend the nonbreeding season in the southeastern portion of the Nearctic and the northern Neotropics during a 17-year period. We used Cox’s proportional hazards models with time-varying covariates to estimate spatial and temporal changes in survival rates of adult Turkey Vultures. Road density, but not landscape composition or configuration, influenced survival rates in space and time. Overall annual survival averaged 0.87 (95% confidence interval [CI]: 0.74–0.98). Mortality risk was low in western and central populations (hazard ratio < 1) but was 3.7 times greater for vultures in the eastern population. Survival during the breeding (0.97, 95% CI: 0.96–0.98) and outbound migration (1.0, 95% CI: 1–1) seasons was significantly higher than the other seasons. Average survival tended to be higher for nonbreeding (0.81, 95% CI: 0.71–0.88) compared to return migration (0.69, 95% CI: 0.56–0.81) seasons. The risk of mortality for all vulture populations increased with road density, and this was greater during the nonbreeding and return migration seasons. The spatial variation in road density across the Americas may generate a network of ecological traps for Turkey Vultures induced to stop in areas of greater road-kill abundance. Road-killed animals acting as an attractant for vultures can increase the occurrence of vulture–vehicle collisions and potentially aggravate human–wildlife conflicts. Further analyses are needed to address survivorship and mortality factors for young birds. Our results may help the implementation of specific mitigation efforts to reduce human–vulture conflicts and vulture mortality. For instance, concentrating efforts to remove road-killed animals in areas where road density is highest can likely reduce vulture–vehicle collisions and associated mortalities of these birds.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duad024","usgsCitation":"Naveda-Rodriguez, A., Bildstein, K.L., Barber, D.R., Therrien, J., Avery, M., Kluever, B., Rush, S.A., and Vilella, F., 2023, Turkey Vulture survival is reduced in areas of greater road density, v. 125, no. 4, duad024, 9 p., https://doi.org/10.1093/ornithapp/duad024.","productDescription":"duad024, 9 p.","ipdsId":"IP-149701","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":498061,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duad024","text":"Publisher Index Page"},{"id":432157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Naveda-Rodriguez, Adrian","contributorId":340683,"corporation":false,"usgs":false,"family":"Naveda-Rodriguez","given":"Adrian","email":"","affiliations":[{"id":17848,"text":"Mississippi State University","active":true,"usgs":false}],"preferred":false,"id":907452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bildstein, Keith L.","contributorId":150854,"corporation":false,"usgs":false,"family":"Bildstein","given":"Keith","email":"","middleInitial":"L.","affiliations":[{"id":18119,"text":"Hawk Mountain Sanctuary, Acopian Center for Conservation Learning","active":true,"usgs":false}],"preferred":false,"id":907453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber, David R.","contributorId":340686,"corporation":false,"usgs":false,"family":"Barber","given":"David","email":"","middleInitial":"R.","affiliations":[{"id":81649,"text":"Acopian Center for Conservation Science","active":true,"usgs":false}],"preferred":false,"id":907454,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Therrien, Jean-Francois","contributorId":336846,"corporation":false,"usgs":false,"family":"Therrien","given":"Jean-Francois","email":"","affiliations":[{"id":80885,"text":"Université de Moncton, Moncton, NB, Canada","active":true,"usgs":false}],"preferred":false,"id":907455,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Avery, Michael L.","contributorId":48890,"corporation":false,"usgs":true,"family":"Avery","given":"Michael L.","affiliations":[],"preferred":false,"id":907456,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kluever, Bryan M.","contributorId":340689,"corporation":false,"usgs":false,"family":"Kluever","given":"Bryan M.","affiliations":[{"id":36658,"text":"U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":907457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rush, Scott A.","contributorId":92139,"corporation":false,"usgs":true,"family":"Rush","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":907458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vilella, Francisco 0000-0003-1552-9989 fvilella@usgs.gov","orcid":"https://orcid.org/0000-0003-1552-9989","contributorId":171363,"corporation":false,"usgs":true,"family":"Vilella","given":"Francisco","email":"fvilella@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907459,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245601,"text":"70245601 - 2023 - A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","interactions":[],"lastModifiedDate":"2023-06-26T13:27:30.871321","indexId":"70245601","displayToPublicDate":"2023-06-20T08:23:18","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"displayTitle":"A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","title":"A body composition model with multiple storage compartments for polar bears (Ursus maritimus)","docAbstract":"Climate warming is rapidly altering Arctic ecosystems. Polar bears (Ursus maritimus) need sea ice as a platform from which to hunt seals, but increased sea-ice loss is lengthening periods when bears are without access to primary hunting habitat. During periods of food scarcity, survival depends on the energy that a bear has stored in body reserves, termed storage energy, making this a key metric in predictive models assessing climate change impacts on polar bears. Here, we developed a body composition model for polar bears that estimates storage energy while accounting for changes in storage tissue composition. We used data of dissected polar bears (n = 31) to link routinely collected field measures of total body mass and straight-line body length to the body composition of individual bears, described in terms of structural mass and two storage compartments, adipose and muscle. We then estimated the masses of metabolizable proteins and lipids within these storage compartments, giving total storage energy. We tested this multi-storage model by using it to predict changes in the lipid stores from an independent dataset of wild polar bears (n = 36) that were recaptured 8–200 days later. Using length and mass measurements, our model successfully predicted direct measurements of lipid changes via isotopic dilutions (root mean squared error of 14.5 kg). Separating storage into two compartments, and allowing the molecular composition of storage to vary, provides new avenues for quantifying energy stores of individuals across their life cycle. The multi-storage body composition model thus provides a basis for further exploring energetic costs of physiological processes that contribute to individual survival and reproductive success. Given bioenergetic models are increasingly used as a tool to predict individual fitness and population dynamics, our approach for estimating individual energy stores could be applicable to a wide range of species.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/conphys/coad043","usgsCitation":"Penk, S.R., Sadana, P., Archer, L.C., Pagano, A.M., Cattet, M.R., Lunn, N.J., Thiemann, G.W., and Molnar, P.K., 2023, A body composition model with multiple storage compartments for polar bears (Ursus maritimus), v. 11, no. 1, coad043, 20 p., https://doi.org/10.1093/conphys/coad043.","productDescription":"coad043, 20 p.","ipdsId":"IP-142122","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":443007,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/conphys/coad043","text":"Publisher Index Page"},{"id":418459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"1","noUsgsAuthors":false,"publicationDate":"2023-06-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Penk, Stephanie R. 0000-0002-8027-4372","orcid":"https://orcid.org/0000-0002-8027-4372","contributorId":312472,"corporation":false,"usgs":false,"family":"Penk","given":"Stephanie","email":"","middleInitial":"R.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadana, Pranav","contributorId":312473,"corporation":false,"usgs":false,"family":"Sadana","given":"Pranav","email":"","affiliations":[{"id":16930,"text":"University of Winnipeg","active":true,"usgs":false}],"preferred":false,"id":876208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archer, Louise C. 0000-0002-1983-3825","orcid":"https://orcid.org/0000-0002-1983-3825","contributorId":312474,"corporation":false,"usgs":false,"family":"Archer","given":"Louise","email":"","middleInitial":"C.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876209,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":876210,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cattet, Marc R. L. 0000-0002-2318-1452","orcid":"https://orcid.org/0000-0002-2318-1452","contributorId":312475,"corporation":false,"usgs":false,"family":"Cattet","given":"Marc","email":"","middleInitial":"R. L.","affiliations":[{"id":13248,"text":"University of Saskatchewan","active":true,"usgs":false}],"preferred":false,"id":876211,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lunn, Nicholas J. 0000-0003-0189-5494","orcid":"https://orcid.org/0000-0003-0189-5494","contributorId":312476,"corporation":false,"usgs":false,"family":"Lunn","given":"Nicholas","email":"","middleInitial":"J.","affiliations":[{"id":36681,"text":"Environment and Climate Change Canada","active":true,"usgs":false}],"preferred":false,"id":876212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thiemann, Gregory W.","contributorId":83023,"corporation":false,"usgs":false,"family":"Thiemann","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":27291,"text":"York University, Toronto, ON","active":true,"usgs":false}],"preferred":false,"id":876213,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Molnar, Peter K. 0000-0001-7260-2674","orcid":"https://orcid.org/0000-0001-7260-2674","contributorId":312477,"corporation":false,"usgs":false,"family":"Molnar","given":"Peter","email":"","middleInitial":"K.","affiliations":[{"id":67687,"text":"University of Toronto Scarborough","active":true,"usgs":false}],"preferred":false,"id":876214,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70245787,"text":"70245787 - 2023 - Ensemble estimation of historical evapotranspiration for the conterminous U.S.","interactions":[],"lastModifiedDate":"2023-06-27T11:48:52.454255","indexId":"70245787","displayToPublicDate":"2023-06-20T06:45:54","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Ensemble estimation of historical evapotranspiration for the conterminous U.S.","docAbstract":"Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall-to-wall explanatory variable maps to generate CONUS-wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national-scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.
Assessing the influence of marshes on mitigating flooding along estuarine shorelines under the pressures of sea level rise requires understanding wave transformation across the marsh. A numerical model was applied to investigate how vegetated marshes influence wave transformation. XBeach non-hydrostatic (XB-NH) was calibrated and validated with high frequency pressure data from the marsh at China Camp State Park in San Pablo Bay, California (USA). The model was used to examine how marsh and hydrodynamic characteristics change the potential for marshes to mitigate wave driven flooding. Model results demonstrate that hydrodynamics, vegetation, and marsh width influence wave transformation most, while marsh morphology parameters such as elevation and slope had least effect. Results suggest that in the range of settings explored here (incident wave heights ranging from 0.5 to 3 m and water levels ranging from current mean higher high water to 3 m above current mean higher high water), in comparison to wave propagation over an unvegetated mudflat, marsh vegetation reduces runup by a median of 40 cm and wave height by a median of 35 cm. Results illustrate how marshes can be strategically utilized to provide flood reduction benefits.
On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water-rich plume at least 58 km high. Using a combination of satellite- and ground-based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min−1) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co-located with an internal gravity wave traveling >80 m s−1 in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high-current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 109 kg s−1), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma-water interaction at the submarine vent.
Sea level rise is affecting reaches of coastal rivers by increasing water levels and propagating tides inland. The transition of river systems into tidal estuaries has been neglected in hydrogeomorphic studies. A better understanding of transitioning reaches is critical to understanding ecosystem dynamics, services, and developing predictive capabilities of change as sea levels rise. We hypothesized that river-floodplain morphology changes from fluvial to tidally dominated regimes, changing suspended sediment concentrations (SSC), sediment deposition, vegetation, and landforms. We tested this using lidar, satellite imagery, and SSC and conductivity measurements along two Coastal Plain rivers of Virginia, USA. Geomorphic channel and floodplain parameters indicated breakpoints into three regimes: fluvial, mixed, and tidal. Maximum channel width occurred with minimum floodplain widths in the mixed regime. Tidal freshwater forests had considerable elevational overlap with marshes but typically were 9.5 cm higher. SSC increased with shoal width through the mixed reaches, with maxima in the tidal reaches where estuarine influences increased. Channel erosion rates indicated that modern sediment loads and hydrology produce slow changes to channel planform and geomorphology that may not be apparent from visual comparisons. Our findings indicated that tidal floodplain forests and marshes in the mixed and tidal reaches are expected to convert to marshes or open water as sea levels rise as limited gradual sloping area exists between the active floodplain and terraces. Tidal floodplain surfaces along mixed hydrology reaches, inland of the estuarine turbidity maximum may be expected to convert to open water while inland sloping floodplains could support tidal wetland migration.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-023-01226-6","usgsCitation":"Kroes, D., Noe, G.E., Hupp, C.R., Doody, T.R., and Bukaveckas, P., 2023, Hydrogeomorphic changes along mid-Atlantic coastal plain rivers transitioning from non-tidal to tidal: Implications for a rising sea level: Estuaries and Coasts, v. 46, p. 1438-1458, https://doi.org/10.1007/s12237-023-01226-6.","productDescription":"21 p.","startPage":"1438","endPage":"1458","ipdsId":"IP-135089","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":435281,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B1UCFT","text":"USGS data release","linkHelpText":"Hydrogeomorphic data along transitioning Coastal Plain rivers (Mattaponi and Pamunkey Rivers): implications for a rising sea level"},{"id":418223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Chesapeake Bay Watershed, Mattaponi River, Pamunkey River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -76.65344171287853,\n 37.86125997466432\n ],\n [\n -77.48781222047384,\n 37.86125997466432\n ],\n [\n -77.48781222047384,\n 37.46887702495529\n ],\n [\n -76.65344171287853,\n 37.46887702495529\n ],\n [\n -76.65344171287853,\n 37.86125997466432\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"46","noUsgsAuthors":false,"publicationDate":"2023-06-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Kroes, Daniel 0000-0001-9104-9077 dkroes@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-9077","contributorId":3830,"corporation":false,"usgs":true,"family":"Kroes","given":"Daniel","email":"dkroes@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":875657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":875659,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doody, Thomas Rossiter 0000-0002-2102-738X tdoody@contractor.usgs.gov","orcid":"https://orcid.org/0000-0002-2102-738X","contributorId":223569,"corporation":false,"usgs":true,"family":"Doody","given":"Thomas","email":"tdoody@contractor.usgs.gov","middleInitial":"Rossiter","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":875660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bukaveckas, P.A. 0000-0002-2636-7818","orcid":"https://orcid.org/0000-0002-2636-7818","contributorId":310428,"corporation":false,"usgs":false,"family":"Bukaveckas","given":"P.A.","affiliations":[{"id":38728,"text":"Virginia Commonwealth University","active":true,"usgs":false}],"preferred":false,"id":875661,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70245161,"text":"70245161 - 2023 - High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia","interactions":[],"lastModifiedDate":"2023-06-19T17:12:31.329271","indexId":"70245161","displayToPublicDate":"2023-06-19T11:51:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia","docAbstract":"During a volcanic crisis, high-rate, localized deformation can indicate magma close to the surface, with important implications for eruption forecasting. However, only a few such examples have been reported, because frequent, dense monitoring is needed. High-resolution Synthetic Aperture Radar (SAR) is capable of achieving <1 m spatial resolution and sub-weekly revisit times, but is under-used. Here we use high-resolution satellite SAR imagery from COSMO-SkyMed, TerraSAR-X, and Sentinel-1 to detect intra-crater uplift preceding the November 2017 onset of eruptive activity at Agung, Indonesia. Processing the SAR imagery with an up-to-date, accurate, high-resolution digital elevation model was crucial for preventing aliasing of the deformation signal and for accurate georeferencing. We show that >15 cm of line-of-sight shortening occurred over a 400-by-400 m area on the crater floor in September-October 2017, accompanying a deep seismic swarm and flank dyke intrusion. We attribute the deformation to the pressurization of a shallow (<200 m deep) hydrothermal system by the injection of magmatic gases and fluids. We also observe a second pulse of intra-crater deformation of 3–5 cm within 4 days to 11 hr prior to the first phreatomagmatic eruption, which is consistent with interaction between the hydrothermal system and the ascending magma. This phreatomagmatic eruption created the central pathway used during the final stages of magma ascent. Our observations have important implications for understanding unrest and eruption forecasting, and demonstrate the potential of monitoring with high-resolution SAR.
","language":"English","publisher":"Wiley","doi":"10.1029/2022JB025669","usgsCitation":"Bemelmans, M., Biggs, J., Poland, M.P., Wookey, J., Ebmeier, S., Diefenbach, A., and Syahbana, D.D., 2023, High-resolution InSAR reveals localized pre-eruptive deformation inside the crater of Agung Volcano, Indonesia: Journal of Geophysical Research B: Solid Earth, v. 128, no. 5, e2022JB025669, 27 p., https://doi.org/10.1029/2022JB025669.","productDescription":"e2022JB025669, 27 p.","ipdsId":"IP-145594","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":443019,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022jb025669","text":"Publisher Index Page"},{"id":418219,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Indonesia","otherGeospatial":"Agung Volcano, Bali","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 115.49507682936888,\n -8.406300591448016\n ],\n [\n 115.51391236474785,\n -8.425323602450476\n ],\n [\n 115.52198473705289,\n -8.44129377777513\n ],\n [\n 115.53026409326424,\n -8.430851814741729\n ],\n [\n 115.55944882390781,\n -8.390309758644221\n ],\n [\n 115.58221705348922,\n -8.367402141157967\n ],\n [\n 115.58263102130024,\n -8.335659853363467\n ],\n [\n 115.5604837434351,\n -8.30350536078592\n ],\n [\n 115.524675527824,\n -8.28425236518369\n ],\n [\n 115.48783239268414,\n -8.28793125803746\n ],\n [\n 115.44064006228348,\n -8.31005143321569\n ],\n [\n 115.42863499577669,\n -8.344867699330223\n ],\n [\n 115.44871243458851,\n -8.381933371662427\n ],\n [\n 115.49507682936888,\n -8.406300591448016\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"128","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Bemelmans, Mark","contributorId":310454,"corporation":false,"usgs":false,"family":"Bemelmans","given":"Mark","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biggs, Juliet","contributorId":206389,"corporation":false,"usgs":false,"family":"Biggs","given":"Juliet","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":875720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wookey, James","contributorId":310455,"corporation":false,"usgs":false,"family":"Wookey","given":"James","email":"","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":875721,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ebmeier, Susanna","contributorId":174225,"corporation":false,"usgs":false,"family":"Ebmeier","given":"Susanna","affiliations":[{"id":7172,"text":"University of Bristol, U.K. and University of Oregon, Eugene","active":true,"usgs":false}],"preferred":false,"id":875722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":204743,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":875723,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Syahbana, Devy Damil","contributorId":243233,"corporation":false,"usgs":false,"family":"Syahbana","given":"Devy","email":"","middleInitial":"Damil","affiliations":[],"preferred":false,"id":875724,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70245153,"text":"70245153 - 2023 - A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong","interactions":[],"lastModifiedDate":"2023-06-19T16:38:44.155755","indexId":"70245153","displayToPublicDate":"2023-06-19T11:22:12","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong","docAbstract":"Non-invasively collected faecal samples are an alternative source of DNA to tissue samples, that may be used in genetic studies of wildlife when direct sampling of animals is difficult. Although several faecal DNA extraction methods exist, their efficacy varies between species. Previous attempts to amplify mitochondrial DNA (mtDNA) markers from faeces of wild dugongs (Dugong dugon) have met with limited success and nuclear markers (microsatellites) have been unsuccessful. This study aimed to establish a tool for sampling both mtDNA and nuclear DNA (nDNA) from dugong faeces by modifying approaches used in studies of other large herbivores. First, a streamlined, cost-effective DNA extraction method that enabled the amplification of both mitochondrial and nuclear markers from large quantities of dugong faeces was developed. Faecal DNA extracted using a new ‘High Volume- Cetyltrimethyl Ammonium Bromide- Phenol-Chloroform-Isoamyl Alcohol’ (HV-CTAB-PCI) method was found to achieve comparable amplification results to extraction of DNA from dugong skin. As most prevailing practices advocate sampling from the outer surface of a stool to maximise capture of sloughed intestinal cells, this study compared amplification success of mtDNA between the outer and inner layers of faeces, but no difference in amplification was found. Assessment of the impacts of faecal age or degradation on extraction, however, demonstrated that fresher faeces with shorter duration of environmental (seawater) exposure amplified both markers better than eroded scats. Using the HV-CTAB-PCI method, nuclear markers were successfully amplified for the first time from dugong faeces. The successful amplification of single nucleotide polymorphism (SNP) markers represents a proof-of-concept showing that DNA from dugong faeces can potentially be utilised in population genetic studies. This novel DNA extraction protocol offers a new tool that will facilitate genetic studies of dugongs and other large and cryptic marine herbivores in remote locations.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0278792","usgsCitation":"Ooi, V., McMichael, L., Hunter, M., Takoukam Kamla, A., and Lanyon, J.M., 2023, A new DNA extraction method (HV-CTAB-PCI) for amplification of nuclear markers from open ocean-retrieved faeces of an herbivorous marine mammal, the dugong: PLoS ONE, v. 18, no. 6, e0278792, 29 p., https://doi.org/10.1371/journal.pone.0278792.","productDescription":"e0278792, 29 p.","ipdsId":"IP-147065","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":443024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0278792","text":"Publisher Index Page"},{"id":418217,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Australia","state":"Queensland","otherGeospatial":"Moreton Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 153.37192416070502,\n -27.859614592565208\n ],\n [\n 153.42962470601918,\n -27.687005800163497\n ],\n [\n 153.43511999604937,\n -27.504375776224627\n ],\n [\n 153.46534409121273,\n -27.406848872159316\n ],\n [\n 153.3939053208257,\n -27.204205934764204\n ],\n [\n 153.38566238578045,\n -27.050146132142267\n ],\n [\n 153.17134607461963,\n -27.050146132142267\n ],\n [\n 153.0422067589185,\n -27.106414779566876\n ],\n [\n 152.99824443867976,\n -27.194430673154535\n ],\n [\n 153.08891672417235,\n -27.23108348366104\n ],\n [\n 153.0202255988005,\n -27.297028138020522\n ],\n [\n 153.08616907915723,\n -27.362933646179656\n ],\n [\n 153.14661726948384,\n -27.38489343868985\n ],\n [\n 153.18233665467994,\n -27.492189631662583\n ],\n [\n 153.2345419099613,\n -27.51168681530772\n ],\n [\n 153.2867471652453,\n -27.601816322987915\n ],\n [\n 153.29224245527553,\n -27.711333458802045\n ],\n [\n 153.34994300058702,\n -27.786714713843168\n ],\n [\n 153.37192416070502,\n -27.859614592565208\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"18","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-06-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Ooi, Vicky","contributorId":310440,"corporation":false,"usgs":false,"family":"Ooi","given":"Vicky","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMichael, Lee","contributorId":310441,"corporation":false,"usgs":false,"family":"McMichael","given":"Lee","email":"","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Margaret 0000-0002-4760-9302","orcid":"https://orcid.org/0000-0002-4760-9302","contributorId":214742,"corporation":false,"usgs":true,"family":"Hunter","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":875695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takoukam Kamla, Aristide","contributorId":204221,"corporation":false,"usgs":false,"family":"Takoukam Kamla","given":"Aristide","email":"","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":875696,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lanyon, Janet M.","contributorId":204224,"corporation":false,"usgs":false,"family":"Lanyon","given":"Janet","email":"","middleInitial":"M.","affiliations":[{"id":13335,"text":"The University of Queensland","active":true,"usgs":false}],"preferred":false,"id":875697,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}