{"pageNumber":"30","pageRowStart":"725","pageSize":"25","recordCount":11004,"records":[{"id":70243156,"text":"70243156 - 2023 - Hindcast of Hurricane Sally impacts on barrier islands in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2023-05-02T13:26:41.325537","indexId":"70243156","displayToPublicDate":"2023-04-15T08:22:50","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Hindcast of Hurricane Sally impacts on barrier islands in the Gulf of Mexico","docAbstract":"

We performed XBeach and ADIRC+SWAN model simulations of Hurricane Sally over Dauphin and Petit Bois Islands off the Alabama-Mississippi coast to evaluate the morphologic response. Simulated water levels compared well with NOAA tide gauge observations to the east of Dauphin Island with a high model skill of 0.9. In addition, the XBeach model results of water levels, mean current speeds and significant wave heights agreed with ADCIRC+SWAN simulations near the offshore boundary and in the channel. Qualitative comparisons between the XBeach simulations and post-storm lidar observations confirmed model predictions of overwash. However, XBeach predicted minor breaches in Dauphin Island, which were not observed. This effort is part of a larger project in which several hydrodynamic and morphodynamic models will be coupled to produce hindcasts over a 15-year period for a larger region along the coast. These evaluations will provide local managers with strategic tools to make decisions about various coastal restoration alternatives.

","largerWorkTitle":"The proceedings of the coastal sediments 2023","conferenceTitle":"Coastal Sediments 2023","conferenceDate":"April 11-15, 2023","conferenceLocation":"New Orleans, LA","language":"English","publisher":"World Scientific","doi":"10.1142/9789811275135_0204","usgsCitation":"Frank-Gilchrist, D.P., Passeri, D., and Bilskie, M.V., 2023, Hindcast of Hurricane Sally impacts on barrier islands in the Gulf of Mexico, in The proceedings of the coastal sediments 2023, New Orleans, LA, April 11-15, 2023, p. 2220-2227, https://doi.org/10.1142/9789811275135_0204.","productDescription":"8 p.","startPage":"2220","endPage":"2227","ipdsId":"IP-147624","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":416614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Mississippi","otherGeospatial":"Dauphin and Petit Bois Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.043598091522,\n 30.30917051732709\n ],\n [\n -88.53511493858724,\n 30.30917051732709\n ],\n [\n -88.53511493858724,\n 30.152412222672723\n ],\n [\n -88.043598091522,\n 30.152412222672723\n ],\n [\n -88.043598091522,\n 30.30917051732709\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2023-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Frank-Gilchrist, Donya P. 0000-0002-7146-0069","orcid":"https://orcid.org/0000-0002-7146-0069","contributorId":292926,"corporation":false,"usgs":true,"family":"Frank-Gilchrist","given":"Donya","email":"","middleInitial":"P.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":871297,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Passeri, Davina L. 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":871298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bilskie, Matthew V.","contributorId":166891,"corporation":false,"usgs":false,"family":"Bilskie","given":"Matthew","email":"","middleInitial":"V.","affiliations":[{"id":16154,"text":"LSU","active":true,"usgs":false}],"preferred":false,"id":871299,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242712,"text":"pp1837D - 2023 - Evaluation of hydrologic processes in the eastern Snake River Plain aquifer using uranium and strontium isotopes, Idaho National Laboratory, eastern Idaho","interactions":[],"lastModifiedDate":"2026-02-18T22:12:09.217716","indexId":"pp1837D","displayToPublicDate":"2023-04-14T06:48:58","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1837","chapter":"D","displayTitle":"Evaluation of Hydrologic Processes in the Eastern Snake River Plain Aquifer Using Uranium and Strontium Isotopes, Idaho National Laboratory, Eastern Idaho","title":"Evaluation of hydrologic processes in the eastern Snake River Plain aquifer using uranium and strontium isotopes, Idaho National Laboratory, eastern Idaho","docAbstract":"

Waste constituents discharged to the eastern Snake River Plain aquifer at the U.S. Department of Energy (DOE) Idaho National Laboratory (INL) pose risks to the water quality of the aquifer. To understand these risks, the U.S. Geological Survey, in cooperation with the DOE, is conducting geochemical studies to better understand the hydrologic processes at the INL that affect the movement of groundwater and waste constituents. In this study, we used natural uranium (234U/238U) and strontium (87Sr/86Sr) isotope ratios of surface water and groundwater to identify the sources of water, the mixing of different source waters, and the flow directions in the shallow part (upper 250 feet) of the aquifer at the INL.

Samples were collected from 17 sites at and near the INL that represent the source-water contributions to the aquifer. These source-water sites included surface water, regional groundwater, and springs. Groundwater samples from 63 sites were collected at and near the INL. For all sites, sample collection dates ranged from 1979 to 2019, but groundwater samples collected at the INL are representative of wet climate cycles when the Big Lost River (BLR) was flowing onto the INL.

The 234U/238U activity ratios and 87Sr/86Sr from groundwater at the INL were plotted on graphs within ternary mixing webs in which the three end members of the mixing web represented specific sources of recharge. The large number of sources of recharge required numerous mixing webs, representing various geographic locations at the INL, so that each mixing web represented an area with just three sources of recharge. Considerations for determining the sources of recharge to groundwater sites included chemical signatures in addition to 234U/238U and 87Sr/86Sr, hydrologic context, and geographic location. The mixing webs were used to estimate the percentage of recharge from specific sources to groundwater at wells.

The results of this study identified groundwater from the Lemhi Range as a source of recharge to the INL, which was a previously unsuspected source of recharge. The estimated spatial distribution of recharge from the BLR and groundwater from the Lost River Range also decreased and increased, respectively, relative to the spatial distribution estimated from an earlier study. Upwelling geothermal water was identified at only one well, which indicates that the upward movement of deep groundwater to the shallow part of the aquifer is largely nonexistent. Mixing between surface water and groundwater, different groundwater recharge sources, or both is ubiquitous at the INL. Mixing of water fully explains the distribution of 234U/238U and 87Sr/86Sr in groundwater at the INL and thus renders unnecessary the hypothesis that fast and slow flow zones at the INL are required to explain the distribution of 234U/238U and 87Sr/86Sr.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1837D","collaboration":"DOE/ID-22259
Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Rattray, G.W., and Paces, J.B., 2023, Evaluation of hydrologic processes in the eastern Snake River Plain aquifer using uranium and strontium isotopes, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.: U.S. Geological Survey Professional Paper 1837–D (DOE/ID-22259), 65 p., https://doi.org/10.3133/pp1837D.","productDescription":"vi, 65 p.","onlineOnly":"Y","ipdsId":"IP-127503","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":415758,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837C","text":"PP 1837 Chapter C","description":"PP 1837 Chapter C"},{"id":415757,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837B","text":"PP 1837 Chapter B","description":"PP 1837 Chapter B"},{"id":415754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1837/d/coverthb.jpg"},{"id":415755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1837/d/pp1837d.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1837 Chapter D"},{"id":415756,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837A","text":"PP 1837 Chapter A","description":"PP 1837 Chapter A"},{"id":500156,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114666.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.73997601464795,\n 43.235490275196184\n ],\n [\n -112.19156981148207,\n 43.235490275196184\n ],\n [\n -112.19156981148207,\n 44.2273523624917\n ],\n [\n -113.73997601464795,\n 44.2273523624917\n ],\n [\n -113.73997601464795,\n 43.235490275196184\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520

","tableOfContents":"","publishedDate":"2023-04-14","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869458,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":869459,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70242711,"text":"pp1837C - 2023 - Determining three-dimensional hydrologic processes in the eastern Snake River Plain aquifer using geochemical mass-balance modeling, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.","interactions":[],"lastModifiedDate":"2023-04-17T11:04:59.33674","indexId":"pp1837C","displayToPublicDate":"2023-04-14T06:48:18","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1837","chapter":"C","displayTitle":"Determining Three-Dimensional Hydrologic Processes in the Eastern Snake River Plain Aquifer Using Geochemical Mass-Balance Modeling, Idaho National Laboratory, Eastern Idaho","title":"Determining three-dimensional hydrologic processes in the eastern Snake River Plain aquifer using geochemical mass-balance modeling, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.","docAbstract":"

Waste constituents discharged to the eastern Snake River Plain aquifer at the U.S. Department of Energy (DOE) Idaho National Laboratory (INL) pose risks to the water quality of the aquifer. To understand these risks, the U.S. Geological Survey, in cooperation with the DOE, used geochemical mass-balance modeling to identify three-dimensional hydrologic processes in that portion of the aquifer underlying the southwestern part of the INL that affect the movement of groundwater and waste constituents. Modeling was performed using water chemistry of 74 water samples collected from 30 wells. Fifty-four of the water samples were collected from 11 wells equipped with multilevel monitoring systems with vertically discrete sampling zones that encompass the upper 750 feet of the aquifer. Water samples from these multilevel wells were collected during 2007‒13, a period when conditions in the aquifer were approximately steady-state because there was little or no recharge from the Big Lost River.

The primary source of water in groundwater at the multilevel wells during 2007‒13 was the Big Lost River. Other sources of water include groundwater from the Little Lost River valley, precipitation, and wastewater. Horizontal groundwater-flow directions appear to be similar in both the shallow and deep parts of the aquifer, and surface-water sources of water in most deep groundwater shows that groundwater moves downward. Surface-water sources of water in deep groundwater noticeably decrease within and below the Matuyama flow and associated sedimentary interbeds, which indicates that these units are semi-impermeable and retard the downward movement of groundwater.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1837C","collaboration":"DOE/ID-22258
Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Suggested citation:\n\nRattray, G.W., 2023, Determining three-dimensional hydrologic processes in the eastern Snake River Plain aquifer using geochemical mass-balance modeling, Idaho National Laboratory, eastern Idaho, with contributions by Treinen, K.C.: U.S. Geological Survey Professional Paper 1837–C (DOE/ID-22258), 133 p., https://doi.org/10.3133/pp1837C.","productDescription":"Report: vii, 133 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-118750","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":415747,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837B","text":"PP 1837 Chapter B","description":"PP 1837 Chapter B"},{"id":415748,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837D","text":"PP 1837 Chapter D","description":"PP 1837 Chapter D"},{"id":415743,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1837/c/coverthb2.jpg"},{"id":415744,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1837/c/pp1837c.pdf","text":"Report","size":"9.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1837 Chapter C"},{"id":415745,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92CEFXN","text":"USGS data release","description":"USGS data release","linkHelpText":"Data for tritium deposition in precipitation in the United States, 1953‒2012"},{"id":415746,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/pp1837A","text":"PP 1837 Chapter A","description":"PP 1837 Chapter A"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -113.73997601464795,\n 43.235490275196184\n ],\n [\n -112.19156981148207,\n 43.235490275196184\n ],\n [\n -112.19156981148207,\n 44.2273523624917\n ],\n [\n -113.73997601464795,\n 44.2273523624917\n ],\n [\n -113.73997601464795,\n 43.235490275196184\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702-4520

","tableOfContents":"","publishedDate":"2023-04-14","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":869457,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70243363,"text":"70243363 - 2023 - Vital rates of a burgeoning population of Humpback Chub in western Grand Canyon","interactions":[],"lastModifiedDate":"2023-07-24T16:46:47.833694","indexId":"70243363","displayToPublicDate":"2023-04-14T06:41:41","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Vital rates of a burgeoning population of Humpback Chub in western Grand Canyon","docAbstract":"

The Colorado River ecosystem has experienced habitat alterations and non-native species invasions, and as a result, many of its native species have experienced extirpations, abundance declines, and range constrictions. Despite these pitfalls, Humpback Chub, Gila cypha, have persisted and, in the last 10-15 years, expanded their range to become abundant in western Grand Canyon, a river segment in which it had been rare for the prior three decades. Here we analyze a 6-year mark-recapture study from a fixed monitoring reach in western Grand Canyon and provide the first estimates of survival and growth (vital rates) for this relatively ‘new’ group of Humpback Chub. We compare vital rates in western Grand Canyon to two life history forms (residents and migrants, which represent fast and slow life history trajectories, respectively) from the more established Little Colorado River (LCR) aggregation in eastern Grand Canyon. Compared to LCR-migrants and LCR-residents, Humpback Chub in western Grand Canyon had intermediate values for apparent survival, growth, and asymptotic length. Relatively high survival of subadults coupled with fast growth allows for rapid population growth in western Grand Canyon. However, a large cohort in 2017 failed to lead to noticeable increases in adults. Seasonal survival patterns were distinct in all three groups, and apparent survival was lowest in western Grand Canyon during spring months. Adult Humpback Chub in western Grand Canyon were mobile and had a high probability of transience (i.e., just passing through the reach) and temporary emigration, demonstrating the need for future movement studies in western Grand Canyon to better distinguish emigration from survival. We discuss how observations are related to disparate temperature regimes experienced by the three groups, and if(how) the relationship between metabolism and temperature influences vital rates within the river network.

","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10415","usgsCitation":"Dzul, M.C., Yackulic, C., Giardina, M.A., Van Haverbeke, D., and Yard, M., 2023, Vital rates of a burgeoning population of Humpback Chub in western Grand Canyon: Transactions of the American Fisheries Society, v. 152, no. 4, p. 443-459, https://doi.org/10.1002/tafs.10415.","productDescription":"17 p.","startPage":"443","endPage":"459","ipdsId":"IP-148437","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":498968,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/tafs.10415","text":"Publisher Index Page"},{"id":435374,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E96ADU","text":"USGS data release","linkHelpText":"Humpback chub (Gila cypha) capture histories and growth data for two areas in the Colorado River network from 2009-2022 and 2017-2022"},{"id":416898,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.601457318797,\n 36.65987844880918\n ],\n [\n -113.91812426407165,\n 36.65987844880918\n ],\n [\n -113.91812426407165,\n 35.63520969136876\n ],\n [\n -111.601457318797,\n 35.63520969136876\n ],\n [\n -111.601457318797,\n 36.65987844880918\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"152","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Dzul, Maria C. 0000-0002-4798-5930 mdzul@usgs.gov","orcid":"https://orcid.org/0000-0002-4798-5930","contributorId":5469,"corporation":false,"usgs":true,"family":"Dzul","given":"Maria","email":"mdzul@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":872166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":218825,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":872167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Giardina, Mariah Aurelia 0000-0001-6753-0450","orcid":"https://orcid.org/0000-0001-6753-0450","contributorId":300798,"corporation":false,"usgs":true,"family":"Giardina","given":"Mariah","email":"","middleInitial":"Aurelia","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":872168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Haverbeke, David R.","contributorId":83838,"corporation":false,"usgs":false,"family":"Van Haverbeke","given":"David R.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":872169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yard, Michael D. 0000-0002-6580-6027","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":291738,"corporation":false,"usgs":false,"family":"Yard","given":"Michael D.","affiliations":[{"id":62744,"text":"Retired, US Geological Survey, Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":872170,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254341,"text":"70254341 - 2023 - Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach","interactions":[],"lastModifiedDate":"2024-05-20T11:34:51.897282","indexId":"70254341","displayToPublicDate":"2023-04-14T06:33:47","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach","docAbstract":"

Prediction of short- (i.e., aquifer is near or at saturated conditions) and long-time (i.e., aquifer is not near or at saturated conditions) baseflow recession characteristics at ungauged stream locations is a current challenge that has been primarily addressed by empirical approaches that relate these characteristics to basin attributes. However, the performance of these models is often only fair with coefficient of determination values ranging from 0.5 to 0.7. In this study, we propose a hybrid physical and machine learning approach to predict the long- and short-time baseflow recession characteristics at ungauged stream locations. This approach is compared to a machine learning method, random forest regression, that relates baseflow recession characteristics to basin attributes in 582 basins across the western and eastern United States. The new approach resulted in lower median and inner quartile ranges (IQR) of absolute normalized errors in predicting long-time baseflow recession characteristics (western: 23%, IQR=32%; eastern: 30%, IQR=39%) compared to estimates of those properties based on random forest regressions (western: 27%, IQR=34%; eastern: 38%, IQR=50%). For the short-time baseflow recession characteristics, the hybrid approach resulted in substantially lower median errors and IQR values (western: 79%, IQR=143%; eastern: 83%, IQR=140%) compared to estimates from random forest regressions (western: 1,577%, IQR=8,887%; eastern: 341%, IQR=2,154%). In addition, this approach identified four major regions in the western United States and three in the eastern United States where the baseflow recession characteristics are mostly constant, and these characteristics only vary based on the geometric properties of aquifers. Lastly, the inter-basin variability of the baseflow recession characteristics was not found to be strongly related to metrics measuring interstorm arrival periods, average number of storms, and average length of storms.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2023.104440","usgsCitation":"Eng, K., Wolock, D.M., and Wieczorek, M., 2023, Predicting baseflow recession characteristics at ungauged stream locations using a physical and machine learning approach: Advances in Water Resources, v. 175, 104440, https://doi.org/10.1016/j.advwatres.2023.104440.","productDescription":"104440","ipdsId":"IP-127260","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":428824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":901033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolock, David M. 0000-0002-6209-938X","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":219213,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":901034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wieczorek, Michael 0000-0003-0999-5457","orcid":"https://orcid.org/0000-0003-0999-5457","contributorId":207911,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":901035,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242682,"text":"ofr20231026 - 2023 - Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019","interactions":[],"lastModifiedDate":"2026-02-11T21:04:06.498805","indexId":"ofr20231026","displayToPublicDate":"2023-04-13T12:02:15","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-1026","displayTitle":"Assessment of Riparian Vegetation Patterns and Change Downstream from Glen Canyon Dam from 2014 to 2019","title":"Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019","docAbstract":"

Changes in riparian vegetation cover and composition occur in relation to flow regime, geomorphic template, and climate, and can have cascading effects on aquatic and terrestrial ecosystems. Tracking such changes over time is therefore an important part of monitoring the condition and trajectory of riparian ecosystems. Maintaining diverse, self-sustaining riparian vegetation comprised of mostly native species is identified in the Glen Canyon Dam Long-Term Experimental and Management Plan as a key resource objective for the section of the Colorado River between Glen Canyon Dam and Lake Mead. The U.S. Geological Survey Grand Canyon Monitoring and Research Center implemented an annual monitoring program in 2014 to assess the status and trends of riparian vegetation along this section of river, particularly as they relate to flow regime. In this report, we summarize plant species composition and cover data collected under the annual monitoring program from 2014 to 2019, with special consideration given to the hydrologic position, associated geomorphic feature class, local climate patterns, native and nonnative species, and floristic region for key vegetation metrics and species. We divided the study area into four river segments (referred to as Glen Canyon, Marble Canyon, eastern Grand Canyon, and western Grand Canyon) on the basis of geography and floristic composition and calculated each recorded plant species’ relative frequency and foliar cover by river segment. These data were then used to evaluate species composition relationships among river segments, hydrologic zones, geomorphic features, and sampling years through ordination analysis. Temporal trends in our focal resource objectives—species richness, total foliar cover, proportion of native to nonnative species richness, proportion of native to nonnative species cover, Tamarix cover, Pluchea sericea cover, and Baccharis species cover—were assessed using mixed-effects models. Four patterns related to species composition emerged: (1) species composition of fixed-site sandbars differed from that of randomly selected sites (including randomly selected sandbars), (2) species composition of Glen Canyon sites differed from that of other previously identified floristic regions, (3) species composition differed across hydrologic zones related to dam operations, and (4) species composition within river segments did not change across years. For temporal patterns, four main findings emerged: (1) trends differed between fixed-sites and randomly selected sites; (2) although few directional changes were observed from 2014 to 2019, Baccharis species cover increased at randomly selected sites in areas influenced by daily water fluctuations; (3) native species cover and richness were greater than nonnative species cover and richness across all hydrologic zones; and (4) the temporal trend metrics used here can be used across floristic groups, enabling assessment of the Colorado River ecosystem as a whole. In addition to these findings, lists of recorded plant species are included as appendixes. The variations and patterns in vegetation status and trends presented in this report can be used as a baseline against which future monitoring can be compared.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231026","collaboration":"Prepared in cooperation with the Bureau of Reclamation Glen Canyon Adaptive Management Program","usgsCitation":"Palmquist, E.C., Butterfield, B.J., and Ralston, B.E., 2023, Assessment of riparian vegetation patterns and change downstream from Glen Canyon Dam from 2014 to 2019: U.S. Geological Survey Open-File Report 2023–1026, 55 p., https://doi.org/10.3133/ofr20231026.","productDescription":"Report: vii, 55 p.; Data Release","numberOfPages":"55","onlineOnly":"Y","ipdsId":"IP-132835","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":499774,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114661.htm","linkFileType":{"id":5,"text":"html"}},{"id":415675,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1026/images"},{"id":415674,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1026/ofr20231026.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":415673,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1026/covrthb.jpg"},{"id":415672,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KEHY2S","text":"Riparian vegetation data downstream of Glen Canyon Dam in Glen Canyon National Recreation Area and Grand Canyon National Park, AZ from 2014 to 2019","description":"Palmquist, E.C., Butterfield, B.J., and Ralston, B.E., 2022, Riparian vegetation data downstream of Glen Canyon Dam in Glen Canyon National Recreation Area and Grand Canyon National Park, AZ from 2014 to 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9KEHY2S."}],"country":"United States","state":"Arizona","otherGeospatial":"Glen Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -114.06028247701303,\n 36.94784441270309\n ],\n [\n -114.06028247701303,\n 35.55756259875736\n ],\n [\n -111.24899178190306,\n 35.55756259875736\n ],\n [\n -111.24899178190306,\n 36.94784441270309\n ],\n [\n -114.06028247701303,\n 36.94784441270309\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"
Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
","tableOfContents":"","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2023-04-13","noUsgsAuthors":false,"publicationDate":"2023-04-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":869339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Butterfield, Bradley J.","contributorId":18096,"corporation":false,"usgs":true,"family":"Butterfield","given":"Bradley J.","affiliations":[],"preferred":false,"id":869340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ralston, Barbara E. 0000-0001-9991-8994 bralston@usgs.gov","orcid":"https://orcid.org/0000-0001-9991-8994","contributorId":606,"corporation":false,"usgs":true,"family":"Ralston","given":"Barbara","email":"bralston@usgs.gov","middleInitial":"E.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":false,"id":869341,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70243529,"text":"70243529 - 2023 - Inferring pathogen presence when sample misclassification and partial observation occur","interactions":[],"lastModifiedDate":"2023-05-11T11:57:40.081025","indexId":"70243529","displayToPublicDate":"2023-04-11T06:55:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Inferring pathogen presence when sample misclassification and partial observation occur","docAbstract":"
  1. Surveillance programmes are essential for detecting emerging pathogens and often rely on molecular methods to make inference about the presence of a target disease agent. However, molecular methods rarely detect target DNA perfectly. For example, molecular pathogen detection methods can result in misclassification (i.e. false positives and false negatives) or partial detection errors (i.e. detections with ‘ambiguous’, ‘uncertain’ or ‘equivocal’ results). Then, when data are to be analysed, these partial observations are either discarded or censored; this, however, disregards information that could be used to make inference about the true state of the system. There is a critical need for more direction and guidance related to how many samples are enough to declare a unit of interest ‘pathogen free’.
  2. Here, we develop a Bayesian hierarchal framework that accommodates false negative, false positive and uncertain detections to improve inference related to the occupancy of a pathogen. We apply our modelling framework to a case study of the fungal pathogen Pseudogymnoascus destructans (Pd) identified in Texas bats at the invasion front of white-nose syndrome. To improve future surveillance programmes, we provide guidance on sample sizes required to be 95% certain a target organism is absent from a site.
  3. We found that the presence of uncertain detections increased the variability of resulting posterior probability distributions of pathogen occurrence, and that our estimates of required sample size were very sensitive to prior information about pathogen occupancy, pathogen prevalence and diagnostic test specificity. In the Pd case study, we found that the posterior probability of occupancy was very low in 2018, but occupancy probability approached 1 in 2020, reflecting increasing prior probabilities of occupancy and prevalence elicited from the site manager.
  4. Our modelling framework provides the user a posterior probability distribution of pathogen occurrence, which allows for subjective interpretation by the decision-maker. To help readers apply and use the methods we developed, we provide an interactive RShiny app that generates target species occupancy estimation and sample size estimates to make these methods more accessible to the scientific community (https://rmummah.shinyapps.io/ambigDetect_sampleSize). This modelling framework and sample size guide may be useful for improving inferences from molecular surveillance data about emerging pathogens, non-native invasive species and endangered species where misclassifications and ambiguous detections occur.
","language":"English","publisher":"British Ecological Society","doi":"10.1111/2041-210X.14102","usgsCitation":"Campbell Grant, E.H., Mummah, R.O., Mosher, B.A., Evans, J., and DiRenzo, G.V., 2023, Inferring pathogen presence when sample misclassification and partial observation occur: Methods in Ecology and Evolution, v. 14, no. 5, p. 1299-1311, https://doi.org/10.1111/2041-210X.14102.","productDescription":"13 p.","startPage":"1299","endPage":"1311","ipdsId":"IP-148152","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443886,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/2041-210x.14102","text":"Publisher Index Page"},{"id":435379,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PDV4LV","text":"USGS data release","linkHelpText":"Inferring pathogen presence when sample misclassification and partial observation occur"},{"id":416954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-04-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":872230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mummah, Riley O.","contributorId":305294,"corporation":false,"usgs":false,"family":"Mummah","given":"Riley","email":"","middleInitial":"O.","affiliations":[{"id":66204,"text":"Massachusetts Cooperative Fish and Wildlife Research Unit, University of Massachusetts, Department of Environmental Conservation, 160 Holdsworth Way, Amherst, Massachusetts 01003","active":true,"usgs":false}],"preferred":false,"id":872231,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mosher, Brittany A.","contributorId":189579,"corporation":false,"usgs":false,"family":"Mosher","given":"Brittany","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":872232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Evans, Jonah","contributorId":239062,"corporation":false,"usgs":false,"family":"Evans","given":"Jonah","email":"","affiliations":[{"id":27442,"text":"Texas parks and Wildlife Department","active":true,"usgs":false}],"preferred":false,"id":872233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DiRenzo, Graziella Vittoria 0000-0001-5264-4762","orcid":"https://orcid.org/0000-0001-5264-4762","contributorId":243404,"corporation":false,"usgs":true,"family":"DiRenzo","given":"Graziella","email":"","middleInitial":"Vittoria","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":872234,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70254971,"text":"70254971 - 2023 - Effects of large-scale disturbance on animal space use: Functional responses by greater sage-grouse after megafire","interactions":[],"lastModifiedDate":"2024-06-11T14:42:09.314762","indexId":"70254971","displayToPublicDate":"2023-04-07T09:37:01","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Effects of large-scale disturbance on animal space use: Functional responses by greater sage-grouse after megafire","docAbstract":"

Global change has altered the nature of disturbance regimes, and megafire events are increasingly common. Megafires result in immediate changes to habitat available to terrestrial wildlife over broad landscapes, yet we know surprisingly little about how such changes shape space use of sensitive species in habitat that remains. Functional responses provide a framework for understanding and predicting changes in space use following habitat alteration, but no previous studies have assessed functional responses as a consequence of megafire. We studied space use and tested for functional responses in habitat use by breeding greater sage-grouse (Centrocercus urophasianus) before and after landscape-level changes induced by a >40,000 ha, high-intensity megafire that burned sagebrush steppe in eastern Idaho, USA. We also incorporated functional responses into predictive resource selection functions (RSFs) to map breeding habitat before and after the fire. Megafire had strong effects on the distribution of available resources and resulted in context-dependent habitat use that was heterogeneous across different components of habitat. We observed functional responses in the use and selection of a variety of resources (shrubs and herbaceous vegetation) for both nesting and brood rearing. Functional responses in the use of nesting habitat were influenced by the overarching effect of megafire on vegetation, whereas responses during brood rearing appeared to be driven by individual variation in available resources that were conditional on nest locations. Importantly, RSFs built using data collected prior to the burn also had poor transferability for predicting space use in a post-megafire landscape. These results have strong implications for understanding and predicting how animals respond to a rapidly changing environment, given that increased severity, frequency, and extent of wildfire are consequences of global change with the capacity to reshape ecosystems. We therefore demonstrate a conceptual framework to better understand space use and aid habitat conservation for wildlife in a rapidly changing world.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.9933","usgsCitation":"Stevens, B.S., Roberts, S., Conway, C.J., and Engelstead, D.K., 2023, Effects of large-scale disturbance on animal space use: Functional responses by greater sage-grouse after megafire: Ecology and Evolution, v. 13, no. 4, e9933, 30 p., https://doi.org/10.1002/ece3.9933.","productDescription":"e9933, 30 p.","ipdsId":"IP-136242","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":443914,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.9933","text":"Publisher Index Page"},{"id":429874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.30314841246594,\n 44.47748992705084\n ],\n [\n -112.30314841246594,\n 44.05252291063391\n ],\n [\n -111.2985432757669,\n 44.05252291063391\n ],\n [\n -111.2985432757669,\n 44.47748992705084\n ],\n [\n -112.30314841246594,\n 44.47748992705084\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","issue":"4","noUsgsAuthors":false,"publicationDate":"2023-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Stevens, Bryan S.","contributorId":171809,"corporation":false,"usgs":false,"family":"Stevens","given":"Bryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":903006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Shane","contributorId":279606,"corporation":false,"usgs":false,"family":"Roberts","given":"Shane","affiliations":[{"id":56023,"text":"idfg","active":true,"usgs":false}],"preferred":false,"id":903007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conway, Courtney J. 0000-0003-0492-2953 cconway@usgs.gov","orcid":"https://orcid.org/0000-0003-0492-2953","contributorId":2951,"corporation":false,"usgs":true,"family":"Conway","given":"Courtney","email":"cconway@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engelstead, Devin K.","contributorId":338188,"corporation":false,"usgs":false,"family":"Engelstead","given":"Devin","email":"","middleInitial":"K.","affiliations":[{"id":37086,"text":"U.S. Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":903009,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242130,"text":"70242130 - 2023 - Hidden in the hills: Phylogeny of the freshwater mussel genus Alasmidonta (Bivalvia: Unionidae) and description of a new species","interactions":[],"lastModifiedDate":"2023-06-08T14:47:03.003874","indexId":"70242130","displayToPublicDate":"2023-04-07T08:33:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3810,"text":"Zoological Journal of the Linnean Society","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Hidden in the hills: Phylogeny of the freshwater mussel genus Alasmidonta (Bivalvia: Unionidae) and description of a new species","title":"Hidden in the hills: Phylogeny of the freshwater mussel genus Alasmidonta (Bivalvia: Unionidae) and description of a new species","docAbstract":"

Inaccurate taxonomy can lead to species in need of conservation being overlooked, which makes revisionary systematics crucially important for imperilled groups. The freshwater mussel genus Alasmidonta is one such group in need of study. Here, we take a multilocus phylogenetic approach to assess species-level taxonomy of Alasmidonta and test monophyly of this genus. Phylogenetic inference resulted in polyphyly of Alasmidonta. Lasmigona, which was included to test monophyly of Alasmidonta, was also polyphyletic. Species delimitation methods disagreed about whether Alasmidonta arcula, Alasmidonta triangulata and Alasmidonta undulata are distinct species, but all delimitation methods agreed that Alasmidonta harbours an undescribed species that would be considered Alasmidonta varicosa under current taxonomy. Given conflict among species delimitation methods and geographical separation, we maintain the current taxonomy for A. arcula and A. triangulata. The undescribed species is restricted to rivers of the Uwharrie Mountains region in North Carolina, USA that flow into the Pee Dee River from the east and can be distinguished morphologically from A. varciosa by higher and wider placed adductor mussels and a hooked pseudocardinal tooth. We offer insights into how supraspecific taxonomy of subtribe Alasmidontina might be resolved and formally describe the lineage from the Uwharrie Mountains region as Uwharrie elktoe, Alasmidonta uwharriensis sp. nov.

","language":"English","publisher":"Oxford Academic Press","doi":"10.1093/zoolinnean/zlac106","usgsCitation":"Whelan, N., Johnson, N., Williams, A.S., Perkins, M.A., Beaver, C.E., and Mays, J.W., 2023, Hidden in the hills: Phylogeny of the freshwater mussel genus Alasmidonta (Bivalvia: Unionidae) and description of a new species: Zoological Journal of the Linnean Society, v. 198, no. 2, p. 650-676, https://doi.org/10.1093/zoolinnean/zlac106.","productDescription":"27 p.; Data Release","startPage":"650","endPage":"676","ipdsId":"IP-138304","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":443919,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/zoolinnean/zlac106","text":"Publisher Index Page"},{"id":415412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":417812,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P47PUC"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.01909716357271,\n 35.05786699652403\n ],\n [\n -78.85956067260797,\n 35.05786699652403\n ],\n [\n -78.85956067260797,\n 36.47874763761361\n ],\n [\n -81.01909716357271,\n 36.47874763761361\n ],\n [\n -81.01909716357271,\n 35.05786699652403\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"198","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Whelan, Nathan V.","contributorId":304024,"corporation":false,"usgs":false,"family":"Whelan","given":"Nathan V.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":868962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nathan 0000-0001-5167-1988","orcid":"https://orcid.org/0000-0001-5167-1988","contributorId":210319,"corporation":false,"usgs":true,"family":"Johnson","given":"Nathan","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":868963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Ashantye’ S.","contributorId":304031,"corporation":false,"usgs":false,"family":"Williams","given":"Ashantye’","email":"","middleInitial":"S.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":868964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perkins, Michael A.","contributorId":178870,"corporation":false,"usgs":false,"family":"Perkins","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":868965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beaver, Caitlin E. 0000-0002-9269-7604","orcid":"https://orcid.org/0000-0002-9269-7604","contributorId":268037,"corporation":false,"usgs":true,"family":"Beaver","given":"Caitlin","email":"","middleInitial":"E.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":868966,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mays, Jason W.","contributorId":304033,"corporation":false,"usgs":false,"family":"Mays","given":"Jason","email":"","middleInitial":"W.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":868967,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70242109,"text":"70242109 - 2023 - The stratigraphy and stratigraphic nomenclature of the Goochland Terrane in the Piedmont Province of east-central Virginia","interactions":[],"lastModifiedDate":"2023-11-20T17:05:35.904071","indexId":"70242109","displayToPublicDate":"2023-04-07T08:25:35","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3481,"text":"Stratigraphy","active":true,"publicationSubtype":{"id":10}},"title":"The stratigraphy and stratigraphic nomenclature of the Goochland Terrane in the Piedmont Province of east-central Virginia","docAbstract":"

The Goochland terrane is a structurally isolated crustal block in the eastern Piedmont of Virginia. It is composed of the previously named State Farm Gneiss, Montpelier Anorthosite, Sabot Amphibolite, and Maidens Gneiss, but also includes the Scotchtown Gneiss, Teman Gneiss, and Old Bandana Gneiss which are formally named and defined herein. The eastern part of the Goochland terrane is antiformal and cored by Mesoproterozoic rocks (the State Farm Gneiss and the Montpelier Anorthosite). These basement units are overlain by a late Neoproterozoic to early Paleozoic (Ediacaran to Early Cambrian) saprolitic, metavolcanic, and metasedimentary sequence that sequentially includes the Scotchtown Gneiss, Sabot Amphibolite and Maidens Gneiss. The western part of the terrane is synformal and includes in its core two additional units that overlie the Maidens Gneiss: the Teman Gneiss and the Old Bandana Gneiss. Based on mineralogy and zircon grain morphology, the protoliths of the Maidens, Teman, and Old Bandana gneisses were predominantly sedimentary rocks. The protoliths of the Teman Gneiss and Old Bandana Gneiss were deposited unconformably upon the protolith of the Maidens Gneiss. The eastern and western parts of the Goochland terrane are separated by the Dabneys fault, which has considerable east-side-up vertical offset and possibly also significant transverse displacement. Correlation of the upper part of the Goochland terrane (Teman and Old Bandana gneisses) with the Setters and Cockeysville gneisses in the Baltimore region suggests that the Goochland terrane was left about 135 miles (ca. 220 km) southwest of its original North American location, which was to the east of Baltimore, Maryland. This displacement was caused by the oblique collision of the eastern North American continent with the western edge of the Gondwanan craton during the later Carboniferous (Pennsylvanian) Period.

","language":"English","publisher":"Micropress","doi":"10.29041/strat.20.1.03","usgsCitation":"Weems, R.E., and Robbins, E., 2023, The stratigraphy and stratigraphic nomenclature of the Goochland Terrane in the Piedmont Province of east-central Virginia: Stratigraphy, v. 20, no. 1, p. 39-58, https://doi.org/10.29041/strat.20.1.03.","productDescription":"20 p.","startPage":"39","endPage":"58","ipdsId":"IP-126463","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":415411,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Goochland Terrane, Piedmont province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.58432298451764,\n 38.424681988885965\n ],\n [\n -78.58432298451764,\n 37.92609933589563\n ],\n [\n -77.43824965406793,\n 37.92609933589563\n ],\n [\n -77.43824965406793,\n 38.424681988885965\n ],\n [\n -78.58432298451764,\n 38.424681988885965\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Weems, Robert E.","contributorId":304011,"corporation":false,"usgs":false,"family":"Weems","given":"Robert","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":868914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robbins, Eleanora I.","contributorId":304012,"corporation":false,"usgs":false,"family":"Robbins","given":"Eleanora I.","affiliations":[],"preferred":false,"id":868915,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70242136,"text":"70242136 - 2023 - Predicted aquatic exposure effects from a national urban stormwater study","interactions":[],"lastModifiedDate":"2023-12-04T16:57:15.989156","indexId":"70242136","displayToPublicDate":"2023-04-07T08:18:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":13794,"text":"Environmental Science: Water Research and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Predicted aquatic exposure effects from a national urban stormwater study","docAbstract":"

A multi-agency study of 438 organic and 62 inorganic chemicals measured in urban stormwater during 50 total runoff events at 21 sites across the United States demonstrated that stormwater discharges can generate localized, aquatic exposures to extensive contaminant mixtures, including organics suspected to cause adverse aquatic-health effects. The aggregated risks to multiple aquatic trophic levels (fish, invertebrates, plants) of the stormwater mixture exposures, which were documented in the national study, were explored herein by calculating cumulative ratios of organic-contaminant in vitro exposure–activity cutoffs (∑EAR) and health-benchmark-weighted cumulative toxicity quotients (∑TQ). Both risk assessment approaches indicated substantial (moderate to high) risk for acute adverse effects to aquatic organisms across multiple trophic levels (fish, macroinvertebrates, non-vascular/vascular plants) at or near stormwater discharge points across the United States. The results are interpreted as potential orders of magnitude underestimates of actual aquatic risk in stormwater control wetlands or in the immediate vicinity of such discharges to surface-water receptors, because the 438 organic-compound analytical space assessed in this study is orders of magnitude less than the 350 000 parent compounds estimated to be in current commercial use globally and the incalculable chemical-space of potential metabolites and degradates.

","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D2EW00933A","usgsCitation":"Bradley, P., Romanok, K., Smalling, K., Masoner, J.R., Kolpin, D., and Gordon, S.E., 2023, Predicted aquatic exposure effects from a national urban stormwater study: Environmental Science: Water Research and Technology, v. 9, p. 3191-3199, https://doi.org/10.1039/D2EW00933A.","productDescription":"9 p.","startPage":"3191","endPage":"3199","ipdsId":"IP-124205","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":443921,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index 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0000-0002-1214-4920","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":214623,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868976,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":868977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868978,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gordon, Stephanie E. 0000-0002-6292-2612 sgordon@usgs.gov","orcid":"https://orcid.org/0000-0002-6292-2612","contributorId":200931,"corporation":false,"usgs":true,"family":"Gordon","given":"Stephanie","email":"sgordon@usgs.gov","middleInitial":"E.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":868979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70242706,"text":"70242706 - 2023 - Shallow deformation on the Kirby Hills fault, Sacramento–San Joaquin Delta, California (USA), revealed from high-resolution seismic reflection data and coring in a fluvial system","interactions":[],"lastModifiedDate":"2023-06-09T15:15:59.382116","indexId":"70242706","displayToPublicDate":"2023-04-06T06:51:28","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Shallow deformation on the Kirby Hills fault, Sacramento–San Joaquin Delta, California (USA), revealed from high-resolution seismic reflection data and coring in a fluvial system","docAbstract":"

The Sacramento–San Joaquin Delta (Delta) in California (USA) is an important part of the state’s freshwater system and is also a major source of agricultural and natural resources. However, the Delta is traversed by a series of faults that make up the easternmost part of the San Andreas fault system at this latitude and pose seismic hazard to this region. In this study, we use new high-resolution chirp subbottom data to map and characterize the shallow expression of the Kirby Hills fault, where it has been mapped to cross the Sacramento River at the western extent of the Delta. The fault is buried here, but we document a broad zone of deformation associated with the eastern strand of the fault that changes in character, along strike, across ~600 m of the river channel. Radiocarbon dates from sediment cores collected in the Sacramento River provide some minimum constraints on the age of deformation. We do not observe evidence of the western strand as previously mapped. We also discuss difficulties of conducting a paleoseismologic study in a fluvial environment.

","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES02525.1","usgsCitation":"Klotsko, S., Maloney, J., and Watt, J., 2023, Shallow deformation on the Kirby Hills fault, Sacramento–San Joaquin Delta, California (USA), revealed from high-resolution seismic reflection data and coring in a fluvial system: Geosphere, v. 19, no. 3, p. 748-769, https://doi.org/10.1130/GES02525.1.","productDescription":"22 p.","startPage":"748","endPage":"769","ipdsId":"IP-144086","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":443936,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1130/ges02525.1","text":"Publisher Index Page"},{"id":415703,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.15618476884723,\n 38.36476843145434\n ],\n [\n -123.15618476884723,\n 37.28049028339727\n ],\n [\n -121.05869835179277,\n 37.28049028339727\n ],\n [\n -121.05869835179277,\n 38.36476843145434\n ],\n [\n -123.15618476884723,\n 38.36476843145434\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"19","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-04-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Klotsko, Shannon","contributorId":304140,"corporation":false,"usgs":false,"family":"Klotsko","given":"Shannon","affiliations":[{"id":24668,"text":"University of North Carolina, Wilmington","active":true,"usgs":false}],"preferred":false,"id":869423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maloney, Jillian","contributorId":304141,"corporation":false,"usgs":false,"family":"Maloney","given":"Jillian","affiliations":[{"id":6608,"text":"San Diego State University","active":true,"usgs":false}],"preferred":false,"id":869424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watt, Janet 0000-0002-4759-3814","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":221271,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":869425,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70243528,"text":"70243528 - 2023 - Environmental factors influencing detection efficiency of an acoustic telemetry array and consequences for data interpretation","interactions":[],"lastModifiedDate":"2023-05-11T11:47:29.744393","indexId":"70243528","displayToPublicDate":"2023-04-06T06:40:51","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Environmental factors influencing detection efficiency of an acoustic telemetry array and consequences for data interpretation","docAbstract":"

Background

Acoustic telemetry is a commonly used technology to monitor animal occupancy and infer movement in aquatic environments. The information that acoustic telemetry provides is vital for spatial planning and management decisions concerning aquatic and coastal environments by characterizing behaviors and habitats such as spawning aggregations, migrations, corridors, and nurseries, among others. However, performance of acoustic telemetry equipment and resulting detection ranges and efficiencies can vary as a function of environmental conditions, leading to potentially biased interpretations of telemetry data. Here, we characterize variation in detection performance using an acoustic telemetry receiver array deployed in Wellfleet Harbor, Massachusetts, USA from 2015 to 2017. The array was designed to study benthic invertebrate movements and provided an in situ opportunity to identify factors driving variation in detection probability.

Results

The near-shore location proximate to environmental monitoring allowed for a detailed examination of factors influencing detection efficiency in a range-testing experiment. Detection ranges varied from < 50 to 1,500 m and efficiencies varied from 0 to 100% within those detection ranges. Detection efficiency was affected by distance, wind speed and direction, wave height and direction, water temperature, water depth, and water quality.

Conclusions

Performance of acoustic telemetry systems is strongly contingent on environmental conditions. Our study found that wind, waves, water temperature, water quality, and depth all affected performance to an extent that could seriously compromise a study if these effects were not taken into consideration. Other unmeasured factors may also be important, depending on the characteristics of each site. This information can help guide future telemetry study designs by helping researchers anticipate the density of receivers required to achieve study objectives. Researchers can further refine and document the reliability of their data by incorporating continuously deployed range-testing tags and prior knowledge on varying detection efficiency into movement and occupancy models.

","language":"English","publisher":"Springer","doi":"10.1186/s40317-023-00317-2","usgsCitation":"Long, M., Jordaan, A., and Castro-Santos, T.R., 2023, Environmental factors influencing detection efficiency of an acoustic telemetry array and consequences for data interpretation: Animal Biotelemetry, v. 11, 18, 13 p., https://doi.org/10.1186/s40317-023-00317-2.","productDescription":"18, 13 p.","ipdsId":"IP-141767","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":443940,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40317-023-00317-2","text":"Publisher Index Page"},{"id":416951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.12152378095689,\n 41.97721573790295\n ],\n [\n -70.12152378095689,\n 41.80349781857885\n ],\n [\n -69.90189169540182,\n 41.80349781857885\n ],\n [\n -69.90189169540182,\n 41.97721573790295\n ],\n [\n -70.12152378095689,\n 41.97721573790295\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2023-04-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Long, Michael 0000-0001-6735-6878","orcid":"https://orcid.org/0000-0001-6735-6878","contributorId":261905,"corporation":false,"usgs":false,"family":"Long","given":"Michael","email":"","affiliations":[{"id":34616,"text":"University of Massachusetts Amherst","active":true,"usgs":false}],"preferred":false,"id":872227,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jordaan, Adrian","contributorId":257709,"corporation":false,"usgs":false,"family":"Jordaan","given":"Adrian","affiliations":[{"id":37201,"text":"UMass Amherst","active":true,"usgs":false}],"preferred":false,"id":872228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":872229,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242000,"text":"sir20235013 - 2023 - Salinity and selenium yield maps derived from geostatistical modeling in the lower Gunnison River Basin, western Colorado, 1992–2013","interactions":[],"lastModifiedDate":"2026-03-02T21:57:03.940791","indexId":"sir20235013","displayToPublicDate":"2023-04-05T10:35:01","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":"2023-5013","displayTitle":"Salinity and Selenium Yield Maps Derived from Geostatistical Modeling in the Lower Gunnison River Basin, Western Colorado, 1992–2013","title":"Salinity and selenium yield maps derived from geostatistical modeling in the lower Gunnison River Basin, western Colorado, 1992–2013","docAbstract":"

Salinity is known to affect drinking-water supplies and damage irrigated agricultural lands. Selenium in high concentrations is harmful to fish and other wildlife. Land managers, water providers, and agricultural producers in the lower Gunnison River Basin in western Colorado expend resources mitigating the effects of these constituents. The U.S. Geological Survey revised existing salinity (total dissolved solids) and selenium models for the lower Gunnison River Basin in an attempt to better identify areas of greatest salinity and selenium yield. This effort developed maps of yields predicted from multiple linear regression (MLR) models for the lower Gunnison River Basin. The models included data for irrigation and nonirrigation seasons and two periods, 1992–2004 and 2005–13.

Concentrations of salinity and selenium and discharge measurements made at the time of sampling were used to compute loads for subbasins (component drainages of the larger lower Gunnison River Basin study area), which were adjusted for inflows and outflows of canal loads. Load regression equations were determined from explanatory basin characteristics that included physical properties, precipitation, land use and cover, surficial deposits (soil and unconsolidated geologic materials), and bedrock geology. Loads of salinity and selenium were converted to yields by using the subbasin drainage areas, and an empirical Bayesian kriging procedure was used to produce robust grids of yields for salinity and selenium.

Salinity yields ranged from 0.00667 to 6.564 tons per year per acre. The highest salinity yields, greater than about 5.0 tons per year per acre, are predicted on the western side of the Uncompahgre River upstream from Delta, Colorado, an area with a high density of irrigated land. The selenium yield map shows a similar pattern, but the highest yields are somewhat more confined to the eastern side of the lower Uncompahgre River and south of the Gunnison River near the confluence with the Uncompahgre River at Delta, Colorado. Selenium yields ranged from 2.6888 x 10-10 to 0.000445 pounds per day per acre. The highest predicted selenium yields, greater than 0.0003 pounds per day per acre, were in the area downstream from Montrose, Colorado, on the eastern side of the Uncompahgre River.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20235013","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Colorado Water Conservation Board","usgsCitation":"Williams, C.A., Gidley, R.G., and Stevens, M.R., 2023, Salinity and selenium yield maps derived from geostatistical modeling in the lower Gunnison River Basin, western Colorado, 1992–2013: U.S. Geological Survey Scientific Investigations Report 2023–5013, 37 p., https://doi.org/10.3133/sir20235013.","productDescription":"Report: vi, 37 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-127438","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":415136,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CW7Q1N","text":"USGS data release","linkHelpText":"Basin Characteristics and Salinity and Selenium Loads and Yields for Selected Subbasins in the Lower Gunnison River Basin, Western Colorado, 1992─2013"},{"id":415232,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5013/images"},{"id":415233,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5013/sir20235013.xml"},{"id":415255,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235013/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5013"},{"id":415135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5013/sir20235013.pdf","text":"Report","size":"13.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5013"},{"id":415134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5013/coverthb.jpg"},{"id":415137,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS data release","linkHelpText":"USGS water data for the Nation: U.S. Geological Survey National Water Information System database"},{"id":500707,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114651.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108.66041487616633,\n 38.99638415429618\n ],\n [\n -108.6616273692395,\n 39.00186401594732\n ],\n [\n -108.6616273692395,\n 38.9967055439632\n ],\n [\n -108.6881779535584,\n 38.77194822283556\n ],\n [\n -108.58197561628282,\n 38.556862390281765\n ],\n [\n -108.19035825380965,\n 38.16912358075567\n ],\n [\n -108.12730061605224,\n 37.915589610235415\n ],\n [\n -107.96135946405924,\n 37.80029529902727\n ],\n [\n -107.76886772774775,\n 37.81078405090291\n ],\n [\n -107.61846017361093,\n 38.26998042097301\n ],\n [\n -107.25524694190712,\n 38.623585049765126\n ],\n [\n -107.0055365452011,\n 38.85181039167898\n ],\n [\n -106.90464345562309,\n 38.99114000809618\n ],\n [\n -106.95004534593326,\n 39.07538965450817\n ],\n [\n -107.02178619634307,\n 39.241636232003856\n ],\n [\n -107.71852594996861,\n 39.17165133541914\n ],\n [\n -108.1185061789019,\n 39.03147242299278\n ],\n [\n -108.37655793950398,\n 38.98134099584442\n ],\n [\n -108.55719417192573,\n 39.05652481206508\n ],\n [\n -108.66041487616633,\n 38.99638415429618\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver, CO 80225

","tableOfContents":"","publishedDate":"2023-04-05","noUsgsAuthors":false,"publicationDate":"2023-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Cory A. 0000-0003-1461-7848 cawillia@usgs.gov","orcid":"https://orcid.org/0000-0003-1461-7848","contributorId":689,"corporation":false,"usgs":true,"family":"Williams","given":"Cory","email":"cawillia@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gidley, Rachel G. 0000-0002-9840-8252","orcid":"https://orcid.org/0000-0002-9840-8252","contributorId":259315,"corporation":false,"usgs":true,"family":"Gidley","given":"Rachel","email":"","middleInitial":"G.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":868487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevens, Michael R. 0000-0002-9476-6335","orcid":"https://orcid.org/0000-0002-9476-6335","contributorId":303903,"corporation":false,"usgs":false,"family":"Stevens","given":"Michael R.","affiliations":[{"id":37196,"text":"Retired USGS employee","active":true,"usgs":false}],"preferred":false,"id":868488,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70241590,"text":"sir20235010 - 2023 - Visualization of petroleum exploration maturity for six petroleum provinces outside the United States and Canada","interactions":[],"lastModifiedDate":"2023-04-05T14:53:25.369229","indexId":"sir20235010","displayToPublicDate":"2023-04-05T09:55:00","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":"2023-5010","displayTitle":"Visualization of Petroleum Exploration Maturity for Six Petroleum Provinces Outside the United States and Canada","title":"Visualization of petroleum exploration maturity for six petroleum provinces outside the United States and Canada","docAbstract":"

Outside the United States and Canada, most of the world’s supplies of oil and natural gas are recovered from conventional (or discrete) oil and gas accumulations. This type of hydrocarbon accumulation remains a target for exploration. In this report, exploration and discovery data are used to visually assist in describing the exploration maturity of selected petroleum provinces with respect to conventional oil and natural gas accumulations. The specific provinces are the Campos Basin (Brazil), the Santos Basin (Brazil), the North Sea Graben (northwestern Europe), the Middle Magdelena Basin (Colombia), the Sirte Basin (Libya), and the Kutei Basin (Indonesia). For each province, discovery data and well data through October 2019 are reported; from these data, depth distributions of the oil in oil fields and natural gas in gas fields were computed.

The concepts of delineated prospective area and explored area include elements of geographic spatial information and statistical data analytics. Graphs showing dynamic growth of discoveries that are tied to the delineated prospective area provide a means of grading prospective area. Visualizations put the results of exploration in the context of geographic and geologic features of the play or basin and can be a tool to assist geologists with the appraisal of the number and sizes of undiscovered petroleum accumulations. Visualizations of exploration drilling and discoveries can (1) assist in conceptualizing a geologic model of the basin, (2) highlight relations among discovered accumulations in different plays or assessment units within the basin, and (3) allow the geologist to identify the missing information needed to complete the geologic model of a basin. Further, if visualization attributes can be quantified, they may be used for formulating quantitative models that predict numbers and sizes of undiscovered oil and gas accumulations. Such modeling approaches include discovery process models, Bayesian network models that characterize play or assessment unit dependencies, and innovative applications of machine learning to complement standard geologic assessments.

The purpose of this report is to show how visualizations can further the understanding of exploration maturity for the six selected petroleum provinces. It also shows how the geologic framework, geologic data, and drilling and discovery trends can give context to the interpretation of the visualizations that lead to appraisal of exploration maturity.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235010","usgsCitation":"Attanasi, E.D., and Freeman, P.A., 2023, Visualization of petroleum exploration maturity for six petroleum provinces outside the United States and Canada: U.S. Geological Survey Scientific Investigations Report 2023–5010, 38 p., https://doi.org/10.3133/sir20235010.","productDescription":"viii, 38 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-119047","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":414671,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235010/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5010"},{"id":414669,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5010/coverthb.jpg"},{"id":414670,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5010/sir20235010.pdf","text":"Report","size":"50.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5010"},{"id":414672,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5010/images/"},{"id":414673,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5010/sir20235010.XML"}],"country":"Brazil, Colombia, Indonesia, Libya, Norway, United Kingdom","otherGeospatial":"Campos Basin, Kutei Basin, Middle Magdelena Basin, North Sea Graben, Santos Basin, Sirte Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -52.300503668764776,\n -33.167402939182026\n ],\n 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Program Coordinator, Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

AskEnergyProgram@usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2023-04-05","noUsgsAuthors":false,"publicationDate":"2023-04-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":867400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Freeman, Philip A. 0000-0002-0863-7431","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":206294,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":867398,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242647,"text":"70242647 - 2023 - Population dynamics and harvest management of eastern mallards","interactions":[],"lastModifiedDate":"2023-06-09T15:15:15.702993","indexId":"70242647","displayToPublicDate":"2023-04-03T07:03:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Population dynamics and harvest management of eastern mallards","docAbstract":"

Managing sustainable harvest of wildlife populations requires regular collection of demographic data and robust estimates of demographic parameters. Estimates can then be used to develop a harvest strategy to guide decision-making. Mallards (Anas platyrhynchos) are an important species in the Atlantic Flyway for many users and they exhibited exponential growth in the eastern United States between the 1970s and 1990s. Since then, estimates of mallard abundance have declined 16%, prompting the Atlantic Flyway Council and United States Fish and Wildlife Service to implement more restrictive hunting regulations and develop a new harvest strategy predicated on an updated population model. Our primary objective was to develop an integrated population model (IPM) for use in an eastern mallard harvest management strategy. We developed an IPM using annual estimates of breeding abundance, 2-season banding and recovery data, and hunter-harvest data from 1998 to 2018. When developing the model, we used novel model selection methods to test various forms of a sub-model for survival including estimating the degree of harvest additivity and any age-specific trends. The top survival sub-model included a negative annual trend on juvenile survival. The IPM posterior estimates for population abundance tracked closely with the observed estimates and estimates of mean annual population growth rate ranged from 0.88 to 1.08. Our population model provided increased precision in abundance estimates compared to survey methods for use in an updated harvest strategy. The IPM posterior estimates of survival rates were relatively stable for adult cohorts, and annual growth rate was positively correlated with the female age ratio, a measure of reproduction. Either or both of those demographic parameters, juvenile survival or reproduction, could be a target for management efforts to address the population decline. The resulting demographic parameters provided information on the equilibrium population size and can be used in an adaptive harvest strategy for mallards in eastern North America.

","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.22405","usgsCitation":"Roberts, A.J., Hostetler, J.A., Stiller, J.C., Devers, P.K., and Link, W., 2023, Population dynamics and harvest management of eastern mallards: Journal of Wildlife Management, v. 87, no. 5, e22405, 18 p., https://doi.org/10.1002/jwmg.22405.","productDescription":"e22405, 18 p.","ipdsId":"IP-148216","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":499332,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jwmg.22405","text":"Publisher Index Page"},{"id":435387,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZMPO0J","text":"USGS data release","linkHelpText":"Data for &quot;Population Dynamics and Harvest Management of Eastern Mallards&quot;"},{"id":415650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"87","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-04-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Anthony J.","contributorId":191131,"corporation":false,"usgs":false,"family":"Roberts","given":"Anthony","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":869215,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostetler, Jeffrey A. 0000-0003-3669-1758","orcid":"https://orcid.org/0000-0003-3669-1758","contributorId":190248,"corporation":false,"usgs":false,"family":"Hostetler","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":869216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stiller, Joshua C.","contributorId":276124,"corporation":false,"usgs":false,"family":"Stiller","given":"Joshua","email":"","middleInitial":"C.","affiliations":[{"id":56930,"text":"New York DEC","active":true,"usgs":false}],"preferred":false,"id":869217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Devers, Patrick K.","contributorId":167173,"corporation":false,"usgs":false,"family":"Devers","given":"Patrick","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":869218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Link, William 0000-0002-9913-0256","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":221718,"corporation":false,"usgs":true,"family":"Link","given":"William","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":869219,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70242089,"text":"70242089 - 2023 - Magnitude conversion and earthquake recurrence rate models for the central and eastern United States","interactions":[],"lastModifiedDate":"2023-04-06T16:37:04.276307","indexId":"70242089","displayToPublicDate":"2023-03-31T11:17:40","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":13787,"text":"Research Information Letter","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"2023-03","title":"Magnitude conversion and earthquake recurrence rate models for the central and eastern United States","docAbstract":"

Development of Seismic Source Characterization (SSC) models, which is an essential part of Probabilistic Seismic Hazard Analyses (PSHA), can help forecast the temporal and spatial distribution of future damaging earthquakes (\uD835\uDC40w≥ 5) in seismically active regions. Because it is impossible to associate all earthquakes with known faults, seismic source models for PSHA often include sources of diffuse seismicity in which future earthquake scenarios are not localized on mapped faults. These sources of diffuse seismicity are referred to as area source zones, distributed seismicity zones, or just source zones. During the early years of PSHA studies, it was assumed that earthquakes in seismotectonic zones have (1) uniform spatial distribution, (2) Poisson temporal distribution, and (3) exponential magnitude distribution (NRC, 2012). In seismically active regions (e.g., the Western United States), where active faults are readily identified, models of the spatial distribution of earthquakes include both the fault source geometries and the distributed seismicity (background) source zones. Source characterization of active faults is complemented by paleoseismic studies with estimates of earthquake magnitudes, dates of occurrences, and slip rates, which provide important information for PSHA studies.

In the Central and Eastern United States (CEUS) very few Quaternary-active faults have the requisite information for use in PSHA (i.e., fault geometry and dimensions, event rates or slip rates, etc.), and we lack knowledge about the causative faults for most observed seismicity in the region. As a result, area source zones are frequently used in site-specific PSHA in the CEUS to represent diffuse seismicity that cannot be associated with faults. However, there are examples of active fault sources in the CEUS, such as the Meers fault, the Cheraw fault, and New Madrid region, where individual faults can be characterized.

The source characterization models for background seismicity are based, to a large extent, on an assumption that spatial distribution of historical and recorded seismicity will not change substantially for time periods of interest for PSHA (approximately the next 50-100 years for engineered structures). Furthermore, studies such as those by Kafka (2007, 2009) found a correlation between the locations of small- to moderate-magnitude earthquakes and the locations of large-magnitude earthquakes, indicating that we can, with some level of confidence, use the spatial pattern of smaller earthquakes to forecast the future pattern of damaging earthquakes.

Within background seismicity zones, the earthquake rate forecast is developed using spatial smoothing of the small to moderate magnitude events in earthquake catalogs. Different methodologies are used for this purpose and can predict varying distributions of seismicity rates. This in turn affects the results of a seismic hazard analysis. The U.S. Geological Survey (USGS) and Nuclear Regulatory Commission (NRC) use different methods for computing spatially smoothed seismicity rates in the CEUS; the USGS uses kernel-based spatial smoothing methods in developing the National Seismic Hazard Model (NSHM), and the method adopted in the Central and Eastern United States Seismic Source Characterization (CEUS-SSC) project is used when evaluating seismic hazard for nuclear power plant siting. These methods are described and the impact on seismic hazard are evaluated in this Research Information Letter (RIL).

Another important input to estimating the rate of distributed seismicity is event magnitudes listed in earthquake catalogs. A substantial source of uncertainty in catalogs is the magnitude assigned to a given earthquake. Numerous different magnitude types exist, with each magnitude type computed in a different way. Therefore, for the sake of consistency, both the CEUS-SSC and the USGS NSHM have attempted to assemble a complete catalog with a uniform magnitude determination. To this end, moment magnitude, \uD835\uDC40w, which is a physics-based measurement, has been adopted as the standard. However, \uD835\uDC40w was not computed routinely until the past few decades. To address this issue, the CEUS-SSC conducted extensive analyses to determine conversion equations from which to take a routinely computed network (e.g., \uD835\uDC40L or \uD835\uDC5AbLg ) and convert it into \uD835\uDC40w. Another issue with using \uD835\uDC40w is that it becomes increasingly difficult to compute for earthquakes with \uD835\uDC40 less than ~4.

This study investigates the effects of moment magnitude estimation and spatial smoothing methods on estimation of the earthquake rate forecast and on seismic hazard. We investigate the validity of the magnitude conversion equations and their associated uncertainties by applying them to a case study for induced earthquakes in southern Kansas and northern Oklahoma, and summarize the use of the decay of the seismic coda to estimate \uD835\uDC40w for small earthquakes (\uD835\uDC40w < 4. Furthermore, the study documents a comparison and assessment of background seismicity smoothing methods implemented by the USGS for the NSHM and used by the CEUS-SSC for siting nuclear facilities based on probabilistic seismic hazard estimates from multiple source zones in the CEUS and for multiple sites. 

","language":"English","publisher":"Nuclear Regulatory Commission","usgsCitation":"Anooshehpoor, R., Weaver, T., Ake, J., Munson, C., Moschetti, M.P., Shelly, D.R., and Powers, P.M., 2023, Magnitude conversion and earthquake recurrence rate models for the central and eastern United States: Research Information Letter 2023-03, 81 p.","productDescription":"81 p.","ipdsId":"IP-148166","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":415346,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":415324,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://adamswebsearch2.nrc.gov/webSearch2/main.jsp?AccessionNumber=ML23073A370","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","otherGeospatial":"central and eastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115,\n 50\n ],\n [\n -115,\n 25\n ],\n [\n -65,\n 25\n ],\n [\n -65,\n 50\n ],\n [\n -115,\n 50\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anooshehpoor, Rasool","contributorId":303980,"corporation":false,"usgs":false,"family":"Anooshehpoor","given":"Rasool","email":"","affiliations":[{"id":34771,"text":"Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":868790,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weaver, Thomas","contributorId":303981,"corporation":false,"usgs":false,"family":"Weaver","given":"Thomas","affiliations":[{"id":34771,"text":"Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":868791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ake, Jon","contributorId":303982,"corporation":false,"usgs":false,"family":"Ake","given":"Jon","email":"","affiliations":[{"id":34771,"text":"Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":868792,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munson, Cliff","contributorId":303983,"corporation":false,"usgs":false,"family":"Munson","given":"Cliff","email":"","affiliations":[{"id":34771,"text":"Nuclear Regulatory Commission","active":true,"usgs":false}],"preferred":false,"id":868793,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868794,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shelly, David R. 0000-0003-2783-5158 dshelly@usgs.gov","orcid":"https://orcid.org/0000-0003-2783-5158","contributorId":206750,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868795,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Powers, Peter M. 0000-0003-2124-6184 pmpowers@usgs.gov","orcid":"https://orcid.org/0000-0003-2124-6184","contributorId":176814,"corporation":false,"usgs":true,"family":"Powers","given":"Peter","email":"pmpowers@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":868796,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70263433,"text":"70263433 - 2023 - The new Self Anchored Suspension (SAS) Bridge of the San Francisco Bay Bridge System: A preliminary study of its response and behavior during a small earthquake","interactions":[],"lastModifiedDate":"2025-02-11T15:25:05.142851","indexId":"70263433","displayToPublicDate":"2023-03-31T09:20:07","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2467,"text":"Journal of Structural Engineering","active":true,"publicationSubtype":{"id":10}},"title":"The new Self Anchored Suspension (SAS) Bridge of the San Francisco Bay Bridge System: A preliminary study of its response and behavior during a small earthquake","docAbstract":"

Seismic behavior and performance of the new Self- Anchored Suspension (SAS) Bridge of the San Francisco Bay Bridge System is studied using response data recorded during the October 14, 2019, \uD835\uDC40\uD835\uDC64⁢4.6 Pleasant Hill earthquake. The new bridge went into service within the last decade as a replacement for the older truss bridge that spanned between Yerba Buena Island and East Bay. During the October 19, 1989, M6.9 Loma Prieta earthquake, which occurred ∼100  km away from the Bay Bridge, a section of the upper deck of the old truss bridge fell onto the lower deck—thus closing this important lifeline between San Francisco and East Bay. The new SAS Bridge (as well as the rest of the Bay Bridge) is instrumented by the California Strong Motion Instrumentation Program (CSMIP). The unique SAS Bridge is suspended by a single tower that is pivotal in trafficking the cable and hanger system to support the eastbound (E) and westbound (W) decks. At both the west and east ends of the SAS, there is a hinge system that connects the W and E decks to the skyways leading to highways. For the west side, the SAS is led to a tunnel at Yerba Buena Island. The response data analyses highlight the complex and yet identifiable coupled response of the deck, tower, and cable system. Using system identification methods including spectral analyses of both acceleration and displacement time history data, the fundamental frequencies (periods) and critical damping percentages are extracted for the main components (tower, deck, and cables) of the bridge where the sensors are deployed. Frequencies (periods) are then compared with the values computed during the design and analysis process of the bridge. The analyses in this paper showed that there is strong evidence of a beating effect attributed to low critical damping percentages and coupled modes. A possible correlation of fundamental periods of such suspension bridges with their span lengths is discussed. The beating effect and period versus span length can be significant topics for further research.

","language":"English","publisher":"American Society of Civil Engineering","doi":"10.1061/JSENDH.STENG-11725","usgsCitation":"Celebi, M., 2023, The new Self Anchored Suspension (SAS) Bridge of the San Francisco Bay Bridge System: A preliminary study of its response and behavior during a small earthquake: Journal of Structural Engineering, v. 149, no. 6, 05023003, 12 p., https://doi.org/10.1061/JSENDH.STENG-11725.","productDescription":"05023003, 12 p.","ipdsId":"IP-138272","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":488064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1061/jsendh.steng-11725","text":"Publisher Index Page"},{"id":481928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay Bridge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.30992911723865,\n 37.83469490117358\n ],\n [\n -122.36848380330268,\n 37.83469490117358\n ],\n [\n -122.36848380330268,\n 37.80847229984835\n ],\n [\n -122.30992911723865,\n 37.80847229984835\n ],\n [\n -122.30992911723865,\n 37.83469490117358\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"149","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":926975,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70241955,"text":"70241955 - 2023 - Assessing arthropod diversity metrics derived from stream environmental DNA: Spatiotemporal variation and paired comparisons with manual sampling","interactions":[],"lastModifiedDate":"2023-04-03T11:43:32.05906","indexId":"70241955","displayToPublicDate":"2023-03-31T06:40:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"title":"Assessing arthropod diversity metrics derived from stream environmental DNA: Spatiotemporal variation and paired comparisons with manual sampling","docAbstract":"

Background

Benthic invertebrate (BI) surveys have been widely used to characterize freshwater environmental quality but can be challenging to implement at desired spatial scales and frequency. Environmental DNA (eDNA) allows an alternative BI survey approach, one that can potentially be implemented more rapidly and cheaply than traditional methods.

Methods

We evaluated eDNA analogs of BI metrics in the Potomac River watershed of the eastern United States. We first compared arthropod diversity detected with primers targeting mitochondrial 16S (mt16S) and cytochrome c oxidase 1 (cox1 or COI) loci to that detected by manual surveys conducted in parallel. We then evaluated spatial and temporal variation in arthropod diversity metrics with repeated sampling in three focal parks. We also investigated technical factors such as filter type used to capture eDNA and PCR inhibition treatment.

Results

Our results indicate that genus-level assessment of eDNA compositions is achievable at both loci with modest technical noise, although database gaps remain substantial at mt16S for regional taxa. While the specific taxa identified by eDNA did not strongly overlap with paired manual surveys, some metrics derived from eDNA compositions were rank-correlated with previously derived biological indices of environmental quality. Repeated sampling revealed statistical differences between high- and low-quality sites based on taxonomic diversity, functional diversity, and tolerance scores weighted by taxon proportions in transformed counts. We conclude that eDNA compositions are efficient and informative of stream condition. Further development and validation of scoring schemes analogous to commonly used biological indices should allow increased application of the approach to management needs.

","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.15163","usgsCitation":"Aunins, A.W., Mueller, S.J., Fike, J., and Cornman, R.S., 2023, Assessing arthropod diversity metrics derived from stream environmental DNA: Spatiotemporal variation and paired comparisons with manual sampling: PeerJ, v. 11, e15163, 34 p., https://doi.org/10.7717/peerj.15163.","productDescription":"e15163, 34 p.","ipdsId":"IP-146615","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":444004,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.15163","text":"Publisher Index Page"},{"id":435391,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NNZNVH","text":"USGS data release","linkHelpText":"Metabarcode sequencing of aquatic environmental DNA from the Potomac River Watershed, 2015-2020"},{"id":415048,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-03-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Aunins, Aaron 0000-0001-5240-1453 aaunins@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-1453","contributorId":5863,"corporation":false,"usgs":true,"family":"Aunins","given":"Aaron","email":"aaunins@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":868369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mueller, Sara J.","contributorId":303889,"corporation":false,"usgs":false,"family":"Mueller","given":"Sara","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":868370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. 0000-0001-8797-7823","orcid":"https://orcid.org/0000-0001-8797-7823","contributorId":207268,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":868372,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70242007,"text":"70242007 - 2023 - Assessing tradeoffs between current and desired vegetation condition in a National Park using historical maps and high resolution lidar data","interactions":[],"lastModifiedDate":"2023-07-24T16:33:34.967038","indexId":"70242007","displayToPublicDate":"2023-03-30T06:39:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Assessing tradeoffs between current and desired vegetation condition in a National Park using historical maps and high resolution lidar data","docAbstract":"

In the United States, National Park Service Civil War battlefield units are managed for both historical accuracy (i.e., to represent landscape conditions at the time of the conflict for historical interpretation), and for natural resource protection. However, managing for both goals can create conflicts as many battlefields were largely open or in second growth forests historically, but now harbor significant forest resources after more than 100 years of preservation. Managing for historical accuracy therefore may require maintenance of the landscape in a successional stage out of phase with the current landscape. We use historical landscape maps and current high-resolution forest structure data derived from lidar to examine tradeoffs in returning the landscape of a major Civil War battlefield (Wilderness Battlefield) to conditions present at the time of the battle. We demonstrate that National Park battlefield units can harbor significant forest resources in contrast to the surrounding landscape, especially in areas of intense commercial, urban, and suburban development. Managing for or restoring landscapes to historical conditions could have important ecological implications.

","language":"English","publisher":"Wiley","doi":"10.1111/rec.13911","usgsCitation":"Young, J.A., and Mahan, C., 2023, Assessing tradeoffs between current and desired vegetation condition in a National Park using historical maps and high resolution lidar data: Restoration Ecology, v. 31, no. 5, e13911, 8 p., https://doi.org/10.1111/rec.13911.","productDescription":"e13911, 8 p.","ipdsId":"IP-145189","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444014,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1111/rec.13911","text":"Publisher Index Page"},{"id":415154,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"5","noUsgsAuthors":false,"publicationDate":"2023-05-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":868511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mahan, Carolyn","contributorId":303907,"corporation":false,"usgs":false,"family":"Mahan","given":"Carolyn","affiliations":[{"id":65925,"text":"Pennsylvania State University - Altoona","active":true,"usgs":false}],"preferred":false,"id":868510,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70241434,"text":"sir20235020 - 2023 - Completion summary for Borehole TAN-2336 at Test Area North, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2026-03-02T22:15:56.861854","indexId":"sir20235020","displayToPublicDate":"2023-03-28T11:16:10","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":"2023-5020","displayTitle":"Completion Summary for Borehole TAN-2336 at Test Area North, Idaho National Laboratory, Idaho","title":"Completion summary for Borehole TAN-2336 at Test Area North, Idaho National Laboratory, Idaho","docAbstract":"

In 2021, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, drilled and constructed borehole TAN-2336 for stratigraphic framework analyses and long-term groundwater monitoring of the eastern Snake River Plain aquifer at the Idaho National Laboratory in southeastern Idaho. Borehole TAN-2336 initially was cored from the depths of 34.0–255.8 ft below land surface (BLS) to collect continuous geologic data and then redrilled to complete construction as a monitoring well completed to about 255 ft BLS. Three sediment layers are described in geophysical data, but only one was recovered in core and described as fine sand with evidence of ash (pumice) near 203 ft BLS. Basalt texture for borehole TAN-2336 generally was described as aphanitic, phaneritic, diktytaxitic, and porphyritic. Basalt flows varied from highly fractured to dense with high to low vesiculation.

Geophysical data were examined with photographed core material to make lithologic descriptions as well as suggest zones where groundwater flow was anticipated. Primary pathways for groundwater, fractured basalt, occur in two areas with the first occurrence near 232.0 ft BLS and the second occurrence near 248.6 ft BLS in borehole TAN-2336. The first occurrence was identified near the top of the water column (232.0 ft BLS) and is more pronounced than the bottom interval (248.6 ft BLS). The location of these fractures in borehole TAN-2336 appear to impact the aquifer tests that were conducted following final well construction. Single-well aquifer tests were completed July 14, 2021, to provide estimates of transmissivity and hydraulic conductivity. Estimates for transmissivity and hydraulic conductivity during aquifer test 1 were 1.24×103 feet squared per day (ft2/d) and 1.76 feet per day (ft/d), respectively. Estimates for transmissivity and hydraulic conductivity during aquifer test 2 were 1.22×103 ft2/d and 1.75 ft/d, respectively. The transmissivity and hydraulic conductivity estimates for well TAN-2336 were within range of those considered from previous aquifer tests in other wells near Test Area North.

Water-quality samples were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Water samples for select inorganic constituents showed concentrations consistent with signatures from regional groundwater. Water-quality samples analyzed for stable isotopes of oxygen and hydrogen are consistent with signatures from irrigation and agricultural recharge inputs to the aquifer. Results for trichloroethene, vinyl chloride, and strontium-90 were all measured above their respective maximum contaminant levels (MCLs) for public drinking water supplies. The nutrient concentration results are likely being impacted by the remediation amendment introduced to the aquifer to address trichloroethylene concentrations from past waste-disposal activities. These waste-disposal activities have resulted in volatile organic compound and radiochemical detections in groundwater samples collected at well TAN-2336.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235020","collaboration":"Prepared in cooperation with the U.S. Department of Energy","programNote":"DOE/ID-22260","usgsCitation":"Twining, B.V., Treinen, K.C., and Trcka, A.R., 2023, Completion summary for Borehole TAN-2336 at Test Area North, Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2023–5020, 33 p. plus appendixes, https://doi.org/10.3133/sir20235020.","productDescription":"Report: vii, 33 p.; Appendix: 2","additionalOnlineFiles":"Y","ipdsId":"IP-137450","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":414342,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5020/sir20235020.XML"},{"id":414336,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5020/coverthb.jpg"},{"id":414337,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5020/sir20235020.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5020"},{"id":414340,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235020/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5020"},{"id":500714,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114615.htm","linkFileType":{"id":5,"text":"html"}},{"id":414341,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5020/images"},{"id":414339,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5020/sir20235020_appendix2.pdf","text":"Appendix 2","size":"43.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5020 Appendix 2"},{"id":414338,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2023/5020/sir20235020_appendix1.pdf","text":"Appendix 1","size":"218 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5020 Appendix 1"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -112.07738340728746,\n 43.34536223650912\n ],\n [\n -112.07738340728746,\n 44.091416267461994\n ],\n [\n -113.46655634842513,\n 44.091416267461994\n ],\n [\n -113.46655634842513,\n 43.34536223650912\n ],\n [\n -112.07738340728746,\n 43.34536223650912\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520

","tableOfContents":"","publishedDate":"2023-03-28","noUsgsAuthors":false,"publicationDate":"2023-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Twining, Brian V. 0000-0003-1321-4721 btwining@usgs.gov","orcid":"https://orcid.org/0000-0003-1321-4721","contributorId":2387,"corporation":false,"usgs":true,"family":"Twining","given":"Brian","email":"btwining@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866843,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Treinen, Kerri C. 0000-0003-0645-6810 ktreinen@usgs.gov","orcid":"https://orcid.org/0000-0003-0645-6810","contributorId":296540,"corporation":false,"usgs":true,"family":"Treinen","given":"Kerri","email":"ktreinen@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866844,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trcka, Allison R. 0000-0001-8498-4737 atrcka@usgs.gov","orcid":"https://orcid.org/0000-0001-8498-4737","contributorId":303227,"corporation":false,"usgs":true,"family":"Trcka","given":"Allison","email":"atrcka@usgs.gov","middleInitial":"R.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":false,"id":866845,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70242842,"text":"70242842 - 2023 - Diverse portfolios: Investing in tributaries for restoration of large river fishes in the Anthropocene","interactions":[],"lastModifiedDate":"2023-04-20T11:38:15.653135","indexId":"70242842","displayToPublicDate":"2023-03-28T06:36:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5738,"text":"Frontiers in Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Diverse portfolios: Investing in tributaries for restoration of large river fishes in the Anthropocene","docAbstract":"

Rehabilitation of large Anthropocene rivers requires engagement of diverse stakeholders across a broad range of sociopolitical boundaries. Competing objectives often constrain options for ecological restoration of large rivers whereas fewer competing objectives may exist in a subset of tributaries. Further, tributaries contribute toward building a “portfolio” of river ecosystem assets through physical and biological processes that may present opportunities to enhance the resilience of large river fishes. Our goal is to review roles of tributaries in enhancing mainstem large river fish populations. We present case histories from two greatly altered and distinct large-river tributary systems that highlight how tributaries contribute four portfolio assets to support large-river fish populations: 1) habitat diversity, 2) connectivity, 3) ecological asynchrony, and 4) density-dependent processes. Finally, we identify future research directions to advance our understanding of tributary roles and inform conservation actions. In the Missouri River United States, we focus on conservation efforts for the state endangered lake sturgeon, which inhabits large rivers and tributaries in the Midwest and Eastern United States. In the Colorado River, Grand Canyon United States, we focus on conservation efforts for recovery of the federally threatened humpback chub. In the Missouri River, habitat diversity focused on physical habitats such as substrate for reproduction, and deep-water habitats for refuge, whereas augmenting habitat diversity for Colorado River fishes focused on managing populations in tributaries with minimally impaired thermal and flow regimes. Connectivity enhancements in the Missouri River focused on increasing habitat accessibility that may require removal of physical structures like low-head dams; whereas in the Colorado River, the lack of connectivity may benefit native fishes as the disconnection provides refuge from non-native fish predation. Hydrologic variability among tributaries was present in both systems, likely underscoring ecological asynchrony. These case studies also described density dependent processes that could influence success of restoration actions. Although actions to restore populations varied by river system, these examples show that these four portfolio assets can help guide restoration activities across a diverse range of mainstem rivers and their tributaries. Using these assets as a guide, we suggest these can be transferable to other large river-tributary systems.

","language":"English","publisher":"Frontiers","doi":"10.3389/fenvs.2023.1151315","usgsCitation":"Bouska, K.L., Healy, B.D., Moore, M.J., Dunn, C.G., Spurgeon, J.J., and Paukert, C.P., 2023, Diverse portfolios: Investing in tributaries for restoration of large river fishes in the Anthropocene: Frontiers in Environmental Science, v. 11, 1151315, 18 p., https://doi.org/10.3389/fenvs.2023.1151315.","productDescription":"1151315, 18 p.","ipdsId":"IP-149017","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":444048,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2023.1151315","text":"Publisher Index Page"},{"id":416046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","noUsgsAuthors":false,"publicationDate":"2023-03-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Bouska, Kristen L. 0000-0002-4115-2313 kbouska@usgs.gov","orcid":"https://orcid.org/0000-0002-4115-2313","contributorId":178005,"corporation":false,"usgs":true,"family":"Bouska","given":"Kristen","email":"kbouska@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":869951,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Healy, Brian D. 0000-0002-4402-638X","orcid":"https://orcid.org/0000-0002-4402-638X","contributorId":304257,"corporation":false,"usgs":true,"family":"Healy","given":"Brian","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":869952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Michael J. 0000-0002-5495-7049","orcid":"https://orcid.org/0000-0002-5495-7049","contributorId":304258,"corporation":false,"usgs":true,"family":"Moore","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":869953,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Corey Garland 0000-0002-7102-2165","orcid":"https://orcid.org/0000-0002-7102-2165","contributorId":288691,"corporation":false,"usgs":true,"family":"Dunn","given":"Corey","email":"","middleInitial":"Garland","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":869954,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Spurgeon, Jonathan J. 0000-0002-6888-5867","orcid":"https://orcid.org/0000-0002-6888-5867","contributorId":304259,"corporation":false,"usgs":true,"family":"Spurgeon","given":"Jonathan","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":869955,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paukert, Craig P. 0000-0002-9369-8545","orcid":"https://orcid.org/0000-0002-9369-8545","contributorId":245524,"corporation":false,"usgs":true,"family":"Paukert","given":"Craig","middleInitial":"P.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":869956,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70242623,"text":"70242623 - 2023 - The geometry and kinematics of the latest paleozoic Allatoona Fault, one of the youngest thrusts in the southernmost Appalachian Hinterland, Alabama and Georgia, U.S.A.","interactions":[],"lastModifiedDate":"2023-04-11T11:38:26.293056","indexId":"70242623","displayToPublicDate":"2023-03-27T06:36:31","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":732,"text":"American Journal of Science","active":true,"publicationSubtype":{"id":10}},"title":"The geometry and kinematics of the latest paleozoic Allatoona Fault, one of the youngest thrusts in the southernmost Appalachian Hinterland, Alabama and Georgia, U.S.A.","docAbstract":"

The Allatoona thrust fault in the southernmost hinterland of the Appalachian Blue Ridge-Piedmont megathrust sheet is among the latest structures in the kinematic sequence of events along the west flank of the orogen. It is an out-of-sequence, craton-directed thrust fault that cuts metamorphic isograds and earlier thrusts, and it has a nearly linear trace of ≥280 km, making it one of the major thrust faults in the orogen. On the northwest, the fault cuts Pennsylvanian or younger(?) regional cross antiforms that cause significant orogenic curvature of older underlying thrust sheets and is likely Permian in age. To the southeast, however, units within the fault hanging wall maintain a nearly constant width resulting in a significant change in the regional structural architecture of the orogen. In the central segment of the fault, where it marks the western/eastern Blue Ridge domain boundary, a ~20 km-long eyelid window (Mulberry Rock window) framed by three amphibolite facies thrust sheets overlying the greenschist facies Talladega belt allochthon, allows a 3-D view into the structural architecture, kinematics, and trajectories of the regional thrusts. Two earlier thrusts within the window (Mulberry Rock and Burnt Hickory Ridge thrusts, with a combined minimum horizontal net slip component of 27 km) are cut by the Allatoona fault, which is a ~15 m-wide high strain zone with top-to-the-northwest displacement, and a >17.2 km horizontal net slip vector. Structural branch points between the Allatoona and Mulberry Rock thrusts indicate that the Mulberry Rock allochthon is a large north-trending horse beneath the Allatoona fault, centered on the Mulberry Rock window, which is likely the result of oblique ramp thrusting over the massive Mulberry Rock Gneiss. The Allatoona fault cuts down obliquely into the tectonostratigraphy progressively deeper both to the northeast and northwest, locally approaching underlying foreland thrust sheets, and cutting older regional structures. To the northeast, the Allatoona fault lies at the base of the Dahlonega gold belt, becoming an internal eastern Blue Ridge thrust at Dawsonville, Georgia. Although that sequence extends another 120 km into North Carolina, continuation of the Allatoona fault that additional distance is in debate. Regardless, the Allatoona is one of the kinematically latest and longest faults in the southern Appalachian orogen.

","language":"English","publisher":"American Journal of Science","doi":"10.2475/001c.72988","usgsCitation":"Tull, J.F., Holm-Denoma, C., Almuntshry, N.A., and McMahan, E.L., 2023, The geometry and kinematics of the latest paleozoic Allatoona Fault, one of the youngest thrusts in the southernmost Appalachian Hinterland, Alabama and Georgia, U.S.A.: American Journal of Science, v. 323, no. 3, 29 p., https://doi.org/10.2475/001c.72988.","productDescription":"29 p.","ipdsId":"IP-142434","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":444072,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.2475/001c.72988","text":"Publisher Index Page"},{"id":415561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Georgia, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.78337204542909,\n 35.275176393361846\n ],\n [\n -84.71613439831707,\n 34.590959801384585\n ],\n [\n -87.17601375653753,\n 33.90106173390045\n ],\n [\n -87.08816092231528,\n 32.911012930100796\n ],\n [\n -86.12177974587156,\n 32.31902234357682\n ],\n [\n -84.54042872987256,\n 32.65249875132356\n ],\n [\n -82.38803429142892,\n 33.82811254034496\n ],\n [\n -81.46557953209633,\n 35.167521993940355\n ],\n [\n -82.78337204542909,\n 35.275176393361846\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"323","issue":"3","noUsgsAuthors":false,"publicationDate":"2023-03-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Tull, James F.","contributorId":139458,"corporation":false,"usgs":false,"family":"Tull","given":"James","email":"","middleInitial":"F.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":869139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holm-Denoma, Christopher S. 0000-0003-3229-5440","orcid":"https://orcid.org/0000-0003-3229-5440","contributorId":219763,"corporation":false,"usgs":true,"family":"Holm-Denoma","given":"Christopher S.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":869140,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Almuntshry, Nawwaf A.","contributorId":304073,"corporation":false,"usgs":false,"family":"Almuntshry","given":"Nawwaf","email":"","middleInitial":"A.","affiliations":[{"id":65962,"text":"University of King Abdulaziz","active":true,"usgs":false}],"preferred":false,"id":869141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMahan, Ericka L.","contributorId":304074,"corporation":false,"usgs":false,"family":"McMahan","given":"Ericka","email":"","middleInitial":"L.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":869142,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70241485,"text":"sir20235018 - 2023 - Selected anthropogenic contaminants in groundwater, Papio-Missouri River Natural Resources District, eastern Nebraska, 1992–2020","interactions":[],"lastModifiedDate":"2026-03-02T22:07:49.228967","indexId":"sir20235018","displayToPublicDate":"2023-03-22T14:13:36","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":"2023-5018","displayTitle":"Selected Anthropogenic Contaminants in Groundwater, Papio-Missouri River Natural Resources District, Eastern Nebraska, 1992–2020","title":"Selected anthropogenic contaminants in groundwater, Papio-Missouri River Natural Resources District, eastern Nebraska, 1992–2020","docAbstract":"

A study in cooperation with the Papio-Missouri River Natural Resources District was completed in 2019 to determine the concentration of contaminants of emerging concern (CEC) in groundwater in the Papio-Missouri River Natural Resources District, eastern Nebraska. Each well was sampled twice (in June and October or November) in 2019, totaling 34 samples. Samples were analyzed for 132 CECs, which include pharmaceutical, steroid hormone, and other organic chemicals. Seven of the 132 CEC analytes were detected in samples collected during this study. The most commonly detected CEC in this study was the antibiotic sulfamethoxazole. Other CECs detected in this study were nicotine, methyl-1H-benzotiazole (industrial product), acetaminophen (analgesic), caffeine, and metformin (diabetes medicine). None of the detected CECs have health-based water-quality standards. The agricultural herbicide atrazine was also sampled for and was detected in 15 of 26 samples from 8 wells, but all samples were below the established water-quality standard.

Nitrate, dissolved oxygen, and iron sampling results for 2010–19 and 1992–2020 were also assessed to determine the extent and trend of anthropogenic contamination in the Papio-Missouri River Natural Resources District. Nitrate as nitrogen was detected at a concentration greater than 4 milligrams per liter in 92 samples (19 percent), and detections in 36 samples (7.6 percent) exceeded 10 milligrams per liter, which is the U.S. Environmental Protection Agency’s maximum contaminant level for drinking water and Nebraska’s Title 118 maximum contaminant level for groundwater. Time series analysis showed that nitrate concentrations are not increasing or decreasing in any of the aquifers except for in three specific well nests, which are in phase 2 management areas. Dissolved oxygen results indicate potential denitrification throughout the Elkhorn alluvial aquifer; iron concentrations indicate potential denitrification in parts of the Missouri River alluvial aquifer.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235018","collaboration":"Prepared in cooperation with the Papio-Missouri River Natural Resources District","usgsCitation":"Hall, B.M., Kavan, C.L., Flynn, A.T., and Cherry, M.L., 2023, Selected anthropogenic contaminants in groundwater, Papio-Missouri River Natural Resources District, eastern Nebraska, 1992–2020: U.S. Geological Survey Scientific Investigations Report 2023–5018, 35 p., https://doi.org/10.3133/sir20235018.","productDescription":"Report: viii, 35 p.; Dataset","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-129446","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":500712,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114614.htm","linkFileType":{"id":5,"text":"html"}},{"id":414566,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235018/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":414475,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":414473,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5018/images"},{"id":414467,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5018/coverthb.jpg"},{"id":414472,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5018/sir20235018.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":414471,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5018/sir20235018.pdf","text":"Report","size":"1.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5018"}],"country":"United States","state":"Nebraska","otherGeospatial":"Papio-Missouri River Natural Resources District","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -96.44002964238103,\n 42.54396877053898\n ],\n [\n -96.58279049799194,\n 42.600578625387556\n ],\n [\n -96.76947777071449,\n 42.600578625387556\n ],\n [\n -96.74751456215893,\n 42.44680377755785\n ],\n [\n -96.62671691510306,\n 42.05663484833863\n ],\n [\n -96.6047537065475,\n 41.68045966846773\n ],\n [\n -96.56082728943636,\n 41.38451863047598\n ],\n [\n -96.51690087232578,\n 41.16994185576513\n ],\n [\n -96.27530557821459,\n 41.18647280254271\n ],\n [\n -96.03371028410338,\n 41.22778191479978\n ],\n [\n -95.83604140710383,\n 41.26906494493187\n ],\n [\n -95.93487584560361,\n 41.63943772246449\n ],\n [\n -96.05567349265895,\n 41.885177311048636\n ],\n [\n -96.25334236965901,\n 42.317015660865195\n ],\n [\n -96.44002964238103,\n 42.54396877053898\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"

Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-03-22","noUsgsAuthors":false,"publicationDate":"2023-03-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Hall, Brent M. 0000-0003-3815-5158 bhall@usgs.gov","orcid":"https://orcid.org/0000-0003-3815-5158","contributorId":4547,"corporation":false,"usgs":true,"family":"Hall","given":"Brent","email":"bhall@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kavan, Cory L. 0000-0002-5887-9316 ckavan@usgs.gov","orcid":"https://orcid.org/0000-0002-5887-9316","contributorId":5677,"corporation":false,"usgs":true,"family":"Kavan","given":"Cory","email":"ckavan@usgs.gov","middleInitial":"L.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866995,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flynn, Amanda T. 0000-0001-9768-2076 aflynn@usgs.gov","orcid":"https://orcid.org/0000-0001-9768-2076","contributorId":176644,"corporation":false,"usgs":true,"family":"Flynn","given":"Amanda","email":"aflynn@usgs.gov","middleInitial":"T.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866996,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cherry, Mikaela L. 0000-0003-1081-0296 mcherry@usgs.gov","orcid":"https://orcid.org/0000-0003-1081-0296","contributorId":303279,"corporation":false,"usgs":true,"family":"Cherry","given":"Mikaela","email":"mcherry@usgs.gov","middleInitial":"L.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":866997,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70247698,"text":"70247698 - 2023 - Metabarcoding analysis of meiobenthic biodiversity along the Gulf of Mexico continental shelf","interactions":[],"lastModifiedDate":"2023-08-11T14:27:27.877857","indexId":"70247698","displayToPublicDate":"2023-03-22T09:23:34","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Metabarcoding analysis of meiobenthic biodiversity along the Gulf of Mexico continental shelf","docAbstract":"

This study explores how diverse the meiobenthic (meiofauna and other benthic micro-eukaryotes) community is throughout the United States Gulf of Mexico (GOM) continental shelf. In late 2010 and 2011, 51 sediment samples were collected along GOM from Texas through Florida at a range of depths (40m–496m). An additional six deep-sea slope sediment cores were collected in December 2010 near the Deepwater Horizon platform (1370–1385m and 1865m). Metabarcoding of the 18S hypervariable V9 region was conducted to assess biodiversity. Within continental shelf samples, there was greater meiobenthic diversity off the Eastern GOM coast in comparison to both Central and Western GOM coast locations. The Eastern GOM coast has known sediment differences from Western GOM sites. These sediment differences along with influences from the Gulf of Mexico Loop Current may account for observed variations in GOM meiobenthic diversity.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2023.108303","usgsCitation":"Brannock, P.M., Demopoulos, A., Landers, S.C., Waits, D.S., and Halanych, K.M., 2023, Metabarcoding analysis of meiobenthic biodiversity along the Gulf of Mexico continental shelf: Estuarine, Coastal and Shelf Science, v. 285, 108303, 11 p., https://doi.org/10.1016/j.ecss.2023.108303.","productDescription":"108303, 11 p.","ipdsId":"IP-143979","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":444121,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2023.108303","text":"Publisher Index Page"},{"id":419746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -81.0454668578711,\n 25.2112866504243\n ],\n [\n -82.26870034867704,\n 26.46838949145966\n ],\n [\n -82.72708466360095,\n 27.33933552895833\n ],\n [\n -82.88356327975112,\n 27.923703811696868\n ],\n [\n -82.69546708608799,\n 28.85741771478554\n ],\n [\n -83.05448982390429,\n 29.044828371309947\n ],\n [\n -84.00249439203462,\n 29.935333298895316\n ],\n [\n -85.17649729113158,\n 29.542297138113014\n ],\n [\n -86.37997870471644,\n 30.195765985638346\n ],\n [\n -87.96931156473273,\n 30.203483534805827\n ],\n [\n -89.11097137994817,\n 29.882704328046657\n ],\n [\n -89.74582087072409,\n 29.106656041968364\n ],\n [\n -90.30786307986214,\n 28.943752350879407\n ],\n [\n -92.53157289617916,\n 29.458633979299037\n ],\n [\n -93.8003865513774,\n 29.500604600212952\n ],\n [\n -94.75696670446546,\n 29.108237482144702\n ],\n [\n -96.00740561464876,\n 28.332182802828413\n ],\n [\n -96.97702364006607,\n 27.67159636325421\n ],\n [\n -97.18084541150141,\n 26.927544006927846\n ],\n [\n -97.05621148925196,\n 26.087197230578298\n ],\n [\n -95.67021883090977,\n 26.02157337070716\n ],\n [\n -94.6724873820428,\n 27.196943925915562\n ],\n [\n -89.67087171666184,\n 27.50767402365959\n ],\n [\n -87.5707278267364,\n 28.476759671528825\n ],\n [\n -85.60214939415401,\n 26.79513667934289\n ],\n [\n -84.15280818816129,\n 24.02363974069364\n ],\n [\n -81.0454668578711,\n 25.2112866504243\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"285","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brannock, Pamela M.","contributorId":328398,"corporation":false,"usgs":false,"family":"Brannock","given":"Pamela","email":"","middleInitial":"M.","affiliations":[{"id":24752,"text":"Rollins College","active":true,"usgs":false}],"preferred":false,"id":880076,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda 0000-0003-2096-4694","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":221145,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landers, Stephen C.","contributorId":328399,"corporation":false,"usgs":false,"family":"Landers","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":78357,"text":"Troy University","active":true,"usgs":false}],"preferred":false,"id":880078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waits, Damien S.","contributorId":328400,"corporation":false,"usgs":false,"family":"Waits","given":"Damien","email":"","middleInitial":"S.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":880079,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Halanych, Kenneth M.","contributorId":328401,"corporation":false,"usgs":false,"family":"Halanych","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[{"id":65271,"text":"University of North Carolina at Wilmington","active":true,"usgs":false}],"preferred":false,"id":880080,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}