{"pageNumber":"38","pageRowStart":"925","pageSize":"25","recordCount":10951,"records":[{"id":70232131,"text":"70232131 - 2022 - Maintenance and dissemination of avian-origin influenza A virus within the northern Atlantic Flyway of North America","interactions":[],"lastModifiedDate":"2023-01-06T13:11:09.711099","indexId":"70232131","displayToPublicDate":"2022-06-06T06:40:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2981,"text":"PLoS Pathogens","active":true,"publicationSubtype":{"id":10}},"title":"Maintenance and dissemination of avian-origin influenza A virus within the northern Atlantic Flyway of North America","docAbstract":"<div class=\"abstract toc-section abstract-type-\"><div class=\"abstract-content\"><p>Wild waterbirds, the natural reservoirs for avian influenza viruses, undergo migratory movements each year, connecting breeding and wintering grounds within broad corridors known as flyways. In a continental or global view, the study of virus movements within and across flyways is important to understanding virus diversity, evolution, and movement. From 2015 to 2017, we sampled waterfowl from breeding (Maine) and wintering (Maryland) areas within the Atlantic Flyway (AF) along the east coast of North America to investigate the spatio-temporal trends in persistence and spread of influenza A viruses (IAV). We isolated 109 IAVs from 1,821 cloacal / oropharyngeal samples targeting mallards<span>&nbsp;</span><i>(Anas platyrhynchos)</i><span>&nbsp;</span>and American black ducks<span>&nbsp;</span><i>(Anas rubripes)</i>, two species having ecological and conservation importance in the flyway that are also host reservoirs of IAV. Isolates with &gt;99% nucleotide similarity at all gene segments were found between eight pairs of birds in the northern site across years, indicating some degree of stability among genome constellations and the possibility of environmental persistence. No movement of whole genome constellations were identified between the two parts of the flyway, however, virus gene flow between the northern and southern study locations was evident. Examination of banding records indicate direct migratory waterfowl movements between the two locations within an annual season, providing a mechanism for the inferred viral gene flow. Bayesian phylogenetic analyses provided evidence for virus dissemination from other North American wild birds to AF dabbling ducks (Anatinae), shorebirds (Charidriformes), and poultry (Galliformes). Evidence was found for virus dissemination from shorebirds to gulls (Laridae), and dabbling ducks to shorebirds and poultry. The findings from this study contribute to the understanding of IAV ecology in waterfowl within the AF.</p></div></div>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.ppat.1010605","usgsCitation":"Prosser, D., Chen, J., Ahlstrom, C., Reeves, A.B., Poulson, R., Sullivan, J.D., McAuley, D., Callahan, C.R., McGowan, P.C., Bahl, J., Stallknecht, D., and Ramey, A.M., 2022, Maintenance and dissemination of avian-origin influenza A virus within the northern Atlantic Flyway of North America: PLoS Pathogens, v. 18, no. 6, e1010605, 25 p., https://doi.org/10.1371/journal.ppat.1010605.","productDescription":"e1010605, 25 p.","ipdsId":"IP-134661","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447535,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.ppat.1010605","text":"Publisher Index Page"},{"id":435822,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UF27FI","text":"USGS data release","linkHelpText":"Data concerning maintenance and dissemination of avian-origin influenza A virus within the Northern Atlantic Flyway of North America"},{"id":401911,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.87109375,\n              36.491973470593685\n            ],\n            [\n              -75.322265625,\n              36.491973470593685\n            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Georgia","active":true,"usgs":false}],"preferred":false,"id":844293,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahlstrom, Christina 0000-0001-5414-8076","orcid":"https://orcid.org/0000-0001-5414-8076","contributorId":214540,"corporation":false,"usgs":true,"family":"Ahlstrom","given":"Christina","email":"","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":844294,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reeves, Andrew B. 0000-0002-7526-0726 areeves@usgs.gov","orcid":"https://orcid.org/0000-0002-7526-0726","contributorId":167362,"corporation":false,"usgs":true,"family":"Reeves","given":"Andrew","email":"areeves@usgs.gov","middleInitial":"B.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":844295,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Poulson, Rebecca L.","contributorId":198807,"corporation":false,"usgs":false,"family":"Poulson","given":"Rebecca L.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":844296,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Jeffery D. 0000-0002-9242-2432","orcid":"https://orcid.org/0000-0002-9242-2432","contributorId":265822,"corporation":false,"usgs":true,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":844297,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McAuley, Daniel 0000-0003-3674-6392 dmcauley@usgs.gov","orcid":"https://orcid.org/0000-0003-3674-6392","contributorId":215182,"corporation":false,"usgs":true,"family":"McAuley","given":"Daniel","email":"dmcauley@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844298,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":844299,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":844300,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bahl, Justin","contributorId":171803,"corporation":false,"usgs":false,"family":"Bahl","given":"Justin","affiliations":[{"id":26950,"text":"University of Texas School of Public Health, 1200 Pressler Street, Houston, TX 77030, USA","active":true,"usgs":false}],"preferred":false,"id":844301,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Stallknecht, David E.","contributorId":225107,"corporation":false,"usgs":false,"family":"Stallknecht","given":"David E.","affiliations":[{"id":36701,"text":"Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine, University of Georgia","active":true,"usgs":false}],"preferred":false,"id":844302,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":844303,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70231907,"text":"70231907 - 2022 - Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","interactions":[],"lastModifiedDate":"2023-01-18T15:51:07.526101","indexId":"70231907","displayToPublicDate":"2022-06-03T08:32:14","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions","docAbstract":"<p>The North American Wetlands Conservation Act (16 U.S.C. 4401-4412) provided funding and administration for wetland management and conservation projects. The North American Wetland Conservation Fund, enabled in 1989 with the Act, provides financial resources. Resource allocation decisions are based, in part, on regional experts, particularly migratory bird Joint Ventures (JVs) (i.e., partnerships for cooperative planning and coordinated management of the continent’s waterfowl populations and habitats). The JVs evaluate funding proposals submitted with their respective regions each year and make funding recommendations to decision makers. Proposal evaluation procedures differ among JVs, however, it could be helpful to consider a transparent, repeatable, and data-driven framework for prioritization within regions. We used structured decision making and linear additive value models for ranking proposals within JV regions. We used two JVs as case studies and constructed two different value models using JV-specific objectives and weights. The framework was developed through a collaborative process with JV staff and stakeholders. Models were written in Microsoft Excel. To test these models, we used six NAWCA proposals submitted to the Upper Mississippi / Great Lakes Joint Venture in 2016 and seven proposals submitted to the Gulf Coast Joint Venture in 2017. We compared proposal ranks assigned by the value model to ranks assigned by each JV’s management board. Ranks assigned by the value model differed from ranks assigned by the board for the Upper Mississippi / Great Lakes Joint Venture, but not for the Gulf Coast Joint Venture. However, ranks from the value model could change markedly with different objective weights and value functions. The weighted linear value model was beneficial for ranking NAWCA proposals because it allows JVs to treat the ranking as a multiple objective problem and tailor the ranking to their specific regional concerns. We believe a structured decision making approach could be adapted by JV staff to facilitate a systematic and transparent process for proposal ranking by their management boards.</p>","language":"English","publisher":"U. S. Fish and Wildlife Service","doi":"10.3996/JFWM-21-089","usgsCitation":"Krainyk, A., Lyons, J.E., Soulliere, G.J., Coluccy, J.M., Wilson, B.C., Brasher, M.G., Al-Saffar, M.A., and Humburg, D.D., 2022, Structured decision making to rank North American Wetland Conservation Act proposals within joint venture regions: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 375-395, https://doi.org/10.3996/JFWM-21-089.","productDescription":"21 p.","startPage":"375","endPage":"395","ipdsId":"IP-122603","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447556,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-21-089","text":"Publisher Index Page"},{"id":401678,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70231846,"text":"sir20215113 - 2022 - Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","interactions":[],"lastModifiedDate":"2026-04-02T19:46:57.445783","indexId":"sir20215113","displayToPublicDate":"2022-06-03T08:07:20","publicationYear":"2022","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":"2021-5113","displayTitle":"Long-Term Groundwater Availability in the Waihe‘e, ‘Īao, and Waikapū Aquifer Systems, Maui, Hawai‘i","title":"Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","docAbstract":"<p>Groundwater levels have declined since the 1940s in the Wailuku area of central Maui, Hawai‘i, on the eastern flank of West Maui volcano, mainly in response to increased groundwater withdrawals. Available data since the 1980s also indicate a thinning of the freshwater lens and an increase in chloride concentrations of pumped water from production wells. These trends, combined with projected increases in demand for groundwater in central Maui, have led to concerns over groundwater availability and have highlighted a need to improve general understanding of the hydrologic effects of proposed groundwater withdrawals in the Waihe‘e, ‘Īao, and Waikapū areas of central Maui.</p><p>A numerical groundwater model was constructed to simulate the flow and salinity of groundwater in central Maui. The model simulates the effects of changes in groundwater withdrawals and recharge on water levels, freshwater-lens thicknesses, and chloride concentrations of pumped water from production wells. The model incorporates updated water-budget estimates of groundwater recharge from infiltration and direct recharge, seepage in stream channels, and inflow from inland areas. Mean annual groundwater recharge from infiltration and direct recharge was estimated using a daily water-budget model and the most current data, including the distributions of monthly rainfall and potential evapotranspiration, for the study area for nine historical periods from 1926 through 2012: 1926–69, 1970–79, 1980–84, 1985–89, 1990–94, 1995–99, 2000–04, 2005–09, and 2010–12. The water-budget model also estimated groundwater recharge based on one hypothetical scenario that used 1980–2010 rainfall and 2017 land cover. For the nine historical periods, estimated recharge from infiltration and direct recharge within the area of the groundwater model ranged from 30.4 million gallons per day (Mgal/d) during 2010–12 to 98.7 Mgal/d during 1926–69. Variability in recharge during these periods mainly reflects changes in rainfall and irrigation over time. Between 2010 and 2014, streamflow restoration in previously diverted streams resulted in an estimated increase in recharge from seepage in stream channels of about 12.5 Mgal/d. Average groundwater inflow of about 39.6 Mgal/d from inland, dike-intruded areas to the main area of interest was estimated from an existing island-wide numerical groundwater-flow model, which is at a larger scale and incorporates a greater number of simplifying assumptions.</p><p>The numerical groundwater model developed for this study was calibrated to 1926–2012 transient water levels, vertical salinity profiles, and chloride concentrations of water pumped by production wells in the study area. The model was then used to evaluate one future recharge and six selected withdrawal scenarios, developed in consultation with the Maui Department of Water Supply, in terms of long-term changes in water level and 50-percent ocean-water salinity surface. The groundwater model was also used to simulate the future salinity of water withdrawn by existing and proposed production wells. The simulations were run to steady-state conditions, providing an estimate of the long-term effects of changes in withdrawal and recharge on the groundwater resource. Results of the simulated future withdrawal scenarios indicate that, relative to 2017–18 rates, the scenarios’ long-term effect of increased withdrawals ultimately leads to lower water levels and a higher 50-percent ocean-water salinity surface indicating a thinning of the freshwater lens. Results also indicate that the increased withdrawals produce some groundwater with chloride concentration below 250 milligrams per liter and some groundwater with higher chloride concentration. The amount of drawdown near production wells and the quality of water withdrawn from production wells is dependent on the rate and spatial distribution of the withdrawals.</p><p>The model was also used to evaluate how groundwater availability may be affected for a drier recharge scenario based on a published study of future climate. Model results of the future recharge scenario indicate that the rate of groundwater recharge is a controlling factor for (1) water levels, (2) the 50-percent ocean-water salinity surface, and (3) the quality of water withdrawn from production wells in the Wailuku area. Coupled with reduced groundwater recharge (with all other factors remaining equal), the modeled future withdrawals in the scenario would tend to cause lower water levels, a higher 50-percent ocean-water salinity surface, and increased salinity of water withdrawn from production wells.</p><p>The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the long-term hydrologic effects of additional groundwater withdrawals in central Maui. The model has several limitations, including its non-uniqueness and inability to account for local-scale heterogeneities. Short-term effects of changes in recharge and withdrawals—and optimization of pumping rates to meet increased demand for water with acceptable salinity—are possible conditions for future simulation analyses.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215113","collaboration":"Prepared in cooperation with the County of Maui Department of Water Supply","usgsCitation":"Rotzoll, K., Oki, D.S., Johnson, A.G., and Souza, W.R., 2022, Long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2021–5113, 80 p., https://doi.org/10.3133/sir20215113.","productDescription":"Report: ix, 80 p., Data Release","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-119307","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":502120,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113156.htm","linkFileType":{"id":5,"text":"html"}},{"id":401475,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P959B45F","text":"SUTRA model used to evaluate long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i","description":"Rotzoll, K., 2022, SUTRA model used to evaluate long-term groundwater availability in the Waihe‘e, ‘Īao, and Waikapū aquifer systems, Maui, Hawai‘i: U.S. Geological Survey data release, https://doi.org/10.5066/P959B45F."},{"id":401474,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5113/sir20215113.pdf","text":"Report","size":"14 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":401473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5113/covrthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.95916748046875,\n              20.720153096892663\n            ],\n            [\n              -156.0003662109375,\n              20.792066100825636\n            ],\n            [\n              -156.26953125,\n              20.958874775031518\n            ],\n            [\n              -156.47003173828125,\n              20.912700155617568\n            ],\n            [\n              -156.60736083984375,\n              21.056307701901847\n            ],\n            [\n              -156.7254638671875,\n              20.93578924489374\n            ],\n            [\n              -156.65679931640625,\n              20.802336592979056\n            ],\n            [\n              -156.533203125,\n              20.756113874762082\n            ],\n            [\n              -156.4947509765625,\n              20.781794909576234\n            ],\n            [\n              -156.4617919921875,\n              20.750977144077833\n            ],\n            [\n              -156.4398193359375,\n              20.601936194281016\n            ],\n            [\n              -156.3629150390625,\n              20.56593890346526\n            ],\n            [\n              -156.2860107421875,\n              20.571081893508193\n            ],\n            [\n              -156.02783203124997,\n              20.6379249854131\n            ],\n            [\n              -155.9564208984375,\n              20.7098770198879\n            ],\n            [\n              -155.95916748046875,\n              20.720153096892663\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_hi@usgs.gov\" data-mce-href=\"mailto:dc_hi@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/piwsc\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/piwsc\">Pacific Islands Water Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov\">U.S. Geological Survey</a><br>Inouye Regional Center<br>1845 Wasp Blvd., B176<br>Honolulu, HI 96818</p>","tableOfContents":"<ul><li>Acknowledgements&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Purpose and Scope&nbsp;&nbsp;</li><li>Setting&nbsp;&nbsp;</li><li>Hydrogeologic Framework and Rock Properties&nbsp;&nbsp;</li><li>Groundwater-Flow System&nbsp;&nbsp;</li><li>Simulation of Groundwater Flow&nbsp;&nbsp;</li><li>Limitations&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Appendix 1. Estimation of Recharge with a Water Budget&nbsp;</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2022-06-03","noUsgsAuthors":false,"publicationDate":"2022-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Rotzoll, Kolja 0000-0002-5910-888X kolja@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":3325,"corporation":false,"usgs":true,"family":"Rotzoll","given":"Kolja","email":"kolja@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":843965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oki, Delwyn S. 0000-0002-6913-8804 dsoki@usgs.gov","orcid":"https://orcid.org/0000-0002-6913-8804","contributorId":1901,"corporation":false,"usgs":true,"family":"Oki","given":"Delwyn","email":"dsoki@usgs.gov","middleInitial":"S.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Adam G. 0000-0003-2448-5746 ajohnson@usgs.gov","orcid":"https://orcid.org/0000-0003-2448-5746","contributorId":4752,"corporation":false,"usgs":true,"family":"Johnson","given":"Adam","email":"ajohnson@usgs.gov","middleInitial":"G.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Souza, William R.","contributorId":90295,"corporation":false,"usgs":true,"family":"Souza","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":843968,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70236670,"text":"70236670 - 2022 - Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022","interactions":[],"lastModifiedDate":"2022-09-15T16:53:08.222861","indexId":"70236670","displayToPublicDate":"2022-06-01T11:41:56","publicationYear":"2022","noYear":false,"publicationType":{"id":25,"text":"Newsletter"},"publicationSubtype":{"id":30,"text":"Newsletter"},"seriesTitle":{"id":12588,"text":"Lateral Lines","active":true,"publicationSubtype":{"id":30}},"title":"Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022","docAbstract":"<p>The Winchester TU Chapter partnered with US Geological Survey scientists to forecast habitat conditions for brook trout in Virginia. The results can be viewed here: https://chesapeake.usgs.gov/fishforecast/ </p><p>TU members deployed stream temperature gages within several streams across the region: Dry River, Passage Creek, Spout Run, Beaver Creek, Mossy Creek. The USGS then used the temperature data to evaluate current and future conditions for brook trout.&nbsp;</p>","language":"English","publisher":"Trout Unlimited, Winchester Chapter #638","usgsCitation":"Hitt, N.P., 2022, Spout Run temperature study revisited- Part II: New insights for trout habitat from TU & USGS collaboration 2022: Lateral Lines, no. June 2022, p. 8-9.","productDescription":"2 p.","startPage":"8","endPage":"9","ipdsId":"IP-141316","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":406771,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":406769,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://winchestertu.org/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","otherGeospatial":"Spout Run","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.12721252441406,\n              39.03\n            ],\n            [\n              -78,\n              39.03\n            ],\n            [\n              -78,\n              39.144972625112224\n            ],\n            [\n              -78.12721252441406,\n              39.144972625112224\n            ],\n            [\n              -78.12721252441406,\n              39.03\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","issue":"June 2022","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":238185,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":851822,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70237855,"text":"70237855 - 2022 - The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA","interactions":[],"lastModifiedDate":"2022-10-27T15:51:09.02612","indexId":"70237855","displayToPublicDate":"2022-06-01T10:44:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2979,"text":"PLoS Biology","active":true,"publicationSubtype":{"id":10}},"title":"The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA","docAbstract":"<p><span>Snake fungal disease (SFD; ophidiomycosis), caused by the pathogen&nbsp;</span><i>Ophidiomyces ophiodiicola</i><span>&nbsp;(</span><i>Oo</i><span>), has been documented in wild snakes in North America and Eurasia, and is considered an emerging disease in the eastern United States of America. However, a lack of historical disease data has made it challenging to determine whether&nbsp;</span><i>Oo</i><span>&nbsp;is a recent arrival to the USA or whether SFD emergence is due to other factors. Here, we examined the genomes of 82&nbsp;</span><i>Oo</i><span>&nbsp;strains to determine the pathogen’s history in the eastern USA.&nbsp;</span><i>Oo</i><span>&nbsp;strains from the USA formed a clade (Clade II) distinct from European strains (Clade I), and molecular dating indicated that these clades diverged too recently (approximately 2,000 years ago) for transcontinental dispersal of&nbsp;</span><i>Oo</i><span>&nbsp;to have occurred via natural snake movements across Beringia. A lack of nonrecombinant intermediates between clonal lineages in Clade II indicates that&nbsp;</span><i>Oo</i><span>&nbsp;has actually been introduced multiple times to North America from an unsampled source population, and molecular dating indicates that several of these introductions occurred within the last few hundred years. Molecular dating also indicated that the most common Clade II clonal lineages have expanded recently in the USA, with time of most recent common ancestor mean estimates ranging from 1985 to 2007 CE. The presence of Clade II in captive snakes worldwide demonstrates a potential mechanism of introduction and highlights that additional incursions are likely unless action is taken to reduce the risk of pathogen translocation and spillover into wild snake populations.</span></p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pbio.3001676","usgsCitation":"Ladner, J.T., Palmer, J.M., Ettinger, C.L., Stajich, J.E., Farrell, T.M., Glorioso, B.M., Lawson, B., Price, S.J., Stengle, A.G., Grear, D.A., and Lorch, J.M., 2022, The population genetics of the causative agent of snake fungal disease indicate recent introductions to the USA: PLoS Biology, v. 20, no. 6, e3001676, 24 p., https://doi.org/10.1371/journal.pbio.3001676.","productDescription":"e3001676, 24 p.","ipdsId":"IP-137982","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research 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,{"id":70237644,"text":"70237644 - 2022 - Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","interactions":[],"lastModifiedDate":"2022-10-18T13:57:05.161824","indexId":"70237644","displayToPublicDate":"2022-06-01T08:44:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (<i>Dreissena</i> spp.) environmental DNA","title":"Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA","docAbstract":"<p><span>Environmental (e)DNA tools are sensitive and cost-effective for early detection of invasive species. However, the uncertainty associated with the interpretation of positive eDNA detections makes it challenging to determine appropriate natural resource management responses. Multiple sources of error can give rise to positive detections of eDNA in a sample when individuals of that species are not present at the site or a widespread infestation is not imminent. Acting on an erroneous eDNA inference could result in needless costs or reductions in desirable resources. Alternatively, failure to rapidly act on eDNA results that truly indicate invader presence could compound negative impacts and lead to high, long-term costs to manage infestations. We used a structured decision making (SDM) process, which incorporates tradeoffs and uncertainties, to evaluate appropriate response actions following hypothetical eDNA detections of invasive dreissenid mussel (</span><i>Dreissena</i><span>&nbsp;spp.) eDNA in Jordanelle Reservoir, Utah (USA). We worked with decision-makers and stakeholders to identify objectives and discrete management action alternatives to assess consequences and tradeoffs. Alternatives ranged from no action to intensive and expensive control efforts. The best performing alternative was delayed containment described by immediate attempts to confirm the eDNA detections using non-molecular sampling techniques followed by mandatory watercraft exit inspections to prevent dreissenid mussel spread to regional water bodies. Non-molecular sampling increased public support for management by demonstrating a commitment to monitor the invasion state before action, whereas containment decreased likelihood of regional spread to other waters. Delayed containment had the lowest downside risk, and the highest upside gains relative to other alternative actions. Sensitivity analyses showed our results to be robust to parameter and outcome uncertainty.</span></p>","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2022.13.2.06","usgsCitation":"Sepulveda, A., Smith, D.R., O'Donnell, K., Owens, N., White, B., Richter, C.A., Merkes, C.M., Wolf, S., Rau, M., Neilson, M., Daniel, W., Dumoulin, C.E., and Hunter, M., 2022, Using structured decision making to evaluate potential management responses to detection of dreissenid mussel (Dreissena spp.) environmental DNA: Management of Biological Invasions, v. 13, no. 2, p. 344-368, https://doi.org/10.3391/mbi.2022.13.2.06.","productDescription":"25 p.","startPage":"344","endPage":"368","ipdsId":"IP-133646","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences 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,{"id":70262275,"text":"70262275 - 2022 - Round Goby captured in a North American estuary: Status and implications in the Hudson River, New York","interactions":[],"lastModifiedDate":"2025-01-22T20:31:54.917634","indexId":"70262275","displayToPublicDate":"2022-06-01T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Round Goby captured in a North American estuary: Status and implications in the Hudson River, New York","docAbstract":"<p><span>Round Goby&nbsp;</span><i>Neogobius melanostomus</i><span>, a nonnative fish species to North America, has been rapidly expanding through the connected waterways of the Laurentian Great Lakes. Herein, we document the eastward and southern expansion of Round Goby into the Hudson River, New York, an iconic coastal estuary that drains to Long Island Sound and the Atlantic seaboard. In summer and early fall 2021, routine fish monitoring conducted by the New York State Department of Environmental Conservation documented a population of Round Goby in the tidal portion of the Hudson River. Over the course of monitoring in 2021, personnel collected 112 Round Goby between Albany, New York, and Poughkeepsie, New York, with the southernmost collection occurring approximately 140 km downstream of invasion front as reported in 2020 within the New York State Canal System. Although Round Goby previously colonized large rivers and streams in the Great Lakes watershed, there is little information about the invasion success and ecological impacts of Round Goby in estuarine environments in North America. We discuss the distribution and biological characteristics of the Hudson River Round Goby population as well as the potential ecological implications and areas of future research and monitoring for this range expansion.</span></p>","language":"English","publisher":"Allen Press","doi":"10.3996/jfwm-22-012","usgsCitation":"Pendleton, R., Berdan, R., George, S.D., Kenney, G., and Sethi, S., 2022, Round Goby captured in a North American estuary: Status and implications in the Hudson River, New York: Journal of Fish and Wildlife Management, v. 13, no. 2, p. 524-533, https://doi.org/10.3996/jfwm-22-012.","productDescription":"10 p.","startPage":"524","endPage":"533","ipdsId":"IP-138487","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/jfwm-22-012","text":"Publisher Index 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,{"id":70231871,"text":"70231871 - 2022 - Variability in marsh migration potential determined by topographic rather than anthropogenic constraints in the Chesapeake Bay region","interactions":[],"lastModifiedDate":"2022-08-02T14:22:39.473636","indexId":"70231871","displayToPublicDate":"2022-05-31T06:32:59","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5456,"text":"Limnology and Oceanography Letters","active":true,"publicationSubtype":{"id":10}},"title":"Variability in marsh migration potential determined by topographic rather than anthropogenic constraints in the Chesapeake Bay region","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Sea level rise (SLR) and saltwater intrusion are driving inland shifts in coastal ecosystems. Here, we make high-resolution (1 m) predictions of land conversion under future SLR scenarios in 81 watersheds surrounding Chesapeake Bay, United States, a hotspot for accelerated SLR and saltwater intrusion. We find that 1050–3748 km<sup>2</sup><span>&nbsp;</span>of marsh could be created by 2100, largely at the expense of forested wetlands. Predicted marsh migration exceeds total current tidal marsh area and is ~ 4× greater than historical observations. Anthropogenic land use in marsh migration areas is concentrated within a few watersheds and minimally impacts calculated metrics of marsh resilience. Despite regional marsh area maintenance, local ecosystem service replacement within vulnerable watersheds remains uncertain. However, our work suggests that topography rather than land use drives spatial variability in wetland vulnerability regionally, and that rural land conversion is needed to compensate for extensive areal losses on heavily developed coasts globally.</p></div></div>","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.10262","usgsCitation":"Molino, G., Carr, J., Ganju, N., and Kirwan, M.L., 2022, Variability in marsh migration potential determined by topographic rather than anthropogenic constraints in the Chesapeake Bay region: Limnology and Oceanography Letters, v. 7, no. 4, p. 321-331, https://doi.org/10.1002/lol2.10262.","productDescription":"11 p.","startPage":"321","endPage":"331","ipdsId":"IP-133300","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":447606,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/lol2.10262","text":"External Repository"},{"id":401520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Chesapeake Bay region","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -75.849609375,\n              39.52099229357195\n            ],\n            [\n              -76.201171875,\n              39.774769485295465\n            ],\n            [\n              -76.79443359375,\n              39.740986355883564\n            ],\n            [\n              -77.23388671874999,\n              39.36827914916014\n            ],\n            [\n              -77.40966796875,\n              38.496593518947584\n            ],\n            [\n              -77.27783203125,\n              37.24782120155428\n            ],\n            [\n              -76.81640625,\n              36.66841891894786\n            ],\n            [\n              -76.1572265625,\n              36.50963615733049\n            ],\n            [\n              -75.89355468749999,\n              36.56260003738545\n            ],\n            [\n              -76.00341796875,\n              36.94989178681327\n            ],\n            [\n              -74.970703125,\n              38.37611542403604\n            ],\n            [\n              -75.25634765625,\n              38.41055825094609\n            ],\n            [\n              -75.498046875,\n              38.25543637637947\n            ],\n            [\n              -75.7177734375,\n              38.30718056188316\n            ],\n            [\n              -75.849609375,\n              39.027718840211605\n            ],\n            [\n              -75.849609375,\n              39.52099229357195\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-05-31","publicationStatus":"PW","contributors":{"authors":[{"text":"Molino, Grace 0000-0001-7345-8619","orcid":"https://orcid.org/0000-0001-7345-8619","contributorId":292186,"corporation":false,"usgs":false,"family":"Molino","given":"Grace","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":844013,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Joel A. 0000-0002-9164-4156 jcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-9164-4156","contributorId":168645,"corporation":false,"usgs":true,"family":"Carr","given":"Joel A.","email":"jcarr@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844014,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":202878,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":844015,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kirwan, Matt L.","contributorId":189205,"corporation":false,"usgs":false,"family":"Kirwan","given":"Matt","middleInitial":"L.","affiliations":[],"preferred":false,"id":844016,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231840,"text":"70231840 - 2022 - Understanding the water resources of a mountain-block aquifer: Tucson Mountains, Arizona","interactions":[],"lastModifiedDate":"2022-05-30T20:50:00.823956","indexId":"70231840","displayToPublicDate":"2022-05-30T15:42:31","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10769,"text":"Journal of Contemporary Water Research & Education","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the water resources of a mountain-block aquifer: Tucson Mountains, Arizona","docAbstract":"<p>Water resources are limited in arid locations such as Tucson Basin. Residential development in the Tucson Mountains to the west of Tucson, Arizona, is limited by groundwater resources. Groundwater samples were collected from fractured bedrock and alluvial aquifers surrounding the Tucson Mountains to assess water quality and recharge history through measurement of stable O, H, and S isotopes; tritium; and<span>&nbsp;</span><sup>14</sup>C. Most groundwater is a mixture of different ages but is commonly several thousand years old. A few sampling locations indicated a component of water recharged after the above-ground nuclear testing of the mid 1950s, and these sites may represent locations near where the aquifer receives present-day recharge. The Tucson Mountains also host sulfide deposits associated with fractures and replacement zones; these locally contribute to poor-quality groundwater. Projections of future climate predict intensifying drought in southwestern North America. In the study area, a combination of strategies such as rainwater harvesting, exploitation of renewable water, and low groundwater use could be used for sustainable use of the groundwater supply.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1936-704X.2021.3369.x","usgsCitation":"Eastoe, C.J., and Beisner, K.R., 2022, Understanding the water resources of a mountain-block aquifer: Tucson Mountains, Arizona: Journal of Contemporary Water Research & Education, v. 175, no. 1, https://doi.org/10.1111/j.1936-704X.2021.3369.x.","productDescription":"14 p.","startPage":"1-14","ipdsId":"IP-130604","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":447613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1936-704x.2021.3369.x","text":"Publisher Index Page"},{"id":401364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Tucson Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.27296447753905,\n              32.155268542097815\n            ],\n            [\n              -110.99761962890625,\n              32.155268542097815\n            ],\n            [\n              -110.99761962890625,\n              32.377062004744786\n            ],\n            [\n              -111.27296447753905,\n              32.377062004744786\n            ],\n            [\n              -111.27296447753905,\n              32.155268542097815\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"175","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Eastoe, Christopher J.","contributorId":173510,"corporation":false,"usgs":false,"family":"Eastoe","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":843936,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beisner, Kimberly R. 0000-0002-2077-6899 kbeisner@usgs.gov","orcid":"https://orcid.org/0000-0002-2077-6899","contributorId":2733,"corporation":false,"usgs":true,"family":"Beisner","given":"Kimberly","email":"kbeisner@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843937,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70238968,"text":"70238968 - 2022 - Stream size, temperature, and density explain body sizes of freshwater salmonids across a range of climate conditions","interactions":[],"lastModifiedDate":"2022-12-19T14:57:53.446229","indexId":"70238968","displayToPublicDate":"2022-05-30T08:57:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Stream size, temperature, and density explain body sizes of freshwater salmonids across a range of climate conditions","docAbstract":"<p><span>Climate change and anthropogenic activities are altering the body sizes of fishes, yet our understanding of factors influencing body size for many taxa remains incomplete. We evaluated the relationships between climate, environmental, and landscape attributes and the body size of different taxa of freshwater trout (Salmonidae) in the USA. Hierarchical spatial modeling across a gradient of habitats (5221 sites) illustrated the importance of watershed effects, which explained 17%–45% of the of the variation in body size across taxa. Stream size had a strong, positive relationship with body size, yet there was approximately tenfold difference in the strength of the relationship across taxa. Trout body size consistently declined with increasing density across taxa. Despite reliance on cold water, we found positive relationships between summer stream temperature and trout body size across most taxa. Our results highlight how providing trout access to larger, productive rivers for the expression of growth and life-history variation would promote body size diversity within and across populations.</span></p>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2021-0343","usgsCitation":"Al-Chokhachy, R.K., Letcher, B., Muhlfeld, C.C., Dunham, J., Cline, T.J., Hitt, N.P., Roberts, J., and Schmetterling, D., 2022, Stream size, temperature, and density explain body sizes of freshwater salmonids across a range of climate conditions: Canadian Journal of Fisheries and Aquatic Sciences, v. 79, no. 10, p. 1729-1744, https://doi.org/10.1139/cjfas-2021-0343.","productDescription":"16 p.","startPage":"1729","endPage":"1744","ipdsId":"IP-131094","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science 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ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":859447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Letcher, Benjamin 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":242666,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":859449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":859450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cline, Timothy Joseph 0000-0002-4955-654X","orcid":"https://orcid.org/0000-0002-4955-654X","contributorId":228871,"corporation":false,"usgs":true,"family":"Cline","given":"Timothy","email":"","middleInitial":"Joseph","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":859451,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hitt, Nathaniel P. 0000-0002-1046-4568 nhitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1046-4568","contributorId":4435,"corporation":false,"usgs":true,"family":"Hitt","given":"Nathaniel","email":"nhitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":859452,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roberts, James 0000-0002-4193-610X jroberts@usgs.gov","orcid":"https://orcid.org/0000-0002-4193-610X","contributorId":5453,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"jroberts@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859453,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schmetterling, David","contributorId":196555,"corporation":false,"usgs":false,"family":"Schmetterling","given":"David","affiliations":[],"preferred":false,"id":859454,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70256676,"text":"70256676 - 2022 - Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture–recapture movement model","interactions":[],"lastModifiedDate":"2024-08-30T15:04:17.421329","indexId":"70256676","displayToPublicDate":"2022-05-28T09:39:55","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture–recapture movement model","docAbstract":"<p><span>Animal movement is a fundamental ecological process affecting the survival and reproduction of individuals, the structure of populations, and the dynamics of communities. Methods to quantify animal movement and spatiotemporal abundances, however, are generally separate and therefore omit linkages between individual-level and population-level processes. We describe an integrated spatial capture–recapture (SCR) movement model to jointly estimate (1) the number and distribution of individuals in a defined spatial region and (2) movement of those individuals through time. We applied our model to a study of polar bears (</span><i>Ursus maritimus</i><span>) in a 28,125 km</span><sup>2</sup><span>&nbsp;survey area of the eastern Chukchi Sea, USA in 2015 that incorporated capture–recapture and telemetry data. In simulation studies, the model provided unbiased estimates of movement, abundance, and detection parameters using a bivariate normal random walk and correlated random walk movement process. Our case study provided detailed evidence of directional movement persistence for both male and female bears, where individuals regularly traversed areas larger than the survey area during the 36-day study period. Scaling from individual- to population-level inferences, we found that densities varied from &lt;0.75 bears/625 km</span><sup>2</sup><span>&nbsp;grid cell/day in nearshore cells to 1.6–2.5 bears/grid cell/day for cells surrounded by sea ice. Daily abundance estimates ranged from 53 to 69 bears, with no trend across days. The cumulative number of unique bears that used the survey area increased through time due to movements into and out of the area, resulting in an estimated 171 individuals using the survey area during the study (95% credible interval 124–250). Abundance estimates were similar to a previous multiyear integrated population model using capture–recapture and telemetry data (2008–2016; Regehr et al., Scientific Reports 8:16780, 2018). Overall, the SCR–movement model successfully quantified both individual- and population-level space use, including the effects of landscape characteristics on movement, abundance, and detection, while linking the movement and abundance processes to directly estimate density within a prescribed spatial region and temporal period. Integrated SCR–movement models provide a generalizable approach to incorporate greater movement realism into population dynamics and link movement to emergent properties including spatiotemporal densities and abundances.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3772","usgsCitation":"Hostetter, N.J., Regehr, E., Wilson, R., Royle, A., and Converse, S.J., 2022, Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture–recapture movement model: Ecology, v. 103, no. 10, e3772, 13 p., https://doi.org/10.1002/ecy.3772.","productDescription":"e3772, 13 p.","ipdsId":"IP-130471","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447644,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.3772","text":"Publisher Index Page"},{"id":433369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","otherGeospatial":"eastern Chukchi Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -176.16804284685193,\n              70.64271222820804\n            ],\n            [\n              -176.4405798143377,\n              63.26571385602864\n            ],\n            [\n              -160.5704824801017,\n              63.43804844317145\n            ],\n            [\n              -160.5759226643521,\n              70.4273607365736\n            ],\n            [\n              -176.16804284685193,\n              70.64271222820804\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"103","issue":"10","noUsgsAuthors":false,"publicationDate":"2022-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":908609,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Regehr, E.V.","contributorId":341555,"corporation":false,"usgs":false,"family":"Regehr","given":"E.V.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":908610,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, R.R.","contributorId":341556,"corporation":false,"usgs":false,"family":"Wilson","given":"R.R.","affiliations":[{"id":40296,"text":"United States Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":908611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Royle, J. Andrew 0000-0003-3135-2167 aroyle@usgs.gov","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":146229,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":908612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":908613,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70231912,"text":"70231912 - 2022 - Toxicological responses to sublethal anticoagulant rodenticide exposure in free-flying hawks","interactions":[],"lastModifiedDate":"2022-10-17T15:31:20.593592","indexId":"70231912","displayToPublicDate":"2022-05-28T08:58:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1564,"text":"Environmental Science and Pollution Research","active":true,"publicationSubtype":{"id":10}},"title":"Toxicological responses to sublethal anticoagulant rodenticide exposure in free-flying hawks","docAbstract":"<p><span>An important component of assessing the hazards of anticoagulant rodenticides to non-target wildlife is observations in exposed free-ranging individuals. The objective of this study was to determine whether environmentally realistic, sublethal first-generation anticoagulant rodenticide (FGAR) exposures via prey can result in direct or indirect adverse effects to free-flying raptors. We offered black-tailed prairie dogs (</span><i>Cynomys ludovicianus</i><span>) that had fed on Rozol® Prairie Dog Bait (Rozol, 0.005% active ingredient chlorophacinone, CPN) to six wild-caught red-tailed hawks (RTHA,&nbsp;</span><i>Buteo jamaicensis</i><span>), and also offered black-tailed prairie dogs that were not exposed to Rozol to another two wild-caught RTHAs for 7&nbsp;days. On day 6, blood was collected to determine CPN’s effects on blood clotting time. On day 7, seven of the eight RTHAs were fitted with VHF radio telemetry transmitters and the RTHAs were released the following day and were monitored for 33&nbsp;days. Prothrombin time (PT) and Russell’s viper venom time confirmed that the CPN-exposed RTHAs were exposed to and were adversely affected by CPN. Four of the six CPN-exposed RTHAs exhibited ptiloerection, an indication of thermoregulatory dysfunction due to CPN toxicity, but no signs of intoxication were observed in the reference hawk or the remaining two CPN-exposed RTHAs. Of note is that PT values were associated with ptiloerection duration and frequency; therefore, sublethal CPN exposure can directly or indirectly evoke adverse effects in wild birds. Although our sample sizes were small, this study is a first to relate coagulation times to adverse clinical signs in free-ranging birds.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s11356-022-20881-z","usgsCitation":"Vyas, N.B., Rattner, B.A., Lockhart, J.M., Hulse, C., Rice, C., Kuncir, F., and Kritz, K., 2022, Toxicological responses to sublethal anticoagulant rodenticide exposure in free-flying hawks: Environmental Science and Pollution Research, v. 29, p. 74024-74037, https://doi.org/10.1007/s11356-022-20881-z.","productDescription":"14 p.","startPage":"74024","endPage":"74037","ipdsId":"IP-129660","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":401682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain Arsenal National Wildlife Refuge","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.90089416503906,\n              39.80220607474971\n            ],\n            [\n              -104.78897094726562,\n              39.80115102364283\n            ],\n            [\n              -104.79034423828125,\n              39.86969567045658\n            ],\n            [\n              -104.86518859863281,\n              39.86969567045658\n            ],\n            [\n              -104.8974609375,\n              39.84281323262067\n            ],\n            [\n              -104.90226745605469,\n              39.828577091142016\n            ],\n            [\n              -104.90089416503906,\n              39.80220607474971\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"29","noUsgsAuthors":false,"publicationDate":"2022-05-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Vyas, Nimish B. 0000-0003-0191-1319 nvyas@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-1319","contributorId":4494,"corporation":false,"usgs":true,"family":"Vyas","given":"Nimish","email":"nvyas@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":844100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lockhart, J. Michael","contributorId":179117,"corporation":false,"usgs":false,"family":"Lockhart","given":"J.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":844101,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hulse, Craig S.","contributorId":292224,"corporation":false,"usgs":false,"family":"Hulse","given":"Craig S.","affiliations":[{"id":37374,"text":"Retired USGS","active":true,"usgs":false}],"preferred":false,"id":844102,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rice, Clifford P.","contributorId":270789,"corporation":false,"usgs":false,"family":"Rice","given":"Clifford P.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":844103,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kuncir, Frank","contributorId":139801,"corporation":false,"usgs":false,"family":"Kuncir","given":"Frank","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":844104,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kritz, Kevin","contributorId":292226,"corporation":false,"usgs":false,"family":"Kritz","given":"Kevin","email":"","affiliations":[{"id":7199,"text":"US FWS","active":true,"usgs":false}],"preferred":false,"id":844105,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70231783,"text":"sir20225029 - 2022 - Hydrogeology and groundwater quality in the San Agustin Basin, New Mexico, 1975–2019","interactions":[],"lastModifiedDate":"2026-04-09T17:09:27.463858","indexId":"sir20225029","displayToPublicDate":"2022-05-27T10:43:00","publicationYear":"2022","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":"2022-5029","displayTitle":"Hydrogeology and Groundwater Quality in the San Agustin Basin, New Mexico, 1975–2019","title":"Hydrogeology and groundwater quality in the San Agustin Basin, New Mexico, 1975–2019","docAbstract":"<p>This report describes the findings of a U.S. Geological Survey study, completed in cooperation with the Bureau of Land Management, focused on better understanding the present-day (1975–2019) hydrogeology and groundwater quality of the San Agustin Basin in west-central New Mexico to support sustainable groundwater resource management. The basin hosts a relatively undeveloped basin-fill and alluvium aquifer system and is topographically divided into east and west subbasins by the McClure Hills. Groundwater chemistry and groundwater elevation data were compiled, collected, and interpreted in the context of groundwater flow and quality. The analyses presented in this report consider groundwater chemistry data collected within the last decade (2010–19) and groundwater elevation data collected from 1975 through 2019 to provide insight into present-day conditions. Groundwater elevations show that groundwater typically moves from the highlands to the lowlands, with a prominent east to west regional trend. Groundwater elevations were lowest in the southwestern portion of the west subbasin, where estimated flow directions suggest underflow through the local highlands into the northern East Fork Gila River watershed, which is further supported by historical groundwater elevation data from the northern East Fork Gila River watershed. Gradual groundwater elevation gradients (about 2 feet per mile) near the east and west subbasin divide suggest that groundwater slowly flows from the east subbasin to the west subbasin.</p><p>Quantitative analyses of groundwater chemistry data show that groundwater in both subbasins has similar chemical characteristics. A systematic east to west groundwater evolution in water chemistry was not observed despite evidenced subbasin connectivity. The absence of this pattern suggests that groundwater mixing is regionally prevalent, sediment reactivity is low and variable, and (or) recharge conditions are comparable in both subbasins. Groundwater chemistry was generally independent of aquifer type, suggesting that the aquifers are hydrologically well connected. Corrected carbon-14 groundwater age estimates in the basin ranged from 232 to 13,916 years before present with a median of 5,409 years. A wide range of groundwater ages is therefore present in the basin, with waters commonly being thousands of years old, thereby supporting generally slow regional groundwater movement. A component of relatively young groundwater, for which estimated ages could not be accurately computed, is also present in the basin, and it may commonly mix with older waters. The spatial distribution of categorical and quantitative groundwater ages indicates that most recharge likely occurs in the highlands through mountain-block recharge and as focused recharge within arroyos, although evidence of modern (1953 and after) groundwater was minimal at sampled sites.</p><p>Median annual gradients (groundwater elevation change over time) indicate that most groundwater elevations in the lowlands changed little (−0.2 to 0.2 foot per year) from 1975 through 2019. Groundwater elevations in the highlands varied more annually, which is likely due to recharge from precipitation events. These more variable groundwater elevations in the highlands compared with the lowlands, along with groundwater ages, provide further evidence that most groundwater recharge takes place in the highlands, with minimal recharge in the lowlands. Median groundwater elevation change for all sites was −0.05 foot per year. Temporal consistency of lowland groundwater elevations suggests that regional groundwater dynamics have been more or less stable through time under current climate and development conditions, although median annual gradients indicate that groundwater elevations may have slightly declined on average between 1975 and 2019.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225029","collaboration":"Prepared in cooperation with Bureau of Land Management and in collaboration with New Mexico Bureau of Geology and Mineral Resources","usgsCitation":"Pepin, J.D., Travis, R.E., Blake, J.M., Rinehart, A., and Koning, D., 2022, Hydrogeology and groundwater quality in the San Agustin Basin, New Mexico, 1975–2019: U.S. Geological Survey Scientific Investigations Report 2022–5029, 61 p., 4 app., https://doi.org/10.3133/sir20225029.","productDescription":"Report: x, 61 p.; 6 Tables; Dataset","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-120066","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":502386,"rank":12,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113080.htm","linkFileType":{"id":5,"text":"html"}},{"id":401145,"rank":11,"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":401143,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table3.1.csv","text":"Table 3.1","size":"29.5 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022-5029 Table 3.1"},{"id":401142,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table3.1.xlsx","text":"Table 3.1","size":"55.2 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022-5029 Table 3.1"},{"id":401141,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table2.1.csv","text":"Table 2.1","size":"14.3 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022-5029 Table 2.1"},{"id":401140,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table2.1.xlsx","text":"Table 2.1","size":"27.6 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022-5029 Table 2.1"},{"id":401138,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table1.1.xlsx","text":"Table 1.1","size":"116 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2022-5029 Table 1.1"},{"id":401137,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5029/images"},{"id":401134,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5029/coverthb.jpg"},{"id":401135,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029.pdf","text":"Report","size":"8.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5029"},{"id":401139,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029_table1.1.csv","text":"Table 1.1","size":"146 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2022-5029 Table 1.1"},{"id":401136,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5029/sir20225029.XML"}],"country":"United States","state":"New Mexico","otherGeospatial":"San Agustin Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.666,\n              34.5\n            ],\n            [\n              -107.333,\n              34.5\n            ],\n            [\n              -107.333,\n              33.333\n            ],\n            [\n              -108.666,\n              33.333\n            ],\n            [\n              -108.666,\n              34.5\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/nm-water\" data-mce-href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a> <br>U.S. Geological Survey <br>6700 Edith Blvd. NE <br>Albuquerque, NM 87113</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Results and Discussion</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Compiled Water Level Data</li><li>Appendix 2. Chemistry Data Analyzed in This Study</li><li>Appendix 3. Compiled Chemistry Data</li><li>Appendix 4. Field Blank and Replicate Chemistry Data</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2022-05-27","noUsgsAuthors":false,"publicationDate":"2022-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Pepin, Jeff D. 0000-0002-7410-9979","orcid":"https://orcid.org/0000-0002-7410-9979","contributorId":222161,"corporation":false,"usgs":true,"family":"Pepin","given":"Jeff","email":"","middleInitial":"D.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Travis, Rebecca E. 0000-0001-8601-7791 rtravis@usgs.gov","orcid":"https://orcid.org/0000-0001-8601-7791","contributorId":5562,"corporation":false,"usgs":true,"family":"Travis","given":"Rebecca E.","email":"rtravis@usgs.gov","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blake, Johanna M. 0000-0003-4667-0096 jmtblake@usgs.gov","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":169698,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","email":"jmtblake@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":843820,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rinehart, Alex","contributorId":194395,"corporation":false,"usgs":false,"family":"Rinehart","given":"Alex","affiliations":[],"preferred":false,"id":843821,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koning, Daniel","contributorId":58355,"corporation":false,"usgs":true,"family":"Koning","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":843822,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70257011,"text":"70257011 - 2022 - Effects of prescribed fire on prenesting movements of wild turkeys in Arkansas","interactions":[],"lastModifiedDate":"2024-09-05T15:36:51.76754","indexId":"70257011","displayToPublicDate":"2022-05-20T10:17:30","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Effects of prescribed fire on prenesting movements of wild turkeys in Arkansas","docAbstract":"<p><span>The restoration of historic disturbance regimes is an increasingly common management strategy to conserve disturbance-dependent communities and species, and enhance resilience of ecosystems to climate change or plant and animal invasions. However, the reintroduction of frequent and wide-scale disturbance may have unexpected consequences on species that are accustomed to an environment absent of frequent disturbance. Implementation of frequent prescribed fire for community restoration has coincided with population declines of eastern wild turkeys (</span><i>Meleagris gallopavo silvestris</i><span>) in the Ozark Highlands of Arkansas. We investigated whether there was evidence of linkage between wild turkey movement behavior and habitat use and the widespread use of prescribed fire that began in 2002 and continued through the end of our study in 2013. We fitted 67 female wild turkeys with satellite transmitters in 2012 and 2013 on the White Rock Ecosystem Restoration Area to estimate annual and seasonal home ranges and examine pre-nesting habitat use at multiple spatial scales. Home range was larger for adults in 2013 (4,750 ha, SE = 946.2,&nbsp;</span><i>n</i><span> = 12) than in 2012 (2,703 ha, SE = 283.4,&nbsp;</span><i>n</i><span> = 19). Mean pre-nesting ranges for adults were 1,633 ha (SE = 238.9,&nbsp;</span><i>n</i><span> = 23) in 2012 and 1,118 ha (SE = 158.8,&nbsp;</span><i>n</i><span> = 18) in 2013, smaller than those of sub-adults, 1,761 ha (SE = 581.2,&nbsp;</span><i>n</i><span> = 3) in 2012 and 5,576 ha (SE = 2260,&nbsp;</span><i>n</i><span> = 8) in 2013. Habitat selection analyses for the pre-nesting period indicated that wild turkeys used locations with more variability in canopy cover and vegetation height and in smaller patch sizes than expected based on availability. However, female wild turkeys selected nesting cover that had more variability in canopy cover and vegetation height but in larger patches. Differences in sub-adults and adult home and seasonal ranges suggest that other factors such as density dependence or social hierarchy could be driving movements as opposed to prescribed fire application. Wild turkey females selected variable vegetation structure during the pre-nesting and nesting periods with characteristics that could be a result of frequent prescribed fire or forest succession. However, we documented no direct evidence these characteristics or other aspects of the prescribed fire program were causing wild turkey population declines.</span></p>","language":"English","publisher":"The Wildlife Society","doi":"10.1002/wsb.1264","usgsCitation":"Pittman, H., and Krementz, D.G., 2022, Effects of prescribed fire on prenesting movements of wild turkeys in Arkansas: Wildlife Society Bulletin, v. 46, no. 2, e1264, 14 p., https://doi.org/10.1002/wsb.1264.","productDescription":"e1264, 14 p.","ipdsId":"IP-077113","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":433507,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Boston Mountain Ranger District of the Ozark‐St. Francis, National Forest, White Rock Ecosystem Restoration Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -94.15913371190965,\n              35.85873194814944\n            ],\n            [\n              -94.15913371190965,\n              35.46671910080133\n            ],\n            [\n              -93.6126286148777,\n              35.46671910080133\n            ],\n            [\n              -93.6126286148777,\n              35.85873194814944\n            ],\n            [\n              -94.15913371190965,\n              35.85873194814944\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Pittman, H.T.","contributorId":341911,"corporation":false,"usgs":false,"family":"Pittman","given":"H.T.","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":909138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krementz, David G. 0000-0002-5661-4541 dkrementz@usgs.gov","orcid":"https://orcid.org/0000-0002-5661-4541","contributorId":2827,"corporation":false,"usgs":true,"family":"Krementz","given":"David","email":"dkrementz@usgs.gov","middleInitial":"G.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":909137,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70231812,"text":"70231812 - 2022 - Nearshore bathymetric changes along the Alaska Beaufort Sea coast and possible physical drivers","interactions":[],"lastModifiedDate":"2022-05-27T13:29:13.252547","indexId":"70231812","displayToPublicDate":"2022-05-20T08:24:48","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Nearshore bathymetric changes along the Alaska Beaufort Sea coast and possible physical drivers","docAbstract":"<p><span>Erosion rates&nbsp;along Alaska's Beaufort Sea coast, among the highest in the world, are negatively impacting communities, industrial and military infrastructure, and wildlife habitat. Decreasing maximal winter ice extent and increasing summer open water duration and extent in the Beaufort Sea may be making the coast more vulnerable to destructive storm waves than during recent, colder, icier decades. Previous studies of Beaufort Sea coastal change have been limited to subaerial analyses of the&nbsp;shoreline. Here we describe nearshore seafloor change by comparing post-World War II (WWII) (1945-53)&nbsp;bathymetry&nbsp;data to recently acquired (1985–2018) bathymetry data and relate the observed seafloor change to adjacent shoreline change near Utqiagvik, within Stefansson Sound, and immediately west of Barter Island and Kaktovik. Within the Utqiagvik region,&nbsp;seabed&nbsp;erosion was generally highest (&gt;1.0&nbsp;m of loss) offshore of Point&nbsp;Barrow&nbsp;and along the eastern end of the Tapkaluk Islands, while there were lesser amounts of deposition (&lt;0.5&nbsp;m of gain) within the protected waters of Elson&nbsp;Lagoon. Sedimentation was generally highest offshore of Point Barrow, in a region of converging currents, and on the landward side of the barrier islands and spits fronting Elson Lagoon, which is likely related to a regional trend of westerly&nbsp;sediment transport&nbsp;and landward migration of the barrier islands. Within Stefansson Sound, perhaps the most notable changes from post-WWII bathymetry data compared to recent data are a switch from mixed, low erosion and deposition in 1997 to low deposition (&lt;0.5&nbsp;m) in 2018 east of the Boulder Patch, a switch from low erosion in 1997 to neutral depth change in 2018 in the channel between the north and south Boulder Patch areas, and higher deposition from 1997 to 2018 landward of the rapidly retreating barrier islands along the Sound's northern border. At Barter Island, high erosion near north-facing shorelines and high deposition near west-facing shorelines generally matched shoreline changes. One of our goals is to identify possible processes responsible for the depth changes we quantified. Using simple metrics that relate sediment characteristics with modeled waves and non-wave induced currents, we show that sediment&nbsp;</span>resuspension<span>&nbsp;and transport by both wave and non-wave driven currents likely contribute to the overall patterns of change within the ∼13&nbsp;m isobath along the open coast, and that the influence of wave action affecting sediment transport is expanding seaward.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2022.104745","usgsCitation":"Zimmermann, M., Erikson, L.H., Gibbs, A.E., Prescott, M., Escarzaga, S.M., Tweedie, C.E., Kasper, J., and Duvoy, P.X., 2022, Nearshore bathymetric changes along the Alaska Beaufort Sea coast and possible physical drivers: Continental Shelf Research, v. 242, 104745, 15 p., https://doi.org/10.1016/j.csr.2022.104745.","productDescription":"104745, 15 p.","ipdsId":"IP-132441","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":447707,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2022.104745","text":"Publisher Index Page"},{"id":401293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea coast","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -164.00390625,\n              69.33383491964828\n            ],\n            [\n              -140.9326171875,\n              69.33383491964828\n            ],\n            [\n              -140.9326171875,\n              72.39570570653261\n            ],\n            [\n              -164.00390625,\n              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Center","active":true,"usgs":true}],"preferred":true,"id":843889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":843890,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Prescott, Megan M.","contributorId":292137,"corporation":false,"usgs":false,"family":"Prescott","given":"Megan M.","affiliations":[{"id":62835,"text":"Lynker Technologies, Under contract to Alaska Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":843891,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Escarzaga, Stephen M.","contributorId":279732,"corporation":false,"usgs":false,"family":"Escarzaga","given":"Stephen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":843892,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tweedie, Craig E.","contributorId":200176,"corporation":false,"usgs":false,"family":"Tweedie","given":"Craig","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":843893,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kasper, Jeremy L. 0000-0003-0975-6114","orcid":"https://orcid.org/0000-0003-0975-6114","contributorId":208630,"corporation":false,"usgs":false,"family":"Kasper","given":"Jeremy L.","affiliations":[{"id":37850,"text":"University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":843894,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Duvoy, Paul X.","contributorId":292138,"corporation":false,"usgs":false,"family":"Duvoy","given":"Paul","email":"","middleInitial":"X.","affiliations":[{"id":62836,"text":"Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK, USA","active":true,"usgs":false}],"preferred":false,"id":843895,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70262466,"text":"70262466 - 2022 - Unique land cover classification to assess day-roost habitat selection of northern long-eared bats on the Coastal Plain of North Carolina, USA","interactions":[],"lastModifiedDate":"2025-01-23T17:13:35.036104","indexId":"70262466","displayToPublicDate":"2022-05-19T11:04:33","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1689,"text":"Forests","active":true,"publicationSubtype":{"id":10}},"title":"Unique land cover classification to assess day-roost habitat selection of northern long-eared bats on the Coastal Plain of North Carolina, USA","docAbstract":"<p><span>Reproductively successful and over-wintering populations of the endangered northern long-eared bat (</span><i><span class=\"html-italic\">Myotis septentrionalis</span></i><span>) have recently been discovered on the Coastal Plain of North Carolina. Empirical data on resource selection within the region is limited, likely hindering management of these coastal forests. Our objectives were to determine roosting home range size, selection of day-roost tree species, second- and third-order roosting habitat selection, and to quantify the overall availability of resources in the surrounding landscape. We found core and peripheral roosting home range estimates were large, yet similar to observations from other areas of contiguous forests. Prior to juvenile volancy, female northern long-eared bats appear to select red maple (</span><i><span class=\"html-italic\">Acer rubrum</span></i><span>), water ash (</span><i><span class=\"html-italic\">Fraxinus caroliniana</span></i><span>), and loblolly pine (</span><i><span class=\"html-italic\">Pinus taeda</span></i><span>) as day-roosts, but then use sweetgum (</span><i><span class=\"html-italic\">Liquidambar styraciflua</span></i><span>), swamp bay (</span><i><span class=\"html-italic\">Persea palustris</span></i><span>), and water tupelo (</span><i><span class=\"html-italic\">Nyssa aquatica</span></i><span>) after juvenile volancy. At the second-order spatial scale, roosting home ranges were associated with woody wetlands farther from anthropogenic development and open water. However, within the third-order scale, northern long-eared bats were associated with undeveloped woody wetlands and upland forests, areas containing shorter trees and occurring proximal to open water. Peripheral and core areas were predicted to comprise approximately 20% of the local landscape. Our results show that complex and large tracts of woody wetlands juxtaposed with upland forests in this part of the Coastal Plain may be important for northern long-eared bats locally, results largely consistent with species management efforts in eastern North America.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/f13050792","usgsCitation":"De La Cruz, J., True, M., Taylor, H., Brown, D., and Ford, W., 2022, Unique land cover classification to assess day-roost habitat selection of northern long-eared bats on the Coastal Plain of North Carolina, USA: Forests, v. 13, no. 5, 792, 12 p., https://doi.org/10.3390/f13050792.","productDescription":"792, 12 p.","ipdsId":"IP-139280","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481087,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/f13050792","text":"Publisher Index Page"},{"id":481010,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -76.75026436537884,\n              36.551057495425155\n            ],\n            [\n              -76.75026436537884,\n              36.10817288230365\n            ],\n            [\n              -75.80386759650264,\n              36.10817288230365\n            ],\n            [\n              -75.80386759650264,\n              36.551057495425155\n            ],\n            [\n              -76.75026436537884,\n              36.551057495425155\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"13","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"De La Cruz, Jesse L.","contributorId":342611,"corporation":false,"usgs":false,"family":"De La Cruz","given":"Jesse L.","affiliations":[{"id":81893,"text":"Virginia Polytechnic and State University","active":true,"usgs":false}],"preferred":false,"id":924270,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"True, Michael C.","contributorId":270631,"corporation":false,"usgs":false,"family":"True","given":"Michael C.","affiliations":[{"id":25550,"text":"Virginia Polytechnic Institute and State University","active":true,"usgs":false}],"preferred":false,"id":924271,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Hila","contributorId":270923,"corporation":false,"usgs":false,"family":"Taylor","given":"Hila","email":"","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":924272,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Dorothy","contributorId":349381,"corporation":false,"usgs":false,"family":"Brown","given":"Dorothy","affiliations":[{"id":83477,"text":"Brown Environmental 13","active":true,"usgs":false}],"preferred":false,"id":924273,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":924274,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70256677,"text":"70256677 - 2022 - Local populations of eastern oyster from Louisiana differ in low salinity tolerance","interactions":[],"lastModifiedDate":"2024-08-30T15:13:48.665336","indexId":"70256677","displayToPublicDate":"2022-05-19T10:05:17","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2885,"text":"North American Journal of Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"Local populations of eastern oyster from Louisiana differ in low salinity tolerance","docAbstract":"<p><span>Eastern oysters&nbsp;</span><i>Crassostrea virginica</i><span>&nbsp;support a critical commercial industry and provide many ecosystem services to coastal estuaries yet are currently threatened by changing estuarine conditions. A changing climate and the effects of river and coastal management are altering freshwater inflows into productive oyster areas, causing more frequent and extreme salinity exposure. Although eastern oysters are tolerant to a wide range of salinity means and variations, more frequent and extreme exposure to low salinity (&lt;5‰) impacts oyster populations and aquaculture operations. This study assessed four Louisiana eastern oyster stocks to explore population-specific responses to low-salinity exposure. Hatchery-produced progeny (10–25 mm) were deployed in baskets kept off-bottom on longline systems in a low-salinity (mean ± 1 standard error of the mean daily salinity = 8.7 ± 0.2‰; range = 1.2–19.0‰) and a moderate-salinity (16.8 ± 0.3‰; 4.8–30.0‰) environment for 1 year, beginning in December 2019, with growth and mortality determined monthly. Significant differences in cumulative mortality between stocks at the end of the study were found at the low-salinity site, with the greatest increase in cumulative mortality occurring mid-July to mid-August. Mortality differences between stocks suggest that some eastern oyster populations (i.e., stocks) may be better suited to low salinity or low-salinity events than others. This difference may be attributed to similarity between site of origin and grow-out site conditions and/or to greater salinity variability and therefore higher phenotypic plasticity in some eastern oyster populations compared with others. The identification of oyster stocks able to survive under extreme low-salinity conditions may facilitate the development of “low-salinity-tolerant” broodstock to support aquaculture in areas experiencing and predicted to experience low-salinity events.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/naaq.10248","usgsCitation":"Swam, L., La Peyre, M., Callam, B., and La Peyre, J., 2022, Local populations of eastern oyster from Louisiana differ in low salinity tolerance: North American Journal of Aquaculture, v. 84, no. 3, p. 381-391, https://doi.org/10.1002/naaq.10248.","productDescription":"11 p.","startPage":"381","endPage":"391","ipdsId":"IP-135300","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":467183,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.library.noaa.gov/view/noaa/62209","text":"External Repository"},{"id":433370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -94.0434688771042,\n              30.101527013125377\n            ],\n            [\n              -94.01703847779518,\n              29.552930802352776\n            ],\n            [\n              -89.01824912136517,\n              28.988744299850225\n            ],\n            [\n              -89.10895991675187,\n              29.46576988537774\n            ],\n            [\n              -94.0434688771042,\n              30.101527013125377\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-05-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Swam, Lauren","contributorId":341557,"corporation":false,"usgs":false,"family":"Swam","given":"Lauren","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Callam, Brian","contributorId":341558,"corporation":false,"usgs":false,"family":"Callam","given":"Brian","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":908616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Peyre, Jerome F.","contributorId":341559,"corporation":false,"usgs":false,"family":"La Peyre","given":"Jerome F.","affiliations":[{"id":32913,"text":"Louisiana State University Agricultural Center","active":true,"usgs":false}],"preferred":false,"id":908617,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231650,"text":"fs20223032 - 2022 - Oklahoma and Landsat","interactions":[],"lastModifiedDate":"2022-09-27T12:12:05.638573","indexId":"fs20223032","displayToPublicDate":"2022-05-18T10:48:40","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3032","displayTitle":"Oklahoma and Landsat","title":"Oklahoma and Landsat","docAbstract":"<p>Oklahoma benefits from a varied landscape abundant in resources. Mountains, grasslands, reservoirs, rivers, fields, and forests offer employment and enjoyment in a State that epitomizes the transition from north to south and east to west. Wheat grows in northern Oklahoma; cotton grows in the south. Wetter deciduous forest lands in the southeast contrast with drier mesas in the northwest. Among the many lakes and reservoirs, the Great Salt Plains Lake on the Arkansas River has thousands of acres of salt flats with unique hourglass-shaped selenite crystals.</p><p>Grassland and grazing permeate the Sooner State, which is the second largest cattle producer in the country. Oil, natural gas, and coal have long played a key role in Oklahoma’s economy and energy industry, whereas wind farms in western Oklahoma are a more recent addition.</p><p>The Landsat series of Earth observation satellites has allowed analysts to search for oil in Oklahoma from hundreds of miles above the Earth. The satellite program also helps Oklahoma’s agriculture industry keep an eye on the condition of crops and grazing land.</p><p>Here are just a few ways Landsat has benefited Oklahoma.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223032","usgsCitation":"U.S. Geological Survey, 2022, Oklahoma and Landsat: U.S. Geological Survey Fact Sheet 2022–3032, 2 p., https://doi.org/10.3133/fs20223032.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-139807","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":400758,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223032/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400753,"rank":3,"type":{"id":31,"text":"Publication 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 \"}}]}","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a> <br>U.S. Geological Survey <br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Viewing Fields</li><li>Characterizing Wildfires</li><li>Examining Tornado Damage</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-18","noUsgsAuthors":false,"publicationDate":"2022-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":127955,"corporation":true,"usgs":false,"organization":"U.S. Geological 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,{"id":70256672,"text":"70256672 - 2022 - Wildlife associates of nine-banded armadillo (Dasypus novemcinctus) burrows in Arkansas","interactions":[],"lastModifiedDate":"2024-08-30T14:24:25.771746","indexId":"70256672","displayToPublicDate":"2022-05-15T09:16:03","publicationYear":"2022","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}},"displayTitle":"Wildlife associates of nine-banded armadillo (<i>Dasypus novemcinctus</i>) burrows in Arkansas","title":"Wildlife associates of nine-banded armadillo (Dasypus novemcinctus) burrows in Arkansas","docAbstract":"<p><span>The Nine-banded Armadillo (</span><i>Dasypus novemcinctus</i><span>) is a widespread burrowing species with an expanding geographic range across the southeastern and midwestern United States. Armadillos dig numerous, large burrows within their home ranges and these burrows are likely used by a diverse suite of wildlife species as has been reported for other burrowing ecosystem engineers such as Gopher Tortoises (</span><i>Gopherus polyphemus</i><span>), Desert Tortoises (</span><i>Gopherus agassizi</i><span>), and Black-tailed Prairie Dogs (</span><i>Cynomys ludovicianus</i><span>). We used motion-triggered game cameras at 35 armadillo burrows in 4 ecoregions of Arkansas and documented 19 species of mammals, 4&nbsp;species of reptile, 1&nbsp;species of amphibian, and 40&nbsp;species of bird interacting with burrows. Bobcat (</span><i>Lynx rufus</i><span>), Coyote (</span><i>Canis latrans</i><span>), Eastern Cottontail (</span><i>Sylvilagus floridanus</i><span>), Gray Fox (</span><i>Urocyon cinereoargenteus</i><span>), Gray Squirrel (</span><i>Sciurus carolinensis</i><span>), Northern Raccoon (</span><i>Procyon lotor</i><span>), Virginia Opossum (</span><i>Didelphis virginiana</i><span>), and unidentified rodents (mice and rats) were documented using burrows in all four ecoregions. We documented wildlife hunting, seeking shelter, rearing young in, and taking over and modifying armadillo burrows. The rate of use was highest in the Mississippi Alluvial Valley, a landscape dominated by agriculture, where natural refugia may be limited and rodents are abundant. Armadillo burrows are clearly visited and used by numerous wildlife species to fulfill various life stage requirements, and this list will likely expand if more attention is devoted to understanding the role of armadillos burrows. Armadillos are important ecosystem engineers, and their ecological role warrants more investigation and attention as opposed to only being viewed and managed as agricultural and garden pests.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.8858","usgsCitation":"DeGregorio, B.A., Veon, J.T., and Massey, A., 2022, Wildlife associates of nine-banded armadillo (Dasypus novemcinctus) burrows in Arkansas: Ecology and Evolution, v. 12, no. 5, e8858, 10 p., https://doi.org/10.1002/ece3.8858.","productDescription":"e8858, 10 p.","ipdsId":"IP-139270","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447786,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.8858","text":"Publisher Index Page"},{"id":433366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-94.042964,33.019219],[-94.043428,33.551425],[-94.061896,33.549764],[-94.072156,33.553864],[-94.073744,33.558285],[-94.067985,33.560961],[-94.056442,33.560998],[-94.056096,33.567252],[-94.082641,33.575492],[-94.119902,33.566999],[-94.126898,33.550647],[-94.131382,33.552934],[-94.136046,33.571388],[-94.143402,33.565505],[-94.151456,33.568387],[-94.14216,33.58139],[-94.156782,33.575749],[-94.161277,33.579271],[-94.161082,33.587972],[-94.183913,33.594682],[-94.194465,33.582886],[-94.217198,33.580737],[-94.211329,33.573774],[-94.201106,33.575851],[-94.192483,33.570425],[-94.189884,33.562454],[-94.196395,33.555123],[-94.203594,33.566546],[-94.208078,33.566911],[-94.226392,33.552912],[-94.250197,33.556765],[-94.251108,33.56528],[-94.236836,33.580914],[-94.240179,33.589536],[-94.257801,33.582508],[-94.27909,33.557026],[-94.290901,33.558872],[-94.290372,33.567905],[-94.280849,33.577187],[-94.287025,33.58241],[-94.301023,33.573022],[-94.309582,33.551673],[-94.319492,33.548864],[-94.33059,33.552692],[-94.33438,33.562536],[-94.344023,33.567824],[-94.352433,33.562172],[-94.34729,33.552197],[-94.355945,33.54318],[-94.381667,33.544035],[-94.399393,33.557077],[-94.397398,33.562314],[-94.378561,33.571329],[-94.382887,33.583268],[-94.403342,33.568424],[-94.412175,33.568691],[-94.430039,33.591124],[-94.439518,33.594154],[-94.449112,33.590894],[-94.471152,33.601588],[-94.469451,33.607316],[-94.452325,33.618817],[-94.462736,33.63091],[-94.448451,33.634497],[-94.448637,33.642766],[-94.459198,33.645146],[-94.464186,33.637655],[-94.485875,33.637867],[-94.45753,34.642961],[-94.431215,35.39429],[-94.617919,36.499414],[-90.152481,36.497952],[-90.158568,36.491574],[-90.15946,36.481343],[-90.142269,36.472138],[-90.152888,36.47093],[-90.1557,36.466103],[-90.14153,36.462993],[-90.137323,36.455411],[-90.133993,36.437906],[-90.143798,36.428483],[-90.139499,36.421457],[-90.13559,36.422897],[-90.138653,36.414547],[-90.131038,36.415069],[-90.109495,36.404073],[-90.080426,36.400763],[-90.064514,36.382085],[-90.066297,36.3593],[-90.077695,36.348478],[-90.075572,36.33404],[-90.081961,36.322097],[-90.069266,36.313152],[-90.06398,36.303038],[-90.0778,36.288349],[-90.075934,36.281485],[-90.083731,36.272332],[-90.114922,36.265595],[-90.118219,36.253491],[-90.124476,36.244198],[-90.129716,36.243235],[-90.126366,36.229367],[-90.14224,36.227522],[-90.15614,36.213706],[-90.179695,36.208262],[-90.199905,36.196848],[-90.204449,36.18694],[-90.21128,36.183392],[-90.220425,36.184764],[-90.23537,36.159153],[-90.231386,36.147348],[-90.235585,36.139474],[-90.266256,36.120559],[-90.293109,36.114368],[-90.29991,36.098236],[-90.319168,36.089976],[-90.320746,36.071326],[-90.333261,36.067504],[-90.337146,36.047754],[-90.347908,36.041939],[-90.351732,36.025347],[-90.37789,35.995683],[-89.733095,36.000608],[-89.719168,35.985976],[-89.719679,35.970939],[-89.714565,35.963034],[-89.652279,35.921462],[-89.644838,35.904351],[-89.64727,35.89492],[-89.665672,35.883301],[-89.677012,35.88572],[-89.688141,35.896946],[-89.714934,35.906247],[-89.741241,35.906749],[-89.768743,35.886663],[-89.773564,35.871697],[-89.769413,35.861558],[-89.704351,35.835726],[-89.701045,35.828227],[-89.706085,35.81826],[-89.734044,35.806174],[-89.765442,35.811214],[-89.781793,35.805084],[-89.799331,35.788503],[-89.799249,35.775439],[-89.821216,35.756716],[-89.846343,35.755732],[-89.877256,35.741369],[-89.909996,35.759396],[-89.956254,35.733386],[-89.955753,35.690621],[-89.931036,35.660044],[-89.898916,35.650904],[-89.886979,35.653637],[-89.878534,35.66482],[-89.864782,35.670385],[-89.851176,35.657432],[-89.856619,35.634444],[-89.894346,35.615535],[-89.910687,35.617536],[-89.945405,35.601611],[-89.956749,35.590511],[-89.95669,35.581426],[-89.941393,35.556555],[-89.910789,35.547515],[-89.910885,35.541072],[-89.903882,35.534175],[-89.911931,35.51741],[-89.919331,35.51387],[-89.951248,35.521866],[-89.956347,35.525594],[-89.958498,35.541703],[-89.989363,35.560043],[-90.02862,35.555249],[-90.039744,35.548041],[-90.050277,35.515275],[-90.043517,35.492298],[-90.018842,35.464816],[-90.031584,35.427662],[-90.04057,35.422925],[-90.056644,35.403786],[-90.041563,35.39662],[-90.044856,35.392964],[-90.054451,35.38965],[-90.069283,35.408306],[-90.062018,35.41518],[-90.070549,35.423291],[-90.074082,35.433983],[-90.067138,35.464833],[-90.085009,35.478835],[-90.107723,35.476935],[-90.114412,35.472467],[-90.129448,35.441931],[-90.169002,35.421853],[-90.179265,35.385194],[-90.166246,35.374745],[-90.13551,35.376668],[-90.146191,35.399468],[-90.143448,35.406671],[-90.130475,35.413745],[-90.112504,35.410153],[-90.09665,35.395257],[-90.074992,35.384152],[-90.087903,35.36327],[-90.110293,35.342786],[-90.103862,35.332405],[-90.109093,35.304987],[-90.139504,35.298828],[-90.149794,35.303288],[-90.158913,35.300637],[-90.168794,35.279088],[-90.152094,35.255989],[-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 \"}}]}","volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-15","publicationStatus":"PW","contributors":{"authors":[{"text":"DeGregorio, Brett Alexander 0000-0002-5273-049X","orcid":"https://orcid.org/0000-0002-5273-049X","contributorId":243214,"corporation":false,"usgs":true,"family":"DeGregorio","given":"Brett","email":"","middleInitial":"Alexander","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Veon, John T.","contributorId":341550,"corporation":false,"usgs":false,"family":"Veon","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":908596,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Massey, Andrhea","contributorId":341551,"corporation":false,"usgs":false,"family":"Massey","given":"Andrhea","email":"","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":908597,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231492,"text":"sim3487 - 2022 - Geologic maps of the Stephenson and Winchester quadrangles, Frederick and Clarke Counties, Virginia, and Inwood and White Hall quadrangles, Berkeley and Jefferson Counties, West Virginia","interactions":[],"lastModifiedDate":"2026-04-01T15:15:19.750245","indexId":"sim3487","displayToPublicDate":"2022-05-13T11:20:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3487","displayTitle":"Geologic Maps of the Stephenson and Winchester Quadrangles, Frederick and Clarke Counties, Virginia, and Inwood and White Hall Quadrangles, Berkeley and Jefferson Counties, West Virginia","title":"Geologic maps of the Stephenson and Winchester quadrangles, Frederick and Clarke Counties, Virginia, and Inwood and White Hall quadrangles, Berkeley and Jefferson Counties, West Virginia","docAbstract":"<p>The study area consists of four contiguous 7.5-minute quadrangles and is located in Frederick and Clarke Counties, Virginia, and Berkeley and Jefferson Counties, West Virginia. The individual quadrangles are Stephenson, Winchester, Inwood, and White Hall. The study area lies within the Great Valley subprovince of the Valley and Ridge physiographic province where about 23,000 feet (ft) (7,000 meters [m]) of Middle Cambrian to Upper Devonian sedimentary rocks are exposed and are overlain by Holocene and older surficial deposits. The area of the four maps is divided into three geologic regions based on the following primary lithologies: (1) Cambrian and Ordovician carbonate rocks of the Great Valley southeast of the North Mountain fault zone and east and west of the core of the Massanutten synclinorium; (2) shale, graywacke, and calcareous shale of the Ordovician Martinsburg Formation of the Great Valley and Massanutten synclinorium; and (3) Ordovician through Devonian clastic rocks and minor limestone and dolostone northwest of and within the North Mountain fault zone. Rocks of all three regions were folded and faulted during the late Paleozoic Alleghanian orogeny (roughly 320 to 250 million years before present). The terrain of this portion of the Great Valley generally is gently to moderately rolling with low local relief with elevations in the study area ranging from about 425 ft (130 m) where Opequon Creek flows out of the eastern edge of the Inwood quadrangle to about 950 ft (290 m) adjacent to Round Hill in the western part of the Winchester quadrangle. Sinkholes and other karst features are common in the carbonate rocks of the Great Valley. The area west of the North Mountain fault zone is underlain by middle Paleozoic strata and consists of a series of ridges and valleys with higher local relief, with elevations ranging from about 785 ft (240 m) in the vicinity of Green Spring in the central part of the White Hall quadrangle to about 1,435 ft (437 m) at the summit of North Mountain in the northeastern part of the White Hall quadrangle.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3487","usgsCitation":"Weary, D.J., Doctor, D.H., and Orndorff, R.C., 2022, Geologic maps of the Stephenson and Winchester quadrangles, Frederick and Clarke Counties, Virginia, and Inwood and White Hall quadrangles, Berkeley and Jefferson Counties, West Virginia: U.S. Geological Survey Scientific Investigations Map 3487, 4 sheets, scale 1:24,000, 33-p. pamphlet, https://doi.org/10.3133/sim3487.","productDescription":"Pamphlet: viii, 33 p.; 4 Sheets: 28.00 x 42.00 inches or smaller; Base Map; Metadata; Database; Read Me","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-009285","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":501931,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113056.htm","linkFileType":{"id":5,"text":"html"}},{"id":400509,"rank":8,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3487/sim3487_openaccess.zip","text":"Open Access","size":"10.5 MB","linkFileType":{"id":6,"text":"zip"}},{"id":400508,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3487/sim3487_basemaps.zip","text":"Base Maps","size":"540 MB","linkFileType":{"id":6,"text":"zip"}},{"id":400507,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3487/sim3487_mapsheets.zip","text":"Map Sheets 1–4","size":"604 MB","linkFileType":{"id":6,"text":"zip"}},{"id":400502,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3487/coverthb3.jpg"},{"id":400505,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3487/sim3487_metadata.zip","text":"Metadata","size":"108 KB","linkFileType":{"id":6,"text":"zip"}},{"id":400506,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3487/sim3487_readme.txt","text":"Read Me","size":"8.50 KB","linkFileType":{"id":2,"text":"txt"}},{"id":400504,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3487/sim3487_database.zip","text":"Database","size":"36.2 MB","linkFileType":{"id":6,"text":"zip"}},{"id":400503,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3487/sim3487_pamphlet.pdf","text":"Pamphlet","size":"9.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3487"}],"country":"United States","state":"Virginia, West Virginia","county":"Berkeley County, Clarke County, Frederick County,  Jefferson County","otherGeospatial":"Inwood, Stephenson, White Hall and Winchester quadrangles","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -78.25,\n              39.375\n            ],\n            [\n              -78,\n              39.375\n            ],\n            [\n              -78,\n              39.125\n            ],\n            [\n              -78.25,\n              39.125\n            ],\n            [\n              -78.25,\n              39.375\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"https://www.usgs.gov/centers/florence-bascom-geoscience-center\" data-mce-href=\"https://www.usgs.gov/centers/florence-bascom-geoscience-center\">Florence Bascom Geoscience Center</a><br>U.S. Geological Survey<br>926A National Center<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Introduction</li><li>Description of Map Units and Stratigraphic Notes</li><li>Conodont Biostratigraphy</li><li>Surficial Deposits</li><li>Structural Geology</li><li>Audio-Magnetotelluric Survey and Section</li><li>Karst</li><li>Economic Geology and Mineral Resources</li><li>Description of Map Units</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2022-05-13","noUsgsAuthors":false,"publicationDate":"2022-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Weary, David J. 0000-0002-6115-6397 dweary@usgs.gov","orcid":"https://orcid.org/0000-0002-6115-6397","contributorId":545,"corporation":false,"usgs":true,"family":"Weary","given":"David","email":"dweary@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":842776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":842777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":842778,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231301,"text":"sir20225042 - 2022 - Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019","interactions":[],"lastModifiedDate":"2026-04-09T17:33:48.530349","indexId":"sir20225042","displayToPublicDate":"2022-05-09T09:35:46","publicationYear":"2022","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":"2022-5042","displayTitle":"Age and Water-Quality Characteristics of Groundwater Discharge to the South Loup River, Nebraska, 2019","title":"Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019","docAbstract":"<p>Streams in the Loup River Basin are sensitive to groundwater withdrawals because of the close hydrologic connection between groundwater and surface water. The U.S. Geological Survey, in cooperation with the Upper Loup and Lower Loup Natural Resources Districts, and the Nebraska Environmental Trust, studied the age and water-quality characteristics of groundwater near the South Loup River to assess the possible effects of a multiyear drought on streamflow.</p><p>Groundwater sampled in wells screened in Quaternary-age deposits displayed a wide range of mean ages (27 to 2,100 years), fraction modern, and susceptibility index values. Groundwater with higher concentrations of chloride and higher specific conductance was indicative of younger groundwater with a narrower age distribution and is more sensitive to climatic disturbances such as short-term drought conditions, based on the calculated susceptibility index. Groundwater samples from wells and springs in Pliocene-age deposits were categorized into two groups with different geochemical and age characteristics. One sample group of springs and wells, called the Western Pliocene, had higher concentrations of chloride and nitrate with young mean ages (18 to 77 years) and narrow age distributions. Groundwater in the Western Pliocene sample group is susceptible to short-term drought. In contrast, the other sample group from Pliocene-age deposits to the east (called Pliocene) had lower concentrations of nitrate, chloride, and mean groundwater ages ranging from 1,900 to 2,900 years old and is less likely to be affected by short-term drought conditions. Groundwater sampled from three wells screened in the Ogallala Formation was shown to have the oldest mean ages ranging from 8,700 to 23,000 years and the lowest calculated susceptibility index values observed in this study. Strong upward hydraulic gradients measured in wells indicated that groundwater from the Ogallala Formation is likely contributing to streamflow of the South Loup River.</p><p>Continuously measured gage height and specific conductance data indicated groundwater discharge from Quaternary-age deposits was highly responsive to precipitation events. In contrast, groundwater discharge from Pliocene-age deposits (Pliocene sample group) was far less responsive, indicating groundwater discharge from Pliocene-age deposits is likely more resilient to short-term drought conditions.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225042","collaboration":"Prepared in cooperation with the Upper Loup and Lower Loup Natural Resources Districts and the Nebraska Environmental Trust","usgsCitation":"Hobza, C.M., and Solder, J.E., 2022, Age and water-quality characteristics of groundwater discharge to the South Loup River, Nebraska, 2019: U.S. Geological Survey Scientific Investigations Report 2022–5042, 57 p., https://doi.org/10.3133/sir20225042.","productDescription":"Report: ix, 57 p.; Data Release","numberOfPages":"72","onlineOnly":"Y","ipdsId":"IP-129114","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":400241,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5042"},{"id":502397,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112991.htm","linkFileType":{"id":5,"text":"html"}},{"id":400244,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9L6B4XE","text":"USGS data release","linkHelpText":"Lumped parameter models of groundwater age, South Loup River, Nebraska"},{"id":400243,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5042/images"},{"id":400242,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5042/sir20225042.XML"},{"id":400333,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.er.usgs.gov/publication/sir20225042/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5042/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Loup River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -100.8599853515625,\n              41.075210270566636\n            ],\n            [\n              -98.5089111328125,\n              41.075210270566636\n            ],\n            [\n              -98.5089111328125,\n              42.07376224008719\n            ],\n            [\n              -100.8599853515625,\n              42.07376224008719\n            ],\n            [\n              -100.8599853515625,\n              41.075210270566636\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/ne-water\" data-mce-href=\"https://www.usgs.gov/centers/ne-water\">Nebraska Water Science Center</a><br>U.S. Geological Survey<br>5231 South 19th Street<br>Lincoln, NE 68512</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Methods</li><li>Water Quality, Groundwater Age, and Streamflow in the South Loup River Basin</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-09","noUsgsAuthors":false,"publicationDate":"2022-05-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842272,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solder, John E. 0000-0002-0660-3326 jsolder@usgs.gov","orcid":"https://orcid.org/0000-0002-0660-3326","contributorId":171916,"corporation":false,"usgs":true,"family":"Solder","given":"John","email":"jsolder@usgs.gov","middleInitial":"E.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842273,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70231478,"text":"70231478 - 2022 - Exposure to crop production alters cecal prokaryotic microbiota, inflates virulome and resistome in wild prairie grouse","interactions":[],"lastModifiedDate":"2022-05-11T11:47:46.072712","indexId":"70231478","displayToPublicDate":"2022-05-08T06:44:58","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Exposure to crop production alters cecal prokaryotic microbiota, inflates virulome and resistome in wild prairie grouse","docAbstract":"<div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Chemically intensive crop production depletes wildlife food resources, hinders animal development, health, survival, and reproduction, and it suppresses wildlife immune systems, facilitating emergence of infectious diseases with excessive mortality rates. Gut microbiota is crucial for wildlife's response to environmental stressors. Its composition and functionality are sensitive to diet changes and environmental pollution associated with modern crop production. In this study we use shotgun metagenomics (median 8,326,092 sequences/sample) to demonstrate that exposure to modern crop production detrimentally affects cecal microbiota of sharp-tailed grouse (<i>Tympanuchus phasianellus</i>: 9 exposed, 18 unexposed and greater prairie chickens (<i>T. cupido</i>; 11, 11). Exposure to crop production had greater effect on microbiota richness (<i>t</i>&nbsp;=&nbsp;6.675,<span>&nbsp;</span><i>P</i>&nbsp;&lt;&nbsp;0.001) and composition (PERMANOVA<span>&nbsp;</span><i>r</i><sup><i>2</i></sup>&nbsp;=&nbsp;0.212,<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.001) than did the host species (<i>t</i>&nbsp;=&nbsp;4.762,<span>&nbsp;</span><i>P</i>&nbsp;&lt;&nbsp;0.001;<span>&nbsp;</span><i>r</i><sup><i>2</i></sup>&nbsp;=&nbsp;0.070,<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.001) or their interaction (<i>t</i>&nbsp;=&nbsp;3.449;<span>&nbsp;</span><i>r</i><sup><i>2</i></sup>&nbsp;=&nbsp;0.072, both<span>&nbsp;</span><i>P</i>&nbsp;=&nbsp;0.001), whereas sex and age had no effect. Although microbiota richness was greater in exposed (<i>T. cupido</i><span>&nbsp;</span>chao1&nbsp;=&nbsp;152.8&nbsp;±&nbsp;20.5;<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>115.3&nbsp;±&nbsp;17.1) than in unexposed (102.9&nbsp;±&nbsp;15.1 and 101.1&nbsp;±&nbsp;17.2, respectively) birds, some beneficial bacteria dropped out of exposed birds' microbiota or declined and were replaced by potential pathogens. Exposed birds also had higher richness and load of virulome (mean&nbsp;±&nbsp;standard deviation;<span>&nbsp;</span><i>T. cupido</i><span>&nbsp;</span>24.8&nbsp;±&nbsp;10.0 and 10.1&nbsp;±&nbsp;5.5, respectively;<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>13.4&nbsp;±&nbsp;6.8/4.9&nbsp;±&nbsp;2.8) and resistome (<i>T. cupido</i><span>&nbsp;</span>46.8&nbsp;±&nbsp;11.7/28.9&nbsp;±&nbsp;10.2,<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>38.3&nbsp;±&nbsp;16.7/18.9&nbsp;±&nbsp;14.2) than unexposed birds (<i>T. cupido</i><span>&nbsp;</span>virulome: 14.2&nbsp;±&nbsp;13.5, 4.5&nbsp;±&nbsp;4.2;<span>&nbsp;</span><i>T. cupido</i><span>&nbsp;</span>resistome: 31.6&nbsp;±&nbsp;20.2 and 13.1&nbsp;±&nbsp;12.0;<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>virulome: 5.2&nbsp;±&nbsp;4.7 and 1.4&nbsp;±&nbsp;1.5;<span>&nbsp;</span><i>T. phasianellus</i><span>&nbsp;</span>resistome: 13.7&nbsp;±&nbsp;16.1 and 4.0&nbsp;±&nbsp;6.4).</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2022.119418","usgsCitation":"Drovetski, S.V., Schmidt, B.K., Lai, J.E., Gross, M.S., Hladik, M.L., Matterson, K.O., and Karouna-Renier, N., 2022, Exposure to crop production alters cecal prokaryotic microbiota, inflates virulome and resistome in wild prairie grouse: Environmental Pollution, v. 306, 119418, 10 p., https://doi.org/10.1016/j.envpol.2022.119418.","productDescription":"119418, 10 p.","ipdsId":"IP-136055","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":447871,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2022.119418","text":"Publisher Index Page"},{"id":400496,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.82080078125,\n              43.02071359427862\n            ],\n            [\n              -103.71093749999999,\n              41.062786068733026\n            ],\n            [\n              -102.041015625,\n              40.9964840143779\n            ],\n            [\n              -102.041015625,\n              40.01078714046552\n            ],\n            [\n              -98.67919921875,\n              40.01078714046552\n            ],\n            [\n              -98.85498046875,\n              43.03677585761058\n            ],\n            [\n              -103.82080078125,\n              43.02071359427862\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"306","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Drovetski, Sergei V. 0000-0002-1832-5597","orcid":"https://orcid.org/0000-0002-1832-5597","contributorId":229520,"corporation":false,"usgs":true,"family":"Drovetski","given":"Sergei","middleInitial":"V.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Brian K. 0000-0003-3796-3110","orcid":"https://orcid.org/0000-0003-3796-3110","contributorId":291624,"corporation":false,"usgs":false,"family":"Schmidt","given":"Brian","email":"","middleInitial":"K.","affiliations":[{"id":48006,"text":"National Museum of Natural History, Smithsonian Institution","active":true,"usgs":false}],"preferred":false,"id":842742,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lai, Jonas Ethan 0000-0001-5000-338X","orcid":"https://orcid.org/0000-0001-5000-338X","contributorId":291625,"corporation":false,"usgs":true,"family":"Lai","given":"Jonas","email":"","middleInitial":"Ethan","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":842743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gross, Michael S. 0000-0002-2433-166X","orcid":"https://orcid.org/0000-0002-2433-166X","contributorId":213604,"corporation":false,"usgs":true,"family":"Gross","given":"Michael","email":"","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842744,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":205314,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matterson, Kenan Oguz 0000-0003-2989-3685","orcid":"https://orcid.org/0000-0003-2989-3685","contributorId":291628,"corporation":false,"usgs":true,"family":"Matterson","given":"Kenan","email":"","middleInitial":"Oguz","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":842746,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":842747,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70231309,"text":"70231309 - 2022 - Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2022-05-06T14:07:26.017969","indexId":"70231309","displayToPublicDate":"2022-05-06T09:01:23","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":605,"text":"AAPG Bulletin","printIssn":"0149-1423","active":true,"publicationSubtype":{"id":10}},"title":"Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico","docAbstract":"<p class=\"abstractnoin\">Massive volumes of gas are sequestered within gas hydrate in subsurface marine sediments in the Gulf of Mexico. Methane associated with gas hydrate is a potentially important economic resource and a significant reservoir of carbon within the global carbon cycle. Nevertheless, uncertainties remain about the genetic source (e.g., microbial, thermogenic) and possible migration history of natural gas incorporated into hydrate. Previous studies have primarily used the hydrocarbon molecular (CH<sub>4</sub>/C<sub>2</sub>H<sub>6</sub>+) and isotopic (δ<sup>13</sup>C-CH<sub>4</sub>, δ<sup>2</sup>H-CH<sub>4</sub>) compositions of natural gas to address these uncertainties. However, hydrocarbon tracers are altered by mixing, oxidation, secondary methanogenesis, or fluid migration, which presents challenges when deciphering the mechanisms responsible for methane formation and accumulation. To evaluate the genetic source of natural gases from Green Canyon Block 955 (GC 955), east of the Sigsbee escarpment, we collected and analyzed samples from the first pressurized hydrate-bearing sediment cores collected from a coarse-grained hydrate reservoir in the Gulf of Mexico. Gas samples were analyzed for hydrocarbon gas (C<sub>1</sub>–C<sub>5</sub>), major gas (e.g., N<sub>2</sub>, CO<sub>2</sub>), and noble gas (He-Xe) abundance and isotopic (e.g., δ<sup>13</sup>C-CH<sub>4</sub>, δ<sup>2</sup>H-CH<sub>4</sub>, δ<sup>13</sup>C-CO<sub>2</sub>, δ<sup>15</sup>N-N<sub>2</sub>,<span>&nbsp;</span><sup>3</sup>He/<sup>4</sup>He,<span>&nbsp;</span><sup>4</sup>He/<sup>20</sup>Ne) compositions. We determined that natural gas in hydrates from this location are predominantly of primary microbial origin (conservatively at least 76%) and are formed by the hydrogenotrophic (CO<sub>2</sub><span>&nbsp;</span>reduction) methanogenesis pathway. We also note increased thermogenic proportions (∼6%) in a hydrate-bearing layer below the main hydrate-bearing interval (separated by a 5-m water-bearing layer). Our results suggest that microbial methane may be abundant below the base of gas hydrate stability at GC 955.</p>","language":"English","publisher":"American Association of Petroleum Geologists","doi":"10.1306/05272120087","usgsCitation":"Moore, M.T., Phillips, S.C., Cook, A., and Darrah, T.H., 2022, Integrated geochemical approach to determine the source of methane in gas hydrate from Green Canyon Block 955 in the Gulf of Mexico: AAPG Bulletin, v. 106, no. 5, p. 949-980, https://doi.org/10.1306/05272120087.","productDescription":"32 p.","startPage":"949","endPage":"980","ipdsId":"IP-125029","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":400279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Green Canyon Block 955, Green Knoll, Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -91.417236328125,\n              26.82407078047018\n            ],\n            [\n              -89.527587890625,\n              26.82407078047018\n            ],\n            [\n              -89.527587890625,\n              28.497660832963472\n            ],\n            [\n              -91.417236328125,\n              28.497660832963472\n            ],\n            [\n              -91.417236328125,\n              26.82407078047018\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"106","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, Myles T. 0000-0002-4405-8349","orcid":"https://orcid.org/0000-0002-4405-8349","contributorId":291397,"corporation":false,"usgs":true,"family":"Moore","given":"Myles","email":"","middleInitial":"T.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":842286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Stephen C. 0000-0003-0858-4701","orcid":"https://orcid.org/0000-0003-0858-4701","contributorId":268177,"corporation":false,"usgs":true,"family":"Phillips","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":842287,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cook, Ann","contributorId":242644,"corporation":false,"usgs":false,"family":"Cook","given":"Ann","affiliations":[{"id":18155,"text":"The Ohio State University","active":true,"usgs":false}],"preferred":false,"id":842288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Darrah, Thomas H.","contributorId":145769,"corporation":false,"usgs":false,"family":"Darrah","given":"Thomas","email":"","middleInitial":"H.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":842289,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70231318,"text":"70231318 - 2022 - Hydroclimate response of spring ecosystems to a two-stage Younger Dryas event in western North America","interactions":[],"lastModifiedDate":"2022-05-06T14:29:19.84111","indexId":"70231318","displayToPublicDate":"2022-05-05T09:26:24","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Hydroclimate response of spring ecosystems to a two-stage Younger Dryas event in western North America","docAbstract":"<p><span>The Younger Dryas (YD) climate event is the preeminent example of abrupt climate change in the recent geologic past. Climate conditions during the YD were spatially complex, and high-resolution sediment cores in the North Atlantic, western Europe, and East Asia have revealed it unfolded in two distinct stages, including an initial stable climatic period between ~ 12.9 and 12.2&nbsp;ka associated with a weakened Atlantic Meridional Overturning Circulation (AMOC) and a second phase characterized by variable conditions until 11.7&nbsp;ka as the AMOC recovered. Decades of investigations into the climate of western North America during the YD have failed to identify this stepped phenomenon. Here we present hydroclimate data from paleospring deposits in Death Valley National Park (California, USA) that demonstrate unequivocal evidence of two-stage partitioning within the YD event. High groundwater levels supported persistent and long-lived spring ecosystems between ~ 13.0 and 12.2&nbsp;ka, which were immediately replaced by alternating wet and dry environments until ~ 11.8&nbsp;ka. These results establish the mid-YD climate transition extended into western North America at approximately the same time it was recorded by hydrologic systems elsewhere in the Northern Hemisphere and show that even short-lived changes in the AMOC can have profound consequences for ecosystems worldwide.</span></p>","language":"English","publisher":"Nature Publications","doi":"10.1038/s41598-022-11377-4","usgsCitation":"Pigati, J.S., and Springer, K.B., 2022, Hydroclimate response of spring ecosystems to a two-stage Younger Dryas event in western North America: Scientific Reports, v. 12, 7373, 7 p., https://doi.org/10.1038/s41598-022-11377-4.","productDescription":"7373, 7 p.","ipdsId":"IP-122733","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":447910,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-022-11377-4","text":"Publisher Index Page"},{"id":435857,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U5XSRY","text":"USGS data release","linkHelpText":"Data release for Hydroclimate response of spring ecosystems to a two-stage Younger Dryas event in western North America"},{"id":400284,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.070068359375,\n              36.217687122250574\n            ],\n            [\n              -116.66931152343749,\n              36.217687122250574\n            ],\n            [\n              -116.66931152343749,\n              37.4356124041315\n            ],\n            [\n              -118.070068359375,\n              37.4356124041315\n            ],\n            [\n              -118.070068359375,\n              36.217687122250574\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"12","noUsgsAuthors":false,"publicationDate":"2022-05-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Pigati, Jeffrey S. 0000-0001-5843-6219 jpigati@usgs.gov","orcid":"https://orcid.org/0000-0001-5843-6219","contributorId":201167,"corporation":false,"usgs":true,"family":"Pigati","given":"Jeffrey","email":"jpigati@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":842301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Springer, Kathleen B. 0000-0002-2404-0264 kspringer@usgs.gov","orcid":"https://orcid.org/0000-0002-2404-0264","contributorId":149826,"corporation":false,"usgs":true,"family":"Springer","given":"Kathleen","email":"kspringer@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":842302,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70231237,"text":"fs20223025 - 2022 - Pennsylvania and Landsat","interactions":[],"lastModifiedDate":"2022-09-27T12:13:22.17303","indexId":"fs20223025","displayToPublicDate":"2022-05-04T08:45:52","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3025","displayTitle":"Pennsylvania and Landsat","title":"Pennsylvania and Landsat","docAbstract":"<p>The Commonwealth of Pennsylvania straddles an array of landscapes. From east to west, its 46,055 square miles connect the sea-level lowlands of the Atlantic seaboard with the rolling hills of the Midwest. It also acts as a bridge between regions from north to south, with the Appalachian Mountains swooping through its center from its northern border with New York to its southern borders with Maryland and West Virginia.</p><p>The Declaration of Independence and U.S. Constitution were signed in the Commonwealth’s largest city, Philadelphia, and it was the second of the original 13 colonies to ratify the Constitution. The pivotal Civil War battle of Gettysburg took place in the southern part of Pennsylvania. Western Pennsylvania was an early hub for the coal, oil, and steel industries that fueled the Nation’s growth in the 20th century and still factor into Pennsylvania’s economy. The varied natural features of Pennsylvania have been an important proving ground for the value of satellite imagery from the USGS Landsat Program. Scientists began to lean on Landsat observations early in the program’s history to map the effect of invasive moths on Commonwealth forests. That activity continues to this day. Space-based imagery has also contributed to the study and management of land change from energy development, urban growth, and shifting land use patterns.</p><p>The Landsat Program’s unparalleled 50-year archive of repeat Earth observations remains a critical public resource for Pennsylvania as climate change and land use patterns present new challenges to land managers and urban planners in the Keystone State.</p><p>Here are just a few examples of how Landsat has benefited Pennsylvania.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223025","usgsCitation":"U.S. Geological Survey, 2022, Pennsylvania and Landsat: U.S. Geological Survey Fact Sheet 2022–3025, 2 p., https://doi.org/10.3133/fs20223025.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-140045","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) 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 \"}}]}","contact":"<p>Program Coordinator, <a href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-land-imaging-program\">National Land Imaging Program</a> <br>U.S. Geological Survey <br>12201 Sunrise Valley Drive <br>Reston, VA 20192</p><p><a href=\"https://pubs.er.usgs.gov/contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Watching Over the Forests</li><li>Mapping the Past, Sketching the Future</li><li>Tracking Change from the Energy Industry</li><li>Landsat—Critical Information Infrastructure for the Nation</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2022-05-04","noUsgsAuthors":false,"publicationDate":"2022-05-04","publicationStatus":"PW","contributors":{"authors":[{"text":"U.S. Geological Survey","contributorId":147999,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey","id":842114,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
]}