{"pageNumber":"101","pageRowStart":"2500","pageSize":"25","recordCount":46638,"records":[{"id":70247917,"text":"70247917 - 2023 - Functional gene composition and metabolic potential of deep-sea coral-associated microbial communities","interactions":[],"lastModifiedDate":"2023-10-11T15:49:50.8594","indexId":"70247917","displayToPublicDate":"2023-08-09T06:39:45","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1338,"text":"Coral Reefs","active":true,"publicationSubtype":{"id":10}},"title":"Functional gene composition and metabolic potential of deep-sea coral-associated microbial communities","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Over the past decade, an abundance of 16S rRNA gene surveys have provided microbiologists with data regarding the prokaryotes present in a coral-associated microbial community. Functional gene studies that provide information regarding what those microbes might do are fewer, particularly for non-tropical corals. Using the GeoChip 5.0S microarray, we present a functional gene study of microbiomes from five species of cold-water corals collected from depths of 296–1567&nbsp;m. These species included two octocorals,<span>&nbsp;</span><i>Acanthogorgia aspera</i><span>&nbsp;</span>and<span>&nbsp;</span><i>Acanthogorgia spissa</i>, and three stony corals:<span>&nbsp;</span><i>Desmophyllum dianthus</i>,<span>&nbsp;</span><i>Desmophyllum pertusum</i><span>&nbsp;</span>(formerly<span>&nbsp;</span><i>Lophelia pertusa</i>), and<span>&nbsp;</span><i>Enallopsammia profunda</i>. A total of 24,281 gene sequences (representing different microbial taxa) encoding for 383 functional gene families and representing 9 metabolic gene categories were identified. Gene categories included metabolism of carbon, nitrogen, phosphorus, and sulfur, as well as virulence, organic remediation, metal homeostasis, secondary metabolism and phylogeny. We found that microbiomes from<span>&nbsp;</span><i>Acanthogorgia</i><span>&nbsp;</span>spp. were the most functionally distinct but also least diverse compared against those from stony corals.<span>&nbsp;</span><i>Desmophyllum</i><span>&nbsp;</span>spp. microbiomes were more similar to each other than to<span>&nbsp;</span><i>E. profunda</i>. Of 383 total gene families detected in this study, less than 20% were significantly different among these deep-water coral species. Similarly, out of 59 metabolic sub-categories for which we were able to make a direct comparison to microbiomes of tropical corals, only 7 were notably different: anaerobic ammonium oxidation (anammox), chitin degradation, and dimethylsulfoniopropionate (DMSP) degradation, all of which had higher representations in deep-water corals; and chromium homeostasis/resistance, copper homeostasis/resistance, antibiotic resistance, and methanogenesis, all of which had higher representation in tropical corals. This implies a broad-scale convergence of the microbial functional genes present within the coral holobiont, independent of coral species, depth, symbiont status, and morphology.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s00338-023-02409-0","usgsCitation":"Pratte, Z.A., Stewart, F.J., and Kellogg, C.A., 2023, Functional gene composition and metabolic potential of deep-sea coral-associated microbial communities: Coral Reefs, v. 42, p. 1011-1023, https://doi.org/10.1007/s00338-023-02409-0.","productDescription":"13 p.","startPage":"1011","endPage":"1023","ipdsId":"IP-144192","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442481,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00338-023-02409-0","text":"Publisher Index Page"},{"id":435229,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RPE8YX","text":"USGS data release","linkHelpText":"Functional Gene Microarray Data From Cold-water Corals (Acanthogorgia spp., Desmophyllum dianthus, Desmophyllum pertusum, and Enallopsammia profunda) from the Atlantic Ocean off the Southeast Coast of the United States-Raw Data"},{"id":420106,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","noUsgsAuthors":false,"publicationDate":"2023-08-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Pratte, Zoe A.","contributorId":214260,"corporation":false,"usgs":false,"family":"Pratte","given":"Zoe","email":"","middleInitial":"A.","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":881003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stewart, Frank J.","contributorId":328672,"corporation":false,"usgs":false,"family":"Stewart","given":"Frank","email":"","middleInitial":"J.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":881004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":881005,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70249411,"text":"70249411 - 2023 - The blue carbon reservoirs from Maine to Long Island, NY","interactions":[],"lastModifiedDate":"2023-10-10T15:33:18.522773","indexId":"70249411","displayToPublicDate":"2023-08-08T10:23:52","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"The blue carbon reservoirs from Maine to Long Island, NY","docAbstract":"<p>In response to the New England Governor and Eastern Canadian Premier 2017 Climate Change Action Plan recommendation to “manage blue carbon resources to preserve and enhance their existing carbon reservoirs,” the U.S. Environmental Protection Agency (EPA) convened a New England Blue Carbon Inventory Workgroup, comprised of a variety of federal, state, academic, and non-profit organizations to develop an inventory of blue carbon stocks from Maine to Long Island, New York. The Workgroup focused its inventory efforts on salt marshes and eelgrass meadows, leveraging existing habitat maps for geographic data. Existing data for soil organic carbon stocks were then used to calculate blue carbon stock estimates. For visual display purposes, sediment carbon heat maps were developed to highlight areas of greatest carbon accumulation. The habitat distribution and sediment carbon heat maps can be accessed on the Northeast Ocean Data Portal (www.northeastoceandata.org/eelgrass) which is a public source of expert-reviewed, interactive maps and data on the ocean ecosystem, economy, and culture of the northeastern United States and can be used to facilitate decision making by government agencies, tribal nations, businesses, non-governmental organizations (NGOs), academic institutions, and individuals. Based on available data and Workgroup calculations, the target geographic area has an estimated 218,222 acres of eelgrass meadows, salt marsh and saline Phragmites, which are estimated to provide a reservoir of 7,523,568 megagrams of blue carbon, or the equivalent to the annual carbon emissions from over 5,944,024 passenger vehicles. Due to data limitations, the carbon stock estimate represents a mere fraction of the actual quantity of accumulated carbon in these habitats. The findings from the Workgroup’s efforts and the resulting map products can help inform land and coastal management policies, fisheries management, and climate change mitigation practices. Further refinements and expansion of data are needed, including more detailed habitat maps, deeper soil core data for soil organic carbon content, and inclusion of more marine flora into calculations. </p>","language":"English","publisher":"Environmental Protection Agency","usgsCitation":"Colarusso, P., Libohova, Z., Shumchenia, E., Eagle, M.J., Christian, M., Vincent, R., and Johnson, B., 2023, The blue carbon reservoirs from Maine to Long Island, NY, 31 p.","productDescription":"31 p.","ipdsId":"IP-146585","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":421823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":421698,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.northeastoceandata.org/files/metadata/Themes/Habitat/EPABlueCarbonReport.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -67.61511760727777,\n              45.22754478031186\n            ],\n            [\n              -69.46772958832273,\n              44.45391256542621\n            ],\n            [\n              -70.41808310369574,\n              44.0249641018155\n            ],\n            [\n              -71.18235185260586,\n              43.43128866248264\n            ],\n            [\n              -71.38130070335747,\n              41.926291445574776\n            ],\n            [\n              -72.88727252479508,\n              41.59585766120409\n            ],\n            [\n              -74.23639888538038,\n              41.298612606793824\n            ],\n            [\n              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D.","contributorId":218700,"corporation":false,"usgs":false,"family":"Colarusso","given":"Philip D.","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":885521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Libohova, Zamir","contributorId":330648,"corporation":false,"usgs":false,"family":"Libohova","given":"Zamir","email":"","affiliations":[{"id":63834,"text":"United States Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":885522,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shumchenia, Emily","contributorId":330649,"corporation":false,"usgs":false,"family":"Shumchenia","given":"Emily","email":"","affiliations":[{"id":78947,"text":"Northeast Regional Ocean Council","active":true,"usgs":false}],"preferred":false,"id":885523,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eagle, Meagan J. 0000-0001-5072-2755 meagle@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":242890,"corporation":false,"usgs":true,"family":"Eagle","given":"Meagan","email":"meagle@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":885524,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christian, Megan","contributorId":330651,"corporation":false,"usgs":false,"family":"Christian","given":"Megan","email":"","affiliations":[{"id":63834,"text":"United States Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":885525,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vincent, Robert","contributorId":330652,"corporation":false,"usgs":false,"family":"Vincent","given":"Robert","email":"","affiliations":[{"id":12444,"text":"Massachusetts Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":885526,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnson, Beverly","contributorId":330653,"corporation":false,"usgs":false,"family":"Johnson","given":"Beverly","email":"","affiliations":[{"id":33413,"text":"Bates College","active":true,"usgs":false}],"preferred":false,"id":885527,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70247684,"text":"70247684 - 2023 - Fuel treatments in shrublands experiencing pinyon and juniper expansion result in trade-offs between desired vegetation and increased fire behavior","interactions":[],"lastModifiedDate":"2023-08-11T16:24:22.45893","indexId":"70247684","displayToPublicDate":"2023-08-07T09:32:15","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Fuel treatments in shrublands experiencing pinyon and juniper expansion result in trade-offs between desired vegetation and increased fire behavior","docAbstract":"<h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Background</h3><p>Native pinyon (<i>Pinus</i><span>&nbsp;</span>spp.) and juniper (<i>Juniperus</i><span>&nbsp;</span>spp.) trees are expanding into shrubland communities across the Western United States. These trees often outcompete with native sagebrush (<i>Artemisia</i><span>&nbsp;</span>spp.) associated species, resulting in increased canopy fuels and reduced surface fuels. Woodland expansion often results in longer fire return intervals with potential for high severity crown fire. Fuel treatments are commonly used to prevent continued tree infilling and growth and reduce fire risk, increase ecological resilience, improve forage quality and quantity, and/or improve wildlife habitat. Treatments may present a trade-off; they restore shrub and herbaceous cover and decrease risk of canopy fire but may increase surface fuel load and surface fire potential. We measured the accumulation of surface and canopy fuels over 10 years from ten sites across the Intermountain West in the Sagebrush Steppe Treatment Evaluation Project woodland network (<a href=\"http://www.sagestep.org/\" data-mce-href=\"http://www.sagestep.org/\">www.SageSTEP.org</a>), which received prescribed fire or mechanical (cut and drop) tree reduction treatments. We used the field data and the Fuel Characteristic Classification System (FCCS) in the Fuel and Fire Tools (FFT) application to estimate surface and canopy fire behavior in treated and control plots in tree expansion phases I, II, and III.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Results</h3><p>Increased herbaceous surface fuel following prescribed fire treatments increased the modeled rate of surface fire spread (ROS) 21-fold and nearly tripled flame length (FL) by year ten post-treatment across all expansion phases. In mechanical treatments, modeled ROS increased 15-fold, FL increased 3.8-fold, and reaction intensity roughly doubled in year ten post-treatment compared to pretreatment and untreated controls. Treatment effects were most pronounced at 97th percentile windspeeds, with modeled ROS up to 82&nbsp;m min<sup>−1</sup><span>&nbsp;</span>in mechanical and 106&nbsp;m min<sup>−1</sup><span>&nbsp;</span>in prescribed fire treatments by 10 years post-treatment compared to 5&nbsp;m min<sup>−1</sup><span>&nbsp;</span>in untreated controls. Crown fire transmissivity risk was eliminated by both fuel treatments.</p><h3 class=\"c-article__sub-heading\" data-test=\"abstract-sub-heading\">Conclusions</h3><p>While prescribed fire and mechanical treatments in shrublands experiencing tree expansion restored understory vegetation and prevented continued juniper and pinyon infilling and growth, these fuel treatments also increased modeled surface fire behavior. Thus, management tradeoffs occur between desired future vegetation and wildfire risk after fuel treatments.</p>","language":"English","publisher":"Springer","doi":"10.1186/s42408-023-00201-7","usgsCitation":"Williams, C.L., Ellsworth, L., Strand, E., Reeves, M.C., Shaff, S.E., Short, K., Chambers, J., Newingham, B., and Tortorelli, C., 2023, Fuel treatments in shrublands experiencing pinyon and juniper expansion result in trade-offs between desired vegetation and increased fire behavior: Fire Ecology, v. 19, 46, 21 p., https://doi.org/10.1186/s42408-023-00201-7.","productDescription":"46, 21 p.","ipdsId":"IP-154672","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":442492,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-023-00201-7","text":"Publisher Index Page"},{"id":419748,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada, Oregon, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -112.242321499979,\n              37.26614922694803\n            ],\n            [\n              -111.73150627380747,\n              40.33982762810214\n            ],\n            [\n              -117.02080093108165,\n              40.473878098349985\n            ],\n            [\n              -116.74789132368525,\n              38.56409342781134\n            ],\n            [\n              -112.242321499979,\n              37.26614922694803\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -121.35613130086793,\n              41.4092957538588\n            ],\n            [\n              -117.52494090332212,\n              43.41419744406673\n            ],\n            [\n              -120.12652755099501,\n              45.42305748463039\n            ],\n            [\n              -122.07668627870967,\n              43.86124338845653\n            ],\n            [\n              -121.35613130086793,\n              41.4092957538588\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"19","noUsgsAuthors":false,"publicationDate":"2023-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Williams, Claire L.","contributorId":328374,"corporation":false,"usgs":false,"family":"Williams","given":"Claire","email":"","middleInitial":"L.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":880021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellsworth, Lisa M.","contributorId":328375,"corporation":false,"usgs":false,"family":"Ellsworth","given":"Lisa M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":880022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strand, Eva","contributorId":328376,"corporation":false,"usgs":false,"family":"Strand","given":"Eva","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":880023,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reeves, Matt C.","contributorId":328377,"corporation":false,"usgs":false,"family":"Reeves","given":"Matt","email":"","middleInitial":"C.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":880024,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shaff, Scott E. 0000-0001-8978-9260","orcid":"https://orcid.org/0000-0001-8978-9260","contributorId":219813,"corporation":false,"usgs":true,"family":"Shaff","given":"Scott","middleInitial":"E.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":880025,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Short, Karen","contributorId":328378,"corporation":false,"usgs":false,"family":"Short","given":"Karen","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":880026,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chambers, Jeanne C.","contributorId":328379,"corporation":false,"usgs":false,"family":"Chambers","given":"Jeanne C.","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":880027,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Newingham, Beth","contributorId":328380,"corporation":false,"usgs":false,"family":"Newingham","given":"Beth","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":880028,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tortorelli, Claire","contributorId":328381,"corporation":false,"usgs":false,"family":"Tortorelli","given":"Claire","email":"","affiliations":[{"id":12711,"text":"UC Davis","active":true,"usgs":false}],"preferred":false,"id":880029,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70247508,"text":"70247508 - 2023 - A spatially explicit modeling framework to guide management of subsidized avian predator densities","interactions":[],"lastModifiedDate":"2023-08-10T11:43:08.209226","indexId":"70247508","displayToPublicDate":"2023-08-07T06:39:17","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"A spatially explicit modeling framework to guide management of subsidized avian predator densities","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Anthropogenic resource subsidization across western ecosystems has contributed to widespread increases in generalist avian predators, including common ravens (<i>Corvus corax</i>; hereafter, raven). Ravens are adept nest predators and can negatively impact species of conservation concern. Predation effects from ravens are especially concerning for greater sage-grouse (<i>Centrocercus urophasianus</i>; hereafter, sage-grouse), which have experienced prolonged population decline. Our objectives were to quantify spatiotemporal patterns in raven density, evaluate sage-grouse nest success concurrent with fluctuating raven densities, and demonstrate a spatially explicit decision support tool to guide management applications to appropriate conflict areas. We combined ~28,000 raven point count surveys with data from more than 900 sage-grouse nests between 2009 and 2019 within the Great Basin, USA. We modeled variation in raven density using a Bayesian hierarchical distance sampling approach with environmental covariates on detection and abundance. Concurrently, we modeled sage-grouse nest survival using a hierarchical frailty model as a function of raven density and other environmental covariates that influence the risk of nest failure. Raven density commonly exceeded 0.5 ravens km<sup>−2</sup><span>&nbsp;</span>and increased at low elevations with more anthropogenic development and/or agriculture. Reduced sage-grouse nest survival was strongly associated with elevated raven density (e.g., &gt;0.5 ravens km<sup>−2</sup>) and varied with topographic ruggedness, shrub cover, and burned areas. For conservation application, we developed a spatially explicit planning tool that predicts nest survival under current and reduced raven numbers within the Great Basin to help direct management actions to localized areas where sage-grouse nests are at highest risk of failure. Our modeling framework can be generalized to multiple species where spatially registered abundance and demographic data are available.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4618","usgsCitation":"O’Neil, S.T., Coates, P.S., Webster, S.C., Brussee, B.E., Dettenmaier, S.J., Tull, J.C., Jackson, P.J., Casazza, M.L., and Espinosa, S.P., 2023, A spatially explicit modeling framework to guide management of subsidized avian predator densities: Ecosphere, v. 14, no. 8, e4618, 20 p., https://doi.org/10.1002/ecs2.4618.","productDescription":"e4618, 20 p.","ipdsId":"IP-145230","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":442498,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4618","text":"Publisher Index Page"},{"id":435232,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96DW3EH","text":"USGS data release","linkHelpText":"Code for a hierarchical model of raven densities linked with sage-grouse nest survival to help guide management of subsidized avian predators, version 1.0"},{"id":435231,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BLVJTS","text":"USGS data release","linkHelpText":"Data to Support Hierarchical Models and Decision Support Maps to Guide Management of Subsidized Avian Predator Densities"},{"id":419691,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Great Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.2868540455589,\n              42.470077280121444\n            ],\n            [\n              -120.24292757983179,\n              38.118170774915555\n            ],\n            [\n              -117.21200144466887,\n              36.332112780767496\n            ],\n            [\n              -114.35678117241328,\n              36.93261209362862\n            ],\n            [\n              -114.35678117241328,\n              42.470077280121444\n            ],\n            [\n              -120.2868540455589,\n              42.470077280121444\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Neil, Shawn T. 0000-0002-0899-5220","orcid":"https://orcid.org/0000-0002-0899-5220","contributorId":206589,"corporation":false,"usgs":true,"family":"O’Neil","given":"Shawn","email":"","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":879908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":879909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webster, Sarah C. 0000-0003-4981-2010","orcid":"https://orcid.org/0000-0003-4981-2010","contributorId":302117,"corporation":false,"usgs":true,"family":"Webster","given":"Sarah","email":"","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":879910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":879911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dettenmaier, Seth J. 0000-0001-6325-8808","orcid":"https://orcid.org/0000-0001-6325-8808","contributorId":302087,"corporation":false,"usgs":true,"family":"Dettenmaier","given":"Seth","email":"","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":879912,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tull, John C. 0000-0002-0680-008X","orcid":"https://orcid.org/0000-0002-0680-008X","contributorId":201650,"corporation":false,"usgs":false,"family":"Tull","given":"John","email":"","middleInitial":"C.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":879913,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jackson, Pat J.","contributorId":206602,"corporation":false,"usgs":false,"family":"Jackson","given":"Pat","email":"","middleInitial":"J.","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":879914,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":879915,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Espinosa, Shawn P.","contributorId":195583,"corporation":false,"usgs":false,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":879916,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70247807,"text":"70247807 - 2023 - Spatial and temporal overlap between hatchery- and natural-origin steelhead and Chinook salmon during spawning in the Klickitat River, Washington, USA","interactions":[],"lastModifiedDate":"2024-01-24T17:30:18.876165","indexId":"70247807","displayToPublicDate":"2023-08-07T06:39:16","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal overlap between hatchery- and natural-origin steelhead and Chinook salmon during spawning in the Klickitat River, Washington, USA","docAbstract":"<div id=\"article__content\" class=\"col-sm-12 col-md-8 col-lg-8 article__content article-row-left\"><div class=\"article__body \"><div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>A goal of many segregated salmonid hatchery programs is to minimize potential interbreeding between hatchery- and natural-origin fish. To assess this on the Klickitat River, Washington, USA, we used radiotelemetry during 2009–2014 to evaluate spatiotemporal spawning overlap between hatchery-origin and natural-origin steelhead<span>&nbsp;</span><i>Oncorhynchus mykiss</i><span>&nbsp;</span>and spring Chinook Salmon<span>&nbsp;</span><i>O. tshawytscha.</i><span>&nbsp;</span>We estimated percentages of tagged fish that spawned naturally in the Klickitat River subbasin, emigrated from the Klickitat River, or died before spawning. For steelhead, 12% of hatchery-origin and 50% of natural-origin fish spawned naturally. For spring Chinook Salmon, 18% of hatchery-origin and 44% of natural-origin fish spawned naturally. Tag loss may result in underestimates in these percentages. Most hatchery-origin steelhead (90%) spawned downstream of rkm 32 and 75% spawned from November to mid-March, while the majority of natural-origin steelhead (64%) spawned upstream of rkm 32 and 75% spawned from mid-March to late May. Spawn timing of hatchery-origin Chinook Salmon (early August to mid-September) overlapped with that of natural-origin Chinook Salmon (late July to late September), and fish of both origins spawned in the same 30-km reach of the river. We estimated the percent of hatchery-origin spawners on the natural spawning grounds (pHOS) to be 12% for steelhead and 40% for spring Chinook Salmon across all study years. A kernel density analysis was used to estimate probability of spatiotemporal overlap between hatchery- and natural-origin spawners. For steelhead, we estimated this overlap to be 25% (95% CI 22.5–28%). For spring Chinook Salmon, tight spatial clustering of hatchery-origin fish resulted in a lower overlap estimate of 21% (13%-31%). We suggest adjusting pHOS estimates using these overlap estimates or similar spatiotemporal data on actual spawner proximity and possible interactions, and that these types of analyses be used in conjunction with gene flow analysis to accurately evaluate effects of individual hatchery programs.</p></div></div></div></div>","language":"English","publisher":"American Fisheries Society","doi":"10.1002/nafm.10945","usgsCitation":"Zendt, J.S., Allen, B., Kock, T.J., Perry, R., and Pope, A., 2023, Spatial and temporal overlap between hatchery- and natural-origin steelhead and Chinook salmon during spawning in the Klickitat River, Washington, USA: North American Journal of Fisheries Management, v. 43, no. 6, p. 1687-1701, https://doi.org/10.1002/nafm.10945.","productDescription":"15 p.","startPage":"1687","endPage":"1701","ipdsId":"IP-150095","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":442500,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10945","text":"Publisher Index Page"},{"id":419920,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Klickitat River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -120.61464912453181,\n              45.72771938418035\n            ],\n            [\n              -120.82413483062325,\n              46.49480247077369\n            ],\n            [\n              -121.44510336977899,\n              46.52093875212026\n            ],\n            [\n              -121.51897546658203,\n              45.721330175550776\n            ],\n            [\n              -121.32915952789224,\n              45.676278902772864\n            ],\n            [\n              -121.23425155854733,\n              45.65807648481219\n            ],\n            [\n              -121.18872659764212,\n              45.5967150188734\n            ],\n            [\n              -121.03749113429595,\n              45.642554957636634\n            ],\n            [\n              -120.61464912453181,\n              45.72771938418035\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"43","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-08-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Zendt, Joseph S.","contributorId":328537,"corporation":false,"usgs":false,"family":"Zendt","given":"Joseph","email":"","middleInitial":"S.","affiliations":[{"id":78390,"text":"Yakama Nation Fisheries Program, 1575 Horseshoe Bend Road, Klickitat, WA 98628","active":true,"usgs":false}],"preferred":false,"id":880531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Brady","contributorId":328538,"corporation":false,"usgs":false,"family":"Allen","given":"Brady","affiliations":[{"id":78392,"text":"Bonneville Power Administration, 905 NE 11th Avenue, Portland, OR 97232","active":true,"usgs":false}],"preferred":false,"id":880532,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kock, Tobias J. 0000-0001-8976-0230","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":214550,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":880533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell 0000-0003-4110-8619","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":220189,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":880534,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pope, Adam C. 0000-0002-7253-2247","orcid":"https://orcid.org/0000-0002-7253-2247","contributorId":223237,"corporation":false,"usgs":true,"family":"Pope","given":"Adam","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":880535,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70247785,"text":"70247785 - 2023 - Validity of the Landsat surface reflectance archive for aquatic science: Implications for cloud-based analysis","interactions":[],"lastModifiedDate":"2023-11-20T17:36:37.180823","indexId":"70247785","displayToPublicDate":"2023-08-06T10:59:24","publicationYear":"2023","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":"Validity of the Landsat surface reflectance archive for aquatic science: Implications for cloud-based analysis","docAbstract":"<p><span>Originally developed for terrestrial science and applications, the US Geological Survey Landsat surface reflectance (SR) archive spanning ~ 40 yr of observations has been increasingly utilized in large-scale water-quality studies. These products, however, have not been rigorously validated using in situ measured reflectance. This letter quantifies and demonstrates the quality of the SR products by harnessing a sizeable global dataset (</span><i>N</i><span> = 1100). We found that the Landsat 8/9 SR in the green and red bands marginally meet the targeted accuracy requirements (30%), whereas the uncertainties in the blue and coastal-aerosol bands ranged from 48% to 110%. We further observed &gt; +25% biases in the visible bands of Landsat 5/7 SR, which can introduce an apparent downward trend when applied in time-series analyses combined with Landsat 8/9. Users must exercise caution when using this archive for trend analyses, and progress in atmospheric correction is required to foster advanced applications of the Landsat archive for aquatic science.</span></p>","language":"English","publisher":"Association for the Sciences of Limnology and Oceanography","doi":"10.1002/lol2.10344","usgsCitation":"Maciel, D.A., Pahlevan, N., Barbosa, C.C., de Moraes de Novo, E.M., Paulino, R.S., Martins, V.S., Vermote, E., and Crawford, C., 2023, Validity of the Landsat surface reflectance archive for aquatic science: Implications for cloud-based analysis: Limnology and Oceanography Letters, v. 8, no. 6, p. 820-858, https://doi.org/10.1002/lol2.10344.","productDescription":"9 p.","startPage":"820","endPage":"858","ipdsId":"IP-149014","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":442503,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lol2.10344","text":"Publisher Index Page"},{"id":419891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"6","noUsgsAuthors":false,"publicationDate":"2023-08-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Maciel, Daniel Andrade","contributorId":328506,"corporation":false,"usgs":false,"family":"Maciel","given":"Daniel","email":"","middleInitial":"Andrade","affiliations":[{"id":78384,"text":"INPE","active":true,"usgs":false}],"preferred":false,"id":880451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pahlevan, Nima","contributorId":328507,"corporation":false,"usgs":false,"family":"Pahlevan","given":"Nima","affiliations":[{"id":78385,"text":"NASA GSFC/ SSAI","active":true,"usgs":false}],"preferred":false,"id":880452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barbosa, Claudio Clemente Faria","contributorId":328508,"corporation":false,"usgs":false,"family":"Barbosa","given":"Claudio","email":"","middleInitial":"Clemente Faria","affiliations":[{"id":78384,"text":"INPE","active":true,"usgs":false}],"preferred":false,"id":880453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de Moraes de Novo, Evlyn Marcia Leao","contributorId":328509,"corporation":false,"usgs":false,"family":"de Moraes de Novo","given":"Evlyn","email":"","middleInitial":"Marcia Leao","affiliations":[{"id":78384,"text":"INPE","active":true,"usgs":false}],"preferred":false,"id":880454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Paulino, Rejane Souza","contributorId":328510,"corporation":false,"usgs":false,"family":"Paulino","given":"Rejane","email":"","middleInitial":"Souza","affiliations":[{"id":78384,"text":"INPE","active":true,"usgs":false}],"preferred":false,"id":880455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Martins, Vitor Souza","contributorId":328511,"corporation":false,"usgs":false,"family":"Martins","given":"Vitor","email":"","middleInitial":"Souza","affiliations":[{"id":78386,"text":"Missippssii State University","active":true,"usgs":false}],"preferred":false,"id":880456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vermote, Eric","contributorId":328512,"corporation":false,"usgs":false,"family":"Vermote","given":"Eric","affiliations":[{"id":39055,"text":"NASA GSFC","active":true,"usgs":false}],"preferred":false,"id":880457,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Crawford, Christopher J. 0000-0002-7145-0709 cjcrawford@usgs.gov","orcid":"https://orcid.org/0000-0002-7145-0709","contributorId":213607,"corporation":false,"usgs":true,"family":"Crawford","given":"Christopher J.","email":"cjcrawford@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":880458,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70256432,"text":"70256432 - 2023 - Effects of sucker gigging on fish populations in Oklahoma scenic rivers","interactions":[],"lastModifiedDate":"2024-09-09T15:31:56.213633","indexId":"70256432","displayToPublicDate":"2023-08-04T10:26:42","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"FWS/CSS-151-2023","title":"Effects of sucker gigging on fish populations in Oklahoma scenic rivers","docAbstract":"<p><span>Suckers (Catostomidae) are ecologically important, and some support popular fisheries, despite not being considered ‘sport fish’ in most states. Gigging suckers is a popular and culturally significant pastime in the Ozark Highlands, but little is known about the effect of gigging harvest on population dynamics of suckers. Therefore, research is needed to determine safe levels of sucker harvest that ensure sustainability of sucker gigging and protect overall ecosystem function. The objectives of this study were to: 1) determine the spatial distribution of common sucker species during spawning season (when sucker gigging is most effective), 2) determine the population size, age&nbsp;</span><span class=\"glossify-tooltip-link glossify-tooltip-popup\" aria-label=\"Something temporarily or permanently constructed, built, or placed; and constructed of natural or manufactured parts including, but not limited to, a building, shed, cabin, porch, bridge, walkway, stair steps, sign, landing, platform, dock, rack, fence, telecommunication device, antennae, fish cleaning table, satellite dish/mount, or well head.\">structure<span>&nbsp;</span></span><span>, and total mortality rate for common sucker species, and 3) model the effects of different harvest rates on sucker populations to determine the harvest rate at which growth overfishing and recruitment overfishing begin. &nbsp;Suckers were sampled using electrofishing, modified fyke netting, gillnetting, hoop netting, and seining and marked with passive integrated transponder (PIT) tags to provide information about population size, demographics, and coarse-scale movement patterns. &nbsp;A subset of fish sampled using the above gears and additional fish collected during gigging tournaments in 2017-2019 and 2021-2022 (no tournament was held in 2020) were used for age analyses. Tournament data collected prior to the initiation of this project were obtained from the state agency. Data from gigging tournaments indicated Golden Redhorse Moxostoma erythrurum, Black Redhorse M. duquesnei, White Sucker Catostomus commersonii, and Spotted Sucker Minytrema melanops were vulnerable to gigging harvest. Selection by giggers for larger individuals was apparent for all species except Golden Redhorse in 2019. Spotted Suckers constituted most fish harvested, but the proportion of each species harvested still varied among years. A total of 943 fish were aged from samples obtained from 2017 to 2022 and results from subsequent analyses indicated a high degree of variation in growth rates within and among species. Over 4,700 suckers were tagged with PIT tags and over 400 recaptures of these tagged fish were made since autumn 2018. Preliminary analyses indicate survival was consistent across samples and species, and detection rates varied by sampling event (3-month periods). Our most likely top multistrata model suggested that a large portion of fish within the upper Spavinaw, lower Spavinaw, and reservoir sections remain in these locations year-round (means: 0.46 – 0.67). Despite this, transition probabilities are still high for movement from upper Spavinaw to lower Spavinaw (mean: 0.32) and from lower Spavinaw to upper Spavinaw (mean: 0.38). Likewise, transition probabilities were high for movement from lower Spavinaw to the reservoir (mean: 0.15) and from the reservoir to lower Spavinaw (mean: 0.32). Transition probabilities between upper Spavinaw and the reservoir were low in both directions (means &lt; 0.01). Population sizes, growth trajectories and length-weight relationships varied among species. Preliminary harvest models suggest species-specific regulation may be scientifically appropriate; however, it may be difficult for giggers to identify species while gigging. Based on our model results, there appears to be little risk of recruitment or growth overfishing for any species at current exploitation levels.</span></p>","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Zetner, D., Shoup, D., and Brewer, S., 2023, Effects of sucker gigging on fish populations in Oklahoma scenic rivers: Cooperator Science Series FWS/CSS-151-2023, ii, 60 p.","productDescription":"ii, 60 p.","ipdsId":"IP-153396","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":431783,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.fws.gov/media/effects-sucker-gigging-fish-populations-oklahoma-scenic-rivers"},{"id":433623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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E.","contributorId":242905,"corporation":false,"usgs":false,"family":"Shoup","given":"D. E.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":907354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":340552,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":907355,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70247418,"text":"sir20235093 - 2023 - Analysis of high-resolution single channel seismic data for use in sediment resource evaluation, eastern Texas and western Louisiana Continental Shelf, Gulf of Mexico","interactions":[],"lastModifiedDate":"2026-03-12T21:16:59.60233","indexId":"sir20235093","displayToPublicDate":"2023-08-04T08:46:47","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5093","displayTitle":"Analysis of High-Resolution Single Channel Seismic Data for Use in Sediment Resource Evaluation, Eastern Texas and Western Louisiana Continental Shelf, Gulf of Mexico","title":"Analysis of high-resolution single channel seismic data for use in sediment resource evaluation, eastern Texas and western Louisiana Continental Shelf, Gulf of Mexico","docAbstract":"<p>Shallow subsurface geologic data recorded as high-resolution seismic profiles are used to interpret the geology of coastal and marine systems. These data were originally recorded on paper rolls that are stored in geophysical archives. Data collection has since converted to entirely digital formats, yet the analog data are still useful for geologic interpretation. This report describes the process of recovering analog copies of seismic profiles from physical archives, electronically scanning, and converting them to industry-standard digital format. The recovered data are also reviewed and assessed for potential sediment resources. The data recovered in this study were collected from the Gulf of Mexico continental shelf offshore of East Texas and West Louisiana. The project is a collaborative study between the U.S. Geological Survey and the Bureau of Ocean Energy Management.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235093","issn":"2328-0328","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management","programNote":"Coastal and Marine Hazards and Resources Program","usgsCitation":"Flocks, J., Forde, A., and Bosse, S., 2023, Analysis of high-resolution single channel seismic data for use in sediment resource evaluation, eastern Texas and western Louisiana Continental Shelf, Gulf of Mexico: U.S. Geological Survey Scientific Investigations Report 2023–5093, 18 p., https://doi.org/10.3133/sir20235093.","productDescription":"Report: viii, 18 p.; Data Release","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-144157","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":419532,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/sir20235093/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5093 HTML"},{"id":419531,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5093/sir20235093.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5093 XML"},{"id":419530,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5093/sir20235093.pdf","size":"4.85 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5093 pdf"},{"id":419529,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5093/images"},{"id":419528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5093/coverthb.jpg"},{"id":419533,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EFUAN3","text":"USGS data release—Archive of digitized analog boomer seismic reflection data collected from the northern Gulf of Mexico—Intersea 1980"},{"id":501060,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115126.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana, Texas","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -91.86243995309941,\n              29.6\n            ],\n            [\n              -94.1,\n              29.6\n            ],\n            [\n              -94.1,\n              28.4\n            ],\n            [\n              -91.86243995309941,\n              28.4\n            ],\n            [\n              -91.86243995309941,\n              29.6\n            ]\n          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jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":879518,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Forde, Arnell S. 0000-0002-5581-2255 aforde@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-2255","contributorId":376,"corporation":false,"usgs":true,"family":"Forde","given":"Arnell","email":"aforde@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":879519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bosse, Stephen T. 0000-0001-6110-2973 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,{"id":70247436,"text":"70247436 - 2023 - DisasterNet: Causal Bayesian networks with normalizing flows for cascading hazards","interactions":[],"lastModifiedDate":"2023-08-08T13:37:18.248038","indexId":"70247436","displayToPublicDate":"2023-08-04T08:30:10","publicationYear":"2023","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"DisasterNet: Causal Bayesian networks with normalizing flows for cascading hazards","docAbstract":"<p><span>Sudden-onset hazards like earthquakes often induce cascading secondary hazards (e.g., landslides, liquefaction, debris flows, etc.) and subsequent impacts (e.g., building and infrastructure damage) that cause catastrophic human and economic losses. Rapid and accurate estimates of these hazards and impacts are critical for timely and effective post-disaster responses. Emerging remote sensing techniques provide pre- and post-event satellite images for rapid hazard estimation. However, hazards and damage often co-occur or colocate with underlying complex cascading geophysical processes, making it challenging to directly differentiate multiple hazards and impacts from satellite imagery using existing single-hazard models. We introduce DisasterNet, a novel family of causal Bayesian networks to model processes that a major hazard triggers cascading hazards and impacts and further jointly induces signal changes in remotely sensed observations. We integrate normalizing flows to effectively model the highly complex causal dependencies in this cascading process. A triplet loss is further designed to leverage prior geophysical knowledge to enhance the identifiability of our highly expressive Bayesian networks. Moreover, a novel stochastic variational inference with normalizing flows is derived to jointly approximate posteriors of multiple unobserved hazards and impacts from noisy remote sensing observations. Integrating with the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system, our framework is evaluated in recent global earthquake events. Evaluation results show that DisasterNet significantly improves multiple hazard and impact estimation compared to existing USGS products.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"KDD '23: Proceedings of the 29th ACM SIGKDD conference on knowledge discovery and data mining","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"ACM SIGKDD Conference on Knowledge Discovery & Data Mining","conferenceDate":"August 6-10, 2023","conferenceLocation":"Long Beach, CA","language":"English","publisher":"Association for Computing Machinery","doi":"10.1145/3580305.3599807","usgsCitation":"Li, X., Burgi, P.M., Ma, W., Noh, H., Wald, D.J., and Xu, S., 2023, DisasterNet: Causal Bayesian networks with normalizing flows for cascading hazards, <i>in</i> KDD '23: Proceedings of the 29th ACM SIGKDD conference on knowledge discovery and data mining, v. 29, Long Beach, CA, August 6-10, 2023, p. 4391-4403, https://doi.org/10.1145/3580305.3599807.","productDescription":"13 p.","startPage":"4391","endPage":"4403","ipdsId":"IP-149697","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":419595,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","noUsgsAuthors":false,"publicationDate":"2023-08-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Li, Xuechun","contributorId":317874,"corporation":false,"usgs":false,"family":"Li","given":"Xuechun","email":"","affiliations":[{"id":69176,"text":"Stonybrook University","active":true,"usgs":false}],"preferred":false,"id":879620,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgi, Paula Madeline 0000-0003-3001-5759","orcid":"https://orcid.org/0000-0003-3001-5759","contributorId":317875,"corporation":false,"usgs":true,"family":"Burgi","given":"Paula","email":"","middleInitial":"Madeline","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879621,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ma, Wei","contributorId":317876,"corporation":false,"usgs":false,"family":"Ma","given":"Wei","email":"","affiliations":[{"id":37969,"text":"Hong Kong Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":879622,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noh, Haeyoung","contributorId":317877,"corporation":false,"usgs":false,"family":"Noh","given":"Haeyoung","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":879623,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":879624,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Xu, Susu","contributorId":300127,"corporation":false,"usgs":false,"family":"Xu","given":"Susu","email":"","affiliations":[{"id":65025,"text":"Stony Brook University, NY, USA","active":true,"usgs":false}],"preferred":false,"id":879625,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70247383,"text":"sir20235073 - 2023 - Response in the water quality of Delavan Lake, Wisconsin, to changes in phosphorus loading—Setting new goals for loading from its drainage basin","interactions":[],"lastModifiedDate":"2026-03-12T20:43:24.534885","indexId":"sir20235073","displayToPublicDate":"2023-08-03T14:21:59","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5073","displayTitle":"Response in the Water Quality of Delavan Lake, Wisconsin, to Changes in Phosphorus Loading—Setting New Goals for Loading from its Drainage Basin","title":"Response in the water quality of Delavan Lake, Wisconsin, to changes in phosphorus loading—Setting new goals for loading from its drainage basin","docAbstract":"<p>During 1989–92, an extensive rehabilitation project was completed in and around Delavan Lake, Wisconsin, to improve the lake’s water quality. However, in 2016, the lake was listed by the Wisconsin Department of Natural Resources as impaired for excessive algal growth (high chlorophyll <i>a</i> concentrations), and high phosphorus input was listed as its likely cause. In addition, the recent (2017–21) mean summer water clarity (as measured with a Secchi disk) was shallower than the goal set by the community (3.0 meters). Based primarily on flow and water-quality data collected in Jackson Creek, which is the main tributary of the lake, the mean annual phosphorus loading to the lake during water years (WYs) 2017–21 was 6,570 kilograms per year (kg/yr), and 306 kg/yr came from uncontrollable sources (atmospheric deposition and groundwater). Phosphorus loading during these years was about 48 percent higher than the long-term mean loading from WY 1984 to WY 2021. Based on results from Canfield-Bachmann phosphorus models, Carlson trophic state index relations, and the Jones and Bachmann chlorophyll <i>a</i> relation, external phosphorus loading would need to be decreased from 6,570 to 5,270 kg/yr (a 21-percent reduction in the potentially controllable external phosphorus load from the base period of WYs 2017–21) for chlorophyll <i>a</i> concentrations greater than 20 micrograms per liter to be detected no more than 5.0 percent of the time (the Wisconsin Department of Natural Resources criterion for chlorophyll <i>a</i> impairment for the lake). Based on Carlson trophic state index relations, external loading would need to be decreased from 6,570 to 4,380 kg/yr (a 35-percent reduction in the potentially controllable external phosphorus load) for summer mean Secchi depths to increase to 3.0 meters. Therefore, for Delavan Lake to reach the water-quality criteria for impairment and the goals for all three water-quality constituents, a 35-percent reduction in the potentially controllable phosphorus load is needed, which equates to a reduction in total phosphorus loading from 6,570 to 4,380 kg/yr. A 35-percent reduction in phosphorus loading to improve the water quality of Delavan Lake is less than the 49-percent reduction in phosphorus loading required for the area near Delavan Lake to improve the water quality of the Rock River and its tributaries indicated in the Rock River total maximum daily load.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235073","collaboration":"Prepared in cooperation with the Town of Delavan and the Delavan Lake Sanitary District","usgsCitation":"Robertson, D.M., Siebers, B.J., and Fredrick, R.A., 2023, Response in the water quality of Delavan Lake, Wisconsin, to changes in phosphorus loading—Setting new goals for loading from its drainage basin: U.S. Geological Survey Scientific Investigations Report 2023–5073, 28 p., https://doi.org/10.3133/sir20235073.","productDescription":"Report: viii, 28 p.; Data Release; Dataset","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-148703","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501038,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115123.htm","linkFileType":{"id":5,"text":"html"}},{"id":419534,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235073/full","text":"Report"},{"id":419467,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":419466,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H85BK0","text":"USGS data release","linkHelpText":"Eutrophication models to simulate changes in the water quality of Green Lake, Wisconsin in response to changes in phosphorus loading, with supporting water-quality data for the lake, its tributaries, and atmospheric deposition"},{"id":419465,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5073/images/"},{"id":419464,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5073/sir20235073.XML","linkFileType":{"id":8,"text":"xml"}},{"id":419463,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5073/sir20235073.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023–5073"},{"id":419462,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5073/coverthb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Delavan Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              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Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Site</li><li>General Approach</li><li>Methods of Data Collection, Flow and Load Estimation, and Eutrophication Modeling</li><li>Lake Water Quality</li><li>Water and Phosphorus Loading to Delavan Lake</li><li>Response in Near-Surface Water Quality to Changes in Phosphorus Loading</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2023-08-03","noUsgsAuthors":false,"publicationDate":"2023-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":217258,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siebers, Benjamin J. 0000-0002-2900-5169","orcid":"https://orcid.org/0000-0002-2900-5169","contributorId":206518,"corporation":false,"usgs":true,"family":"Siebers","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fredrick, Reed A. 0000-0002-7771-0655","orcid":"https://orcid.org/0000-0002-7771-0655","contributorId":317831,"corporation":false,"usgs":true,"family":"Fredrick","given":"Reed","email":"","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879393,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70247410,"text":"sim3500 - 2023 - Estimating streambed hydraulic conductivity for selected streams in the Mississippi Alluvial Plain using continuous resistivity profiling methods—Delta region","interactions":[],"lastModifiedDate":"2026-02-19T17:47:47.386574","indexId":"sim3500","displayToPublicDate":"2023-08-03T11:07:12","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3500","displayTitle":"Estimating Streambed Hydraulic Conductivity for Selected Streams in the Mississippi Alluvial Plain Using Continuous Resistivity Profiling Methods—Delta Region","title":"Estimating streambed hydraulic conductivity for selected streams in the Mississippi Alluvial Plain using continuous resistivity profiling methods—Delta region","docAbstract":"<h1>Introduction</h1><p class=\"Citation\"><span>&nbsp;</span>The Mississippi Alluvial Plain is one of the most important agricultural regions in the United States, and crop productivity relies on groundwater irrigation from an aquifer system whose full capacity is unknown. Groundwater withdrawals from the Mississippi River Valley alluvial aquifer have resulted in substantial groundwater-level declines and reductions in base flow in streams within the Mississippi Alluvial Plain. These effects are limiting well production and threatening future water availability in the region.</p><p class=\"Citation\">A comprehensive assessment of water availability in the Mississippi Alluvial Plain is critically important for making well-informed management decisions about sustainability, establishing best practices for water use, and predicting changes to water levels in the Mississippi Alluvial Plain over the next 50–100 years. The first step in the new regional modeling effort was to run the existing Mississippi Embayment Regional Aquifer Study (MERAS) model and perform data-worth and uncertainty analyses to prioritize data collection efforts to improve model forecasts. Parameter estimation indicated that streambed conductance was one of the variables that the model was most sensitive to, but little data were available to constrain those general estimates.</p><p class=\"Citation\">From this characterization of the existing data, a map of the streams that the MERAS model was most sensitive to was created by the U.S. Geological Survey to guide the collection of 862 kilometers of waterborne resistivity surveys within the Delta region of Mississippi to characterize streambed lithology. This technique characterizes the streambed itself and the 15–30 meters below the streambed that control the exchange of water between the stream and the alluvial aquifer. These data can be used to map changes in the lithology of the streambed and identify areas of potential groundwater/surface-water exchange. Additionally, electrical and nuclear well logs from the study area were compared to facilitate the development of a petrophysical relation between the waterborne resistivity data and hydraulic conductivity. Resistivity values may then be used as a cost-effective way to approximate aquifer hydraulic conductivity distributions for use in regional groundwater models.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3500","issn":"2329-132X","collaboration":"Prepared in cooperation with the Arkansas Department of Health, Arkansas Game and Fish Commission, Delta Council, Delta FARM, Delta Sustainable Water Resources Task Force, Delta Wildlife HydroGeophysics Group, Aarhus University, Mississippi Department of  Environmental Quality, Mississippi State University, Missouri Department of Natural Resources, The Nature Conservancy, U.S. Army Corps of Engineers, U.S. Department of Agriculture-Agricultural Research Service, University of Arkansas, University of Mississippi, Yazoo Mississippi Delta Joint Water Management District","usgsCitation":"Adams, R.F., Miller, B.V., Kress, W.H., Minsley, B.J., and Rigby, J.R., 2023, Estimating streambed hydraulic conductivity for selected streams in the Mississippi Alluvial Plain using continuous resistivity profiling methods—Delta region: U.S. Geological Survey Scientific Investigations Map 3500, 2 sheets, https://doi.org/10.3133/sim3500.","productDescription":"2 Sheets: 45.00 x 34.25 inches and 45.00 x 34.55 inches","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-115128","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":419523,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WQPRFB","text":"USGS—Waterborne resistivity inverted models, Mississippi Alluvial Plain, 2016–2018"},{"id":419522,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3500/sim3500_sheet2.pdf","size":"14.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3500 sheet 2"},{"id":419521,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3500/sim3500_sheet1.pdf","size":"15.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3500 sheet 1"},{"id":419520,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3500/coverthb.jpg"},{"id":500206,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115125.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arkansas, Louisiana, Mississippi","otherGeospatial":"Mississippi Alluvial Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90,\n              35\n            ],\n            [\n              -91.25,\n              35\n            ],\n            [\n              -91.25,\n              31\n            ],\n            [\n              -90,\n              31\n            ],\n            [\n              -90,\n              35\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>For more information about this publication, contact<br><a data-mce-href=\"mailto:gs-w-lmg_center_director@usgs.gov\" href=\"mailto:gs-w-lmg_center_director@usgs.gov\">Director, Lower Mississippi-Gulf Water Science Center</a></p><p>U.S. Geological Survey<br>640 Grassmere Park, Suite 100<br>Nashville, TN 37211</p><p>For additional information, visit<br><a href=\"https://www.usgs.gov/centers/lmg-water/\" data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\">https://www.usgs.gov/centers/lmg-water/</a></p><div class=\"elementToProof\"><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></div>","tableOfContents":"<ul><li>Introduction</li><li>Surficial Geology</li><li>Methods</li><li>Waterborne Resistivity</li><li>Estimated Hydraulic Conductivity</li><li>Figure Annotations</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-08-03","noUsgsAuthors":false,"publicationDate":"2023-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Adams, Ryan F. 0000-0001-7299-329X rfadams@usgs.gov","orcid":"https://orcid.org/0000-0001-7299-329X","contributorId":5499,"corporation":false,"usgs":true,"family":"Adams","given":"Ryan","email":"rfadams@usgs.gov","middleInitial":"F.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":879480,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Benjamin 0000-0003-4795-3442 bvmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-4795-3442","contributorId":197345,"corporation":false,"usgs":true,"family":"Miller","given":"Benjamin","email":"bvmiller@usgs.gov","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879481,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kress, Wade H. 0000-0002-6833-028X wkress@usgs.gov","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":1576,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","email":"wkress@usgs.gov","middleInitial":"H.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":879482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":879483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rigby, James R. 0000-0002-5611-6307","orcid":"https://orcid.org/0000-0002-5611-6307","contributorId":196374,"corporation":false,"usgs":false,"family":"Rigby","given":"James R.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":879484,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70247954,"text":"70247954 - 2023 - Scaling microseismic cloud shape during hydraulic stimulation using in-situ stress and permeability","interactions":[],"lastModifiedDate":"2023-08-29T14:00:46.383677","indexId":"70247954","displayToPublicDate":"2023-08-03T08:54:21","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7501,"text":"JGR Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Scaling microseismic cloud shape during hydraulic stimulation using in-situ stress and permeability","docAbstract":"<p><span>Forecasting microseismic cloud shape as a proxy of stimulated rock volume may improve the design of an energy extraction system. The microseismic cloud created during hydraulic stimulation of geothermal reservoirs is known empirically to extend in the general direction of the maximum principal stress. However, this empirical relationship is often inconsistent with reported results, and the cloud growth process remains poorly understood. This study investigates microseismic cloud growth using data obtained from a hydraulic stimulation project in Basel, Switzerland, and explores its correlation with measured in situ stress. We applied principal component analysis to a time series of microseismicity for macroscopic characterization of microseismic cloud growth in two- and three-dimensional space. The microseismic cloud, in addition to extending in the general direction of maximum principal stress, expanded in the direction of intermediate principal stress. The orientation of the least microseismic cloud growth was stable and almost identical to the minimum principal stress direction. Further, microseismic cloud shape ratios showed good agreement when compared with in situ stress magnitude ratios. The permeability tensor estimated from microseismicity also provided a good correlation in terms of direction and magnitude with the microseismic cloud growth. We show that in situ stress plays a dominant role by controlling the permeability of each existing fracture in the reservoir fracture system. Consequently, microseismic cloud growth can be scaled by in situ stress as a first-order approximation if there is sufficient variation in the orientation of existing faults.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2023JB026839","usgsCitation":"Mukuhira, Y., Yang, M., Ishibashi, T., Okamoto, K., Moriya, H., Kumano, Y., Asanuma, H., Shapiro, S., Rubinstein, J., Ito, T., Yan, K., and Zuo, Y., 2023, Scaling microseismic cloud shape during hydraulic stimulation using in-situ stress and permeability: JGR Solid Earth, v. 128, no. 8, e2023JB026839, 22 p., https://doi.org/10.1029/2023JB026839.","productDescription":"e2023JB026839, 22 p.","ipdsId":"IP-125506","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":442518,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2023jb026839","text":"Publisher Index Page"},{"id":420234,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Switzerland","city":"Basel","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              7.540327928882107,\n              47.62\n            ],\n            [\n              7.541369472820975,\n              47.54\n            ],\n            [\n              7.68,\n              47.54\n            ],\n            [\n              7.68,\n              47.62\n            ],\n            [\n              7.540327928882107,\n              47.62\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"128","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Mukuhira, Y.","contributorId":328759,"corporation":false,"usgs":false,"family":"Mukuhira","given":"Y.","email":"","affiliations":[{"id":36517,"text":"Tohoku University","active":true,"usgs":false}],"preferred":false,"id":881218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, M.","contributorId":328760,"corporation":false,"usgs":false,"family":"Yang","given":"M.","email":"","affiliations":[{"id":36517,"text":"Tohoku University","active":true,"usgs":false}],"preferred":false,"id":881219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ishibashi, T.","contributorId":328761,"corporation":false,"usgs":false,"family":"Ishibashi","given":"T.","email":"","affiliations":[{"id":40273,"text":"National Institute of Advanced Industrial Science and Technology","active":true,"usgs":false}],"preferred":false,"id":881220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Okamoto, K.","contributorId":328762,"corporation":false,"usgs":false,"family":"Okamoto","given":"K.","email":"","affiliations":[{"id":40273,"text":"National Institute of Advanced Industrial Science and Technology","active":true,"usgs":false}],"preferred":false,"id":881221,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moriya, H.","contributorId":328763,"corporation":false,"usgs":false,"family":"Moriya","given":"H.","email":"","affiliations":[{"id":36517,"text":"Tohoku University","active":true,"usgs":false}],"preferred":false,"id":881222,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kumano, Y.","contributorId":328764,"corporation":false,"usgs":false,"family":"Kumano","given":"Y.","email":"","affiliations":[{"id":78484,"text":"JAPEX","active":true,"usgs":false}],"preferred":false,"id":881223,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Asanuma, H.","contributorId":328765,"corporation":false,"usgs":false,"family":"Asanuma","given":"H.","email":"","affiliations":[{"id":40273,"text":"National Institute of Advanced Industrial Science and Technology","active":true,"usgs":false}],"preferred":false,"id":881224,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shapiro, S.A.","contributorId":328766,"corporation":false,"usgs":false,"family":"Shapiro","given":"S.A.","email":"","affiliations":[{"id":37963,"text":"Freie Universität Berlin","active":true,"usgs":false}],"preferred":false,"id":881225,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Rubinstein, Justin 0000-0003-1274-6785","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":215341,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":881226,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ito, T.","contributorId":328767,"corporation":false,"usgs":false,"family":"Ito","given":"T.","affiliations":[{"id":36517,"text":"Tohoku University","active":true,"usgs":false}],"preferred":false,"id":881227,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Yan, K.","contributorId":328768,"corporation":false,"usgs":false,"family":"Yan","given":"K.","email":"","affiliations":[{"id":36517,"text":"Tohoku University","active":true,"usgs":false}],"preferred":false,"id":881228,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zuo, Y.","contributorId":328769,"corporation":false,"usgs":false,"family":"Zuo","given":"Y.","email":"","affiliations":[{"id":78485,"text":"Chengdu University of Technology","active":true,"usgs":false}],"preferred":false,"id":881229,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70247705,"text":"70247705 - 2023 - Converted-wave reverse time migration imaging in subduction zone settings","interactions":[],"lastModifiedDate":"2023-08-14T12:30:30.866658","indexId":"70247705","displayToPublicDate":"2023-08-03T07:29:09","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Converted-wave reverse time migration imaging in subduction zone settings","docAbstract":"<p class=\"chapter-para\">We use a newly developed 2-D elastic reverse time migration (RTM) imaging algorithm based on the Helmholtz decomposition to test approaches for imaging the descending slab in subduction zone regions using local earthquake sources. Our elastic RTM method is designed to reconstruct incident and scattered wavefields at depth, isolate constituent<span>&nbsp;</span><i>P-</i><span>&nbsp;</span>and<span>&nbsp;</span><i>S-</i>wave components via Helmholtz decomposition, and evaluate normalized imaging functions that leverage dominant<span>&nbsp;</span><i>P</i><span>&nbsp;</span>and<span>&nbsp;</span><i>S</i><span>&nbsp;</span>signals. This method allows us to target particular converted-wave scattering geometries, for example incident<span>&nbsp;</span><i>S</i><span>&nbsp;</span>to scattered<span>&nbsp;</span><i>P</i>, which may be expected to have dominant signals in any given data set. The method is intended to be applied to dense seismic array observations that adequately capture both incident and converted wavefields. We draw a direct connection between our imaging functions and the first-order contrasts in shear wave material properties across seismic discontinuities. Through tests on synthetic data using either<span>&nbsp;</span><i>S</i><span>&nbsp;</span>→<span>&nbsp;</span><i>P</i><span>&nbsp;</span>or<span>&nbsp;</span><i>P</i><span>&nbsp;</span>→<span>&nbsp;</span><i>S</i><span>&nbsp;</span>conversions, we find that our technique can successfully recover the structure of a subducting slab using data from a dense wide-angle array of surface stations. We also calculate images with a small-aperture array to test the impact of array geometry on image resolution and interpretability. Our results show that our imaging technique is capable of imaging multiple seismic discontinuities at depth, even with a small number of earthquakes, but that limitations arise when a small aperture array is considered. In this case, the presence of artefacts makes it more difficult to determine the location of seismic discontinuities.</p>","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggad308","usgsCitation":"Langer, L., Pollitz, F., and McGuire, J., 2023, Converted-wave reverse time migration imaging in subduction zone settings: Geophysical Journal International, v. 235, no. 2, p. 1384-1402, https://doi.org/10.1093/gji/ggad308.","productDescription":"19 p.","startPage":"1384","endPage":"1402","ipdsId":"IP-146378","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":442528,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggad308","text":"Publisher Index Page"},{"id":419761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"235","issue":"2","noUsgsAuthors":false,"publicationDate":"2023-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Langer, Leah 0000-0002-5384-0500","orcid":"https://orcid.org/0000-0002-5384-0500","contributorId":298853,"corporation":false,"usgs":true,"family":"Langer","given":"Leah","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":880108,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":880109,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McGuire, Jeffrey J. 0000-0001-9235-2166","orcid":"https://orcid.org/0000-0001-9235-2166","contributorId":219786,"corporation":false,"usgs":true,"family":"McGuire","given":"Jeffrey J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":880110,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70247433,"text":"70247433 - 2023 - Resilience of riparian vegetation productivity to early 21st century drought in northern California, USA","interactions":[],"lastModifiedDate":"2023-08-07T12:13:27.955306","indexId":"70247433","displayToPublicDate":"2023-08-03T07:10:44","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Resilience of riparian vegetation productivity to early 21st century drought in northern California, USA","docAbstract":"<div class=\"abstract-group  metis-abstract\"><div class=\"article-section__content en main\"><p>Drought and intensive land use can interact as stressors on riparian vegetation, especially along rivers flowing through seasonally dry landscapes. Knowledge of past riparian vegetation response to drought and land use change can provide land managers with a better understanding of changes induced by upstream management actions, climate change, and chronic stressors. To investigate the response of riparian vegetation productivity to drought and land use, we developed a 21-year time series (2000–2020) of growing season vegetation dynamics using near-infrared reflectance of vegetation (NIR<sub>V</sub>) derived from satellite data across 30 watershed subbasins that drain into the San Francisco Bay Delta in central California, USA. We observed a strong response of riparian vegetation to drought, but rapid recovery and very few long-term declines in productivity. At a local level, vegetation communities' response to drought and post-drought productivity dynamics were highly variable across biophysical settings and land use gradients. Most of the riparian areas with long-term declines in NIR<sub>V</sub><span>&nbsp;</span>were located in the lower elevation Coast Range on the western side of the study area where there is little to no water engineering or agricultural irrigation runoff to subsidize riparian vegetation. Riparian areas with the greatest long-term increase were along rivers draining the higher elevation Sierra Nevada range to the east. Our results suggest that river systems with a high proportion of water originating as snowmelt may be more buffered against long-term drought-driven declines in productivity than those dependent exclusively on winter rainfall. The long-term increase in NIR<sub>V</sub><span>&nbsp;</span>in the vast majority of riparian areas within our study area may also have been driven in part by increasing atmospheric CO<sub>2</sub><span>&nbsp;</span>concentrations, which have been shown to increase plant water use efficiency.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.4638","usgsCitation":"Selmants, P., Conrad, C.R., Wilson, T., and Villarreal, M.L., 2023, Resilience of riparian vegetation productivity to early 21st century drought in northern California, USA: Ecosphere, v. 14, no. 8, e4638, 10 p., https://doi.org/10.1002/ecs2.4638.","productDescription":"e4638, 10 p.","ipdsId":"IP-144817","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":442533,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.4638","text":"Publisher Index Page"},{"id":435233,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PT6DYC","text":"USGS data release","linkHelpText":"Spatial data of California riparian vegetation productivity trends over time (2000-2020) and environmental covariates"},{"id":419557,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -122.31024648927419,\n              38.451960956521106\n            ],\n            [\n              -122.17846709209289,\n              38.107140456611035\n            ],\n            [\n              -121.60742303764215,\n              37.34278608643963\n            ],\n            [\n              -120.8167466545559,\n              36.32322872629197\n            ],\n            [\n              -119.49895268274545,\n              35.218415938114646\n            ],\n            [\n              -118.7082762996592,\n              35.14661192090209\n            ],\n            [\n              -118.7082762996592,\n              36.146072780960196\n            ],\n            [\n              -119.63073207992679,\n              37.621645541592656\n            ],\n            [\n              -120.46533492873961,\n              38.93195341540286\n            ],\n            [\n              -121.51957010618794,\n              40.28554472076502\n            ],\n            [\n              -122.17846709209289,\n              40.88600356913588\n            ],\n            [\n              -123.10092287236046,\n              40.4862965568405\n            ],\n            [\n              -122.83736407799836,\n              39.340807940338664\n            ],\n            [\n              -122.31024648927419,\n              38.451960956521106\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"14","issue":"8","noUsgsAuthors":false,"publicationDate":"2023-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Selmants, Paul 0000-0001-6211-3957 pselmants@usgs.gov","orcid":"https://orcid.org/0000-0001-6211-3957","contributorId":192591,"corporation":false,"usgs":true,"family":"Selmants","given":"Paul","email":"pselmants@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":879604,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrad, Caroline Rose 0000-0002-0496-8081","orcid":"https://orcid.org/0000-0002-0496-8081","contributorId":236945,"corporation":false,"usgs":true,"family":"Conrad","given":"Caroline","email":"","middleInitial":"Rose","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":879605,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Tamara 0000-0001-7399-7532 tswilson@usgs.gov","orcid":"https://orcid.org/0000-0001-7399-7532","contributorId":2975,"corporation":false,"usgs":true,"family":"Wilson","given":"Tamara","email":"tswilson@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":879606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":879607,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70247435,"text":"70247435 - 2023 - Biophysical factors control invasive annual grass hot spots in the Mojave Desert","interactions":[],"lastModifiedDate":"2023-10-23T15:50:31.324403","indexId":"70247435","displayToPublicDate":"2023-08-03T06:56:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Biophysical factors control invasive annual grass hot spots in the Mojave Desert","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>Invasive annual grasses can promote ecosystem state changes and habitat loss in the American Southwest. Non-native annual grasses such as<span>&nbsp;</span><i>Bromus</i><span>&nbsp;</span>spp<i>. a</i>nd<span>&nbsp;</span><i>Schismus</i><span>&nbsp;</span>spp. have invaded the Mojave Desert and degraded habitat through increased fire occurrence, severity, and shifting plant community composition. Thus, it is important to identify and characterize the areas where persistent invasion has occurred, identifying where subsequent habitat degradation has increased. Previous plot and landscape-scale analyses have revealed anthropogenic and biophysical correlates with the establishment and dominance of invasive annual grasses in the Mojave Desert. However, these studies have been limited in spatial and temporal scales. Here we use Landsat imagery validated using an extensive network of plot data to map persistent and productive populations of invasive annual grass, called<span>&nbsp;</span><i>hot spots</i>, across the entire Mojave Desert ecoregion over 12&nbsp;years (2009–2020). We also identify important variables for predicting<span>&nbsp;</span><i>hot spot</i><span>&nbsp;</span>distribution using the Random Forest algorithm and identifying the most invaded subregions. We identified<span>&nbsp;</span><i>hot spots</i><span>&nbsp;</span>in over 5% of the Mojave Desert mostly on the western and eastern edges of the ecoregion, and invasive grasses were detected in over 90% of the Mojave Desert at least once in that time. Across the entire Mojave Desert, our results indicate that soil texture, aspect, winter precipitation, and elevation are the highest-ranking predictive variables of invasive grass<span>&nbsp;</span><i>hot spots</i>, while anthropogenic variables contributed the least to the accuracy of the predictive model. The total area covered by<span>&nbsp;</span><i>hot spots</i><span>&nbsp;</span>varied significantly among subregions of the Mojave Desert. We found that anthropogenic variables became more important in explaining invasive annual establishment and persistence as spatial scale was reduced to the subregional level. Our findings have important implications for informing where land management actions can prioritize reducing invasive annual persistence and promoting restoration efforts.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10530-023-03142-z","usgsCitation":"Smith, T.C., Bishop, T., Duniway, M.C., Villarreal, M.L., Knight, A.C., Munson, S.M., Waller, E.K., Jensen, R., and Gill, R., 2023, Biophysical factors control invasive annual grass hot spots in the Mojave Desert: Biological Invasions, v. 25, p. 3839-3859, https://doi.org/10.1007/s10530-023-03142-z.","productDescription":"21 p.","startPage":"3839","endPage":"3859","ipdsId":"IP-145951","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":442534,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10530-023-03142-z","text":"Publisher Index Page"},{"id":419555,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -116.91885200845788,\n              36.175859123828786\n            ],\n            [\n              -116.91885200845788,\n              34.00154237614139\n            ],\n            [\n              -114.2173743662469,\n              34.00154237614139\n            ],\n            [\n              -114.2173743662469,\n              36.175859123828786\n            ],\n            [\n              -116.91885200845788,\n              36.175859123828786\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"25","noUsgsAuthors":false,"publicationDate":"2023-08-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, Tanner Corless","contributorId":317870,"corporation":false,"usgs":false,"family":"Smith","given":"Tanner","email":"","middleInitial":"Corless","affiliations":[{"id":69173,"text":"Brigham Young University, Department of Biology, Provo, Utah, USA","active":true,"usgs":false}],"preferred":false,"id":879611,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bishop, Tara B.B.","contributorId":215034,"corporation":false,"usgs":false,"family":"Bishop","given":"Tara B.B.","affiliations":[{"id":39160,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT USA","active":true,"usgs":false}],"preferred":false,"id":879612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":879613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":879614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":879615,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":879616,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waller, Eric K.","contributorId":317871,"corporation":false,"usgs":false,"family":"Waller","given":"Eric","email":"","middleInitial":"K.","affiliations":[{"id":69174,"text":"Contracted to USGS, Portland, Oregon, USA","active":true,"usgs":false}],"preferred":false,"id":879617,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jensen, Ryan","contributorId":317872,"corporation":false,"usgs":false,"family":"Jensen","given":"Ryan","email":"","affiliations":[{"id":69175,"text":"Brigham Young University, Department of Geography, Provo, Utah, USA","active":true,"usgs":false}],"preferred":false,"id":879618,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gill, Richard A.","contributorId":317873,"corporation":false,"usgs":false,"family":"Gill","given":"Richard A.","affiliations":[{"id":69173,"text":"Brigham Young University, Department of Biology, Provo, Utah, USA","active":true,"usgs":false}],"preferred":false,"id":879619,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70247474,"text":"70247474 - 2023 - Potassium-39-derived 36Ar production during fission-neutron irradiation and its effect on 40Ar/39Ar ages","interactions":[],"lastModifiedDate":"2023-08-09T13:33:02.864013","indexId":"70247474","displayToPublicDate":"2023-08-03T06:38:13","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Potassium-39-derived <i>36</i>Ar production during fission-neutron irradiation and its effect on <i>40</i>Ar/<i>39</i>Ar ages","title":"Potassium-39-derived 36Ar production during fission-neutron irradiation and its effect on 40Ar/39Ar ages","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-gulliver text-s\"><div id=\"ab005\" class=\"abstract author\"><div id=\"as005\"><p id=\"sp0005\">Various interference reactions producing unwanted Ar isotopes from K, Ca, Cl and Ar require correction to satisfy the<span>&nbsp;</span><sup>40</sup>Ar/<sup>39</sup>Ar age equation. Using GEANT4, we design and build a model Cadmium Lined In Core Irradiation Tube (CLICIT) irradiation facility, as used in the Oregon State TRIGA Reactor (OSTR). We illustrate the complexity of the irradiation of geologic samples within this framework and determine an overlooked production channel of<span>&nbsp;</span><sup>36</sup>Ar. The production of<span>&nbsp;</span><sup>36</sup>Ar is fed from the<span>&nbsp;</span><sup>39</sup>K(n,<i>α</i>)<sup>36</sup>Cl nuclear channel,<span>&nbsp;</span><sup>36</sup>Cl subsequently decays to<span>&nbsp;</span><sup>36</sup>Ar (<sup>39</sup>K(n,<i>α,<span class=\"math\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=\">β</span></span></i>)<span>&nbsp;</span><sup>36</sup>Ar). Simulations in this work using a<span>&nbsp;</span><sup>235</sup><span>U fission neutron&nbsp;energy spectrum&nbsp;and modelled CLICIT facility, determine a production ratio for this reaction (</span><sup>36</sup>Cl/<sup>39</sup>Ar)<sub>K</sub>&nbsp;=&nbsp;0.40&nbsp;±&nbsp;0.01 (1<i><span class=\"math\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=\">σ</span></span></i><span>); greater than an order of magnitude larger than any other K interference. The magnitude of the resulting age bias for an unknown sample will be a function of the integrated&nbsp;neutron flux, the length of irradiation (fluence), the time elapsed since irradiation, and the age relationship between the unknown and neutron&nbsp;fluence&nbsp;monitor. We show using the raw data of (Niespolo et al., 2017) that the age of Alder Creek&nbsp;sanidine&nbsp;can be modified to be ca. 0.1% older (1</span><i><span class=\"math\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=\">σ</span></span></i>), at the 2σ level of current analytical precision for the Alder Creek age for this study. The<span>&nbsp;</span><sup>39</sup>K(n,<i><span class=\"math\"><span id=\"MathJax-Element-6-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=\">α</span></span></i>,<i><span class=\"math\"><span id=\"MathJax-Element-7-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=\">β</span></span></i>)<sup>36</sup><span>Ar inference should be incorporated into routine data analysis and may be especially important in the&nbsp;intercalibration&nbsp;of the&nbsp;</span><sup>40</sup>Ar/<sup>39</sup>Ar system with other chronometers (e.g.,<span>&nbsp;</span><sup>206</sup>Pb/<sup>238</sup>U).</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2023.07.017","usgsCitation":"Carter, J., Renne, P.R., and Morgan, L.E., 2023, Potassium-39-derived 36Ar production during fission-neutron irradiation and its effect on 40Ar/39Ar ages: Geochimica et Cosmochimica Acta, v. 357, p. 26-34, https://doi.org/10.1016/j.gca.2023.07.017.","productDescription":"9 p.","startPage":"26","endPage":"34","ipdsId":"IP-150326","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":442543,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.gca.2023.07.017","text":"Publisher Index Page"},{"id":419655,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"357","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Carter, Jack N.","contributorId":317971,"corporation":false,"usgs":false,"family":"Carter","given":"Jack N.","affiliations":[{"id":38176,"text":"Berkeley Geochronology Center","active":true,"usgs":false}],"preferred":false,"id":879818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Renne, Paul R. 0000-0003-1769-5235","orcid":"https://orcid.org/0000-0003-1769-5235","contributorId":229577,"corporation":false,"usgs":false,"family":"Renne","given":"Paul","email":"","middleInitial":"R.","affiliations":[{"id":37390,"text":"Department of Earth and Planetary Science, University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":879819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgan, Leah E. 0000-0001-9930-524X lemorgan@usgs.gov","orcid":"https://orcid.org/0000-0001-9930-524X","contributorId":176174,"corporation":false,"usgs":true,"family":"Morgan","given":"Leah","email":"lemorgan@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":879820,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70255242,"text":"70255242 - 2023 - Bayesian spatio-temporal survival analysis for all types of censoring with application to a wildlife disease study","interactions":[],"lastModifiedDate":"2024-06-13T14:33:03.488364","indexId":"70255242","displayToPublicDate":"2023-08-01T09:29:43","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1577,"text":"Environmetrics","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian spatio-temporal survival analysis for all types of censoring with application to a wildlife disease study","docAbstract":"<p><span>In this article, we consider modeling arbitrarily censored survival data with spatio-temporal covariates. We demonstrate that under the piecewise constant hazard function, the likelihood for uncensored or right-censored subjects is proportional to the likelihood of multiple conditionally independent Poisson random variables. To address left- or interval-censored subjects, we propose to impute the exact event times and convert them into uncensored subjects, enabling the application of the integrated nested Laplace approximation to update model parameters using the imputed data. We introduce an iterative algorithm that alternates between imputing event times for left- and interval-censored subjects and re-estimating model parameters. The proposed method is assessed through a simulation study and applied to analyze a spatio-temporal survival dataset in a wildlife disease study investigating bovine tuberculosis in white-tailed deer in Michigan.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/env.2823","usgsCitation":"Yao, K., Zhu, J., O'Brien, D., and Walsh, D.P., 2023, Bayesian spatio-temporal survival analysis for all types of censoring with application to a wildlife disease study: Environmetrics, v. 34, no. 8, e2823, 13 p., https://doi.org/10.1002/env.2823.","productDescription":"e2823, 13 p.","ipdsId":"IP-146224","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":442561,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"http://dx.doi.org/10.1002/env.2823","text":"Publisher Index Page"},{"id":430134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Yao, Kehui","contributorId":339161,"corporation":false,"usgs":false,"family":"Yao","given":"Kehui","email":"","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":903822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhu, Jun","contributorId":73485,"corporation":false,"usgs":true,"family":"Zhu","given":"Jun","email":"","affiliations":[],"preferred":false,"id":903823,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Brien, Daniel  J.","contributorId":339164,"corporation":false,"usgs":false,"family":"O'Brien","given":"Daniel  J.","affiliations":[{"id":36986,"text":"Michigan Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":903824,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Walsh, Daniel P. 0000-0002-7772-2445","orcid":"https://orcid.org/0000-0002-7772-2445","contributorId":219539,"corporation":false,"usgs":true,"family":"Walsh","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":903825,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70257347,"text":"70257347 - 2023 - Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands","interactions":[],"lastModifiedDate":"2024-08-28T16:23:55.197568","indexId":"70257347","displayToPublicDate":"2023-08-01T09:11:07","publicationYear":"2023","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":"Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands","docAbstract":"<p>Mercury (Hg) is a widespread element and persistent pollutant, harmful to fish, wildlife, and humans in its organic, methylated form. The risk of Hg contamination is driven by factors that regulate Hg loading, methylation, bioaccumulation, and biomagnification. In remote locations, with infrequent access and limited data, understanding the relative importance of these factors can pose a challenge. Here, we assessed Hg concentrations in an apex predator fish species, lake trout (Salvelinus namaycush), collected from 14 lakes spanning two National Parks in southwest Alaska, U.S.A. We then examined factors associated with the variation in fish Hg concentrations using a Bayesian hierarchical model. We found that total Hg concentrations in water were consistently low among lakes (0.11–0.50 ng L− 1). Conversely, total Hg concentrations in lake trout spanned a thirty-fold range (101–3046 ng g− 1 dry weight), with median values at 7 lakes exceeding Alaska’s human consumption threshold. Model results showed that fish age and, to a lesser extent, body condition best explained variation in Hg concentration among fish within a lake, with Hg elevated in older, thinner lake trout. Other factors, including plankton methyl Hg content, fish species richness, volcano proximity, and glacier loss, best explained variation in lake trout Hg concentration among lakes. Collectively, these results provide evidence that multiple, hierarchically nested factors control fish Hg levels in these lakes. </p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2023.121678","usgsCitation":"Bartz, K.K., Hannam, M.P., Wilson, T.L., Lepak, R., Ogorek, J.M., Young, D.B., Eagles-Smith, C., and Krabbenhoft, D.P., 2023, Understanding drivers of mercury in lake trout (Salvelinus namaycush), a top-predator fish in southwest Alaska's parklands: Environmental Pollution, v. 330, 121678, 11 p., https://doi.org/10.1016/j.envpol.2023.121678.","productDescription":"121678, 11 p.","ipdsId":"IP-149237","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":442564,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envpol.2023.121678","text":"Publisher Index Page"},{"id":433253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Katmai National Park and Preserve, Lake Clark National Park and Preserve","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -155.59006149445355,\n              60.857310763857726\n            ],\n            [\n              -155.59006149445355,\n              58.42599213711503\n            ],\n            [\n              -152.59863331288238,\n              58.42599213711503\n            ],\n            [\n              -152.59863331288238,\n              60.857310763857726\n            ],\n            [\n              -155.59006149445355,\n              60.857310763857726\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"330","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bartz, Krista K.","contributorId":200705,"corporation":false,"usgs":false,"family":"Bartz","given":"Krista","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":910037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hannam, Michael P.","contributorId":199775,"corporation":false,"usgs":false,"family":"Hannam","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":910038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Tammy L. 0000-0002-3672-8277","orcid":"https://orcid.org/0000-0002-3672-8277","contributorId":293684,"corporation":false,"usgs":true,"family":"Wilson","given":"Tammy","email":"","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":910039,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lepak, Ryan F. 0000-0003-2806-1895","orcid":"https://orcid.org/0000-0003-2806-1895","contributorId":210990,"corporation":false,"usgs":false,"family":"Lepak","given":"Ryan F.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":910040,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ogorek, Jacob M. 0000-0002-6327-0740 jmogorek@usgs.gov","orcid":"https://orcid.org/0000-0002-6327-0740","contributorId":4960,"corporation":false,"usgs":true,"family":"Ogorek","given":"Jacob","email":"jmogorek@usgs.gov","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":910041,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Daniel","contributorId":58468,"corporation":false,"usgs":false,"family":"Young","given":"Daniel","affiliations":[{"id":35763,"text":"National Park Service, Lake Clark National Park and Preserve, Port Alsworth, AK","active":true,"usgs":false}],"preferred":false,"id":910042,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":221745,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin A.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":910043,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - 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,{"id":70248782,"text":"70248782 - 2023 - CONUS404: The NCAR-USGS 4-km long-term regional hydroclimate reanalysis over the CONUS","interactions":[],"lastModifiedDate":"2023-12-11T16:43:40.955033","indexId":"70248782","displayToPublicDate":"2023-08-01T08:24:59","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"CONUS404: The NCAR-USGS 4-km long-term regional hydroclimate reanalysis over the CONUS","docAbstract":"<p><span>A unique, high-resolution, hydroclimate reanalysis, 40-plus-year (October 1979–September 2021), 4 km (named as CONUS404), has been created using the Weather Research and Forecasting Model by dynamically downscaling of the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate dataset (ERA5) over the conterminous United States. The paper describes the approach for generating the dataset, provides an initial evaluation, including biases, and indicates how interested users can access the data. The motivation for creating this National Center for Atmospheric Research (NCAR)–U.S. Geological Survey (USGS) collaborative dataset is to provide research and end-user communities with a high-resolution, self-consistent, long-term, continental-scale hydroclimate dataset appropriate for forcing hydrological models and conducting hydroclimate scientific analyses over the conterminous United States. The data are archived and accessible on the USGS Black Pearl tape system and on the NCAR supercomputer Campaign storage system.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-21-0326.1","usgsCitation":"Rasmussen, R.M., Chen, F., Liu, C.H., Ikeda, K., Prein, A., Kim, J., Schneider, T., Dai, A., Gochis, D., Dugger, A., Zhang, Y., Jaye, A., Dudhia, J., He, C., Harrold, M., Xue, L., Chen, S., Newman, A., Dougherty, E., Abolafia-Rozenzweig, R., Lybarger, N., Viger, R.J., Lesmes, D.P., Skalak, K., Brakebill, J., Cline, D.W., Dunne, K.A., Rasmussen, K., and Miguez-Macho, G., 2023, CONUS404: The NCAR-USGS 4-km long-term regional hydroclimate reanalysis over the CONUS: Bulletin of the American Meteorological Society, v. 104, no. 8, p. 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H.","contributorId":329883,"corporation":false,"usgs":false,"family":"Liu","given":"C.","email":"","middleInitial":"H.","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ikeda, K.","contributorId":329884,"corporation":false,"usgs":false,"family":"Ikeda","given":"K.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883586,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prein, A.","contributorId":329885,"corporation":false,"usgs":false,"family":"Prein","given":"A.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883587,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kim, J.","contributorId":245126,"corporation":false,"usgs":false,"family":"Kim","given":"J.","affiliations":[{"id":49088,"text":"Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275, USA","active":true,"usgs":false}],"preferred":false,"id":883588,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schneider, T.","contributorId":216061,"corporation":false,"usgs":false,"family":"Schneider","given":"T.","affiliations":[],"preferred":false,"id":883589,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dai, A.","contributorId":329886,"corporation":false,"usgs":false,"family":"Dai","given":"A.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883590,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gochis, D.","contributorId":329888,"corporation":false,"usgs":false,"family":"Gochis","given":"D.","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883591,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dugger, A.","contributorId":329890,"corporation":false,"usgs":false,"family":"Dugger","given":"A.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883592,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Zhang, Y.","contributorId":274978,"corporation":false,"usgs":false,"family":"Zhang","given":"Y.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":883593,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jaye, A.","contributorId":329892,"corporation":false,"usgs":false,"family":"Jaye","given":"A.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883594,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Dudhia, J.","contributorId":329895,"corporation":false,"usgs":false,"family":"Dudhia","given":"J.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883595,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"He, C.","contributorId":76951,"corporation":false,"usgs":true,"family":"He","given":"C.","email":"","affiliations":[],"preferred":false,"id":883596,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Harrold, M.","contributorId":329899,"corporation":false,"usgs":false,"family":"Harrold","given":"M.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883597,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Xue, L.","contributorId":329901,"corporation":false,"usgs":false,"family":"Xue","given":"L.","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883598,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Chen, S.","contributorId":7856,"corporation":false,"usgs":true,"family":"Chen","given":"S.","affiliations":[],"preferred":false,"id":883599,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Newman, A.","contributorId":32791,"corporation":false,"usgs":true,"family":"Newman","given":"A.","affiliations":[],"preferred":false,"id":883600,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Dougherty, E.","contributorId":329905,"corporation":false,"usgs":false,"family":"Dougherty","given":"E.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883601,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Abolafia-Rozenzweig, R.","contributorId":329908,"corporation":false,"usgs":false,"family":"Abolafia-Rozenzweig","given":"R.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883602,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Lybarger, N.","contributorId":329911,"corporation":false,"usgs":false,"family":"Lybarger","given":"N.","email":"","affiliations":[{"id":24610,"text":"NCAR","active":true,"usgs":false}],"preferred":false,"id":883603,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - 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Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":883606,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Brakebill, John 0000-0001-9235-6810","orcid":"https://orcid.org/0000-0001-9235-6810","contributorId":211038,"corporation":false,"usgs":true,"family":"Brakebill","given":"John","email":"","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":883608,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Cline, Donald Walter 0009-0003-9161-9991","orcid":"https://orcid.org/0009-0003-9161-9991","contributorId":329914,"corporation":false,"usgs":true,"family":"Cline","given":"Donald","email":"","middleInitial":"Walter","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":883607,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Dunne, Krista A. 0000-0002-1220-6140 kadunne@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-6140","contributorId":203816,"corporation":false,"usgs":true,"family":"Dunne","given":"Krista","email":"kadunne@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":883609,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Rasmussen, K.","contributorId":329918,"corporation":false,"usgs":false,"family":"Rasmussen","given":"K.","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":883610,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Miguez-Macho, G.","contributorId":329921,"corporation":false,"usgs":false,"family":"Miguez-Macho","given":"G.","affiliations":[{"id":78737,"text":"U. de Santiago de Compestelo, Spain","active":true,"usgs":false}],"preferred":false,"id":883611,"contributorType":{"id":1,"text":"Authors"},"rank":29}]}}
,{"id":70247424,"text":"70247424 - 2023 - Diving deeper into seep distribution along the Cascadia Convergent Margin, USA","interactions":[],"lastModifiedDate":"2023-08-24T10:58:55.814335","indexId":"70247424","displayToPublicDate":"2023-07-31T07:12:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Diving deeper into seep distribution along the Cascadia Convergent Margin, USA","docAbstract":"<div class=\"JournalAbstract\"><p>Previous margin-wide studies of methane seep distribution along the Cascadia Subduction Zone indicate peaks in seep density within the landward limit of the of gas hydrate stability zone (GHSZ; ≤500 m depth), suggesting a link between current ocean warming, acceleration of hydrate dissociated, and methane emissions. This inferred connection, however, may not account for regional geologic and/or structural complexities driving methane seepage. Expanding upon an existing seep database by adding new seeps data, we conducted statistical and spatial analyses to determine margin-wide distribution trends and offer a tectonic framework for understanding the tendency toward non-normality and spatial clustering. We then highlight the role of local-scale drivers of seep formation in addition to the first-order tectonic framework, using systematic geologic/geomorphic characterization of seep emission sites in southern Cascadia and case studies using meta-attribute analysis of seismic reflection data.. Seep distribution along the margin is non-random, but instead of clustering along the 500-m isobath, regions of high seep density occur in canyons and topographic highs. New findings from this study conclude that co-location of the outer arc high (OAH) and the landward limit of the GHSZ may explain high concentrations of seeps where deformation is the greatest and hydrates are unstable. Detailed analysis of the spatial relationships between seep sites and geologic-geomorphic features in southern Cascadia reveal a link between seeps and anticlines, with 52% of the seeps found in association with anticlines, 36% found at faults, 16% associated with canyons, and 11% at seafloor failure scarps. Given that a majority of anticlines are located along or seaward of the OAH in the actively deforming outer wedge, we suggest that the location of the OAH is a primary structural control on seep distribution. This scenario is supported by neural network analysis of multichannel seismic data revealing zones of probable fluid migration along vertical pipes, faults, and chimneys in the vicinity of active seep sites on anticlines. Determining linkages between seeps and submarine tectonic geomorphology is a crucial first step for understanding and forecasting the distribution of methane seepage, but also a necessity for evaluating causal relationships between ocean warming and gas-hydrate stability.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2023.1205211","usgsCitation":"Rudebusch, J.A., Prouty, N.G., Conrad, J.E., Watt, J., Kluesner, J., Hill, J.C., Miller, N.C., Watson, S.J., and Hillman, J., 2023, Diving deeper into seep distribution along the Cascadia Convergent Margin, USA: Frontiers in Earth Science, v. 11, 1205211, 16 p., https://doi.org/10.3389/feart.2023.1205211.","productDescription":"1205211, 16 p.","ipdsId":"IP-150730","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":442585,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2023.1205211","text":"Publisher Index Page"},{"id":435236,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J10NH5","text":"USGS data release","linkHelpText":"Geochemistry of authigenic carbonates from Cascadia Margin"},{"id":419541,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, Washington","otherGeospatial":"Cascadia convergent margin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -124.23767208597519,\n              39.615494532530164\n            ],\n            [\n              -122.9862852670795,\n              39.82206391967978\n            ],\n            [\n              -122.50710041731864,\n              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nprouty@usgs.gov","orcid":"https://orcid.org/0000-0002-8922-0688","contributorId":3350,"corporation":false,"usgs":true,"family":"Prouty","given":"Nancy","email":"nprouty@usgs.gov","middleInitial":"G.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":879559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conrad, James E. 0000-0001-6655-694X jconrad@usgs.gov","orcid":"https://orcid.org/0000-0001-6655-694X","contributorId":2316,"corporation":false,"usgs":true,"family":"Conrad","given":"James","email":"jconrad@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":879560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Watt, Janet 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Box 30368, Lower Hutt, Wellington 5040, Aotearoa/New Zealand","active":true,"usgs":false}],"preferred":false,"id":879566,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70247421,"text":"70247421 - 2023 - Waterfowl show spatiotemporal trends in influenza A H5 and H7 infections but limited taxonomic variation","interactions":[],"lastModifiedDate":"2023-10-11T15:42:10.924708","indexId":"70247421","displayToPublicDate":"2023-07-31T07:04:42","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Waterfowl show spatiotemporal trends in influenza A H5 and H7 infections but limited taxonomic variation","docAbstract":"<p>Influenza A viruses in wild birds pose threats to the poultry industry, wild birds, and human health under certain conditions. Of particular importance are wild waterfowl, which are the primary reservoir of low pathogenicity influenza viruses that ultimately cause high pathogenicity outbreaks in poultry farms. Despite much work on the drivers of influenza A virus prevalence, the underlying viral subtype dynamics are still mostly unexplored. Nevertheless, understanding these dynamics, particularly for the agriculturally significant H5 and H7 subtypes, is important for mitigating the risk of outbreaks in domestic poultry farms. Here, using an expansive surveillance database, we take a large-scale look at the spatial, temporal, and taxonomic drivers in the prevalence of these two subtypes among influenza A positive wild waterfowl. We document spatiotemporal trends that are consistent with past work, particularly an uptick in H5 viruses in late autumn and H7 viruses in spring. Interestingly, despite large species differences in temporal trends in overall influenza A virus prevalence, we document only modest differences in the relative abundance of these two subtypes and little, if any, temporal differences among species. As such, it appears that differences in species' phenology, physiology, and behaviors that influence overall susceptibility to influenza A viruses play a much lesser role in relative susceptibility to different subtypes. Instead, species likely freely pass viruses among each other regardless of subtype. Importantly, despite the similarities among species documented here, individual species still may play important roles in moving viruses across large geographic areas or sustaining local outbreaks through their different migratory behaviors.</p>","language":"English","publisher":"Wiley","doi":"10.1002/eap.2906","usgsCitation":"Kent, C.M., Bevins, S.N., Mullinax, J.M., Sullivan, J.D., and Prosser, D., 2023, Waterfowl show spatiotemporal trends in influenza A H5 and H7 infections but limited taxonomic variation: Ecological Applications, v. 33, no. 7, e2906, 11 p., https://doi.org/10.1002/eap.2906.","productDescription":"e2906, 11 p.","ipdsId":"IP-147544","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":442588,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/eap.2906","text":"Publisher Index Page"},{"id":435237,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K4ARTI","text":"USGS data release","linkHelpText":"Predicted H5 and H7 subtype Avian Influenza Prevalence for Wild Waterfowl Species Across the Continental United States"},{"id":419539,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"7","noUsgsAuthors":false,"publicationDate":"2023-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Kent, Cody M.","contributorId":265823,"corporation":false,"usgs":false,"family":"Kent","given":"Cody","email":"","middleInitial":"M.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":879543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bevins, Sarah N.","contributorId":212845,"corporation":false,"usgs":false,"family":"Bevins","given":"Sarah","email":"","middleInitial":"N.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":879544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullinax, Jennifer M.","contributorId":221170,"corporation":false,"usgs":false,"family":"Mullinax","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":879545,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":879546,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Prosser, Diann 0000-0002-5251-1799","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":217931,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":879547,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70247392,"text":"70247392 - 2023 - Ten best practices for effective phenological research","interactions":[],"lastModifiedDate":"2023-09-20T16:21:32.476662","indexId":"70247392","displayToPublicDate":"2023-07-29T10:00:24","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2031,"text":"International Journal of Biometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Ten best practices for effective phenological research","docAbstract":"<p><span>The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project’s needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s00484-023-02502-7","usgsCitation":"Primack, R., Gallinat, A., Ellwood, E.R., Crimmins, T., Schwartz, M., Staudinger, M., and Miller-Rushing, A., 2023, Ten best practices for effective phenological research: International Journal of Biometeorology, v. 67, p. 1509-1522, https://doi.org/10.1007/s00484-023-02502-7.","productDescription":"14 p.","startPage":"1509","endPage":"1522","ipdsId":"IP-137838","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":442599,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00484-023-02502-7","text":"Publisher Index Page"},{"id":419502,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"67","noUsgsAuthors":false,"publicationDate":"2023-07-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Primack, Richard","contributorId":317841,"corporation":false,"usgs":false,"family":"Primack","given":"Richard","email":"","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":879436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallinat, Amanda S.","contributorId":317842,"corporation":false,"usgs":false,"family":"Gallinat","given":"Amanda S.","affiliations":[],"preferred":false,"id":879437,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellwood, Elizabeth R.","contributorId":317843,"corporation":false,"usgs":false,"family":"Ellwood","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":879438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crimmins, Theresa M.","contributorId":317844,"corporation":false,"usgs":false,"family":"Crimmins","given":"Theresa M.","affiliations":[],"preferred":false,"id":879439,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwartz, Mark D.","contributorId":317845,"corporation":false,"usgs":false,"family":"Schwartz","given":"Mark D.","affiliations":[],"preferred":false,"id":879440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Staudinger, Michelle 0000-0002-4535-2005","orcid":"https://orcid.org/0000-0002-4535-2005","contributorId":215140,"corporation":false,"usgs":true,"family":"Staudinger","given":"Michelle","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":879441,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller-Rushing, Abraham J.","contributorId":317846,"corporation":false,"usgs":false,"family":"Miller-Rushing","given":"Abraham J.","affiliations":[],"preferred":false,"id":879442,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70247915,"text":"70247915 - 2023 - Satellite tracking reveals use of Biscayne National Park by sea turtles tagged in multiple locations","interactions":[],"lastModifiedDate":"2023-08-29T15:21:22.255682","indexId":"70247915","displayToPublicDate":"2023-07-29T07:23:48","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5094,"text":"Regional Studies in Marine Science","onlineIssn":"2352-4855","active":true,"publicationSubtype":{"id":10}},"title":"Satellite tracking reveals use of Biscayne National Park by sea turtles tagged in multiple locations","docAbstract":"<p><span>Although historical observations date back to the 1800’s, there is little information on&nbsp;sea turtle&nbsp;occupancy within Biscayne National Park (BNP). The park is located along the Florida&nbsp;reef&nbsp;tract and is dominated by the Gulfstream, which acts as a corridor for many marine animals. Here we used satellite&nbsp;telemetry&nbsp;to determine areas of use in BNP for two species of imperiled sea turtles, loggerhead (</span><span><i>Caretta caretta</i></span><span>) and green (</span><span><i>Chelonia mydas</i></span><span>) turtles. We included data for turtles tagged between 2009–2021 at sites both within park waters and in five locations outside the park boundary; individuals were captured both in the water and on land. We tagged 60 individuals (female, n&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>=</mo></math>\"><span class=\"MJX_Assistive_MathML\">=</span></span></span><span>&nbsp;48; male, n&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-2-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>=</mo></math>\"><span class=\"MJX_Assistive_MathML\">=</span></span></span><span>&nbsp;3; immature, n&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>=</mo></math>\"><span class=\"MJX_Assistive_MathML\">=</span></span></span><span>&nbsp;9); loggerheads (n&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-4-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>=</mo></math>\"><span class=\"MJX_Assistive_MathML\">=</span></span></span><span>&nbsp;33) ranged in size from 66.2 to 109.9&nbsp;cm CCL (curved&nbsp;carapace&nbsp;length) and green turtles (n&nbsp;</span><span class=\"math\"><span id=\"MathJax-Element-5-Frame\" class=\"MathJax_SVG\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo is=&quot;true&quot;>=</mo></math>\"><span class=\"MJX_Assistive_MathML\">=</span></span></span><span>&nbsp;27) ranged in size from 39.1 to 111.9&nbsp;cm CCL. We used behavioral switching state-space modeling (SSM) to obtain daily predicted positions for each turtle, classified turtle behavior within the park as either foraging, migration, or both foraging and migration, and summarized high-use areas for each species across all months of the year. Turtles used park waters year-round, with concentrated use of deeper waters during&nbsp;seasonal migrations. Across all 60 turtles, 21 spent their tracking time foraging within BNP boundaries and 30 used the park as part of their migratory pathway; five turtles used the park for both foraging and migration, and the remaining four had SSM points very close to the park. Loggerhead migration occurred from February through November, whereas green turtle migration was concentrated in August. Both turtle species exhibited high overlap (i.e., usage) with&nbsp;seagrass&nbsp;habitat. These findings are relevant as managers consider strategies to minimize anthropogenic impacts to resident and migratory sea turtles using park waters.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rsma.2023.103098","usgsCitation":"Hart, K., Benscoter, A., Turner, H.M., Cherkiss, M., Crowder, A., Guzy, J.C., Roche, D., Sasso, C.R., Goodwin, G.D., and Burkholder, D.A., 2023, Satellite tracking reveals use of Biscayne National Park by sea turtles tagged in multiple locations: Regional Studies in Marine Science, v. 65, 103098, 9 p. Data Release, https://doi.org/10.1016/j.rsma.2023.103098.","productDescription":"103098, 9 p. Data Release","ipdsId":"IP-148875","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442603,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rsma.2023.103098","text":"Publisher Index Page"},{"id":420246,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KDAM0N","linkFileType":{"id":5,"text":"html"}},{"id":420113,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Biscayne National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -80.40612048281238,\n              25.67318683377998\n            ],\n            [\n              -80.40612048281238,\n              25.217035566727816\n            ],\n            [\n              -80.08079009602143,\n              25.217035566727816\n            ],\n            [\n              -80.08079009602143,\n              25.67318683377998\n            ],\n            [\n              -80.40612048281238,\n              25.67318683377998\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"65","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":220333,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benscoter, Allison 0000-0003-4205-3808","orcid":"https://orcid.org/0000-0003-4205-3808","contributorId":216194,"corporation":false,"usgs":true,"family":"Benscoter","given":"Allison","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880987,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turner, Haley M. 0000-0002-5578-5939","orcid":"https://orcid.org/0000-0002-5578-5939","contributorId":316772,"corporation":false,"usgs":false,"family":"Turner","given":"Haley","email":"","middleInitial":"M.","affiliations":[{"id":68691,"text":"Wetland and Aquatic Research Center","active":true,"usgs":false}],"preferred":false,"id":880988,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":222180,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880989,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crowder, Andrew 0000-0001-6978-6265","orcid":"https://orcid.org/0000-0001-6978-6265","contributorId":218467,"corporation":false,"usgs":true,"family":"Crowder","given":"Andrew","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880990,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Guzy, Jacquelyn C. 0000-0003-2648-398X","orcid":"https://orcid.org/0000-0003-2648-398X","contributorId":288520,"corporation":false,"usgs":true,"family":"Guzy","given":"Jacquelyn","email":"","middleInitial":"C.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880991,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roche, David 0000-0002-3329-2746 droche@usgs.gov","orcid":"https://orcid.org/0000-0002-3329-2746","contributorId":204332,"corporation":false,"usgs":true,"family":"Roche","given":"David","email":"droche@usgs.gov","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":880992,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sasso, Christopher R.","contributorId":296894,"corporation":false,"usgs":false,"family":"Sasso","given":"Christopher","email":"","middleInitial":"R.","affiliations":[{"id":64230,"text":"NOAA-NMFS Southwest Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":880993,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Goodwin, Glenn D. 0000-0001-6802-9924","orcid":"https://orcid.org/0000-0001-6802-9924","contributorId":316773,"corporation":false,"usgs":false,"family":"Goodwin","given":"Glenn","email":"","middleInitial":"D.","affiliations":[{"id":13165,"text":"Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":880994,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Burkholder, Derek A. 0000-0001-6315-6932","orcid":"https://orcid.org/0000-0001-6315-6932","contributorId":289783,"corporation":false,"usgs":false,"family":"Burkholder","given":"Derek","email":"","middleInitial":"A.","affiliations":[{"id":62249,"text":"Halmos College of Natural Sciences and Oceanography, Department of Marine and Environmental Science, Nova Southeastern University","active":true,"usgs":false}],"preferred":false,"id":880995,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70247434,"text":"70247434 - 2023 - Estuarine salinity extremes: Using the Coastal Salinity Index to quantify the role of droughts, floods, hurricanes, and freshwater flow alteration","interactions":[],"lastModifiedDate":"2023-08-07T14:14:35.740737","indexId":"70247434","displayToPublicDate":"2023-07-28T09:07:52","publicationYear":"2023","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1587,"text":"Estuarine, Coastal and Shelf Science","active":true,"publicationSubtype":{"id":10}},"title":"Estuarine salinity extremes: Using the Coastal Salinity Index to quantify the role of droughts, floods, hurricanes, and freshwater flow alteration","docAbstract":"<p><span>In the face of accelerating climate change, advancing understanding of how extreme climatic events influence estuarine&nbsp;salinities&nbsp;can help to inform resource management. Extreme salinities driven by droughts, hurricanes, floods, and freshwater flow alterations can lead to ecological transformations in&nbsp;estuarine ecosystems. Here, we applied the Coastal Salinity Index (CSI; Conrads and Darby 2017) to 22 years (1998–2020) of salinity data in a Louisiana&nbsp;estuary&nbsp;(Barataria Estuary, USA) to elucidate the impacts of extreme events on estuarine salinities. The CSI is an index to quantify salinity patterns at a specific location through long-term averages and deviations from historical average conditions. We calculated and compared CSI values for four stations distributed along an estuarine salinity gradient. We identified 10 events between 1998 and 2020 that produced extreme salinities, including two droughts, four hurricanes, three floods, and one freshwater diversion. The droughts of 2000 and 2006 caused surface&nbsp;</span>water salinities<span>&nbsp;to increase substantially throughout the estuary. The effects of hurricanes were highly variable, with some storms leading to elevated salinities throughout the entire estuary (e.g., Hurricanes Katrina and&nbsp;Rita&nbsp;in 2005), whereas other storms led to elevated salinities for some but not all stations (e.g., Hurricanes Gustav and Ike in 2008 or Hurricane Isaac in 2012). The opening of a freshwater river diversion in 2010 contributed to fresher conditions throughout the estuary and appeared to reduce or eliminate the increases in salinity that normally occur during the summer, although these effects were short-lived. Mississippi River floods in 2008, 2011, and 2019 reduced salinities throughout the estuary, but the effects were most pronounced in the lower estuary compared to the upper estuary. Collectively, our results advance understanding of the influence of extreme events on estuarine salinity regimes. Our analyses also highlight the value of the CSI for identifying periods with extreme salinities (i.e., extreme high or low salinities) via calculations that place salinity levels within and across estuaries within a historical context.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2023.108445","usgsCitation":"Feher, L., Osland, M., and Swarzenski, C., 2023, Estuarine salinity extremes: Using the Coastal Salinity Index to quantify the role of droughts, floods, hurricanes, and freshwater flow alteration: Estuarine, Coastal and Shelf Science, v. 291, 108445, 12 p., https://doi.org/10.1016/j.ecss.2023.108445.","productDescription":"108445, 12 p.","ipdsId":"IP-149499","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":442607,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecss.2023.108445","text":"Publisher Index Page"},{"id":419561,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Barataria Estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -90.75,\n              30\n            ],\n            [\n              -90.75,\n              29\n            ],\n            [\n              -89.5,\n              29\n            ],\n            [\n              -89.5,\n              30\n            ],\n            [\n              -90.75,\n              30\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"291","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Feher, Laura 0000-0002-5983-6190","orcid":"https://orcid.org/0000-0002-5983-6190","contributorId":221894,"corporation":false,"usgs":true,"family":"Feher","given":"Laura","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":879608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osland, Michael 0000-0001-9902-8692","orcid":"https://orcid.org/0000-0001-9902-8692","contributorId":222814,"corporation":false,"usgs":true,"family":"Osland","given":"Michael","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":879609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Christopher 0000-0001-9843-1471","orcid":"https://orcid.org/0000-0001-9843-1471","contributorId":300309,"corporation":false,"usgs":false,"family":"Swarzenski","given":"Christopher","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":879610,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70242866,"text":"sir20235004 - 2023 - Hydrogeologic framework of southwestern Louisiana","interactions":[],"lastModifiedDate":"2026-03-02T17:53:40.937008","indexId":"sir20235004","displayToPublicDate":"2023-07-28T08:29:03","publicationYear":"2023","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2023-5004","displayTitle":"Hydrogeologic Framework of Southwestern Louisiana","title":"Hydrogeologic framework of southwestern Louisiana","docAbstract":"<p class=\"Citation\">A hydrogeologic framework was constructed for the Coastal Lowlands aquifer system in southwestern Louisiana. Data from previous hydrogeologic and geologic studies were synthesized and expanded using 2,242 geophysical logs to map 4 hydrogeologic units: the Chicot aquifer system, Evangeline aquifer, Jasper aquifer system, and Catahoula aquifer. Raster surfaces were created for the base and thickness of each unit to provide a generalized framework that can be used for regional groundwater studies and as a foundation for additional or local refinement.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20235004","issn":"2328-0328","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development, Public Works and Water Resources Division","usgsCitation":"Lindaman, M.A., 2023, Hydrogeologic framework of southwestern Louisiana: U.S. Geological Survey Scientific Investigations Report 2023–5004, 31 p., https://doi.org/10.3133/sir20235004.","productDescription":"Report: viii, 31 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","ipdsId":"IP-122892","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":500684,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_115145.htm","linkFileType":{"id":5,"text":"html"}},{"id":416090,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OLQLPP","text":"USGS data release—Altitudes and thicknesses of hydrogeologic units of southwestern Louisiana"},{"id":418797,"rank":4,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20235004/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2023-5004 HTML"},{"id":416086,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2023/5004/sir20235004.pdf","text":"Report","size":"11.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2023-5004 pdf"},{"id":416085,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2023/5004/coverthb.jpg"},{"id":416087,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2023/5004/sir20235004.XML","linkFileType":{"id":8,"text":"xml"},"description":"SIR 2023-5004 XML"},{"id":416089,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2023/5004/images"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -93.8755523969756,\n              31.15178116509101\n            ],\n            [\n              -93.8755523969756,\n              29.54078056892797\n            ],\n            [\n              -91.89886143926024,\n              29.54078056892797\n            ],\n            [\n              -91.89886143926024,\n              31.15178116509101\n            ],\n            [\n              -93.8755523969756,\n              31.15178116509101\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","contact":"<p>Director, Lower Mississippi-Gulf Water Science Center <br>U.S. Geological Survey&nbsp;<br><span class=\"HQEo7\" role=\"link\" data-markjs=\"true\" data-mce-tabindex=\"0\">640 Grassmere Park, Suite 100 <br>Nashville, TN 37211</span>&nbsp;<br><a data-mce-href=\"https://www.usgs.gov/centers/lmg-water/\" href=\"https://www.usgs.gov/centers/lmg-water/\">https://www.usgs.gov/centers/lmg-water/</a></p><div class=\"elementToProof\"><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></div>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methodology</li><li>Characteristics of Hydrogeologic Units</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2023-07-28","noUsgsAuthors":false,"publicationDate":"2023-07-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Lindaman, Maxwell A. 0000-0003-1786-1272","orcid":"https://orcid.org/0000-0003-1786-1272","contributorId":219064,"corporation":false,"usgs":true,"family":"Lindaman","given":"Maxwell A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":870050,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
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