{"pageNumber":"466","pageRowStart":"11625","pageSize":"25","recordCount":184606,"records":[{"id":70223467,"text":"70223467 - 2021 - Rebounds, regresses, and recovery: A 15-year study of the coral reef community at Pila‘a, Kaua‘i after decades of natural and anthropogenic stress events","interactions":[],"lastModifiedDate":"2021-10-06T15:57:00.3995","indexId":"70223467","displayToPublicDate":"2021-08-26T08:29:51","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Rebounds, regresses, and recovery: A 15-year study of the coral reef community at Pila‘a, Kaua‘i after decades of natural and anthropogenic stress events","docAbstract":"<p><span>Pila‘a reef on the north shore of Kaua‘i, Hawai‘i was subjected to a major flood event in 2001 that deposited extensive sediment on the reef flat, resulting in high coral mortality. To document potential recovery, this study replicated benthic and sediment surveys conducted immediately following the event and 15 years later. Coral cores were analyzed to determine coral growth rates and density. Our results suggest that significant reduction in terrigenous sediments has led to partial ecosystem recovery based on coral species and colony increases, more balanced size frequency distributions, improved coral condition, and enhanced coral recruitment despite lack of recovery of large dead coral colonies. However, within this 15-year period, episodic storms and a bleaching event impeded the recovery process, preventing full recovery and continuously threatening the coral reef community. As climate change progresses, the intensity and frequency of these disturbances are predicted to increase.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2021.112306","usgsCitation":"Rodgers, K., Richards Dona, A., Stender, Y.O., Tsang, A.O., Han, J.H., Weible, R., Prouty, N.G., Storlazzi, C.D., and Graham, A.M., 2021, Rebounds, regresses, and recovery: A 15-year study of the coral reef community at Pila‘a, Kaua‘i after decades of natural and anthropogenic stress events: Marine Pollution Bulletin, v. 171, 112306, 16 p., https://doi.org/10.1016/j.marpolbul.2021.112306.","productDescription":"112306, 16 p.","ipdsId":"IP-098759","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451062,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpolbul.2021.112306","text":"Publisher Index Page"},{"id":388580,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kaua'i Island, Pila'a reef","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -159.58602905273438,\n              22.119357730123134\n            ],\n            [\n              -159.2523193359375,\n              22.119357730123134\n            ],\n            [\n              -159.2523193359375,\n              22.317683823893706\n            ],\n            [\n              -159.58602905273438,\n              22.317683823893706\n            ],\n            [\n              -159.58602905273438,\n              22.119357730123134\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"171","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rodgers, Ku'ulei S.","contributorId":131044,"corporation":false,"usgs":false,"family":"Rodgers","given":"Ku'ulei S.","affiliations":[{"id":7212,"text":"University of Hawai‘i, Hawai‘i Institute of Marine Biology","active":true,"usgs":false}],"preferred":false,"id":822105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richards Dona, A.","contributorId":264856,"corporation":false,"usgs":false,"family":"Richards Dona","given":"A.","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":822110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stender, Y. O.","contributorId":264855,"corporation":false,"usgs":false,"family":"Stender","given":"Y.","email":"","middleInitial":"O.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":822109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tsang, A. O.","contributorId":264854,"corporation":false,"usgs":false,"family":"Tsang","given":"A.","email":"","middleInitial":"O.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":822107,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Han, J. H. J.","contributorId":264853,"corporation":false,"usgs":false,"family":"Han","given":"J.","email":"","middleInitial":"H. J.","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":822106,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Weible, Rebecca","contributorId":264858,"corporation":false,"usgs":false,"family":"Weible","given":"Rebecca","email":"","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":822111,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prouty, Nancy G. 0000-0002-8922-0688 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":822108,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":822127,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Graham, Andrew M.","contributorId":178896,"corporation":false,"usgs":false,"family":"Graham","given":"Andrew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":822128,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70223401,"text":"ofr20211030J - 2021 - System characterization report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A)","interactions":[{"subject":{"id":70223401,"text":"ofr20211030J - 2021 - System characterization report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A)","indexId":"ofr20211030J","publicationYear":"2021","noYear":false,"chapter":"J","displayTitle":"System Characterization Report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A)","title":"System characterization report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A)"},"predicate":"IS_PART_OF","object":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"id":1}],"isPartOf":{"id":70221266,"text":"ofr20211030 - 2021 - System characterization of Earth observation sensors","indexId":"ofr20211030","publicationYear":"2021","noYear":false,"title":"System characterization of Earth observation sensors"},"lastModifiedDate":"2024-11-06T15:36:02.779518","indexId":"ofr20211030J","displayToPublicDate":"2021-08-26T08:13:17","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1030","chapter":"J","displayTitle":"System Characterization Report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A)","title":"System characterization report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A)","docAbstract":"<h1>Executive Summary</h1><p>This report addresses system characterization of the China-Brazil Earth Resources Satellite-4A (CBERS–4A) multispectral remote sensing satellite and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2021. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.</p><p>CBERS–4A is a joint Chinese-Brazilian medium-resolution satellite launched in December 2019 by the China National Space Agency/National Institute for Space Research (Brazil) on a Chang Zheng 4B rocket from the Taiyuan Satellite Launch Center for Earth resources monitoring. The CBERS–4A mission continues the CBERS mission that has been in continual operation since the launch of CBERS–1 in 1999.</p><p>The CBERS–4A satellite was designed and built by Academia Chinesa de Tecnologia Espacial/National Institute for Space Research and uses the Phoenix-Eye bus. CBERS–4A carries the multispectral camera and wide field imager sensors for medium-resolution land imaging and the wide swath panchromatic and multispectral camera sensor for high-resolution land imaging. This assessment focused on the multispectral camera sensor only. More information on CBERS sensors is available in the “<a data-mce-href=\"https://doi.org/10.3133/cir1468\" href=\"https://doi.org/10.3133/cir1468\" target=\"_blank\" rel=\"noopener\">2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium</a>” and at <a href=\"https://www.gov.br/pt-br/servicos/obter-imagens-de-sensoriamento-remoto-da-terra-geradas-pelo-satelite-cbers-04a\" data-mce-href=\"https://www.gov.br/pt-br/servicos/obter-imagens-de-sensoriamento-remoto-da-terra-geradas-pelo-satelite-cbers-04a\">https://www.gov.br/pt-br/servicos/obter-imagens-de-sensoriamento-remoto-da-terra-geradas-pelo-satelite-cbers-04a</a>.</p><p>The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that CBERS–4A provides an interior (band-to-band) geometric performance in the range of −0.02 to −0.16 pixel; an exterior geometric accuracy performance of −22.02 (−1.47 pixels) to −16.06 meters (−1.07 pixels); a radiometric accuracy performance of –0.006 to 0.925 (offset and slope); and a spatial performance for relative edge response in the range of 0.39 to 0.44, for full width at half maximum in the range of 2.38 to 2.56 pixels, and for a modulation transfer function at a Nyquist frequency in the range of 0.001 to 0.013.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030J","usgsCitation":"Vrabel, J.C., Stensaas, G.L., Anderson, C., Christopherson, J., Kim, M., Park, S., and Cantrell, S., 2021, System characterization report on the China-Brazil Earth Resources Satellite-4A (CBERS–4A), chap. J <i>of</i> Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 35 p., https://doi.org/10.3133/ofr20211030J.","productDescription":"v, 35 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-130782","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":388510,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/j/ofr20211030j.pdf","text":"Report","size":"12.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030J"},{"id":388509,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/j/coverthb.jpg"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/eros\" data-mce-href=\"https://www.usgs.gov/centers/eros\">Earth Resources Observation and Science Center</a> <br>U.S. Geological Survey<br>47914 252nd Street <br>Sioux Falls, SD 57198</p><p><a href=\"../contact\" data-mce-href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>System Description</li><li>Procedures</li><li>Measurements</li><li>Analysis</li><li>Summary and Conclusions</li><li>Selected References</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2021-08-26","noUsgsAuthors":false,"publicationDate":"2021-08-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Vrabel, James C. 0000-0002-0120-4721","orcid":"https://orcid.org/0000-0002-0120-4721","contributorId":264751,"corporation":false,"usgs":false,"family":"Vrabel","given":"James C.","affiliations":[{"id":27608,"text":"Contractor to the USGS","active":true,"usgs":false}],"preferred":false,"id":821947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stensaas, Gregory L. 0000-0001-6679-2416 stensaas@usgs.gov","orcid":"https://orcid.org/0000-0001-6679-2416","contributorId":2551,"corporation":false,"usgs":true,"family":"Stensaas","given":"Gregory","email":"stensaas@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":821948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Cody 0000-0001-5612-1889 chanderson@usgs.gov","orcid":"https://orcid.org/0000-0001-5612-1889","contributorId":195521,"corporation":false,"usgs":true,"family":"Anderson","given":"Cody","email":"chanderson@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":821949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Christopherson, Jon 0000-0002-2472-0059 jonchris@usgs.gov","orcid":"https://orcid.org/0000-0002-2472-0059","contributorId":2552,"corporation":false,"usgs":true,"family":"Christopherson","given":"Jon","email":"jonchris@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":821950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kim, Minsu 0000-0003-4472-0926 minsukim@contractor.usgs.gov","orcid":"https://orcid.org/0000-0003-4472-0926","contributorId":216429,"corporation":false,"usgs":true,"family":"Kim","given":"Minsu","email":"minsukim@contractor.usgs.gov","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":821951,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Park, Seonkyung 0000-0003-3203-1998","orcid":"https://orcid.org/0000-0003-3203-1998","contributorId":223182,"corporation":false,"usgs":true,"family":"Park","given":"Seonkyung","email":"","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":821952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cantrell, Simon J. 0000-0001-6909-1973","orcid":"https://orcid.org/0000-0001-6909-1973","contributorId":259304,"corporation":false,"usgs":false,"family":"Cantrell","given":"Simon J.","affiliations":[{"id":54490,"text":"KBR, Inc., under contract to USGS","active":true,"usgs":false}],"preferred":true,"id":821953,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70224746,"text":"70224746 - 2021 - Editorial special issue natural capital accounting: The content, the context, and the framework","interactions":[],"lastModifiedDate":"2021-10-04T12:50:14.000494","indexId":"70224746","displayToPublicDate":"2021-08-26T07:48:15","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Editorial special issue natural capital accounting: The content, the context, and the framework","docAbstract":"<p>No abstract available.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2021.101347","usgsCitation":"La Notte, A., Vallecillo, S., Maes, J., Shapiro, C.D., Bagstad, K.J., Carter Ingram, J., and Glynn, P.D., 2021, Editorial special issue natural capital accounting: The content, the context, and the framework: Ecosystem Services, v. 51, 101347, 3 p., https://doi.org/10.1016/j.ecoser.2021.101347.","productDescription":"101347, 3 p.","ipdsId":"IP-129040","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":390177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"La Notte, Alessandra 0000-0001-6951-709X","orcid":"https://orcid.org/0000-0001-6951-709X","contributorId":266187,"corporation":false,"usgs":false,"family":"La Notte","given":"Alessandra","email":"","affiliations":[{"id":54942,"text":"Joint Research Centre","active":true,"usgs":false}],"preferred":false,"id":824538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vallecillo, Sara 0000-0002-5105-6253","orcid":"https://orcid.org/0000-0002-5105-6253","contributorId":266188,"corporation":false,"usgs":false,"family":"Vallecillo","given":"Sara","email":"","affiliations":[{"id":54942,"text":"Joint Research Centre","active":true,"usgs":false}],"preferred":false,"id":824539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maes, Joachim","contributorId":190801,"corporation":false,"usgs":false,"family":"Maes","given":"Joachim","email":"","affiliations":[],"preferred":false,"id":824540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shapiro, Carl D. 0000-0002-9868-7896 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-9868-7896","contributorId":211863,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":824541,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":824542,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Carter Ingram, Jane 0000-0002-9710-4935","orcid":"https://orcid.org/0000-0002-9710-4935","contributorId":266189,"corporation":false,"usgs":false,"family":"Carter Ingram","given":"Jane","email":"","affiliations":[{"id":54943,"text":"Pollination Group","active":true,"usgs":false}],"preferred":false,"id":824543,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":824544,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70223356,"text":"ofr20211069 - 2021 - Changes in forest connectivity from beech bark disease in Pictured Rocks National Lakeshore in the Upper Peninsula of Michigan","interactions":[],"lastModifiedDate":"2021-08-26T14:23:27.409191","indexId":"ofr20211069","displayToPublicDate":"2021-08-25T16:00:16","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1069","displayTitle":"Changes in Forest Connectivity from Beech Bark Disease in Pictured Rocks National Lakeshore in the Upper Peninsula of Michigan","title":"Changes in forest connectivity from beech bark disease in Pictured Rocks National Lakeshore in the Upper Peninsula of Michigan","docAbstract":"<p>Within the forests of Pictured Rocks National Lakeshore, biologists are trying to understand the effects beech bark disease has on wildlife species, especially species that need forest connectivity to thrive. This project used aerial imagery collected in 2005, shortly after beech bark disease infestation, and satellite imagery from 2018. The 2018 imagery represents present day conditions and was used to locate forest canopy gaps through object-based image analysis. Forest canopy gaps were identified using the multiresolution segmentation algorithm within Trimble’s eCognition software. A time change analysis was completed to understand how the forest canopy had changed from 2005 to 2018. The analysis showed areas that had maintained forest canopy, maintained a forest canopy gap, created a new canopy gap (closed forest canopy in 2005 but open canopy gap in 2018), or created new forest canopy (open canopy gap in 2005 but closed forest canopy in 2018). There were 9,127 acres of forest canopy lost, and 72.8 percent of that lost canopy occurred in a forest type where Fagus grandifolia Ehrh. (American beech) is a common tree species. The datasets developed through this project can enhance knowledge of where canopy gaps exist and help place focus on certain areas for wildlife studies. In addition, these datasets can be used in future studies to monitor the health of the forest and conduct additional change analyses.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211069","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Sattler, S.R., 2021, Changes in forest connectivity from beech bark disease in Pictured Rocks National Lakeshore in the Upper Peninsula of Michigan: U.S. Geological Survey Open-File Report 2021–1069, 12 p., https://doi.org/10.3133/ofr20211069.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-124452","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":388432,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1069/images"},{"id":388429,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1069/coverthb.jpg"},{"id":388430,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1069/ofr20211069.pdf","text":"Report","size":"6.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1069"},{"id":388431,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EZEAYD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Effects of beech bark disease on forest connectivity in Pictured Rocks National Lakeshore from 2005 to 2018"}],"country":"United States","state":"Michigan","otherGeospatial":"Pictures Rocks National Lakeshore","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -86.62307739257812,\n              46.42176587242696\n            ],\n            [\n              -86.4349365234375,\n              46.45961954102543\n            ],\n            [\n              -86.20147705078125,\n              46.57585481240773\n            ],\n            [\n              -86.02706909179688,\n              46.619261036171515\n            ],\n            [\n              -86.00509643554686,\n              46.669229446893404\n            ],\n            [\n              -86.08612060546875,\n              46.66545985627255\n            ],\n            [\n              -86.14105224609375,\n              46.677710064644344\n            ],\n            [\n              -86.4459228515625,\n              46.557916007595786\n            ],\n            [\n              -86.48712158203125,\n              46.55602736725248\n            ],\n            [\n              -86.6217041015625,\n              46.44826620185314\n            ],\n            [\n              -86.62307739257812,\n              46.42176587242696\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a data-mce-href=\"https://www.usgs.gov/centers/umesc\" href=\"https://www.usgs.gov/centers/umesc\">Upper Midwest Environmental Sciences Center</a> <br>U.S. Geological Survey <br>2630 Fanta Reed Road <br>La Crosse, WI 54603</p><p><a data-mce-href=\"../contact\" href=\"../contact\">Contact Pubs Warehouse</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Study Area</li><li>Methods</li><li>Discussion and Conclusions</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"publishedDate":"2021-08-25","noUsgsAuthors":false,"publicationDate":"2021-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Sattler, Stephanie R. 0000-0003-4417-2480 ssattler@usgs.gov","orcid":"https://orcid.org/0000-0003-4417-2480","contributorId":152030,"corporation":false,"usgs":true,"family":"Sattler","given":"Stephanie","email":"ssattler@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":821850,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70263638,"text":"70263638 - 2021 - When Punjab cried wolf: How a rumor triggered an “earthquake” in India","interactions":[],"lastModifiedDate":"2025-02-19T16:57:33.611474","indexId":"70263638","displayToPublicDate":"2021-08-25T10:53:22","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"When Punjab cried wolf: How a rumor triggered an “earthquake” in India","docAbstract":"<p><span>In recent years, earthquake felt reports contributed via online systems have provided increasingly valuable sources of data to characterize earthquakes and their effects. Contributed felt reports are accompanied by increases in website traffic, which are themselves potentially useful for the early detection of seismic events. In February 2017 the European‐Mediterranean Seismic Centre detected an unusual surge in traffic from the Punjab region in northwestern India, although no nearby seismic event was detected instrumentally. Had crowdsourcing detected a felt earthquake that instruments had missed? Or did Punjab cry wolf? In this Earthquake Lites report, we describe the sleuthing endeavor undertaken to find an answer.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"https://doi.org/10.1785/0220210130","usgsCitation":"Martin, S., Bossu, R., Steed, R., Landes, M., Srinagesh, D., Srinivas, D., and Hough, S.E., 2021, When Punjab cried wolf: How a rumor triggered an “earthquake” in India: Seismological Research Letters, v. 92, no. 6, p. 3887-3898, https://doi.org/https://doi.org/10.1785/0220210130.","productDescription":"12 p.","startPage":"3887","endPage":"3898","ipdsId":"IP-130668","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":482227,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"India","otherGeospatial":"Punjab","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              72.75,\n              32.15\n            ],\n            [\n              72.75,\n              28\n            ],\n            [\n              78,\n              28\n            ],\n            [\n              78,\n              32.15\n            ],\n            [\n              72.75,\n              32.15\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"92","issue":"6","noUsgsAuthors":false,"publicationDate":"2021-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Martin, S.S.","contributorId":350980,"corporation":false,"usgs":false,"family":"Martin","given":"S.S.","affiliations":[{"id":16807,"text":"Australian National University","active":true,"usgs":false}],"preferred":false,"id":927631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bossu, Remy","contributorId":198780,"corporation":false,"usgs":false,"family":"Bossu","given":"Remy","email":"","affiliations":[],"preferred":false,"id":927632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Steed, R.","contributorId":350981,"corporation":false,"usgs":false,"family":"Steed","given":"R.","affiliations":[{"id":35319,"text":"EMSC","active":true,"usgs":false}],"preferred":false,"id":927633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Landes, Matthieu","contributorId":198781,"corporation":false,"usgs":false,"family":"Landes","given":"Matthieu","email":"","affiliations":[],"preferred":false,"id":927634,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Srinagesh, D.","contributorId":18631,"corporation":false,"usgs":true,"family":"Srinagesh","given":"D.","email":"","affiliations":[],"preferred":false,"id":927635,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Srinivas, D.","contributorId":350983,"corporation":false,"usgs":false,"family":"Srinivas","given":"D.","affiliations":[{"id":83893,"text":"NGRI, Hyderabad","active":true,"usgs":false}],"preferred":false,"id":927636,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927637,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70223424,"text":"70223424 - 2021 - Coalescent methods reconstruct contributions of natural colonization and stocking to origins of Michigan inland Cisco (Coregonus artedi)","interactions":[],"lastModifiedDate":"2022-01-07T15:57:22.646685","indexId":"70223424","displayToPublicDate":"2021-08-25T10:21:11","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Coalescent methods reconstruct contributions of natural colonization and stocking to origins of Michigan inland Cisco (<i>Coregonus artedi</i>)","title":"Coalescent methods reconstruct contributions of natural colonization and stocking to origins of Michigan inland Cisco (Coregonus artedi)","docAbstract":"<p><span>Fish population structure in previously glaciated regions is often influenced by natural colonization processes and human-mediated dispersal, including fish stocking. Endemic populations are of conservation interest because they may contain rare and unique genetic variation. While coregonines are native to certain Michigan inland lakes, some were stocked with fish from Great Lakes sources, calling into question the origin of extant populations. While most stocking targeted lake whitefish (</span><i>Coregonus clupeaformis</i><span>), cisco (</span><i>C. artedi</i><span>) were also stocked from the Great Lakes to inland waterbodies. We used&nbsp;population genetic&nbsp;data (microsatellite genotypes and mitochondrial (mt)DNA sequences), coalescent modeling, and approximate Bayesian computation to investigate the origins of 12 inland Michigan cisco populations. The spatial distribution of mtDNA haplotypes suggests Michigan is an&nbsp;introgression&nbsp;zone for two ancestral cisco lineages associated with separate glacial&nbsp;refugia. Low levels of genetic diversity and high levels of genetic divergence were observed for populations located well inland of the Great Lakes relative to populations occupying waterbodies near the Great Lakes. Estimates of recent Great Lakes gene flow ranged from 27 to 48% for populations near the Great Lakes&nbsp;shoreline&nbsp;but were substantially lower (under 8%) for populations further inland. Inland lakes with elevated recent gene flow estimates may have been recipients of stocked coregonine fry, including cisco. Low levels of genetic diversity paired with a high likelihood of&nbsp;endemism&nbsp;as indicated by strong genetic divergence and low Great Lakes population inputs suggest the analyzed cisco populations occupying southern Michigan kettle lakes are of elevated conservation interest.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2021.08.008","usgsCitation":"Homola, J.J., Robinson, J.D., Kanefsky, J., Stott, W., Whelan, G., and Scribner, K.T., 2021, Coalescent methods reconstruct contributions of natural colonization and stocking to origins of Michigan inland Cisco (Coregonus artedi): Journal of Great Lakes Research, v. 47, no. 6, p. 1781-1792, https://doi.org/10.1016/j.jglr.2021.08.008.","productDescription":"12 p.","startPage":"1781","endPage":"1792","ipdsId":"IP-124168","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":388588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -88.505859375,\n              41.47566020027821\n            ],\n            [\n              -81.38671875,\n              41.47566020027821\n            ],\n            [\n              -81.38671875,\n              46.830133640447386\n            ],\n            [\n              -88.505859375,\n              46.830133640447386\n            ],\n            [\n              -88.505859375,\n              41.47566020027821\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"47","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Homola, Jared J.","contributorId":264547,"corporation":false,"usgs":false,"family":"Homola","given":"Jared","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":822012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, John D","contributorId":264810,"corporation":false,"usgs":false,"family":"Robinson","given":"John","email":"","middleInitial":"D","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":822013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kanefsky, Jeannette","contributorId":243198,"corporation":false,"usgs":false,"family":"Kanefsky","given":"Jeannette","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":822014,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stott, Wendylee 0000-0002-5252-4901 wstott@usgs.gov","orcid":"https://orcid.org/0000-0002-5252-4901","contributorId":191249,"corporation":false,"usgs":true,"family":"Stott","given":"Wendylee","email":"wstott@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":822015,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Whelan, Gary","contributorId":146115,"corporation":false,"usgs":false,"family":"Whelan","given":"Gary","email":"","affiliations":[{"id":16584,"text":"Fisheries Division, Michigan Department of Natural Resources, P.O. Box 30446, Lansing, MI 48909","active":true,"usgs":false}],"preferred":false,"id":822016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scribner, Kim T","contributorId":264811,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim","email":"","middleInitial":"T","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":822017,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70223450,"text":"70223450 - 2021 - An experimental evaluation of the efficacy of imaging flow cytometry (FlowCam) for detecting invasive Dreissened and Corbiculid bivalve veligers","interactions":[],"lastModifiedDate":"2021-12-10T16:40:28.007302","indexId":"70223450","displayToPublicDate":"2021-08-25T10:16:39","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2592,"text":"Lake and Reservoir Management","active":true,"publicationSubtype":{"id":10}},"title":"An experimental evaluation of the efficacy of imaging flow cytometry (FlowCam) for detecting invasive Dreissened and Corbiculid bivalve veligers","docAbstract":"<p><span>Zebra (</span><i>Dreissena polymorpha</i><span>) and quagga (</span><i>D. bugensis</i><span>) mussels, first introduced from central Asia into the Great Lakes of North America in the late 1980s, have crossed the continental divide and more recently spread across western North America. At the same time, several new technologies have been developed for the early detection of dreissenids, including the FlowCam, a digital imaging-in-flow instrument, intended to detect dreissenid planktonic larvae (veligers). However, the efficacy of this technology has rarely been tested. We experimentally evaluated the FlowCam’s ability to capture identifiable images of quagga mussel veligers under 2 different types of conditions: (i) deionized water, and (ii) Columbia River Basin water (CRBW), including natural sediment and native plankton. We further evaluated the FlowCam’s ability to distinguish between dreissenid veligers and corbiculid veligers (Asian clam,&nbsp;</span><i>Corbicula fluminea</i><span>). We interpret our results to indicate that the FlowCam can consistently detect dreissenid veligers across a range of veliger densities. Moreover, the presence of other plankton and detritus only slightly affected dreissenid detection by the FlowCam. However, the orientation of individual bivalve veligers as they were imaged by the FlowCam precluded specific identification of a substantial proportion (24.8%) of veligers as either dreissenid or corbiculid. We suggest that the FlowCam is an important detection tool best utilized as part of a multifaceted approach, including traditional microscopy and possibly environmental DNA.</span></p>","language":"English","publisher":"Tayor and Francis Group","doi":"10.1080/10402381.2021.1961176","usgsCitation":"Hassett, W., Zimmerman, J., Rollwagen-Bollens, G., Bollens, S.M., and Counihan, T., 2021, An experimental evaluation of the efficacy of imaging flow cytometry (FlowCam) for detecting invasive Dreissened and Corbiculid bivalve veligers: Lake and Reservoir Management, v. 37, no. 4, p. 406-417, https://doi.org/10.1080/10402381.2021.1961176.","productDescription":"12 p.","startPage":"406","endPage":"417","ipdsId":"IP-073274","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":388587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"4","noUsgsAuthors":false,"publicationDate":"2021-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Hassett, Whitney","contributorId":190161,"corporation":false,"usgs":false,"family":"Hassett","given":"Whitney","email":"","affiliations":[],"preferred":false,"id":822048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Julie","contributorId":190163,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Julie","affiliations":[],"preferred":false,"id":822049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rollwagen-Bollens, Gretchen","contributorId":190162,"corporation":false,"usgs":false,"family":"Rollwagen-Bollens","given":"Gretchen","email":"","affiliations":[],"preferred":false,"id":822050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bollens, Stephen M. 0000-0001-9214-9037","orcid":"https://orcid.org/0000-0001-9214-9037","contributorId":148958,"corporation":false,"usgs":false,"family":"Bollens","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":822051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Counihan, Timothy D. 0000-0003-4967-6514","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":207532,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":822052,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70223676,"text":"70223676 - 2021 - Discrete sample introduction module for quantitative and isotopic analysis of methane and other gases by cavity ring-down spectroscopy","interactions":[],"lastModifiedDate":"2021-09-14T16:59:23.317558","indexId":"70223676","displayToPublicDate":"2021-08-25T08:18:12","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Discrete sample introduction module for quantitative and isotopic analysis of methane and other gases by cavity ring-down spectroscopy","docAbstract":"<div class=\"container container_scaled-down\"><div class=\"row\"><div class=\"col-xs-12\"><div id=\"abstractBox\" class=\"article_abstract-content hlFld-Abstract\"><p class=\"articleBody_abstractText\">Carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>) are natural and anthropogenic products that play a central role in the global carbon cycle and regulating Earth’s climate. Applications utilizing laser absorption spectroscopy, which continuously measure concentrations and stable isotope ratios of these greenhouse gases, are routinely employed to measure the source and magnitude of atmospheric inputs. We developed a discrete sample introduction module (DSIM) to enable measurements of methane and CO<sub>2</sub><span>&nbsp;</span>concentrations and δ<sup>13</sup>C values from limited volume (5–100 mL) gas samples when interfaced with a commercially available cavity ring-down spectroscopy (CRDS) analyzer. The analysis has a dynamic range that spans six orders of magnitude from 100% analyte to the lower limit of instrument detection (2 ppm). We demonstrate system performance for methane by comparing concentrations and δ<sup>13</sup>C results from the DSIM-CRDS system and traditional methods for a variety of sample types, including low concentration (nanomolar CH<sub>4</sub>) seawater and high concentration (&gt;90% CH<sub>4</sub>) natural gas. The expansive concentration range of the field-portable DSIM-CRDS system can measure enhances analytical performance for investigating methane and CO<sub>2</sub><span>&nbsp;</span>dynamics and, potentially, other gases measured by laser absorption spectroscopy.</p></div></div></div></div>","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.1c01386","usgsCitation":"Pohlman, J., Casso, M., Magen, C., and Bergeron, E., 2021, Discrete sample introduction module for quantitative and isotopic analysis of methane and other gases by cavity ring-down spectroscopy: Environmental Science & Technology, v. 55, no. 17, p. 12066-12074, https://doi.org/10.1021/acs.est.1c01386.","productDescription":"9 p.","startPage":"12066","endPage":"12074","ipdsId":"IP-130600","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451068,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.1c01386","text":"Publisher Index Page"},{"id":436224,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99B34V1","text":"USGS data release","linkHelpText":"Comparison of methane concentration and stable carbon isotope data for natural samples analyzed by discrete sample introduction module - cavity ring down spectroscopy (DSIM-CRDS) and traditional methods"},{"id":388724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"17","noUsgsAuthors":false,"publicationDate":"2021-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Pohlman, John 0000-0002-3563-4586","orcid":"https://orcid.org/0000-0002-3563-4586","contributorId":220804,"corporation":false,"usgs":true,"family":"Pohlman","given":"John","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":822288,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casso, Michael 0000-0002-6990-9090 mcasso@usgs.gov","orcid":"https://orcid.org/0000-0002-6990-9090","contributorId":2904,"corporation":false,"usgs":true,"family":"Casso","given":"Michael","email":"mcasso@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":822289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Magen, Cedric","contributorId":265132,"corporation":false,"usgs":false,"family":"Magen","given":"Cedric","email":"","affiliations":[{"id":54603,"text":"University of Maryland Center for Environmental Science, Chesapeake Biological Lab, Solomons MD","active":true,"usgs":false}],"preferred":false,"id":822290,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bergeron, Emile M. ebergeron@usgs.gov","contributorId":3449,"corporation":false,"usgs":true,"family":"Bergeron","given":"Emile M.","email":"ebergeron@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":822329,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70224289,"text":"70224289 - 2021 - Spatiotemporal dynamics of CO2 gas exchange from headwater mountain streams","interactions":[],"lastModifiedDate":"2021-09-20T12:49:53.852729","indexId":"70224289","displayToPublicDate":"2021-08-25T07:43:13","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal dynamics of CO2 gas exchange from headwater mountain streams","docAbstract":"<div class=\"article-section__content en main\"><p>Mountain streams play an important role in the global carbon cycle by transporting, metabolizing, and exchanging carbon they receive from the terrestrial environment. The rates at which these processes occur remain highly uncertain because of a paucity of observations and the difficulty of measuring gas exchange rates in steep, turbulent mountain streams. This uncertainty is compounded by large temporal and spatial variability in stream carbon dioxide (CO<sub>2</sub>) concentrations in mountain environments. In this study, we measured diel, seasonal, and annual variations in CO<sub>2</sub><span>&nbsp;</span>partial pressure (<i>p</i>CO<sub>2</sub>) in seven headwater streams and a groundwater spring in the Colorado Rocky Mountains to determine how CO<sub>2</sub><span>&nbsp;</span>exchange fluxes (<img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/6dcb36c7-fe40-41af-8c8e-768c11738d04/jgrg22024-math-0001.png\" alt=\"urn:x-wiley:21698953:media:jgrg22024:jgrg22024-math-0001\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/6dcb36c7-fe40-41af-8c8e-768c11738d04/jgrg22024-math-0001.png\">) vary with time, annual precipitation, and landscape characteristics. Our results show that temporal variability in<span>&nbsp;</span><i>p</i>CO<sub>2</sub><span>&nbsp;</span>and<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/e26eac8a-866e-4250-b5d1-dde6672d03d6/jgrg22024-math-0002.png\" alt=\"urn:x-wiley:21698953:media:jgrg22024:jgrg22024-math-0002\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/e26eac8a-866e-4250-b5d1-dde6672d03d6/jgrg22024-math-0002.png\"><span>&nbsp;</span>in mountain streams is large and is strongly influenced by solar radiation, the accumulation and melting of seasonal snowpacks, and interannual variations in precipitation. Spatial variations in<span>&nbsp;</span><i>p</i>CO<sub>2</sub><span>&nbsp;</span>and<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/c639387c-a043-4d5c-8b9f-0d845a0023aa/jgrg22024-math-0003.png\" alt=\"urn:x-wiley:21698953:media:jgrg22024:jgrg22024-math-0003\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/c639387c-a043-4d5c-8b9f-0d845a0023aa/jgrg22024-math-0003.png\"><span>&nbsp;</span>were related to landscape characteristics, with soil organic matter, wetlands, and likely groundwater discharge zones having a positive influence. Periglacial features, such as ice and rock glaciers, had a negative influence on stream<span>&nbsp;</span><i>p</i>CO<sub>2</sub><span>&nbsp;</span>and<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/dad80ea0-7b25-43fd-8520-9ddb3318d4da/jgrg22024-math-0004.png\" alt=\"urn:x-wiley:21698953:media:jgrg22024:jgrg22024-math-0004\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/dad80ea0-7b25-43fd-8520-9ddb3318d4da/jgrg22024-math-0004.png\">. Estimated<span>&nbsp;</span><img class=\"section_image\" src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/15dcd4a7-487a-4b6e-a9a4-c3bef5905bd3/jgrg22024-math-0005.png\" alt=\"urn:x-wiley:21698953:media:jgrg22024:jgrg22024-math-0005\" data-mce-src=\"https://agupubs.onlinelibrary.wiley.com/cms/asset/15dcd4a7-487a-4b6e-a9a4-c3bef5905bd3/jgrg22024-math-0005.png\"><span>&nbsp;</span>from streams in an alpine/subalpine region of Colorado was 3.4&nbsp;kg&nbsp;C&nbsp;m<sup>−2</sup>&nbsp;yr<sup>−1</sup><span>&nbsp;</span>normalized to stream surface area (95% CI: 2.1–5.0&nbsp;kg&nbsp;C&nbsp;m<sup>−2</sup>&nbsp;yr<sup>−1</sup>), consistent with recent work on CO<sub>2</sub><span>&nbsp;</span>exchange from mountain streams in the Swiss Alps. Our results highlight the importance of mountain streams as substantial contributors in the global carbon cycle.</p></div>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JG006509","usgsCitation":"Clow, D.W., Striegl, R.G., and Dornblaser, M., 2021, Spatiotemporal dynamics of CO2 gas exchange from headwater mountain streams: Journal of Geophysical Research: Biogeosciences, v. 126, no. 9, e2021JG006509, 18 p., https://doi.org/10.1029/2021JG006509.","productDescription":"e2021JG006509, 18 p.","ipdsId":"IP-118820","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":451070,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021jg006509","text":"Publisher Index Page"},{"id":436226,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S775Y4","text":"USGS data release","linkHelpText":"Continuous water-quality data for selected streams in Rocky Mountain National Park, Colorado, water years 2011-19 (ver. 2.0, January 2022)"},{"id":436225,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RNS5FP","text":"USGS data release","linkHelpText":"Continuous water-quality data for selected streams in Rocky Mountain National Park, Colorado, water years 2011-19"},{"id":389471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Loch Vale","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -105.74821472167969,\n              40.16418235037417\n            ],\n            [\n              -105.50102233886719,\n              40.16418235037417\n            ],\n            [\n              -105.50102233886719,\n              40.33660027347341\n            ],\n            [\n              -105.74821472167969,\n              40.33660027347341\n            ],\n            [\n              -105.74821472167969,\n              40.16418235037417\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"126","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-09-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":823465,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":823466,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dornblaser, Mark 0000-0002-6298-3757","orcid":"https://orcid.org/0000-0002-6298-3757","contributorId":220741,"corporation":false,"usgs":true,"family":"Dornblaser","given":"Mark","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":823467,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70231659,"text":"70231659 - 2021 - Mapping wetland burned area from Sentinel-2 across the southeastern United States and its contributions relative to Landsat 8 (2016-2019)","interactions":[],"lastModifiedDate":"2022-05-19T12:16:16.833966","indexId":"70231659","displayToPublicDate":"2021-08-25T07:13:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5678,"text":"Fire","active":true,"publicationSubtype":{"id":10}},"title":"Mapping wetland burned area from Sentinel-2 across the southeastern United States and its contributions relative to Landsat 8 (2016-2019)","docAbstract":"<div class=\"art-abstract in-tab hypothesis_container\">Prescribed fires and wildfires are common in wetland ecosystems across the Southeastern United States. However, the wetland burned area has been chronically underestimated across the region due to (1) spectral confusion between open water and burned area, (2) rapid post-fire vegetation regrowth, and (3) high annual precipitation limiting clear-sky satellite observations. We developed a machine learning algorithm specifically for burned area in wetlands, and applied the algorithm to the Sentinel-2 archive (2016–2019) across the Southeastern US (&gt;290,000 km<sup>2</sup>). Combining Landsat-8 imagery with Sentinel-2 increased the annual clear-sky observation count from 17 to 46 in 2016 and from 16 to 78 in 2019. When validated with WorldView imagery, the Sentinel-2 burned area had a 29% and 30% omission and commission rates of error for burned area, respectively, compared to the US Geological Survey Landsat-8 Burned Area Product (L8 BA), which had a 47% and 8% omission and commission rate of error, respectively. The Sentinel-2 algorithm and the L8 BA mapped burned area within 78% and 60% of wetland fire perimeters (<span class=\"html-italic\">n</span><span>&nbsp;</span>= 555) compiled from state and federal agencies, respectively. This analysis demonstrated the potential of Sentinel-2 to support efforts to track the burned area, especially across challenging ecosystem types, such as wetlands.<span id=\"_mce_caret\" data-mce-bogus=\"1\" data-mce-type=\"format-caret\"><span></span></span></div>","language":"English","publisher":"MDPI","doi":"10.3390/fire4030052","usgsCitation":"Vanderhoof, M.K., Hawbaker, T., Teske, C., Ku, A., Noble, J., and Picotte, J., 2021, Mapping wetland burned area from Sentinel-2 across the southeastern United States and its contributions relative to Landsat 8 (2016-2019): Fire, v. 4, no. 3, 52, 25 p., https://doi.org/10.3390/fire4030052.","productDescription":"52, 25 p.","ipdsId":"IP-127398","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":451071,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fire4030052","text":"Publisher Index Page"},{"id":436227,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9S8SLEM","text":"USGS data release","linkHelpText":"Wetland burned area extent derived from Sentinel-2 across the southeastern U.S. (2016-2019)"},{"id":400801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Montana, 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{\"name\":\"Florida\",\"nation\":\"USA  \"}}]}","volume":"4","issue":"3","noUsgsAuthors":false,"publicationDate":"2021-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":843283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":843284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teske, Casey","contributorId":224732,"corporation":false,"usgs":false,"family":"Teske","given":"Casey","email":"","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":843285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ku, Andrea","contributorId":291889,"corporation":false,"usgs":false,"family":"Ku","given":"Andrea","affiliations":[{"id":27232,"text":"Former USGS Student Contractor","active":true,"usgs":false}],"preferred":false,"id":843286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noble, Joe","contributorId":257938,"corporation":false,"usgs":false,"family":"Noble","given":"Joe","email":"","affiliations":[{"id":36874,"text":"Tall Timbers Research Station","active":true,"usgs":false}],"preferred":false,"id":843287,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Picotte, Joshua J. 0000-0002-4021-4623","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":202800,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":843288,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70249720,"text":"70249720 - 2021 - Exploring environmental factors that drive diel variations in tree water storage using wavelet analysis","interactions":[],"lastModifiedDate":"2023-10-25T11:59:54.29182","indexId":"70249720","displayToPublicDate":"2021-08-25T06:52:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7170,"text":"Frontiers in Water","active":true,"publicationSubtype":{"id":10}},"title":"Exploring environmental factors that drive diel variations in tree water storage using wavelet analysis","docAbstract":"<div class=\"JournalAbstract\"><p>Internal water storage within trees can be a critical reservoir that helps trees overcome both short- and long-duration environmental stresses. We monitored changes in internal tree water storage in a ponderosa pine on daily and seasonal scales using moisture probes, a dendrometer, and time-lapse electrical resistivity imaging (ERI). These data were used to investigate how patterns of in-tree water storage are affected by changes in sapflow rates, soil moisture, and meteorologic factors such as vapor pressure deficit. Measurements of xylem fluid electrical conductivity were constant in the early growing season while inverted sapwood electrical conductivity steadily increased, suggesting that increases in sapwood electrical conductivity did not result from an increase in xylem fluid electrical conductivity. Seasonal increases in stem electrical conductivity corresponded with seasonal increases in trunk diameter, suggesting that increased electrical conductivity may result from new growth. On the daily scale, changes in inverted sapwood electrical conductivity correspond to changes in sapwood moisture. Wavelet analyses indicated that lag times between inverted electrical conductivity and sapflow increased after storm events, suggesting that as soils wetted, reliance on internal water storage decreased, as did the time required to refill daily deficits in internal water storage. We found short time lags between sapflow and inverted electrical conductivity with dry conditions, when ponderosa pine are known to reduce stomatal conductance to avoid xylem cavitation. A decrease in diel amplitudes of inverted sapwood electrical conductivity during dry periods suggest that the ponderosa pine relied on internal water storage to supplement transpiration demands, but as drought conditions progressed, tree water storage contributions to transpiration decreased. Time-lapse ERI- and wavelet-analysis results highlight the important role internal tree water storage plays in supporting transpiration throughout a day and during periods of declining subsurface moisture.</p></div>","language":"English","publisher":"Frontiers","doi":"10.3389/frwa.2021.682285","usgsCitation":"Harmon, R., Barnard, H., Day-Lewis, F., Mao, D., and Singha, K., 2021, Exploring environmental factors that drive diel variations in tree water storage using wavelet analysis: Frontiers in Water, v. 3, 682285, 22 p., https://doi.org/10.3389/frwa.2021.682285.","productDescription":"682285, 22 p.","ipdsId":"IP-130437","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":451074,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/frwa.2021.682285","text":"Publisher Index Page"},{"id":422091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Gordon Gulch","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"coordinates\": [\n          [\n            [\n              -105.5213291829561,\n              40.029532063000204\n            ],\n            [\n              -105.5213291829561,\n              39.982722180293365\n            ],\n            [\n              -105.46742751059293,\n              39.982722180293365\n            ],\n            [\n              -105.46742751059293,\n              40.029532063000204\n            ],\n            [\n              -105.5213291829561,\n              40.029532063000204\n            ]\n          ]\n        ],\n        \"type\": \"Polygon\"\n      }\n    }\n  ]\n}","volume":"3","noUsgsAuthors":false,"publicationDate":"2021-08-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Harmon, Ryan","contributorId":331165,"corporation":false,"usgs":false,"family":"Harmon","given":"Ryan","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":886848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, Holly","contributorId":331166,"corporation":false,"usgs":false,"family":"Barnard","given":"Holly","affiliations":[{"id":36621,"text":"University of Colorado","active":true,"usgs":false}],"preferred":false,"id":886849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick 0000-0003-3526-886X","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":216359,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":886850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mao, Deqiang","contributorId":331169,"corporation":false,"usgs":false,"family":"Mao","given":"Deqiang","email":"","affiliations":[{"id":79141,"text":"Shandong University","active":true,"usgs":false}],"preferred":false,"id":886851,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singha, Kamini","contributorId":331170,"corporation":false,"usgs":false,"family":"Singha","given":"Kamini","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":886852,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70223331,"text":"sir20215072 - 2021 - Evaluation of actual evapotranspiration rates from the Operational Simplified Surface Energy Balance (SSEBop) model in Florida and parts of Alabama and Georgia, 2000–17","interactions":[],"lastModifiedDate":"2021-08-25T11:39:29.585628","indexId":"sir20215072","displayToPublicDate":"2021-08-24T14:28:01","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5072","displayTitle":"Evaluation of Actual Evapotranspiration Rates from the Operational Simplified Surface Energy Balance (SSEBop) Model in Florida and Parts of Alabama and Georgia, 2000–17","title":"Evaluation of actual evapotranspiration rates from the Operational Simplified Surface Energy Balance (SSEBop) model in Florida and parts of Alabama and Georgia, 2000–17","docAbstract":"<p>Evapotranspiration (ET) is the water-vapor flux transported from the surface of the Earth into the atmosphere and is the sum of surface water directly evaporated and subsurface water transpired by plants. ET rates are commonly estimated by using potential or reference ET, which might differ from actual ET rates. Actual evapotranspiration (ETa) rates can be estimated by using the Operational Simplified Surface Energy Balance (SSEBop) model. This report evaluates SSEBop ETa rates at the point and basin scales in Florida and parts of Alabama and Georgia for 2000–17. ETa rates computed by using data from 24 micrometeorological stations in Florida are referred to as mETa rates and were used to quantify biases in the SSEBop ETa rates, stratified by generalized land-use type. Bias was computed as mETa minus SSEBop ETa rates for given generalized land-use types, and bias-correction equations were computed by using least-squares regressions. In addition to mETa rates at station locations, annual average ETa rates calculated from the application of a water-balance method to 55 basins in Florida and parts of Alabama and Georgia were used to assess the accuracy of the annual SSEBop ETa rates at the basin scale. Another independent model used to simulate ETa rates was based on monthly reference ET from the statewide daily reference evapotranspiration (ETo) gridded dataset for Florida computed by using Geostationary Operational Environmental Satellite estimates of solar radiation (GOES ETo). ETa at grid points was computed as monthly GOES ETo multiplied by ratios of monthly mETa to GOES ETo, computed at micrometeorological stations and stratified by each generalized land-use type.</p><p>The coefficient of determination (R<sup>2</sup>) between monthly mETa and SSEBop ETa rates for all stations combined improved from 0.37 before bias correction of SSEBop ETa rates to 0.79 after the bias correction stratified by land-use type. For individual land-uses types, R<sup>2</sup> varied from 0.59 for the monthly mETa at a station in the land-use type forest to 0.82 for the monthly mETa at stations in the land-use type shallow-water-table pasture. Root-mean-square error (RMSE) was computed as a function of the difference between SSEBop ETa rates and mETa rates. RMSE of monthly SSEBop ETa rates was 1.27 inches per month before the bias corrections improved to 0.73 inch per month after the bias corrections. RMSE for bias-corrected annual SSEBop ETa rates based on micrometeorological stations with complete years of records ranged from 2.01 inches per year (in/yr) for the land-use type of agriculture to 5.73 in/yr for the land-use type of deep water-table pasture, or 4.96 and 21.21 percent errors relative to annual mETa rates, respectively. Bias-corrected annual SSEBop ETa rates were also compared to annual ETa rates computed by using a water-balance method (wbETa) for 55 basins in Florida. Differences in bias-corrected average annual SSEBop ETa rates and average annual wbETa rates for the 55 basins ranged from −3.67 to 5.29 in/yr (−9.24 to 17.36 percent). RMSE when computed as a function of the differences between annual SSEBop ETa rates and wbETa rates decreased, on average, from 4.13 in/yr for the uncorrected bias SSEBop ETa rates to 1.95 in/yr for the bias-corrected SSEBop rates. The average annual bias-corrected SSEBop ETa rates, from all basins, was 36.46 in/yr or 3.41 percent lower than the average annual wbETa rate of 37.79 inches.</p><p>Bias in SSEBop ETa rates varies based on time step (monthly versus annual), scale (point, basin, statewide), and land-use type. Applications to hydrologic models should consider bias relative to the inherent error in models. Bias-corrected SSEBop ETa rates could be used as calibration targets in models of hydrologic processes, such as groundwater models. Annual bias in SSEBop ETa introduced to the model calibration is typically below the margin of error associated with typical residuals in model simulations, depending on scale. Surface-water and groundwater-flow models with RMSEs on the order of a few feet could benefit from bias-corrected SSEBop values of ETa.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215072","collaboration":"Prepared in cooperation with Northwest Florida Water Management District, Suwannee River Water Management District, St. Johns River Water Management District, South Florida Water Management District, Southwest Florida Water Management District, and Tampa Bay Water","usgsCitation":"Sepúlveda, N., 2021, Evaluation of actual evapotranspiration rates from the Operational Simplified Surface Energy Balance (SSEBop) model in Florida and parts of Alabama and Georgia, 2000–17: U.S. Geological Survey Scientific Investigations Report 2021–5072, 66 p., https://doi.org/10.3133/sir20215072.","productDescription":"Report: x, 66 p.; Data Release","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-112971","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":388346,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5072/coverthb.jpg"},{"id":388349,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5072/images"},{"id":388347,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5072/sir20215072.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5072"},{"id":388348,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99AB3X4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data sets of actual evapotranspiration rates from 2000 to 2017 for basins in Florida and parts of Alabama and Georgia, calculated using the water-balance method, the bias-corrected Operational Simplified Surface Energy Balance (SSEBop) model, and the land-use crop coefficients model"}],"country":"United States","state":"Alabama, Florida, Georgia","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -87.71484375,\n              25.005972656239187\n            ],\n            [\n              -79.98046875,\n              25.005972656239187\n            ],\n            [\n              -79.98046875,\n              31.98944183792288\n            ],\n            [\n              -87.71484375,\n              31.98944183792288\n            ],\n            [\n              -87.71484375,\n              25.005972656239187\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a data-mce-href=\"mailto:gs-w-cfwsc_center_director@usgs.gov\" href=\"mailto:gs-w-cfwsc_center_director@usgs.gov\">Director</a>, <a data-mce-href=\"https://www.usgs.gov/centers/car-fl-water\" href=\"https://www.usgs.gov/centers/car-fl-water\">Caribbean-Florida Water Science Center</a><br>U.S. Geological Survey<br>4446 Pet Lane, Suite 108<br>Lutz, FL 33559 <br> </p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Purpose and Scope</li><li>Models Used to Simulate Actual Evapotranspiration</li><li>Evaluation of SSEBop Rates</li><li>Model Limitations</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2021-08-24","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Sepulveda, Nicasio 0000-0002-6333-1865 nsepul@usgs.gov","orcid":"https://orcid.org/0000-0002-6333-1865","contributorId":1454,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Nicasio","email":"nsepul@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":821783,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70223361,"text":"sir20215080 - 2021 - Estimation of dissolved-solids concentrations using continuous water-quality monitoring and regression models at four sites in the Yuma area, Arizona and California, January 2017 through March 2019","interactions":[],"lastModifiedDate":"2021-08-25T11:44:55.7065","indexId":"sir20215080","displayToPublicDate":"2021-08-24T14:20:10","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5080","displayTitle":"Estimation of Dissolved-Solids Concentrations Using Continuous Water-Quality Monitoring and Regression Models at Four Sites in the Yuma Area, Arizona and California, January 2017 through March 2019","title":"Estimation of dissolved-solids concentrations using continuous water-quality monitoring and regression models at four sites in the Yuma area, Arizona and California, January 2017 through March 2019","docAbstract":"<p>Multiple linear regression models were developed to estimate dissolved-solids concentrations in water at four sites in the Yuma area between Imperial Dam, Arizona and California and the southerly international boundary with Mexico at San Luis, Arizona. Continuous and discrete water-quality data were collected at gaging stations in the Colorado River upstream from Imperial Dam, Arizona-California, the Colorado River below Cooper wasteway near Yuma, Arizona, the Yuma Main Drain above Arizona–Sonora, Mexico boundary, and the 242 lateral above Main Drain at the Arizona–Sonora boundary. Continuous specific conductance and water temperature data were collected at each site between January 2017 and March 2019. Bi-weekly to monthly dissolved-solids water samples were collected during the same period. Continuous specific conductance data collected at the Colorado River below Cooper wasteway were affected by poorly mixed streamflow during periods when the Pilot Knob Hydro-electric Plant was releasing water to the river. The continuous specific conductance data for the site downstream from Cooper wasteway were corrected using mean specific conductance values computed from cross-section measurements collected during site visits. Continuous specific conductance data were affected by sensor fouling issues at the 242 lateral site, and continued operation at the site would require more frequent visits for cleaning and service to ensure data quality.</p><p>During the study, instream specific conductance readings ranged from 966 to 3,030 microsiemens per centimeter (μS/cm) at 25 degrees Celsius. Computed dissolved-solids concentrations from discrete samples ranged from 690 to 2,580 milligrams per liter (mg/L). Dissolved-solids concentrations were estimated from regression models using the optimal relation between dissolved solids and environmental factors, such as specific conductance, water temperature, dissolved oxygen, streamflow, and seasonality. Specific conductance was the primary factor at all four sites and explained 87.6 to 94 percent of variation in dissolved solids. Water temperature, as an indicator of seasonality, was determined to be a statistically significant secondary factor at both the Colorado River above Imperial Dam and Colorado River below Cooper wasteway sites explaining an additional 6.9 and 2.1 percent of variation in dissolved solids, respectively. Regression models explained 87.6 to 96.9 percent of the variation in dissolved solids; the root mean square error in the modeled data ranged between about 6 and 27 mg/L.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215080","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Cederberg, J.R., Paretti, N.V., Coes, A.L., Hermosillo, E., Andrade, L., 2021, Estimation of dissolved-solids concentrations using continuous water-quality monitoring and regression models at four sites in the Yuma area, Arizona and California, January 2017 through March 2019: U.S. Geological Survey Scientific Investigations Report 2021–5080, 26 p., https://doi.org/10.3133/sir20215080.","productDescription":"Report: vii, 26 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-111110","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":436228,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SMK908","text":"USGS data release","linkHelpText":"Water-Quality Field Blank and Replicate Sample Data, Instantaneous and Mean Daily Discharge Data, and Dissolved-Solids Concentrations Data Collected in Four Waterways of Southwest Arizona, January 2017-March 2019"},{"id":388445,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/p9SMK908","linkHelpText":"Supplemental streamflow, quality-assurance, and dissolved-solids concentration datasets used for regression model development at four sites in the Yuma area, Arizona and California, January 2017 through March 2019"},{"id":388447,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5080/covrthb.jpg"},{"id":388448,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5080/sir20215080.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, California","otherGeospatial":"Yuma area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.873046875,\n              32.58384932565662\n            ],\n            [\n              -114.3896484375,\n              32.58384932565662\n            ],\n            [\n              -114.3896484375,\n              32.88881315761995\n            ],\n            [\n              -114.873046875,\n              32.88881315761995\n            ],\n            [\n              -114.873046875,\n              32.58384932565662\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_az@usgs.gov\" data-mce-href=\"mailto:dc_az@usgs.gov\">Director</a>,<br><a href=\"https://www.usgs.gov/centers/az-water\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/az-water\">Arizona Water Science Center</a><br><a href=\"https://www.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/\">U.S. Geological Survey</a><br>520 N. Park Avenue<br>Tucson, AZ 85719</p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Methods&nbsp;&nbsp;</li><li>Results&nbsp; &nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-08-24","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Cederberg, Jay R. 0000-0001-6649-7353 cederber@usgs.gov","orcid":"https://orcid.org/0000-0001-6649-7353","contributorId":964,"corporation":false,"usgs":true,"family":"Cederberg","given":"Jay","email":"cederber@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paretti, Nicholas V. 0000-0003-2178-4820 nparetti@usgs.gov","orcid":"https://orcid.org/0000-0003-2178-4820","contributorId":173412,"corporation":false,"usgs":true,"family":"Paretti","given":"Nicholas","email":"nparetti@usgs.gov","middleInitial":"V.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821858,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coes, Alissa L. 0000-0001-6682-5417 alcoes@usgs.gov","orcid":"https://orcid.org/0000-0001-6682-5417","contributorId":4231,"corporation":false,"usgs":true,"family":"Coes","given":"Alissa","email":"alcoes@usgs.gov","middleInitial":"L.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821859,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hermosillo, Edyth 0000-0003-1648-1016 ehermosillo@usgs.gov","orcid":"https://orcid.org/0000-0003-1648-1016","contributorId":175455,"corporation":false,"usgs":true,"family":"Hermosillo","given":"Edyth","email":"ehermosillo@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821860,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andrade, Lucia 0000-0003-3741-1404","orcid":"https://orcid.org/0000-0003-3741-1404","contributorId":264674,"corporation":false,"usgs":true,"family":"Andrade","given":"Lucia","email":"","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":821861,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70223360,"text":"ofr20211074 - 2021 - Assessment of barrier island morphological change in northern Alaska","interactions":[],"lastModifiedDate":"2021-08-25T11:35:00.440129","indexId":"ofr20211074","displayToPublicDate":"2021-08-24T12:41:57","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1074","displayTitle":"Assessment of Barrier Island Morphological Change in Northern Alaska","title":"Assessment of barrier island morphological change in northern Alaska","docAbstract":"<p>Arctic barriers islands are highly dynamic features influenced by a variety of oceanographic, geologic, and environmental factors. Many Alaskan barrier islands and spits serve as habitat and protection for native species, as well as shelter the coast from waves and storms that cause flooding and degradation of coastal villages. This study summarizes changes to barrier morphology in time and space along the North Slope coast of Alaska between the United States-Canadian border and Cape Beaufort from 1947 to 2020. Changes considered in this study include number of barriers, area and perimeter, shoreline length, barrier sinuosity and width, presence and number of relict terminus features, presence and coverage of tundra vegetation, barrier orientation, and elevation metrics. Wave conditions are also summarized and related to changes in barrier morphology. The results in this report help to better predict future barrier evolution and prevalence along Alaska’s coast by increasing our understanding of Arctic barrier development, migration and degradation.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211074","usgsCitation":"Hamilton, A.I., Gibbs, A.E., Erikson, L.H., and Engelstad, A.C., 2021, Assessment of barrier island morphological change in northern Alaska: U.S. Geological Survey Open-File Report 2021–1074, 28 p., https://doi.org/10.3133/ofr20211074.","productDescription":"Report: vi , 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-122308","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":388442,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90EQ1H7","linkHelpText":"Historical shorelines and morphological metrics for barrier islands and spits along the north coast of Alaska between Cape Beaufort and the U.S.-Canadian border, 1947 to 2019"},{"id":388441,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1074/ofr20211074.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":388440,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1074/covrthb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -160.83984375,\n              69.16255790810499\n            ],\n            [\n              -141.240234375,\n              69.16255790810499\n            ],\n            [\n              -141.240234375,\n              72.01972876525514\n            ],\n            [\n              -160.83984375,\n              72.01972876525514\n            ],\n            [\n              -160.83984375,\n              69.16255790810499\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"http://www.usgs.gov/centers/pcmsc/\" data-mce-href=\"http://www.usgs.gov/centers/pcmsc/\">Pacific Coastal and Marine Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>Pacific Coastal and Marine Science Center<br>2885 Mission St.<br>Santa Cruz, CA 95060</p>","tableOfContents":"<ul><li>Acknowledgments&nbsp;&nbsp;</li><li>Abstract&nbsp;&nbsp;</li><li>Introduction&nbsp;&nbsp;</li><li>Methods&nbsp;&nbsp;</li><li>Results&nbsp;&nbsp;</li><li>Summary&nbsp;&nbsp;</li><li>References Cited&nbsp;&nbsp;</li><li>Appendix 1. Feature Type and Name or Geographical Area of Barrier Island Chains&nbsp;&nbsp;</li><li>Appendix 2. Total Barrier Chain Area&nbsp;&nbsp;</li><li>Appendix 3. Wave Roses for Each Era at Different Locations along Alaska's North Slope</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2021-08-24","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Hamilton, Anna I.","contributorId":201415,"corporation":false,"usgs":true,"family":"Hamilton","given":"Anna","email":"","middleInitial":"I.","affiliations":[{"id":16286,"text":"Tetra Tech","active":true,"usgs":false},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821853,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821854,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":821855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engelstad, Anita C. 0000-0002-0211-4189","orcid":"https://orcid.org/0000-0002-0211-4189","contributorId":24884,"corporation":false,"usgs":true,"family":"Engelstad","given":"Anita C.","affiliations":[],"preferred":true,"id":821856,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70223421,"text":"70223421 - 2021 - Seasonally dynamic nutrient modeling quantifies storage lags and time-varying reactivity across large river basins","interactions":[],"lastModifiedDate":"2021-08-27T15:16:07.4255","indexId":"70223421","displayToPublicDate":"2021-08-24T10:12:21","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Seasonally dynamic nutrient modeling quantifies storage lags and time-varying reactivity across large river basins","docAbstract":"<p><span>Nutrients that have gradually accumulated in soils, groundwaters, and river sediments in the United States over the past century can remobilize and increase current downstream loading, obscuring effects of conservation practices aimed at protecting water resources. Drivers of storage accumulation and release of nutrients are poorly understood at the spatial scale of basins to watersheds. Predicting water quality outcomes in large river basins demands modeling storage lags and time varying reactivity that models of mean conditions typically cannot elucidate. We developed a seasonally dynamic approach to large-scale nutrient modeling based on a multiscale framework and nutrient storage lags were quantified for the nearly 190 000 small catchments that feed the rivers across the northeastern United States where catchment mean transit times were found to be around 4.7 (2–10) years for nitrogen and 1.3 (0.7–2) years for phosphorus. Nutrient loads carried in river flow in the current season contained a significant—and sometimes dominant—portion of mass lagged in its release from catchment storage repositories. Our approach of integrating storage releases with seasonally dynamic hydroclimatic drivers sets the stage to assess the accumulated effects of nutrient storage and lagged releases to the river interacting with seasonally varying nutrient reactivity and societal management actions throughout large river basins.</span></p>","language":"English","publisher":"IOP Publishing","doi":"10.1088/1748-9326/ac1af4","usgsCitation":"Schmadel, N., Harvey, J., and Schwarz, G.E., 2021, Seasonally dynamic nutrient modeling quantifies storage lags and time-varying reactivity across large river basins: Environmental Research Letters, v. 16, no. 9, 095004, 11 p., https://doi.org/10.1088/1748-9326/ac1af4.","productDescription":"095004, 11 p.","ipdsId":"IP-126236","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":451077,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/ac1af4","text":"Publisher Index Page"},{"id":436229,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NRFWOV","text":"USGS data release","linkHelpText":"Mean seasonal SPARROW model inputs and simulated nitrogen and phosphorus loads for the Northeastern United States 2002 base year"},{"id":388586,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Schmadel, Noah 0000-0002-2046-1694","orcid":"https://orcid.org/0000-0002-2046-1694","contributorId":219105,"corporation":false,"usgs":true,"family":"Schmadel","given":"Noah","email":"","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":822009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harvey, Judson 0000-0002-2654-9873","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":219104,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":822010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":213621,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory","email":"gschwarz@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":822011,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70224580,"text":"70224580 - 2021 - Nonlinear shifts in infectious rust disease due to climate change","interactions":[],"lastModifiedDate":"2021-09-29T13:39:18.489479","indexId":"70224580","displayToPublicDate":"2021-08-24T08:35:10","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Nonlinear shifts in infectious rust disease due to climate change","docAbstract":"<p><span>Range shifts of infectious plant disease are expected under climate change. As plant diseases move, emergent abiotic-biotic interactions are predicted to modify their distributions, leading to unexpected changes in disease risk. Evidence of these complex range shifts due to climate change, however, remains largely speculative. Here, we combine a long-term study of the infectious tree disease, white pine blister rust, with a six-year field assessment of drought-disease interactions in the southern Sierra Nevada. We find that climate change between 1996 and 2016 moved the climate optimum of the disease into higher elevations. The nonlinear climate change-disease relationship contributed to an estimated 5.5 (4.4–6.6) percentage points (p.p.) decline in disease prevalence in arid regions and an estimated 6.8 (5.8–7.9) p.p. increase in colder regions. Though climate change likely expanded the suitable area for blister rust by 777.9 (1.0–1392.9) km</span><sup>2</sup><span>&nbsp;into previously inhospitable regions, the combination of host-pathogen and drought-disease interactions contributed to a substantial decrease (32.79%) in mean disease&nbsp;prevalence between surveys. Specifically, declining alternate host abundance suppressed infection probabilities at high elevations, even as climatic conditions became more suitable. Further, drought-disease interactions varied in strength and direction across an aridity gradient—likely decreasing infection risk at low elevations while simultaneously increasing infection risk at high elevations. These results highlight the critical role of aridity in modifying host-pathogen-drought interactions. Variation in aridity across topographic gradients can strongly mediate plant disease range shifts in response to climate change.</span></p>","language":"English","publisher":"Springer Nature","doi":"10.1038/s41467-021-25182-6","usgsCitation":"Dudney, J., Willing, C., Das, A., Latimer, A.M., Nesmith, J.C., and Battles, J.J., 2021, Nonlinear shifts in infectious rust disease due to climate change: Nature Communications, v. 12, 5102, 13 p., https://doi.org/10.1038/s41467-021-25182-6.","productDescription":"5102, 13 p.","ipdsId":"IP-122388","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":451079,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-021-25182-6","text":"Publisher Index Page"},{"id":389950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Kings Canyon National Park, Sequoia National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -118.30352783203125,\n              36.69485094156225\n            ],\n            [\n              -118.41888427734374,\n              37.03325468997236\n            ],\n            [\n              -118.69903564453124,\n              37.21939331752986\n            ],\n            [\n              -118.828125,\n              37.23907530202184\n            ],\n            [\n              -118.85559082031249,\n              37.19533058280065\n            ],\n            [\n              -118.75946044921874,\n              37.07271048132943\n            ],\n            [\n              -118.80615234374999,\n              36.95208671786997\n            ],\n            [\n              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of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":824156,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Das, Adrian 0000-0002-3937-2616 adas@usgs.gov","orcid":"https://orcid.org/0000-0002-3937-2616","contributorId":201236,"corporation":false,"usgs":true,"family":"Das","given":"Adrian","email":"adas@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":824157,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Latimer, Andrew M.","contributorId":229043,"corporation":false,"usgs":false,"family":"Latimer","given":"Andrew","email":"","middleInitial":"M.","affiliations":[{"id":41559,"text":"Department of Plant Sciences, University of California Davis, One Shields Ave., Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":824158,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nesmith, Jonathan C B","contributorId":245216,"corporation":false,"usgs":false,"family":"Nesmith","given":"Jonathan","email":"","middleInitial":"C B","affiliations":[{"id":49124,"text":"National Park Service, Sierra Nevada Network Inventory & Monitoring Program","active":true,"usgs":false}],"preferred":false,"id":824159,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Battles, John J.","contributorId":102006,"corporation":false,"usgs":false,"family":"Battles","given":"John","email":"","middleInitial":"J.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":824160,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70225709,"text":"70225709 - 2021 - The Holocene dynamics of Ryder Glacier and ice tongue in north Greenland","interactions":[],"lastModifiedDate":"2021-11-04T13:41:17.401004","indexId":"70225709","displayToPublicDate":"2021-08-24T08:25:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3554,"text":"The Cryosphere","active":true,"publicationSubtype":{"id":10}},"title":"The Holocene dynamics of Ryder Glacier and ice tongue in north Greenland","docAbstract":"<p><span>The northern sector of the Greenland Ice Sheet is considered to be particularly susceptible to ice mass loss arising from increased glacier discharge in the coming decades. However, the past extent and dynamics of outlet glaciers in this region, and hence their vulnerability to climate change, are poorly documented. In the summer of 2019, the Swedish icebreaker&nbsp;</span><i>Oden</i><span>&nbsp;entered the previously unchartered waters of Sherard Osborn Fjord, where Ryder Glacier drains approximately 2 % of Greenland's ice sheet into the Lincoln Sea. Here we reconstruct the Holocene dynamics of Ryder Glacier and its ice tongue by combining radiocarbon dating with sedimentary facies analyses along a 45 km transect of marine sediment cores collected between the modern ice tongue margin and the mouth of the fjord. The results illustrate that Ryder Glacier retreated from a grounded position at the fjord mouth during the Early Holocene (</span><span class=\"inline-formula\">&gt;</span><span> </span><span class=\"inline-formula\">10.7±0.4</span><span> ka cal BP) and receded more than 120 km to the end of Sherard Osborn Fjord by the Middle Holocene (</span><span class=\"inline-formula\">6.3±0.3</span><span> ka cal BP), likely becoming completely land-based. A re-advance of Ryder Glacier occurred in the Late Holocene, becoming marine-based around&nbsp;</span><span class=\"inline-formula\">3.9±0.4</span><span> ka cal BP. An ice tongue, similar in extent to its current position was established in the Late Holocene (between&nbsp;</span><span class=\"inline-formula\">3.6±0.4</span><span>&nbsp;and&nbsp;</span><span class=\"inline-formula\">2.9±0.4</span><span> ka cal BP) and extended to its maximum historical position near the fjord mouth around&nbsp;</span><span class=\"inline-formula\">0.9±0.3</span><span> ka cal BP. Laminated, clast-poor sediments were deposited during the entire retreat and regrowth phases, suggesting the persistence of an ice tongue that only collapsed when the glacier retreated behind a prominent topographic high at the landward end of the fjord. Sherard Osborn Fjord narrows inland, is constrained by steep-sided cliffs, contains a number of bathymetric pinning points that also shield the modern ice tongue and grounding zone from warm Atlantic waters, and has a shallowing inland sub-ice topography. These features are conducive to glacier stability and can explain the persistence of Ryder's ice tongue while the glacier remained marine-based. However, the physiography of the fjord did not halt the dramatic retreat of Ryder Glacier under the relatively mild changes in climate forcing during the Holocene. Presently, Ryder Glacier is grounded more than 40 km seaward of its inferred position during the Middle Holocene, highlighting the potential for substantial retreat in response to ongoing climate change.</span></p>","language":"English","publisher":"European Geosciences Union","doi":"10.5194/tc-15-4073-2021","usgsCitation":"O’Regan, M., Cronin, T.M., Reilly, B., Olsen Alstrup, A.K., Gemery, L., Golub, A., Mayer, L.A., Morlighem, M., Moros, M., Munk, O.L., Nilsson, J., Pearce, C., Detlef, H., Stranne, C., Vermassen, F., West, G., and Jakobsson, M., 2021, The Holocene dynamics of Ryder Glacier and ice tongue in north Greenland: The Cryosphere, v. 15, p. 4073-4097, https://doi.org/10.5194/tc-15-4073-2021.","productDescription":"25 p.","startPage":"4073","endPage":"4097","ipdsId":"IP-127375","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":451081,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-15-4073-2021","text":"Publisher Index Page"},{"id":391381,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Greenland","otherGeospatial":"Ryder Glacier","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -63.6328125,\n              80.17871349622823\n            ],\n            [\n              -32.34375,\n              80.17871349622823\n            ],\n            [\n              -32.34375,\n              83.57940370073115\n            ],\n            [\n              -63.6328125,\n              83.57940370073115\n            ],\n            [\n              -63.6328125,\n              80.17871349622823\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"15","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"O’Regan, Matt","contributorId":197135,"corporation":false,"usgs":false,"family":"O’Regan","given":"Matt","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":826358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":826359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Brendan","contributorId":258076,"corporation":false,"usgs":false,"family":"Reilly","given":"Brendan","email":"","affiliations":[],"preferred":false,"id":826360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olsen Alstrup, Aage K.","contributorId":268312,"corporation":false,"usgs":false,"family":"Olsen Alstrup","given":"Aage","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":826361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gemery, Laura 0000-0003-1966-8732","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":245413,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":826362,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Golub, Anna","contributorId":268313,"corporation":false,"usgs":false,"family":"Golub","given":"Anna","email":"","affiliations":[],"preferred":false,"id":826363,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mayer, Larry A.","contributorId":69583,"corporation":false,"usgs":true,"family":"Mayer","given":"Larry","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":826364,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morlighem, Mathieu","contributorId":141050,"corporation":false,"usgs":false,"family":"Morlighem","given":"Mathieu","email":"","affiliations":[{"id":6976,"text":"University of California, Irvine","active":true,"usgs":false}],"preferred":false,"id":826365,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Moros, Matthias","contributorId":268314,"corporation":false,"usgs":false,"family":"Moros","given":"Matthias","email":"","affiliations":[],"preferred":false,"id":826366,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Munk, Ole L.","contributorId":268315,"corporation":false,"usgs":false,"family":"Munk","given":"Ole","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":826367,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Nilsson, Johan","contributorId":166855,"corporation":false,"usgs":false,"family":"Nilsson","given":"Johan","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":826368,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Pearce, Christof","contributorId":197126,"corporation":false,"usgs":false,"family":"Pearce","given":"Christof","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":826369,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Detlef, Henrieka","contributorId":268316,"corporation":false,"usgs":false,"family":"Detlef","given":"Henrieka","email":"","affiliations":[],"preferred":false,"id":826370,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Stranne, Christian","contributorId":166862,"corporation":false,"usgs":false,"family":"Stranne","given":"Christian","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":826371,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Vermassen, Flor","contributorId":268317,"corporation":false,"usgs":false,"family":"Vermassen","given":"Flor","email":"","affiliations":[],"preferred":false,"id":826372,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"West, Gabriel","contributorId":258085,"corporation":false,"usgs":false,"family":"West","given":"Gabriel","email":"","affiliations":[],"preferred":false,"id":826373,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Jakobsson, Martin","contributorId":166854,"corporation":false,"usgs":false,"family":"Jakobsson","given":"Martin","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":826374,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}}
,{"id":70224330,"text":"70224330 - 2021 - Thyroid disruption and oxidative stress in American kestrels following embryonic exposure to the alternative flame retardants, EHTBB and TBPH","interactions":[],"lastModifiedDate":"2021-09-23T12:50:23.708822","indexId":"70224330","displayToPublicDate":"2021-08-24T07:47:43","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1523,"text":"Environment International","active":true,"publicationSubtype":{"id":10}},"title":"Thyroid disruption and oxidative stress in American kestrels following embryonic exposure to the alternative flame retardants, EHTBB and TBPH","docAbstract":"<div id=\"ab015\" class=\"abstract author\" lang=\"en\"><div id=\"as015\"><p id=\"sp0015\">Brominated flame retardant chemicals, such as 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (EHTBB) (CAS #: 183658–27-7) and bis(2-ethylhexyl)-2,3,4,5-tetrabromophthalate (TBPH) (CAS #: 26040–51-7), have been detected in avian tissues and eggs from remote regions. Exposure to EHTBB and TBPH has been shown to cause oxidative stress and altered thyroid function in rodents and fish, yet no controlled studies have examined potential adverse effects of exposure in birds. Because flame retardants have been detected in wild raptors, we used American kestrels (<i>Falco sparverius</i>) as a model raptor to determine whether<span>&nbsp;</span><i>in ovo</i><span>&nbsp;</span>exposure to EHTBB or TBPH affected growth, hatching success, oxidative stress, or thyroid function. We exposed kestrel embryos to nominal concentrations (10, 50, or 100&nbsp;ng&nbsp;g<sup>−1</sup><span>&nbsp;</span>egg weight) of EHTBB and TBPH via egg-injection on embryonic day 5. Embryonic exposure (~23 d) to EHTBB increased thyroid gland mass, reduced glandular colloid and total thyroxine (T4) in hatchling males and females, whereas deiodinase enzyme activity increased in males but decreased in females. Hatchlings exposed to TBPH in ovo exhibited reduced colloid and increased oxidative stress. Although exposure to EHTBB and TBPH caused several physiological effects (e.g., heart and brain mass), only exposure to 50&nbsp;ng&nbsp;g<sup>−1</sup><span>&nbsp;</span>EHTBB appeared to reduce hatching success. Our results suggest these flame retardants may be hazardous for predatory birds. Future research should evaluate long-term survival and fitness consequences in birds exposed to these chemicals.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envint.2021.106826","usgsCitation":"Goodchild, C., Karouna-Renier, N., Henry, P.F., Letcher, R.J., Schultz, S.L., Maddox, C.M., Bean, T., Peters, L.E., Palace, V.P., and Fernie, K.J., 2021, Thyroid disruption and oxidative stress in American kestrels following embryonic exposure to the alternative flame retardants, EHTBB and TBPH: Environment International, v. 157, 106826, 11 p., https://doi.org/10.1016/j.envint.2021.106826.","productDescription":"106826, 11 p.","ipdsId":"IP-129632","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":451084,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envint.2021.106826","text":"Publisher Index Page"},{"id":436230,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E6PSNO","text":"USGS data release","linkHelpText":"Biomarker responses in American kestrels exposed in ovo to EHTBB and TBPH"},{"id":389645,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"157","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Goodchild, CHristopher","contributorId":265929,"corporation":false,"usgs":false,"family":"Goodchild","given":"CHristopher","affiliations":[{"id":54572,"text":"University of Central Oklahoma","active":true,"usgs":false}],"preferred":false,"id":823767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Karouna-Renier, Natalie 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":200983,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":823768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henry, Paula F. P. 0000-0002-7601-5546 phenry@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-5546","contributorId":4485,"corporation":false,"usgs":true,"family":"Henry","given":"Paula","email":"phenry@usgs.gov","middleInitial":"F. P.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":823769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Letcher, Robert J.","contributorId":176209,"corporation":false,"usgs":false,"family":"Letcher","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":823770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schultz, Sandra L. 0000-0003-3394-2857 sschultz@usgs.gov","orcid":"https://orcid.org/0000-0003-3394-2857","contributorId":5966,"corporation":false,"usgs":true,"family":"Schultz","given":"Sandra","email":"sschultz@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":823771,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maddox, Catherine M.","contributorId":192013,"corporation":false,"usgs":false,"family":"Maddox","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":823772,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bean, Thomas","contributorId":202972,"corporation":false,"usgs":false,"family":"Bean","given":"Thomas","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":823773,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peters, Lisa E.","contributorId":176211,"corporation":false,"usgs":false,"family":"Peters","given":"Lisa","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":823774,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Palace, Vince P.","contributorId":176210,"corporation":false,"usgs":false,"family":"Palace","given":"Vince","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":823775,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fernie, Kimberly J.","contributorId":176208,"corporation":false,"usgs":false,"family":"Fernie","given":"Kimberly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":823776,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70224308,"text":"70224308 - 2021 - Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay","interactions":[],"lastModifiedDate":"2021-09-21T12:47:16.692844","indexId":"70224308","displayToPublicDate":"2021-08-24T07:45:03","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"abs0010\" class=\"abstract author\" lang=\"en\"><div id=\"abssec0010\"><p id=\"abspara0010\">Reliable and long-term hindcast data of water levels are essential in quantifying return period and values of extreme water levels. In order to inform design decisions on a local flood control district level, process-based numerical modeling has proven an essential tool to provide the needed temporal and spatial coverage for different extreme value analysis methods. To determine the importance of different physical processes to the extreme water levels we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to simulate a large, urban, high-energy coastal estuary (the San Francisco Bay). The unstructured grid with 1D/2DH model elements, allows for efficient model simulations and therefore it was possible to simulate over 70 years between 1950 and 2019. Results show significant skill in reproducing observations for the entire modeled time period with an average root-mean-square error of 8.0&nbsp;cm. A process-based modeling approach allows for the explicit in- and exclusion of different physical processes to quantify their importance to the extremes. For the 100-year still water level (SWL), tide (70%) and non-tidal residual (NTR) (25%) explain the majority of the simulated high water levels in the Bay relative to Mean Higher High Water (MHHW). However, closer to the Delta, local fluvial inflow increases in importance. For longer return periods, the importance of tide decreases and the importance of remote NTRs and fluvial inflow increases.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.coastaleng.2021.103984","usgsCitation":"Nederhoff, C.M., Saleh, R., Tehranirad, B., Herdman, L.M., Erikson, L.H., Barnard, P.L., and Van der Wegen, M., 2021, Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay: Coastal Engineering, v. 170, 103984, 12 p., https://doi.org/10.1016/j.coastaleng.2021.103984.","productDescription":"103984, 12 p.","ipdsId":"IP-126090","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":451086,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2021.103984","text":"Publisher Index Page"},{"id":436231,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WWB9V4","text":"USGS data release","linkHelpText":"Hydrodynamic model of the San Francisco Bay and Delta, California"},{"id":389536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.837890625,\n              36.91476428895589\n            ],\n            [\n              -120.73974609374999,\n              36.91476428895589\n            ],\n            [\n              -120.73974609374999,\n              38.66835610151506\n            ],\n            [\n              -123.837890625,\n              38.66835610151506\n            ],\n            [\n              -123.837890625,\n              36.91476428895589\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Nederhoff, Cornelis M. 0000-0003-0552-3428","orcid":"https://orcid.org/0000-0003-0552-3428","contributorId":265889,"corporation":false,"usgs":false,"family":"Nederhoff","given":"Cornelis","email":"","middleInitial":"M.","affiliations":[{"id":33886,"text":"Deltares USA","active":true,"usgs":false}],"preferred":true,"id":823670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saleh, Rohin","contributorId":265891,"corporation":false,"usgs":false,"family":"Saleh","given":"Rohin","email":"","affiliations":[{"id":54818,"text":"Alameda Flood Control District","active":true,"usgs":false}],"preferred":false,"id":823676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tehranirad, Babak 0000-0002-1634-9165","orcid":"https://orcid.org/0000-0002-1634-9165","contributorId":265890,"corporation":false,"usgs":true,"family":"Tehranirad","given":"Babak","email":"","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":823671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Herdman, Liv M. 0000-0002-5444-6441 lherdman@usgs.gov","orcid":"https://orcid.org/0000-0002-5444-6441","contributorId":149964,"corporation":false,"usgs":true,"family":"Herdman","given":"Liv","email":"lherdman@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":823672,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":823673,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barnard, Patrick L. 0000-0003-1414-6476 pbarnard@usgs.gov","orcid":"https://orcid.org/0000-0003-1414-6476","contributorId":140982,"corporation":false,"usgs":true,"family":"Barnard","given":"Patrick","email":"pbarnard@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":823674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Van der Wegen, Mick","contributorId":191095,"corporation":false,"usgs":false,"family":"Van der Wegen","given":"Mick","email":"","affiliations":[],"preferred":false,"id":823675,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70226501,"text":"70226501 - 2021 - Random variable","interactions":[],"lastModifiedDate":"2021-11-22T14:16:14.179646","indexId":"70226501","displayToPublicDate":"2021-08-24T07:25:24","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Random variable","docAbstract":"<p id=\"Par1\" class=\"Para\">A random variable is a function that assigns a value in a sample space to an element of an arbitrary set (James<span>&nbsp;</span><span class=\"CitationRef\">1992</span>; Pawlowsky-Glahn et al.<span>&nbsp;</span><span class=\"CitationRef\">2015</span>). It is a model for a random experiment: the arbitrary set is an abstraction of the experimental conditions, the values taken by the random variable are in the sample space, and the function itself models the assignment of outcomes, thus also describing its frequency of appearance. In simpler terms, for the purpose of this presentation, a random variable is a function that assigns to each of the outcomes of a random experiment a value with a certain probability. A random variable also goes by stochastic variable and aleatory variable. Random variables are usually annotated as Roman capital letters, such as<span>&nbsp;</span><i class=\"EmphasisTypeItalic \">X</i><span>&nbsp;</span>or<span>&nbsp;</span><i class=\"EmphasisTypeItalic \">Y</i>.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Encyclopedia of Mathematical Geosciences","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-3-030-26050-7_429-1","usgsCitation":"Olea, R., 2021, Random variable, chap. <i>of</i> Encyclopedia of Mathematical Geosciences, HTML Document, https://doi.org/10.1007/978-3-030-26050-7_429-1.","productDescription":"HTML Document","ipdsId":"IP-124122","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":391978,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":224285,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":827121,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70230324,"text":"70230324 - 2021 - A ground motion model for GNSS peak ground displacement","interactions":[],"lastModifiedDate":"2022-04-07T12:22:56.814703","indexId":"70230324","displayToPublicDate":"2021-08-24T07:18:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A ground motion model for GNSS peak ground displacement","docAbstract":"<p><span>We present an updated ground‐motion model (GMM) for&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"msub\"><span id=\"MathJax-Span-4\" class=\"mi\">M</span><span id=\"MathJax-Span-5\" class=\"mi\">w</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;6–9 earthquakes using Global Navigation Satellite Systems (GNSS) observations of the peak ground displacement (PGD). Earthquake GMMs inform a range of Earth science and engineering applications, including source characterization, seismic hazard evaluations, loss estimates, and seismic design standards. A typical GMM is characterized by simplified metrics describing the earthquake source (magnitude), observation distance, and site terms. Most often, GMMs are derived from broadband seismometer and accelerometer observations, yet during strong shaking, these traditional seismic instruments are affected by baseline offsets, leading to inaccurate recordings of low‐frequency ground motions such as displacement. The incorporation of geodetic data sources, particularly for characterizing the unsaturated ground displacement of large‐magnitude events, has proven valuable as a complement to traditional seismic approaches and led to the development of an initial point‐source GMM based on PGD estimated from high‐rate GNSS data. Here, we improve the existing GMM to more effectively account for fault finiteness, slip heterogeneity, and observation distance. We evaluate the limitations of the currently available GNSS earthquake data set to calibrate the GMM. In particular, the observed earthquake data set is lacking in observations within 100&nbsp;km of large‐magnitude events (</span><span class=\"inline-formula no-formula-id\">⁠<span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub><mo xmlns=&quot;&quot;>&amp;gt;</mo><mn xmlns=&quot;&quot;>8</mn></math>\"><span id=\"MathJax-Span-6\" class=\"math\"><span><span id=\"MathJax-Span-7\" class=\"mrow\"><span id=\"MathJax-Span-8\" class=\"msub\"><span id=\"MathJax-Span-9\" class=\"mi\">M</span><span id=\"MathJax-Span-10\" class=\"mi\">w</span></span><span id=\"MathJax-Span-11\" class=\"mo\">&gt;</span><span id=\"MathJax-Span-12\" class=\"mn\">8</span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw&gt;8</span></span>⁠</span><span>), inhibiting evaluation of fault dimensions for earthquakes too large to be represented as point sources in the near field. To that end, we separately consider previously validated synthetic GNSS waveforms within 10–1000&nbsp;km of&nbsp;</span><span class=\"inline-formula no-formula-id\"><span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><msub xmlns=&quot;&quot;><mi>M</mi><mi mathvariant=&quot;normal&quot;>w</mi></msub></math>\"><span id=\"MathJax-Span-13\" class=\"math\"><span><span id=\"MathJax-Span-14\" class=\"mrow\"><span id=\"MathJax-Span-15\" class=\"msub\"><span id=\"MathJax-Span-16\" class=\"mi\">M</span><span id=\"MathJax-Span-17\" class=\"mi\">w</span></span></span></span></span><span class=\"MJX_Assistive_MathML\">Mw</span></span></span><span>&nbsp;7.8–9.3 Cascadia subduction zone scenario ruptures. The synthetic data highlight the importance of fault distance rather than point‐source metrics and improve our preparedness for large‐magnitude earthquakes with spatiotemporal qualities unlike those in our existing data set.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120210042","usgsCitation":"Goldberg, D.E., Melgar, D., Hayes, G., Sahakian, V., and Crowell, B.W., 2021, A ground motion model for GNSS peak ground displacement: Bulletin of the Seismological Society of America, v. 111, no. 5, p. 2393-2407, https://doi.org/10.1785/0120210042.","productDescription":"15 p.","startPage":"2393","endPage":"2407","ipdsId":"IP-130463","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":436232,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P905JY97","text":"USGS data release","linkHelpText":"High-rate GNSS Observations and Finite Fault Models of Moderate to Large Earthquakes"},{"id":398304,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"111","issue":"5","noUsgsAuthors":false,"publicationDate":"2021-08-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Goldberg, Dara Elyse 0000-0002-0923-3180","orcid":"https://orcid.org/0000-0002-0923-3180","contributorId":289891,"corporation":false,"usgs":true,"family":"Goldberg","given":"Dara","email":"","middleInitial":"Elyse","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":839983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Melgar, Diego","contributorId":193030,"corporation":false,"usgs":false,"family":"Melgar","given":"Diego","email":"","affiliations":[],"preferred":false,"id":840013,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":839984,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sahakian, Valerie J.","contributorId":208097,"corporation":false,"usgs":false,"family":"Sahakian","given":"Valerie J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":839986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crowell, Brendan W.","contributorId":184207,"corporation":false,"usgs":false,"family":"Crowell","given":"Brendan","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":839985,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70241793,"text":"70241793 - 2021 - Trade-offs in initial and long-term handling efficiency of PIT-tag and photographic identification methods","interactions":[],"lastModifiedDate":"2023-03-27T12:02:37.912389","indexId":"70241793","displayToPublicDate":"2021-08-24T07:01:19","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Trade-offs in initial and long-term handling efficiency of PIT-tag and photographic identification methods","docAbstract":"<div id=\"ab015\" class=\"abstract author\" lang=\"en\"><div id=\"as015\"><p id=\"sp0015\">Individual identification is required for long-term investigations that examine population-level changes in survival or abundance, and mechanisms associated with these changes in wild populations. Such identification generally requires the application of a unique mark, or the documentation of characteristics distinctive to each individual animal. To minimize impacts to often declining populations, scientific and ethical concerns encourage marking strategies that minimize handling time (i.e., stress) for captured individuals. We examined the relative efficacy of passive integrated transponder (PIT)-tagging and photo-identification to identify individual Boreal toads (<i>Anaxyrus boreas boreas</i>) in field and indoor settings. We evaluated whether initial handling time was influenced by identification method (PIT-tag or photo-identification) or environment (field or indoor) and assessed the applicability of each method in long-term monitoring programs. Initial handling time was higher for PIT-tagging than photo-identification and higher in the field than in an indoor environment; however, handling time for previously PIT-tagged individuals was greatly reduced such that photo-identification led to&nbsp;&gt;&nbsp;5.5 times more handling time than PIT-tagging over the course of a toad's lifetime. Investigators must determine the trade-off between initial and subsequent handling times to minimize the expected (mean) cumulative handling time for an individual over the course of a study. Cumulative handling time is a function of the study design and the species’ survival and detection probabilities. We developed a Shiny Application to allow investigators to determine the identification method that minimizes handling time for their own study system.</p></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2021.108110","usgsCitation":"Roberts, L., Fueka, A.B., Muths, E.L., Hardy, B., and Bailey, L., 2021, Trade-offs in initial and long-term handling efficiency of PIT-tag and photographic identification methods: Ecological Indicators, v. 130, 108110, 6 p., https://doi.org/10.1016/j.ecolind.2021.108110.","productDescription":"108110, 6 p.","ipdsId":"IP-124718","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451091,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2021.108110","text":"Publisher Index Page"},{"id":436233,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P924OCXC","text":"USGS data release","linkHelpText":"Handling times: tagging vs photos, Boreal toads in WY/CO 2020"},{"id":414765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"130","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, Lindsey","contributorId":303675,"corporation":false,"usgs":false,"family":"Roberts","given":"Lindsey","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":867741,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fueka, Abigail B.","contributorId":272882,"corporation":false,"usgs":false,"family":"Fueka","given":"Abigail","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":867744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":867743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardy, Bennett","contributorId":303568,"corporation":false,"usgs":false,"family":"Hardy","given":"Bennett","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":867742,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, Larissa L.","contributorId":229353,"corporation":false,"usgs":false,"family":"Bailey","given":"Larissa L.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":867745,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70226186,"text":"70226186 - 2021 - Is there tree senescence? The fecundity evidence","interactions":[],"lastModifiedDate":"2021-11-16T12:53:49.546189","indexId":"70226186","displayToPublicDate":"2021-08-24T06:51:34","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3164,"text":"Proceedings of the National Academy of Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Is there tree senescence? The fecundity evidence","docAbstract":"<div id=\"abstract-2\" class=\"section abstract\"><p id=\"p-7\">Despite its importance for forest regeneration, food webs, and human economies, changes in tree fecundity with tree size and age remain largely unknown. The allometric increase with tree diameter assumed in ecological models would substantially overestimate seed contributions from large trees if fecundity eventually declines with size. Current estimates are dominated by overrepresentation of small trees in regression models. We combined global fecundity data, including a substantial representation of large trees. We compared size–fecundity relationships against traditional allometric scaling with diameter and two models based on crown architecture. All allometric models fail to describe the declining rate of increase in fecundity with diameter found for 80% of 597 species in our analysis. The strong evidence of declining fecundity, beyond what can be explained by crown architectural change, is consistent with physiological decline. A downward revision of projected fecundity of large trees can improve the next generation of forest dynamic models.</p></div>","language":"English","publisher":"PNAS","doi":"10.1073/pnas.2106130118","usgsCitation":"Qiu, T., Aavena Acuna, M., Andrus, R.A., Ascoli, D., Bergeron, Y., Berretti, R., Bogdziewicz, M., Boivin, T., Bonal, R., Caignard, T., Calama, R., Camarero, J., Clark, C., Courbaud, B., Delzon, S., Donoso Calderon, S., Farfan-Rios, W., Gehring, C.A., Gilbert, G.S., Greenberg, C.H., Guo, Q., Hille Ris Lambers, J., Hoshizaki, H., Ibanez, I., Journé, V., Kilner, C., Kobe, R., Koenig, W., Kunstler, G., LaMontagne, J., Ledwon, M., Lutz, J.A., Motta, R., Myers, J.A., Nagel, T.A., Noguchi, K., Nunez, C., Pearse, I.S., Perez-Izquierdo, C., Piechnik, L., Poulson, J., Poulton-Kamakura, R., Redmond, M., Reid, C., Rodman, K.C., Scher, C.L., Schmidt Van Marle, H., Seget, B., Sharma, S., Silman, M., Swenson, J., Swift, M., Uriarte, M., Vacchiano, G., Valencia, R., Vander Yacht, A., Veblen, T.T., Whipple, A., Whitham, T.G., Wion, A., Wright, J., Zhu, K., Zimmerman, J.K., Zywiec, M., and Clark, J.S., 2021, Is there tree senescence? The fecundity evidence: Proceedings of the National Academy of Sciences, v. 118, no. 34, e2106130118, 10 p., https://doi.org/10.1073/pnas.2106130118.","productDescription":"e2106130118, 10 p.","ipdsId":"IP-127584","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":451093,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2106130118","text":"Publisher Index Page"},{"id":391737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"118","issue":"34","noUsgsAuthors":false,"publicationDate":"2021-08-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Qiu, Tong","contributorId":268817,"corporation":false,"usgs":false,"family":"Qiu","given":"Tong","affiliations":[{"id":55678,"text":"Duke U","active":true,"usgs":false}],"preferred":false,"id":826749,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aavena Acuna, Marie-Claire","contributorId":268818,"corporation":false,"usgs":false,"family":"Aavena Acuna","given":"Marie-Claire","email":"","affiliations":[{"id":37346,"text":"Universidad de Chile","active":true,"usgs":false}],"preferred":false,"id":826750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andrus, Robert A.","contributorId":229021,"corporation":false,"usgs":false,"family":"Andrus","given":"Robert","email":"","middleInitial":"A.","affiliations":[{"id":41541,"text":"Department of Geography, University of Colorado Boulder, Guggenheim 110, 260 UCB, Boulder, Colorado, 80309-0260, USA","active":true,"usgs":false}],"preferred":false,"id":826751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ascoli, Davide","contributorId":224289,"corporation":false,"usgs":false,"family":"Ascoli","given":"Davide","email":"","affiliations":[{"id":40848,"text":"University of Torino","active":true,"usgs":false}],"preferred":false,"id":826752,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bergeron, Yves","contributorId":256848,"corporation":false,"usgs":false,"family":"Bergeron","given":"Yves","email":"","affiliations":[{"id":40150,"text":"Adam Mickiewicz University, Poland","active":true,"usgs":false}],"preferred":false,"id":826753,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Berretti, Roberta","contributorId":268819,"corporation":false,"usgs":false,"family":"Berretti","given":"Roberta","email":"","affiliations":[{"id":55679,"text":"U Turin","active":true,"usgs":false}],"preferred":false,"id":826754,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bogdziewicz, Michal","contributorId":256849,"corporation":false,"usgs":false,"family":"Bogdziewicz","given":"Michal","email":"","affiliations":[{"id":36493,"text":"USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":826755,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Boivin, Thomas","contributorId":268820,"corporation":false,"usgs":false,"family":"Boivin","given":"Thomas","email":"","affiliations":[{"id":55680,"text":"INRAE, France","active":true,"usgs":false}],"preferred":false,"id":826756,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bonal, Raul","contributorId":268821,"corporation":false,"usgs":false,"family":"Bonal","given":"Raul","email":"","affiliations":[{"id":55681,"text":"University of Madrid","active":true,"usgs":false}],"preferred":false,"id":826757,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Caignard, Thomas","contributorId":268822,"corporation":false,"usgs":false,"family":"Caignard","given":"Thomas","email":"","affiliations":[{"id":55680,"text":"INRAE, France","active":true,"usgs":false}],"preferred":false,"id":826758,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Calama, Rafael","contributorId":268823,"corporation":false,"usgs":false,"family":"Calama","given":"Rafael","email":"","affiliations":[{"id":55682,"text":"INIA-CIFOR, Spain","active":true,"usgs":false}],"preferred":false,"id":826759,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Camarero, Julio","contributorId":268824,"corporation":false,"usgs":false,"family":"Camarero","given":"Julio","email":"","affiliations":[{"id":38355,"text":"Instituto Pirenaico de Ecologia","active":true,"usgs":false}],"preferred":false,"id":826760,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Clark, Connie","contributorId":268825,"corporation":false,"usgs":false,"family":"Clark","given":"Connie","email":"","affiliations":[{"id":55678,"text":"Duke U","active":true,"usgs":false}],"preferred":false,"id":826761,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Courbaud, Benoit","contributorId":256858,"corporation":false,"usgs":false,"family":"Courbaud","given":"Benoit","email":"","affiliations":[{"id":39773,"text":"Univ. 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,{"id":70228916,"text":"70228916 - 2021 - Linking demographic rates to local environmental conditions: Empirical data to support climate adaptation strategies for Eleutherodactylus frogs","interactions":[],"lastModifiedDate":"2022-02-24T23:43:49.016459","indexId":"70228916","displayToPublicDate":"2021-08-23T17:15:32","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3871,"text":"Global Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Linking demographic rates to local environmental conditions: Empirical data to support climate adaptation strategies for <i>Eleutherodactylus </i> frogs","title":"Linking demographic rates to local environmental conditions: Empirical data to support climate adaptation strategies for Eleutherodactylus frogs","docAbstract":"<p><span>Conducting managed species translocations and establishing climate change&nbsp;<a class=\"topic-link\" title=\"Learn more about refugia from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/refugium\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/refugium\">refugia</a>&nbsp;are adaptation strategies to cope with projected consequences of global warming, but successful implementation requires on-the-ground validation of demographic responses to transient climate conditions. Here we estimated the effect of nine abiotic and biotic factors on local occupancy and an index of abundance (few or chorus) for four amphibian species (</span><span><i><a class=\"topic-link\" title=\"Learn more about Eleutherodactylus from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/eleutherodactylus\" data-mce-href=\"https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/eleutherodactylus\">Eleutherodactylus</a></i><i>&nbsp;wightmanae</i></span><span>,&nbsp;</span><i>E. brittoni</i><span>,&nbsp;</span><i>E. antillensis,</i><span>&nbsp;and&nbsp;</span><i>E. coqui</i><span>) in Puerto Rico, USA. We also assessed how the same factors influenced reproductive activity of&nbsp;</span><i>E. coqui</i><span>&nbsp;and how species responded to hurricane María (20 September 2017). As predicted, occupancy and abundance of&nbsp;</span><i>E. wightmanae</i><span>,&nbsp;</span><i>E. brittoni</i><span>&nbsp;and&nbsp;</span><i>E. coqui</i><span>&nbsp;were positively and strongly influenced by abiotic covariates (e.g., relative humidity) that characterize high elevation, mesic habitats.&nbsp;</span><i>E. antillensis</i><span>&nbsp;exhibited the opposite pattern, with highest probabilities (≥0.6) recorded at ≤300&nbsp;m and with average relative humidity&lt;75%. Biotic covariates (e.g., canopy cover) had a weak influence on both parameters, regardless of species. High probabilities (≥0.9) of detecting an&nbsp;</span><i>E. coqui</i><span>&nbsp;chorus and active nests occurred at sites experiencing average relative humidity of&gt;80% and temperature of ≤26&nbsp;°C. Moderate to high probabilities of detecting a chorus (0.4–0.7) were recorded at sites with average temperatures&gt;26&nbsp;°C, but no reproductive activity was detected, implying that monitoring abundance alone could misrepresent the capacity of a local population to sustain itself. The possibility underscores the importance of understanding the interplay between local demographic and environmental parameters in the advent of global warming to help guide monitoring and management decisions, especially for high elevation specialists. Hurricanes can inflict marked reductions in population numbers, but impacts vary by location and species. We found that the abundance (chorus) of&nbsp;</span><i>E. antillensis</i><span>&nbsp;and&nbsp;</span><i>E. brittoni</i><span>&nbsp;increased after the hurricane, but the abundance of the other two species did not differ between years. Lack of impacts was probably mediated by low structural damage to forest tracts (e.g., 9% canopy loss). Our findings help assess habitat suitability in terms of parameters that foster local population growth, which provides a basis for testing spatio-temporal predictions about demographic rates in potential climate refugia and for designing criteria to help guide managed translocations.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gecco.2021.e01624","usgsCitation":"Rivera-Burgos, A., Collazo, J.A., Terando, A., and Pacifici, K., 2021, Linking demographic rates to local environmental conditions: Empirical data to support climate adaptation strategies for Eleutherodactylus frogs: Global Ecology and Conservation, v. 28, e01624,16 p., https://doi.org/10.1016/j.gecco.2021.e01624.","productDescription":"e01624,16 p.","ipdsId":"IP-119108","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":451095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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,{"id":70223323,"text":"70223323 - 2021 - Novel microbiome dominated by Arcobacter during anoxic excurrent flow from an ocean blue hole in Andros Island, The Bahamas","interactions":[],"lastModifiedDate":"2021-08-24T11:57:41.742546","indexId":"70223323","displayToPublicDate":"2021-08-23T15:18:36","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Novel microbiome dominated by Arcobacter during anoxic excurrent flow from an ocean blue hole in Andros Island, The Bahamas","docAbstract":"<p><span>Andros Island, The Bahamas, composed of porous carbonate rock, has about 175 inland blue holes and over 50 known submerged ocean caves along its eastern barrier reef. These ocean blue holes can have both vertical and horizontal zones that penetrate under the island. Tidal forces drive water flow in and out of these caves. King Kong Cavern has a vertical collapse zone and a deep penetration under Andros Island that emits sulfidic, anoxic water and masses of thin, mucoid filaments ranging to meters in length and off-white turbid water during ebb flow. Our objective was to determine the microbial composition of this mucoid material and the unconsolidated water column turbidity based on the concept that they represent unique lithoautotrophic microbial material swept from the cave into the surrounding ocean. Bacterial DNA extracted from these filaments and surrounding turbid water was characterized using PCR that targeted a portion of the 16S rRNA gene. The genus Arcobacter dominated both the filaments and the water column above the cave entrance.&nbsp;</span><i>Arcobacter nitrofigilis</i><span>&nbsp;and&nbsp;</span><i>Arcobacter</i><span>&nbsp;sp. UDC415 in the mucoid filaments accounted for as much as 80% of mapped DNA reads. In the water column&nbsp;</span><i>Arcobacter</i><span>&nbsp;comprised from 65% to over 85% of the reads in the depth region from about 18 m to 34 m. Bacterial species diversity was much higher in surface water and in water deeper than 36 m than in the intermediate zone. Community composition indicates that ebb flow from the cavern influences the entire water column at least to within 6 m of the surface and perhaps the near surface as well.</span><br><br></p>","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0256305","usgsCitation":"Iwanowicz, D.D., Jonas, R.B., Schill, W.B., and Marano-Briggs, K., 2021, Novel microbiome dominated by Arcobacter during anoxic excurrent flow from an ocean blue hole in Andros Island, The Bahamas: PLoS ONE, v. 16, no. 8, e0256305, 16 p., https://doi.org/10.1371/journal.pone.0256305.","productDescription":"e0256305, 16 p.","ipdsId":"IP-126590","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":451097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0256305","text":"Publisher Index Page"},{"id":388384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"The Bahamas","otherGeospatial":"Andros Island, King Kong Cavern","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.93701171875,\n              24.455900450790526\n            ],\n            [\n              -77.52777099609375,\n              24.455900450790526\n            ],\n            [\n              -77.52777099609375,\n              24.857780406707583\n            ],\n            [\n              -77.93701171875,\n              24.857780406707583\n            ],\n            [\n              -77.93701171875,\n              24.455900450790526\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-08-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":821735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jonas, Robert B","contributorId":264606,"corporation":false,"usgs":false,"family":"Jonas","given":"Robert","email":"","middleInitial":"B","affiliations":[{"id":12909,"text":"George Mason University","active":true,"usgs":false}],"preferred":false,"id":821736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schill, William B. 0000-0002-9217-984X wschill@usgs.gov","orcid":"https://orcid.org/0000-0002-9217-984X","contributorId":2736,"corporation":false,"usgs":true,"family":"Schill","given":"William","email":"wschill@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":821737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marano-Briggs, Kay kmbriggs@usgs.gov","contributorId":40316,"corporation":false,"usgs":true,"family":"Marano-Briggs","given":"Kay","email":"kmbriggs@usgs.gov","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":821786,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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